1
|
Viegas RG, Martins IBS, Leite VBP. Understanding the Energy Landscape of Intrinsically Disordered Protein Ensembles. J Chem Inf Model 2024; 64:4149-4157. [PMID: 38713459 DOI: 10.1021/acs.jcim.4c00080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
A substantial portion of various organisms' proteomes comprises intrinsically disordered proteins (IDPs) that lack a defined three-dimensional structure. These IDPs exhibit a diverse array of conformations, displaying remarkable spatiotemporal heterogeneity and exceptional conformational flexibility. Characterizing the structure or structural ensemble of IDPs presents significant conceptual and methodological challenges owing to the absence of a well-defined native structure. While databases such as the Protein Ensemble Database (PED) provide IDP ensembles obtained through a combination of experimental data and molecular modeling, the absence of reaction coordinates poses challenges in comprehensively understanding pertinent aspects of the system. In this study, we leverage the energy landscape visualization method (JCTC, 6482, 2019) to scrutinize four IDP ensembles sourced from PED. ELViM, a methodology that circumvents the need for a priori reaction coordinates, aids in analyzing the ensembles. The specific IDP ensembles investigated are as follows: two fragments of nucleoporin (NUL: 884-993 and NUS: 1313-1390), yeast sic 1 N-terminal (1-90), and the N-terminal SH3 domain of Drk (1-59). Utilizing ELViM enables the comprehensive validation of ensembles, facilitating the detection of potential inconsistencies in the sampling process. Additionally, it allows for identifying and characterizing the most prevalent conformations within an ensemble. Moreover, ELViM facilitates the comparative analysis of ensembles obtained under diverse conditions, thereby providing a powerful tool for investigating the functional mechanisms of IDPs.
Collapse
Affiliation(s)
- Rafael G Viegas
- Federal Institute of Education, Science and Technology of São Paulo (IFSP), Catanduva, São Paulo 15.808-305, Brazil
- Department of Physics, São Paulo State University (UNESP), Institute of Biosciences, Humanities and Exact Sciences, São José do Rio Preto, São Paulo 15054-000, Brazil
| | - Ingrid B S Martins
- Department of Physics, São Paulo State University (UNESP), Institute of Biosciences, Humanities and Exact Sciences, São José do Rio Preto, São Paulo 15054-000, Brazil
| | - Vitor B P Leite
- Department of Physics, São Paulo State University (UNESP), Institute of Biosciences, Humanities and Exact Sciences, São José do Rio Preto, São Paulo 15054-000, Brazil
| |
Collapse
|
2
|
Waszkiewicz R, Michaś A, Białobrzewski MK, Klepka BP, Cieplak-Rotowska MK, Staszałek Z, Cichocki B, Lisicki M, Szymczak P, Niedzwiecka A. Hydrodynamic Radii of Intrinsically Disordered Proteins: Fast Prediction by Minimum Dissipation Approximation and Experimental Validation. J Phys Chem Lett 2024; 15:5024-5033. [PMID: 38696815 PMCID: PMC11103702 DOI: 10.1021/acs.jpclett.4c00312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 04/12/2024] [Accepted: 04/26/2024] [Indexed: 05/04/2024]
Abstract
The diffusion coefficients of globular and fully unfolded proteins can be predicted with high accuracy solely from their mass or chain length. However, this approach fails for intrinsically disordered proteins (IDPs) containing structural domains. We propose a rapid predictive methodology for estimating the diffusion coefficients of IDPs. The methodology uses accelerated conformational sampling based on self-avoiding random walks and includes hydrodynamic interactions between coarse-grained protein subunits, modeled using the generalized Rotne-Prager-Yamakawa approximation. To estimate the hydrodynamic radius, we rely on the minimum dissipation approximation recently introduced by Cichocki et al. Using a large set of experimentally measured hydrodynamic radii of IDPs over a wide range of chain lengths and domain contributions, we demonstrate that our predictions are more accurate than the Kirkwood approximation and phenomenological approaches. Our technique may prove to be valuable in predicting the hydrodynamic properties of both fully unstructured and multidomain disordered proteins.
Collapse
Affiliation(s)
- Radost Waszkiewicz
- Institute
of Theoretical Physics, Faculty of Physics, University of Warsaw, L. Pasteura 5, 02-093 Warsaw, Poland
| | - Agnieszka Michaś
- Institute
of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668 Warsaw, Poland
| | - Michał K. Białobrzewski
- Institute
of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668 Warsaw, Poland
| | - Barbara P. Klepka
- Institute
of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668 Warsaw, Poland
| | | | - Zuzanna Staszałek
- Institute
of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668 Warsaw, Poland
| | - Bogdan Cichocki
- Institute
of Theoretical Physics, Faculty of Physics, University of Warsaw, L. Pasteura 5, 02-093 Warsaw, Poland
| | - Maciej Lisicki
- Institute
of Theoretical Physics, Faculty of Physics, University of Warsaw, L. Pasteura 5, 02-093 Warsaw, Poland
| | - Piotr Szymczak
- Institute
of Theoretical Physics, Faculty of Physics, University of Warsaw, L. Pasteura 5, 02-093 Warsaw, Poland
| | - Anna Niedzwiecka
- Institute
of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668 Warsaw, Poland
| |
Collapse
|
3
|
Muli CS, Tarasov SG, Walters KJ. High-throughput assay exploiting disorder-to-order conformational switches: application to the proteasomal Rpn10:E6AP complex. Chem Sci 2024; 15:4041-4053. [PMID: 38487241 PMCID: PMC10935766 DOI: 10.1039/d3sc06370d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 02/05/2024] [Indexed: 03/17/2024] Open
Abstract
Conformational switching is pervasively driven by protein interactions, particularly for intrinsically disordered binding partners. We developed a dually orthogonal fluorescence-based assay to monitor such events, exploiting environmentally sensitive fluorophores. This assay is applied to E3 ligase E6AP, as its AZUL domain induces a disorder-to-order switch in an intrinsically disordered region of the proteasome, the so-named Rpn10 AZUL-binding domain (RAZUL). By testing various fluorophores, we developed an assay appropriate for high-throughput screening of Rpn10:E6AP-disrupting ligands. We found distinct positions in RAZUL for fluorophore labeling with either acrylodan or Atto610, which had disparate spectral responses to E6AP binding. E6AP caused a hypsochromic shift with increased fluorescence of acrylodan-RAZUL while decreasing fluorescence intensity of Atto610-RAZUL. Combining RAZUL labeled with either acrylodan or Atto610 into a common sample achieved robust and orthogonal measurement of the E6AP-induced conformational switch. This approach is generally applicable to disorder-to-order (or vice versa) transitions mediated by molecular interactions.
Collapse
Affiliation(s)
- Christine S Muli
- Protein Processing Section, Center for Structural Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health Frederick MD 21702 USA
| | - Sergey G Tarasov
- Biophysics Resource, Center for Structural Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health Frederick MD 21702 USA
| | - Kylie J Walters
- Protein Processing Section, Center for Structural Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health Frederick MD 21702 USA
| |
Collapse
|
4
|
Jeschke G. Protein ensemble modeling and analysis with MMMx. Protein Sci 2024; 33:e4906. [PMID: 38358120 PMCID: PMC10868441 DOI: 10.1002/pro.4906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 01/04/2024] [Accepted: 01/06/2024] [Indexed: 02/16/2024]
Abstract
Proteins, especially of eukaryotes, often have disordered domains and may contain multiple folded domains whose relative spatial arrangement is distributed. The MMMx ensemble modeling and analysis toolbox (https://github.com/gjeschke/MMMx) can support the design of experiments to characterize the distributed structure of such proteins, starting from AlphaFold2 predictions or folded domain structures. Weak order can be analyzed with reference to a random coil model or to peptide chains that match the residue-specific Ramachandran angle distribution of the loop regions and are otherwise unrestrained. The deviation of the mean square end-to-end distance of chain sections from their average over sections of the same sequence length reveals localized compaction or expansion of the chain. The shape sampled by disordered chains is visualized by superposition in the principal axes frame of their inertia tensor. Ensembles of different sizes and with weighted conformers can be compared based on a similarity parameter that abstracts from the ensemble width.
Collapse
Affiliation(s)
- Gunnar Jeschke
- Department of Chemistry and Applied BiosciencesETH ZürichZürichSwitzerland
| |
Collapse
|
5
|
Lotthammer JM, Ginell GM, Griffith D, Emenecker RJ, Holehouse AS. Direct prediction of intrinsically disordered protein conformational properties from sequence. Nat Methods 2024; 21:465-476. [PMID: 38297184 PMCID: PMC10927563 DOI: 10.1038/s41592-023-02159-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Accepted: 12/20/2023] [Indexed: 02/02/2024]
Abstract
Intrinsically disordered regions (IDRs) are ubiquitous across all domains of life and play a range of functional roles. While folded domains are generally well described by a stable three-dimensional structure, IDRs exist in a collection of interconverting states known as an ensemble. This structural heterogeneity means that IDRs are largely absent from the Protein Data Bank, contributing to a lack of computational approaches to predict ensemble conformational properties from sequence. Here we combine rational sequence design, large-scale molecular simulations and deep learning to develop ALBATROSS, a deep-learning model for predicting ensemble dimensions of IDRs, including the radius of gyration, end-to-end distance, polymer-scaling exponent and ensemble asphericity, directly from sequences at a proteome-wide scale. ALBATROSS is lightweight, easy to use and accessible as both a locally installable software package and a point-and-click-style interface via Google Colab notebooks. We first demonstrate the applicability of our predictors by examining the generalizability of sequence-ensemble relationships in IDRs. Then, we leverage the high-throughput nature of ALBATROSS to characterize the sequence-specific biophysical behavior of IDRs within and between proteomes.
Collapse
Affiliation(s)
- Jeffrey M Lotthammer
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Garrett M Ginell
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Griffith
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Ryan J Emenecker
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Alex S Holehouse
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA.
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA.
| |
Collapse
|
6
|
Holehouse AS, Kragelund BB. The molecular basis for cellular function of intrinsically disordered protein regions. Nat Rev Mol Cell Biol 2024; 25:187-211. [PMID: 37957331 DOI: 10.1038/s41580-023-00673-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/26/2023] [Indexed: 11/15/2023]
Abstract
Intrinsically disordered protein regions exist in a collection of dynamic interconverting conformations that lack a stable 3D structure. These regions are structurally heterogeneous, ubiquitous and found across all kingdoms of life. Despite the absence of a defined 3D structure, disordered regions are essential for cellular processes ranging from transcriptional control and cell signalling to subcellular organization. Through their conformational malleability and adaptability, disordered regions extend the repertoire of macromolecular interactions and are readily tunable by their structural and chemical context, making them ideal responders to regulatory cues. Recent work has led to major advances in understanding the link between protein sequence and conformational behaviour in disordered regions, yet the link between sequence and molecular function is less well defined. Here we consider the biochemical and biophysical foundations that underlie how and why disordered regions can engage in productive cellular functions, provide examples of emerging concepts and discuss how protein disorder contributes to intracellular information processing and regulation of cellular function.
Collapse
Affiliation(s)
- Alex S Holehouse
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St Louis, MO, USA.
- Center for Biomolecular Condensates, Washington University in St Louis, St Louis, MO, USA.
| | - Birthe B Kragelund
- REPIN, Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| |
Collapse
|
7
|
Tesei G, Trolle AI, Jonsson N, Betz J, Knudsen FE, Pesce F, Johansson KE, Lindorff-Larsen K. Conformational ensembles of the human intrinsically disordered proteome. Nature 2024; 626:897-904. [PMID: 38297118 DOI: 10.1038/s41586-023-07004-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 12/19/2023] [Indexed: 02/02/2024]
Abstract
Intrinsically disordered proteins and regions (collectively, IDRs) are pervasive across proteomes in all kingdoms of life, help to shape biological functions and are involved in numerous diseases. IDRs populate a diverse set of transiently formed structures and defy conventional sequence-structure-function relationships1. Developments in protein science have made it possible to predict the three-dimensional structures of folded proteins at the proteome scale2. By contrast, there is a lack of knowledge about the conformational properties of IDRs, partly because the sequences of disordered proteins are poorly conserved and also because only a few of these proteins have been characterized experimentally. The inability to predict structural properties of IDRs across the proteome has limited our understanding of the functional roles of IDRs and how evolution shapes them. As a supplement to previous structural studies of individual IDRs3, we developed an efficient molecular model to generate conformational ensembles of IDRs and thereby to predict their conformational properties from sequences4,5. Here we use this model to simulate nearly all of the IDRs in the human proteome. Examining conformational ensembles of 28,058 IDRs, we show how chain compaction is correlated with cellular function and localization. We provide insights into how sequence features relate to chain compaction and, using a machine-learning model trained on our simulation data, show the conservation of conformational properties across orthologues. Our results recapitulate observations from previous studies of individual protein systems and exemplify how to link-at the proteome scale-conformational ensembles with cellular function and localization, amino acid sequence, evolutionary conservation and disease variants. Our freely available database of conformational properties will encourage further experimental investigation and enable the generation of hypotheses about the biological roles and evolution of IDRs.
Collapse
Affiliation(s)
- Giulio Tesei
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Anna Ida Trolle
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Nicolas Jonsson
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Johannes Betz
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Frederik E Knudsen
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Francesco Pesce
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kristoffer E Johansson
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| |
Collapse
|
8
|
Jin H, Liu D, Ni Y, Wang H, Long D. Quantitative Ensemble Interpretation of Membrane Paramagnetic Relaxation Enhancement (mPRE) for Studying Membrane-Associated Intrinsically Disordered Proteins. J Am Chem Soc 2024; 146:791-800. [PMID: 38146836 DOI: 10.1021/jacs.3c10847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
An understanding of the functional role played by a membrane-associated intrinsically disordered protein (IDP) requires characterization of its heterogeneous conformations as well as its poses relative to the membranes, which is of great interest but technically challenging. Here, we explore the membrane paramagnetic relaxation enhancement (mPRE) for constructing ensembles of IDPs that dynamically associate with membrane mimetics incorporating spin-labeled lipids. To accurately interpret the mPRE Γ2 rates, both the dynamics of IDPs and spin probe molecules are taken into account, with the latter described by a weighted three-dimensional (3D) grid model built based on all-atom simulations. The IDP internal conformations, orientations, and immersion depths in lipid bilayers are comprehensively optimized in the Γ2-based ensemble modeling. Our approach is tested and validated on the example of POPG bicelle-bound disordered cytoplasmic domain of CD3ε (CD3εCD), a component of the T-cell receptor (TCR) complex. The mPRE-derived CD3εCD ensemble provides new insights into the IDP-membrane fuzzy association, in particular for the tyrosine-based signaling motif that plays a critical role in TCR signaling. The comparative analysis of the ensembles for wild-type CD3εCD and mutants that mimic the mono- and dual-phosphorylation effects suggests a delicate membrane regulatory mechanism for activation and inhibition of the TCR activity.
Collapse
Affiliation(s)
- Hong Jin
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Dan Liu
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Yu Ni
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Hui Wang
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Dong Long
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
- Department of Chemistry, University of Science and Technology of China, Hefei 230026, China
| |
Collapse
|
9
|
Seth S, Stine B, Bhattacharya A. Fine structures of intrinsically disordered proteins. J Chem Phys 2024; 160:014902. [PMID: 38165099 DOI: 10.1063/5.0176306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 12/05/2023] [Indexed: 01/03/2024] Open
Abstract
We report simulation studies of 33 single intrinsically disordered proteins (IDPs) using coarse-grained bead-spring models where interactions among different amino acids are introduced through a hydropathy matrix and additional screened Coulomb interaction for the charged amino acid beads. Our simulation studies of two different hydropathy scales (HPS1, HPS2) [Dignon et al., PLoS Comput. Biol. 14, e1005941 (2018); Tesei et al. Proc. Natl. Acad. Sci. U. S. A. 118, e2111696118 (2021)] and the comparison with the existing experimental data indicate an optimal interaction parameter ϵ = 0.1 and 0.2 kcal/mol for the HPS1 and HPS2 hydropathy scales. We use these best-fit parameters to investigate both the universal aspects as well as the fine structures of the individual IDPs by introducing additional characteristics. (i) First, we investigate the polymer-specific scaling relations of the IDPs in comparison to the universal scaling relations [Bair et al., J. Chem. Phys. 158, 204902 (2023)] for the homopolymers. By studying the scaled end-to-end distances ⟨RN2⟩/(2Lℓp) and the scaled transverse fluctuations l̃⊥2=⟨l⊥2⟩/L, we demonstrate that IDPs are broadly characterized with a Flory exponent of ν ≃ 0.56 with the conclusion that conformations of the IDPs interpolate between Gaussian and self-avoiding random walk chains. Then, we introduce (ii) Wilson charge index (W) that captures the essential features of charge interactions and distribution in the sequence space and (iii) a skewness index (S) that captures the finer shape variation of the gyration radii distributions as a function of the net charge per residue and charge asymmetry parameter. Finally, our study of the (iv) variation of ⟨Rg⟩ as a function of salt concentration provides another important metric to bring out finer characteristics of the IDPs, which may carry relevant information for the origin of life.
Collapse
Affiliation(s)
- Swarnadeep Seth
- Department of Physics, University of Central Florida, Orlando, Florida 32816-2385, USA
| | - Brandon Stine
- Department of Physics, University of Central Florida, Orlando, Florida 32816-2385, USA
| | - Aniket Bhattacharya
- Department of Physics, University of Central Florida, Orlando, Florida 32816-2385, USA
| |
Collapse
|
10
|
Ghafouri H, Lazar T, Del Conte A, Tenorio Ku LG, Tompa P, Tosatto SCE, Monzon AM. PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins. Nucleic Acids Res 2024; 52:D536-D544. [PMID: 37904608 PMCID: PMC10767937 DOI: 10.1093/nar/gkad947] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/10/2023] [Accepted: 10/13/2023] [Indexed: 11/01/2023] Open
Abstract
The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.
Collapse
Affiliation(s)
| | - Tamas Lazar
- VIB-VUB Center for Structural Biology, Vlaams Instituut voor Biotechnologie (VIB), Brussels, Belgium
- Structural Biology Brussels, Department of Bioengineering, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Alessio Del Conte
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | | | - Peter Tompa
- VIB-VUB Center for Structural Biology, Vlaams Instituut voor Biotechnologie (VIB), Brussels, Belgium
- Structural Biology Brussels, Department of Bioengineering, Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Institute of Enzymology, Research Centre for Natural Sciences (RCNS), Budapest, Hungary
| | | | | |
Collapse
|
11
|
Liu ZH, Teixeira JMC, Zhang O, Tsangaris TE, Li J, Gradinaru CC, Head-Gordon T, Forman-Kay JD. Local Disordered Region Sampling (LDRS) for ensemble modeling of proteins with experimentally undetermined or low confidence prediction segments. Bioinformatics 2023; 39:btad739. [PMID: 38060268 PMCID: PMC10733734 DOI: 10.1093/bioinformatics/btad739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 10/30/2023] [Accepted: 12/06/2023] [Indexed: 12/08/2023] Open
Abstract
SUMMARY The Local Disordered Region Sampling (LDRS, pronounced loaders) tool is a new module developed for IDPConformerGenerator, a previously validated approach to model intrinsically disordered proteins (IDPs). The IDPConformerGenerator LDRS module provides a method for generating all-atom conformations of intrinsically disordered protein regions at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB or mmCIF formatted structural template of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo-Side Chain Entropy, transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, the ability to be used as a library and via command-line, and the computational speed of the IDPConformerGenerator platform. AVAILABILITY AND IMPLEMENTATION The LDRS module is part of the IDPConformerGenerator modeling suite, which can be downloaded from GitHub at https://github.com/julie-forman-kay-lab/IDPConformerGenerator. IDPConformerGenerator is written in Python3 and works on Linux, Microsoft Windows, and Mac OS versions that support DSSP. Users can utilize LDRS's Python API for scripting the same way they can use any part of IDPConformerGenerator's API, by importing functions from the "idpconfgen.ldrs_helper" library. Otherwise, LDRS can be used as a command line interface application within IDPConformerGenerator. Full documentation is available within the command-line interface as well as on IDPConformerGenerator's official documentation pages (https://idpconformergenerator.readthedocs.io/en/latest/).
Collapse
Affiliation(s)
- Zi Hao Liu
- Molecular Medicine Program, Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - João M C Teixeira
- Molecular Medicine Program, Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Oufan Zhang
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, Berkeley, CA 94720, United States
- Department of Chemistry, University of California, Berkeley, Berkeley, CA 94720-1460, United States
| | - Thomas E Tsangaris
- Department of Physics, University of Toronto, Toronto, ON M5S 1A7, Canada
- Department of Chemical and Physical Sciences, University of Toronto Mississauga, Mississauga, ON L5L 1C6, Canada
| | - Jie Li
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, Berkeley, CA 94720, United States
- Department of Chemistry, University of California, Berkeley, Berkeley, CA 94720-1460, United States
| | - Claudiu C Gradinaru
- Department of Physics, University of Toronto, Toronto, ON M5S 1A7, Canada
- Department of Chemical and Physical Sciences, University of Toronto Mississauga, Mississauga, ON L5L 1C6, Canada
| | - Teresa Head-Gordon
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, Berkeley, CA 94720, United States
- Department of Chemistry, University of California, Berkeley, Berkeley, CA 94720-1460, United States
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720-1462, United States
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720-1762, United States
| | - Julie D Forman-Kay
- Molecular Medicine Program, Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, ON M5S 1A8, Canada
| |
Collapse
|
12
|
Balasubramanian S, Maharana S, Srivastava A. "Boundary residues" between the folded RNA recognition motif and disordered RGG domains are critical for FUS-RNA binding. J Biol Chem 2023; 299:105392. [PMID: 37890778 PMCID: PMC10687056 DOI: 10.1016/j.jbc.2023.105392] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 09/19/2023] [Accepted: 10/19/2023] [Indexed: 10/29/2023] Open
Abstract
Fused in sarcoma (FUS) is an abundant RNA-binding protein, which drives phase separation of cellular condensates and plays multiple roles in RNA regulation. The RNA-binding ability of FUS protein is crucial to its cellular function. Here, our molecular simulation study on the FUS-RNA complex provides atomic resolution insights into the observations from biochemical studies and also illuminates our understanding of molecular driving forces that mediate the structure, stability, and interaction of the RNA recognition motif (RRM) and RGG domains of FUS with a stem-loop junction RNA. We observe clear cooperativity and division of labor among the ordered (RRM) and disordered domains (RGG1 and RGG2) of FUS that leads to an organized and tighter RNA binding. Irrespective of the length of RGG2, the RGG2-RNA interaction is confined to the stem-loop junction and the proximal stem regions. On the other hand, the RGG1 interactions are primarily with the longer RNA stem. We find that the C terminus of RRM, which make up the "boundary residues" that connect the folded RRM with the long disordered RGG2 stretch of the protein, plays a critical role in FUS-RNA binding. Our study provides high-resolution molecular insights into the FUS-RNA interactions and forms the basis for understanding the molecular origins of full-length FUS interaction with RNA.
Collapse
Affiliation(s)
| | - Shovamayee Maharana
- Department of Molecular and Cell Biology, Indian Institute of Science Bangalore, Bangalore, Karnataka, India
| | - Anand Srivastava
- Molecular Biophysics Unit, Indian Institute of Science Bangalore, Bangalore, Karnataka, India.
| |
Collapse
|
13
|
Adhikari S, Mondal J. Machine Learning Subtle Conformational Change due to Phosphorylation in Intrinsically Disordered Proteins. J Phys Chem B 2023; 127:9433-9449. [PMID: 37905972 DOI: 10.1021/acs.jpcb.3c05136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Phosphorylation of intrinsically disordered proteins/regions (IDPs/IDRs) has a profound effect in biological functions such as cell signaling, protein folding or unfolding, and long-range allosteric effects. However, here we focus on two IDPs, namely 83-residue IDR transcription factor Ash1 and 92-residue long N-terminal region of CDK inhibitor Sic1 protein, found in Saccharomyces cerevisiae, for which experimental measurements of average conformational properties, namely, radius of gyration and structure factor, indicate negligible changes upon phosphorylation. Here, we show that a judicious dissection of conformational ensemble via combination of unsupervised machine learning and extensive molecular dynamics (MD) trajectories can highlight key differences and similarities among the phosphorylated and wild-type IDP. In particular, we develop Markov state model (MSM) using the latent-space dimensions of an autoencoder, trained using multi-microsecond long MD simulation trajectories. Examination of structural changes among the states, prior to and upon phosphorylation, captured several similarities and differences in their backbone contact maps, secondary structure, and torsion angles. Hydrogen bonding analysis revealed that phosphorylation not only increases the number of hydrogen bonds but also switches the pattern of hydrogen bonding between the backbone and side chain atoms with the phosphorylated residues. We also observe that although phosphorylation introduces salt bridges, there is a loss of the cation-π interaction. Phosphorylation also improved the probability for long-range hydrophobic contacts and also enhanced interaction with water molecules and improved the local structure of water as evident from the geometric order parameters. The observations on these machine-learnt states gave important insights, as it would otherwise be difficult to determine experimentally which is important, if we were to understand the role of phosphorylation of IDPs in their biological functions.
Collapse
|
14
|
Nussinov R, Liu Y, Zhang W, Jang H. Protein conformational ensembles in function: roles and mechanisms. RSC Chem Biol 2023; 4:850-864. [PMID: 37920394 PMCID: PMC10619138 DOI: 10.1039/d3cb00114h] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/02/2023] [Indexed: 11/04/2023] Open
Abstract
The sequence-structure-function paradigm has dominated twentieth century molecular biology. The paradigm tacitly stipulated that for each sequence there exists a single, well-organized protein structure. Yet, to sustain cell life, function requires (i) that there be more than a single structure, (ii) that there be switching between the structures, and (iii) that the structures be incompletely organized. These fundamental tenets called for an updated sequence-conformational ensemble-function paradigm. The powerful energy landscape idea, which is the foundation of modernized molecular biology, imported the conformational ensemble framework from physics and chemistry. This framework embraces the recognition that proteins are dynamic and are always interconverting between conformational states with varying energies. The more stable the conformation the more populated it is. The changes in the populations of the states are required for cell life. As an example, in vivo, under physiological conditions, wild type kinases commonly populate their more stable "closed", inactive, conformations. However, there are minor populations of the "open", ligand-free states. Upon their stabilization, e.g., by high affinity interactions or mutations, their ensembles shift to occupy the active states. Here we discuss the role of conformational propensities in function. We provide multiple examples of diverse systems, including protein kinases, lipid kinases, and Ras GTPases, discuss diverse conformational mechanisms, and provide a broad outlook on protein ensembles in the cell. We propose that the number of molecules in the active state (inactive for repressors), determine protein function, and that the dynamic, relative conformational propensities, rather than the rigid structures, are the hallmark of cell life.
Collapse
Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research Frederick MD 21702 USA
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University Tel Aviv 69978 Israel
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| | - Yonglan Liu
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| | - Wengang Zhang
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research Frederick MD 21702 USA
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| |
Collapse
|
15
|
Białobrzewski MK, Klepka BP, Michaś A, Cieplak-Rotowska MK, Staszałek Z, Niedźwiecka A. Diversity of hydrodynamic radii of intrinsically disordered proteins. EUROPEAN BIOPHYSICS JOURNAL : EBJ 2023; 52:607-618. [PMID: 37831084 PMCID: PMC10618399 DOI: 10.1007/s00249-023-01683-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 08/08/2023] [Accepted: 09/06/2023] [Indexed: 10/14/2023]
Abstract
Intrinsically disordered proteins (IDPs) form an important class of biomolecules regulating biological processes in higher organisms. The lack of a fixed spatial structure facilitates them to perform their regulatory functions and allows the efficiency of biochemical reactions to be controlled by temperature and the cellular environment. From the biophysical point of view, IDPs are biopolymers with a broad configuration state space and their actual conformation depends on non-covalent interactions of its amino acid side chain groups at given temperature and chemical conditions. Thus, the hydrodynamic radius (Rh) of an IDP of a given polymer length (N) is a sequence- and environment-dependent variable. We have reviewed the literature values of hydrodynamic radii of IDPs determined experimentally by SEC, AUC, PFG NMR, DLS, and FCS, and complement them with our FCS results obtained for a series of protein fragments involved in the regulation of human gene expression. The data collected herein show that the values of hydrodynamic radii of IDPs can span the full space between the folded globular and denatured proteins in the Rh(N) diagram.
Collapse
Affiliation(s)
- Michał K Białobrzewski
- Laboratory of Biological Physics, Institute of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668, Warsaw, Poland
| | - Barbara P Klepka
- Laboratory of Biological Physics, Institute of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668, Warsaw, Poland
| | - Agnieszka Michaś
- Laboratory of Biological Physics, Institute of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668, Warsaw, Poland
| | - Maja K Cieplak-Rotowska
- Laboratory of Biological Physics, Institute of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668, Warsaw, Poland
- Division of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Pasteura 5, PL-02093, Warsaw, Poland
- The International Institute of Molecular Mechanisms and Machines, Polish Academy of Sciences, Flisa 6, PL-02247, Warsaw, Poland
| | - Zuzanna Staszałek
- Laboratory of Biological Physics, Institute of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668, Warsaw, Poland
| | - Anna Niedźwiecka
- Laboratory of Biological Physics, Institute of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, PL-02668, Warsaw, Poland.
| |
Collapse
|
16
|
Vedel IM, Papagiannoula A, Naudi-Fabra S, Milles S. Nuclear magnetic resonance/single molecule fluorescence combinations to study dynamic protein systems. Curr Opin Struct Biol 2023; 82:102659. [PMID: 37499445 PMCID: PMC10565672 DOI: 10.1016/j.sbi.2023.102659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 05/04/2023] [Accepted: 06/28/2023] [Indexed: 07/29/2023]
Abstract
Many proteins require different structural states or conformations for function, and intrinsically disordered proteins, i.e. proteins without stable three-dimensional structure, are certainly an extreme. Single molecule fluorescence and nuclear magnetic resonance (NMR) spectroscopy are both exceptionally well suited to decipher and describe these states and their interconversion. Different time scales, from picoseconds to several milliseconds, can be addressed by both techniques. The length scales probed and the sample requirements (e.g. concentration, molecular weight, sample complexity) are, however, vastly different, making NMR and single molecule fluorescence an excellent combination for integrated studies. Here, we review recently undertaken approaches for the combined use of NMR and single molecule fluorescence to study protein dynamics.
Collapse
Affiliation(s)
- Ida Marie Vedel
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Rössle-Str. 10, 13125 Berlin, Germany
| | - Andromachi Papagiannoula
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Rössle-Str. 10, 13125 Berlin, Germany
| | - Samuel Naudi-Fabra
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Rössle-Str. 10, 13125 Berlin, Germany
| | - Sigrid Milles
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Rössle-Str. 10, 13125 Berlin, Germany.
| |
Collapse
|
17
|
Chao TH, Rekhi S, Mittal J, Tabor DP. Data-Driven Models for Predicting Intrinsically Disordered Protein Polymer Physics Directly from Composition or Sequence. MOLECULAR SYSTEMS DESIGN & ENGINEERING 2023; 8:1146-1155. [PMID: 38222029 PMCID: PMC10786636 DOI: 10.1039/d3me00053b] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
The molecular-level understanding of intrinsically disordered proteins is challenging due to experimental characterization difficulties. Computational understanding of IDPs also requires fundamental advances, as the leading tools for predicting protein folding (e.g., AlphaFold), typically fail to describe the structural ensembles of IDPs. The focus of this paper is to 1) develop new representations for intrinsically disordered proteins and 2) pair these representations with classical machine learning and deep learning models to predict the radius of gyration and derived scaling exponent of IDPs. Here, we build a new physically-motivated feature called the bag of amino acid interactions representation, which encodes pairwise interactions explicitly into the representation. This feature essentially counts and weights all possible non-bonded interactions in a sequence and thus is, in principle, compatible with arbitrary sequence lengths. To see how well this new feature performs, both categorical and physically-motivated featurization techniques are tested on a computational dataset containing 10,000 sequences simulated at the coarse-grained level. The results indicate that this new feature outperforms the other purely categorical and physically-motivated features and possesses solid extrapolation capabilities. For future use, this feature can potentially provide physical insights into amino acid interactions, including their temperature dependence, and be applied to other protein spaces.
Collapse
Affiliation(s)
- Tzu-Hsuan Chao
- Department of Chemistry, Texas A&M University, PO Box 30012, College Station, TX 77842-3012, USA
| | - Shiv Rekhi
- Department of Chemistry, Texas A&M University, PO Box 30012, College Station, TX 77842-3012, USA
| | - Jeetain Mittal
- Department of Chemistry, Texas A&M University, PO Box 30012, College Station, TX 77842-3012, USA
| | - Daniel P Tabor
- Department of Chemistry, Texas A&M University, PO Box 30012, College Station, TX 77842-3012, USA
| |
Collapse
|
18
|
Tsangaris TE, Smyth S, Gomes GNW, Liu ZH, Milchberg M, Bah A, Wasney GA, Forman-Kay JD, Gradinaru CC. Delineating Structural Propensities of the 4E-BP2 Protein via Integrative Modeling and Clustering. J Phys Chem B 2023; 127:7472-7486. [PMID: 37595014 PMCID: PMC10858721 DOI: 10.1021/acs.jpcb.3c04052] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/20/2023]
Abstract
The intrinsically disordered 4E-BP2 protein regulates mRNA cap-dependent translation through interaction with the predominantly folded eukaryotic initiation factor 4E (eIF4E). Phosphorylation of 4E-BP2 dramatically reduces the level of eIF4E binding, in part by stabilizing a binding-incompatible folded domain. Here, we used a Rosetta-based sampling algorithm optimized for IDRs to generate initial ensembles for two phospho forms of 4E-BP2, non- and 5-fold phosphorylated (NP and 5P, respectively), with the 5P folded domain flanked by N- and C-terminal IDRs (N-IDR and C-IDR, respectively). We then applied an integrative Bayesian approach to obtain NP and 5P conformational ensembles that agree with experimental data from nuclear magnetic resonance, small-angle X-ray scattering, and single-molecule Förster resonance energy transfer (smFRET). For the NP state, inter-residue distance scaling and 2D maps revealed the role of charge segregation and pi interactions in driving contacts between distal regions of the chain (∼70 residues apart). The 5P ensemble shows prominent contacts of the N-IDR region with the two phosphosites in the folded domain, pT37 and pT46, and, to a lesser extent, delocalized interactions with the C-IDR region. Agglomerative hierarchical clustering led to partitioning of each of the two ensembles into four clusters with different global dimensions and contact maps. This helped delineate an NP cluster that, based on our smFRET data, is compatible with the eIF4E-bound state. 5P clusters were differentiated by interactions of C-IDR with the folded domain and of the N-IDR with the two phosphosites in the folded domain. Our study provides both a better visualization of fundamental structural poses of 4E-BP2 and a set of falsifiable insights on intrachain interactions that bias folding and binding of this protein.
Collapse
Affiliation(s)
- Thomas E Tsangaris
- Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada
- Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada
| | - Spencer Smyth
- Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada
- Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada
| | - Gregory-Neal W Gomes
- Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada
- Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada
| | - Zi Hao Liu
- Program in Molecular Medicine, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Moses Milchberg
- Program in Molecular Medicine, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Alaji Bah
- Program in Molecular Medicine, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Gregory A Wasney
- Peter Gilgan Centre for Research and Learning, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Julie D Forman-Kay
- Program in Molecular Medicine, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Claudiu C Gradinaru
- Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada
- Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada
| |
Collapse
|
19
|
Maiti S, Heyden M. Model-Dependent Solvation of the K-18 Domain of the Intrinsically Disordered Protein Tau. J Phys Chem B 2023; 127:7220-7230. [PMID: 37556237 DOI: 10.1021/acs.jpcb.3c01726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
A known imbalance between intra-protein and protein-water interactions in many empirical force fields results in collapsed conformational ensembles of intrinsically disordered proteins in explicit solvent simulations that disagree with experiments. Multiple strategies have been introduced in the literature to modify protein-water interactions, which improve agreement between experiments and simulations. In this work, we combine simulations with standard and modified force fields with a spatially resolved analysis of solvation free energy contributions and compare the consequences of each strategy. We find that enhanced Lennard-Jones (LJ) interactions between protein atoms and water oxygens primarily improve the solvation of nonpolar functional groups of the protein. In contrast, modified electrostatics in the water model or strengthened LJ interactions between the protein and water hydrogens mainly affect the hydration of polar functional groups. Modified electrostatics further impact the average orientation of water molecules in the hydration shell. As a result, protein-water interactions with the first hydration layers are strengthened, while interactions with water molecules in higher hydration shells are weakened. Hence, distinct strategies to balance intra-protein and protein-water interactions in simulations have qualitatively different effects on protein solvation. These differences are not necessarily captured by comparisons to experiments that report on global parameters describing protein conformational ensembles, e.g., the radius of gyration, but will influence the tendency of a protein to form aggregates or phase-separated droplets.
Collapse
Affiliation(s)
- Sthitadhi Maiti
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States
| | - Matthias Heyden
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States
| |
Collapse
|
20
|
Lalmansingh JM, Keeley AT, Ruff KM, Pappu RV, Holehouse AS. SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins. J Chem Theory Comput 2023; 19:5609-5620. [PMID: 37463458 DOI: 10.1021/acs.jctc.3c00190] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite simulation analysis of unfolded regions of proteins (SOURSOP), an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.
Collapse
Affiliation(s)
- Jared M Lalmansingh
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Alex T Keeley
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana-Champaign, Illinois 61801, United States
| | - Kiersten M Ruff
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Rohit V Pappu
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Alex S Holehouse
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri 63110, United States
| |
Collapse
|
21
|
Heesink G, Marseille MJ, Fakhree MAA, Driver MD, van Leijenhorst-Groener KA, Onck PR, Blum C, Claessens MM. Exploring Intra- and Inter-Regional Interactions in the IDP α-Synuclein Using smFRET and MD Simulations. Biomacromolecules 2023; 24:3680-3688. [PMID: 37407505 PMCID: PMC10428166 DOI: 10.1021/acs.biomac.3c00404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 06/23/2023] [Indexed: 07/07/2023]
Abstract
Theoretical concepts from polymer physics are often used to describe intrinsically disordered proteins (IDPs). However, amino acid interactions within and between regions of the protein can lead to deviations from typical polymer scaling behavior and even to short-lived secondary structures. To investigate the key interactions in the dynamic IDP α-synuclein (αS) at the amino acid level, we conducted single-molecule fluorescence resonance energy transfer (smFRET) experiments and coarse-grained molecular dynamics (CG-MD) simulations. We find excellent agreement between experiments and simulations. Our results show that a physiological salt solution is a good solvent for αS and that the protein is highly dynamic throughout its entire chain, with local intra- and inter-regional interactions leading to deviations from global scaling. Specifically, we observe expansion in the C-terminal region, compaction in the NAC region, and a slightly smaller distance between the C- and N-termini than expected. Our simulations indicate that the compaction in the NAC region results from hydrophobic aliphatic contacts, mostly between valine and alanine residues, and cation-π interactions between lysine and tyrosine. In addition, hydrogen bonds also seem to contribute to the compaction of the NAC region. The expansion of the C-terminal region is due to intraregional electrostatic repulsion and increased chain stiffness from several prolines. Overall, our study demonstrates the effectiveness of combining smFRET experiments with CG-MD simulations to investigate the key interactions in highly dynamic IDPs at the amino acid level.
Collapse
Affiliation(s)
- Gobert Heesink
- Nanobiophysics,
Faculty of Science and Technology, MESA + Institute for Nanotechnology
and Technical Medical Centre, University
of Twente, PO Box 217, 7500 AE Enschede, The Netherlands
| | - Mirjam J. Marseille
- Nanobiophysics,
Faculty of Science and Technology, MESA + Institute for Nanotechnology
and Technical Medical Centre, University
of Twente, PO Box 217, 7500 AE Enschede, The Netherlands
| | - Mohammad A. A. Fakhree
- Nanobiophysics,
Faculty of Science and Technology, MESA + Institute for Nanotechnology
and Technical Medical Centre, University
of Twente, PO Box 217, 7500 AE Enschede, The Netherlands
| | - Mark D. Driver
- Micromechanics,
Zernike Institute for Advanced Materials, University of Groningen, 9747 AG Groningen, The Netherlands
| | - Kirsten A. van Leijenhorst-Groener
- Nanobiophysics,
Faculty of Science and Technology, MESA + Institute for Nanotechnology
and Technical Medical Centre, University
of Twente, PO Box 217, 7500 AE Enschede, The Netherlands
| | - Patrick R. Onck
- Micromechanics,
Zernike Institute for Advanced Materials, University of Groningen, 9747 AG Groningen, The Netherlands
| | - Christian Blum
- Nanobiophysics,
Faculty of Science and Technology, MESA + Institute for Nanotechnology
and Technical Medical Centre, University
of Twente, PO Box 217, 7500 AE Enschede, The Netherlands
| | - Mireille M.A.E. Claessens
- Nanobiophysics,
Faculty of Science and Technology, MESA + Institute for Nanotechnology
and Technical Medical Centre, University
of Twente, PO Box 217, 7500 AE Enschede, The Netherlands
| |
Collapse
|
22
|
Mondal A, Lenz S, MacCallum JL, Perez A. Hybrid computational methods combining experimental information with molecular dynamics. Curr Opin Struct Biol 2023; 81:102609. [PMID: 37224642 DOI: 10.1016/j.sbi.2023.102609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/12/2023] [Accepted: 04/23/2023] [Indexed: 05/26/2023]
Abstract
A goal of structural biology is to understand how macromolecules carry out their biological roles by identifying their metastable states, mechanisms of action, pathways leading to conformational changes, and the thermodynamic and kinetic relationships between those states. Integrative modeling brings structural insights into systems where traditional structure determination approaches cannot help. We focus on the synergies and challenges of integrative modeling combining experimental data with molecular dynamics simulations.
Collapse
Affiliation(s)
- Arup Mondal
- Quantum Theory Project, Department of Chemistry, University of Florida, Leigh, UK. https://twitter.com/@amondal_chem
| | - Stefan Lenz
- Department of Chemistry, University of Calgary, 2500 University Drive, Canada
| | - Justin L MacCallum
- Department of Chemistry, University of Calgary, 2500 University Drive, Canada. https://twitter.com/@jlmaccal
| | - Alberto Perez
- Quantum Theory Project, Department of Chemistry, University of Florida, Leigh, UK.
| |
Collapse
|
23
|
Liu ZH, Teixeira JM, Zhang O, Tsangaris TE, Li J, Gradinaru CC, Head-Gordon T, Forman-Kay JD. Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.25.550520. [PMID: 37546943 PMCID: PMC10402175 DOI: 10.1101/2023.07.25.550520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
The Local Disordered Region Sampling (LDRS, pronounced loaders) tool, developed for the IDPConformerGenerator platform (Teixeira et al. 2022), provides a method for generating all-atom conformations of intrinsically disordered regions (IDRs) at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB structure of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo Side Chain Entropy (MC-SCE) (Bhowmick and Head-Gordon 2015), transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, ability to be used as a library and via command-line, and computational speed of the IDPConformerGenerator platform.
Collapse
Affiliation(s)
- Zi Hao Liu
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - João M.C. Teixeira
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Oufan Zhang
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, California 94720, United States of America
- Department of Chemistry, University of California, Berkeley, California 94720-1460 United States of America
| | - Thomas E. Tsangaris
- Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada
- Department of Chemical and Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada
| | - Jie Li
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, California 94720, United States of America
- Department of Chemistry, University of California, Berkeley, California 94720-1460 United States of America
| | - Claudiu C. Gradinaru
- Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada
- Department of Chemical and Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada
| | - Teresa Head-Gordon
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, California 94720, United States of America
- Department of Chemistry, University of California, Berkeley, California 94720-1460 United States of America
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720-1462, United States of America
- Department of Bioengineering, University of California, Berkeley, California 94720-1762, United States of America
| | - Julie D. Forman-Kay
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| |
Collapse
|
24
|
Appadurai R, Koneru JK, Bonomi M, Robustelli P, Srivastava A. Clustering Heterogeneous Conformational Ensembles of Intrinsically Disordered Proteins with t-Distributed Stochastic Neighbor Embedding. J Chem Theory Comput 2023; 19:4711-4727. [PMID: 37338049 PMCID: PMC11108026 DOI: 10.1021/acs.jctc.3c00224] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Intrinsically disordered proteins (IDPs) populate a range of conformations that are best described by a heterogeneous ensemble. Grouping an IDP ensemble into "structurally similar" clusters for visualization, interpretation, and analysis purposes is a much-desired but formidable task, as the conformational space of IDPs is inherently high-dimensional and reduction techniques often result in ambiguous classifications. Here, we employ the t-distributed stochastic neighbor embedding (t-SNE) technique to generate homogeneous clusters of IDP conformations from the full heterogeneous ensemble. We illustrate the utility of t-SNE by clustering conformations of two disordered proteins, Aβ42, and α-synuclein, in their APO states and when bound to small molecule ligands. Our results shed light on ordered substates within disordered ensembles and provide structural and mechanistic insights into binding modes that confer specificity and affinity in IDP ligand binding. t-SNE projections preserve the local neighborhood information, provide interpretable visualizations of the conformational heterogeneity within each ensemble, and enable the quantification of cluster populations and their relative shifts upon ligand binding. Our approach provides a new framework for detailed investigations of the thermodynamics and kinetics of IDP ligand binding and will aid rational drug design for IDPs.
Collapse
Affiliation(s)
- Rajeswari Appadurai
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India
| | | | - Massimiliano Bonomi
- Structural Bioinformatics Unit, Department of Structural Biology and Chemistry. CNRS UMR 3528, C3BI, CNRS USR 3756, Institut Pasteur, Paris, France
| | - Paul Robustelli
- Dartmouth College, Department of Chemistry, Hanover, NH, 03755, USA
| | - Anand Srivastava
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India
| |
Collapse
|
25
|
Li J, Zhang O, Lee S, Namini A, Liu ZH, Teixeira JMC, Forman-Kay JD, Head-Gordon T. Learning Correlations between Internal Coordinates to Improve 3D Cartesian Coordinates for Proteins. J Chem Theory Comput 2023; 19:4689-4700. [PMID: 36749957 PMCID: PMC10404647 DOI: 10.1021/acs.jctc.2c01270] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
We consider a generic representation problem of internal coordinates (bond lengths, valence angles, and dihedral angles) and their transformation to 3-dimensional Cartesian coordinates of a biomolecule. We show that the internal-to-Cartesian process relies on correctly predicting chemically subtle correlations among the internal coordinates themselves, and learning these correlations increases the fidelity of the Cartesian representation. We developed a machine learning algorithm, Int2Cart, to predict bond lengths and bond angles from backbone torsion angles and residue types of a protein, which allows reconstruction of protein structures better than using fixed bond lengths and bond angles or a static library method that relies on backbone torsion angles and residue types in a local environment. The method is able to be used for structure validation, as we show that the agreement between Int2Cart-predicted bond geometries and those from an AlphaFold 2 model can be used to estimate model quality. Additionally, by using Int2Cart to reconstruct an IDP ensemble, we are able to decrease the clash rate during modeling. The Int2Cart algorithm has been implemented as a publicly accessible python package at https://github.com/THGLab/int2cart.
Collapse
Affiliation(s)
- Jie Li
- Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Oufan Zhang
- Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Seokyoung Lee
- Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Ashley Namini
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5S 1A8, Canada
| | - Zi Hao Liu
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5S 1A8, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5G 1X8, Canada
| | - João M C Teixeira
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5S 1A8, Canada
| | - Julie D Forman-Kay
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5S 1A8, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5G 1X8, Canada
| | - Teresa Head-Gordon
- Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States
| |
Collapse
|
26
|
Koren G, Meir S, Holschuh L, Mertens HDT, Ehm T, Yahalom N, Golombek A, Schwartz T, Svergun DI, Saleh OA, Dzubiella J, Beck R. Intramolecular structural heterogeneity altered by long-range contacts in an intrinsically disordered protein. Proc Natl Acad Sci U S A 2023; 120:e2220180120. [PMID: 37459524 PMCID: PMC10372579 DOI: 10.1073/pnas.2220180120] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 06/02/2023] [Indexed: 07/20/2023] Open
Abstract
Short-range interactions and long-range contacts drive the 3D folding of structured proteins. The proteins' structure has a direct impact on their biological function. However, nearly 40% of the eukaryotes proteome is composed of intrinsically disordered proteins (IDPs) and protein regions that fluctuate between ensembles of numerous conformations. Therefore, to understand their biological function, it is critical to depict how the structural ensemble statistics correlate to the IDPs' amino acid sequence. Here, using small-angle X-ray scattering and time-resolved Förster resonance energy transfer (trFRET), we study the intramolecular structural heterogeneity of the neurofilament low intrinsically disordered tail domain (NFLt). Using theoretical results of polymer physics, we find that the Flory scaling exponent of NFLt subsegments correlates linearly with their net charge, ranging from statistics of ideal to self-avoiding chains. Surprisingly, measuring the same segments in the context of the whole NFLt protein, we find that regardless of the peptide sequence, the segments' structural statistics are more expanded than when measured independently. Our findings show that while polymer physics can, to some level, relate the IDP's sequence to its ensemble conformations, long-range contacts between distant amino acids play a crucial role in determining intramolecular structures. This emphasizes the necessity of advanced polymer theories to fully describe IDPs ensembles with the hope that it will allow us to model their biological function.
Collapse
Affiliation(s)
- Gil Koren
- The School of Physics and Astronomy, Department of Condensed Matter, Tel Aviv University, Tel Aviv69978, Israel
- The Center for Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv69978, Israel
- The Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv69978, Israel
| | - Sagi Meir
- The School of Physics and Astronomy, Department of Condensed Matter, Tel Aviv University, Tel Aviv69978, Israel
- The Center for Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv69978, Israel
- The Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv69978, Israel
| | - Lennard Holschuh
- Applied Theoretical Physics-Computational Physics, Physikalisches Institut, Albert-Ludwigs-Universit Freiburg, FreiburgD-79104, Germany
| | | | - Tamara Ehm
- The School of Physics and Astronomy, Department of Condensed Matter, Tel Aviv University, Tel Aviv69978, Israel
- The Center for Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv69978, Israel
- The Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv69978, Israel
- Faculty of Physics and Center for NanoScience, Ludwig-Maximilians-Universität, MünchenD-80539, Germany
| | - Nadav Yahalom
- The Center for Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv69978, Israel
- The Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv69978, Israel
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences and Tel Aviv University Center for Light–Matter Interaction, Tel Aviv University, Tel Aviv6997801, Israel
| | - Adina Golombek
- The Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv69978, Israel
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences and Tel Aviv University Center for Light–Matter Interaction, Tel Aviv University, Tel Aviv6997801, Israel
| | - Tal Schwartz
- The Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv69978, Israel
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences and Tel Aviv University Center for Light–Matter Interaction, Tel Aviv University, Tel Aviv6997801, Israel
| | - Dmitri I. Svergun
- European Molecular Biology Laboratory, Hamburg Unit, Hamburg22607, Germany
| | - Omar A. Saleh
- BMSE Program, University of California, Santa Barbara, CA93110
- Materials Department, University of California, Santa Barbara, CA93110
| | - Joachim Dzubiella
- Applied Theoretical Physics-Computational Physics, Physikalisches Institut, Albert-Ludwigs-Universit Freiburg, FreiburgD-79104, Germany
- Cluster of Excellence livMatS @ FIT–Freiburg Center for Interactive Materials and Bioinspired Technologies, Albert-Ludwigs-Universit Freiburg, FreiburgD-79104, Germany
| | - Roy Beck
- The School of Physics and Astronomy, Department of Condensed Matter, Tel Aviv University, Tel Aviv69978, Israel
- The Center for Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv69978, Israel
- The Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv69978, Israel
| |
Collapse
|
27
|
Pesce F, Lindorff-Larsen K. Combining Experiments and Simulations to Examine the Temperature-Dependent Behavior of a Disordered Protein. J Phys Chem B 2023. [PMID: 37433228 DOI: 10.1021/acs.jpcb.3c01862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2023]
Abstract
Intrinsically disordered proteins are a class of proteins that lack stable folded conformations and instead adopt a range of conformations that determine their biochemical functions. The temperature-dependent behavior of such disordered proteins is complex and can vary depending on the specific protein and environment. Here, we have used molecular dynamics simulations and previously published experimental data to investigate the temperature-dependent behavior of histatin 5, a 24-residue-long polypeptide. We examined the hypothesis that histatin 5 undergoes a loss of polyproline II (PPII) structure with increasing temperature, leading to more compact conformations. We found that the conformational ensembles generated by the simulations generally agree with small-angle X-ray scattering data for histatin 5, but show some discrepancies with the hydrodynamic radius as probed by pulsed-field gradient NMR spectroscopy, and with the secondary structure information derived from circular dichroism. We attempted to reconcile these differences by reweighting the conformational ensembles against the scattering and NMR data. By doing so, we were in part able to capture the temperature-dependent behavior of histatin 5 and to link the observed decrease in hydrodynamic radius with increasing temperature to a loss of PPII structure. We were, however, unable to achieve agreement with both the scattering and NMR data within experimental errors. We discuss different possible reasons for this including inaccuracies in the force field, differences in conditions of the NMR and scattering experiments, and issues related to the calculation of the hydrodynamic radius from conformational ensembles. Our study highlights the importance of integrating multiple types of experimental data when modeling conformational ensembles of disordered proteins and how environmental factors such as the temperature influence them.
Collapse
Affiliation(s)
- Francesco Pesce
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark
| |
Collapse
|
28
|
Alston JJ, Ginell GM, Soranno A, Holehouse AS. The Analytical Flory Random Coil Is a Simple-to-Use Reference Model for Unfolded and Disordered Proteins. J Phys Chem B 2023; 127:4746-4760. [PMID: 37200094 PMCID: PMC10875986 DOI: 10.1021/acs.jpcb.3c01619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Denatured, unfolded, and intrinsically disordered proteins (collectively referred to here as unfolded proteins) can be described using analytical polymer models. These models capture various polymeric properties and can be fit to simulation results or experimental data. However, the model parameters commonly require users' decisions, making them useful for data interpretation but less clearly applicable as stand-alone reference models. Here we use all-atom simulations of polypeptides in conjunction with polymer scaling theory to parameterize an analytical model of unfolded polypeptides that behave as ideal chains (ν = 0.50). The model, which we call the analytical Flory random coil (AFRC), requires only the amino acid sequence as input and provides direct access to probability distributions of global and local conformational order parameters. The model defines a specific reference state to which experimental and computational results can be compared and normalized. As a proof-of-concept, we use the AFRC to identify sequence-specific intramolecular interactions in simulations of disordered proteins. We also use the AFRC to contextualize a curated set of 145 different radii of gyration obtained from previously published small-angle X-ray scattering experiments of disordered proteins. The AFRC is implemented as a stand-alone software package and is also available via a Google Colab notebook. In summary, the AFRC provides a simple-to-use reference polymer model that can guide intuition and aid in interpreting experimental or simulation results.
Collapse
Affiliation(s)
- Jhullian J. Alston
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Garrett M. Ginell
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Andrea Soranno
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Alex S. Holehouse
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| |
Collapse
|
29
|
Marasco M, Kirkpatrick J, Carlomagno T, Hub JS, Anselmi M. Experiment-guided molecular simulations define a heterogeneous structural ensemble for the PTPN11 tandem SH2 domains. Chem Sci 2023; 14:5743-5755. [PMID: 37265738 PMCID: PMC10231330 DOI: 10.1039/d3sc00746d] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 05/04/2023] [Indexed: 06/03/2023] Open
Abstract
SHP2 plays an important role in regulating cellular processes, and its pathogenic mutations cause developmental disorders and are linked to cancer. SHP2 is a multidomain protein, comprising two SH2 domains arranged in tandem, a catalytic PTP domain, and a disordered C-terminal tail. SHP2 is activated upon binding two linked phosphopeptides to its SH2 domains, and the peptide orientation and spacing between binding sites are critical for enzymatic activation. For decades, the tandem SH2 has been extensively studied to identify the relative orientation of the two SH2 domains that most effectively binds effectors. So far, neither crystallography nor experiments in solution have provided conclusive results. Using experiment-guided molecular simulations, we determine the heterogeneous structural ensemble of the tandem SH2 in solution in agreement with experimental data from small-angle X-ray scattering and NMR residual dipolar couplings. In the solution ensemble, N-SH2 adopts different orientations and positions relative to C-SH2. We suggest that the intrinsic structural plasticity of the tandem SH2 allows SHP2 to respond to external stimuli and is essential for its functional activity.
Collapse
Affiliation(s)
- Michelangelo Marasco
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center New York NY USA
| | - John Kirkpatrick
- School of Biosciences, University of Birmingham Edgbaston B15 2TT Birmingham UK
| | - Teresa Carlomagno
- School of Biosciences, University of Birmingham Edgbaston B15 2TT Birmingham UK
- Institute of Cancer and Genomic Sciences, University of Birmingham Edgbaston B15 2TT Birmingham UK
| | - Jochen S Hub
- Theoretical Physics and Center for Biophysics, Saarland University 66123 Saarbrücken Germany
| | - Massimiliano Anselmi
- Theoretical Physics and Center for Biophysics, Saarland University 66123 Saarbrücken Germany
| |
Collapse
|
30
|
Paladino A, Vitagliano L, Graziano G. The Action of Chemical Denaturants: From Globular to Intrinsically Disordered Proteins. BIOLOGY 2023; 12:biology12050754. [PMID: 37237566 DOI: 10.3390/biology12050754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/15/2023] [Accepted: 05/18/2023] [Indexed: 05/28/2023]
Abstract
Proteins perform their many functions by adopting either a minimal number of strictly similar conformations, the native state, or a vast ensemble of highly flexible conformations. In both cases, their structural features are highly influenced by the chemical environment. Even though a plethora of experimental studies have demonstrated the impact of chemical denaturants on protein structure, the molecular mechanism underlying their action is still debated. In the present review, after a brief recapitulation of the main experimental data on protein denaturants, we survey both classical and more recent interpretations of the molecular basis of their action. In particular, we highlight the differences and similarities of the impact that denaturants have on different structural classes of proteins, i.e., globular, intrinsically disordered (IDP), and amyloid-like assemblies. Particular attention has been given to the IDPs, as recent studies are unraveling their fundamental importance in many physiological processes. The role that computation techniques are expected to play in the near future is illustrated.
Collapse
Affiliation(s)
- Antonella Paladino
- Institute of Biostructures and Bioimaging, CNR, Via Pietro Castellino 111, 80131 Naples, Italy
| | - Luigi Vitagliano
- Institute of Biostructures and Bioimaging, CNR, Via Pietro Castellino 111, 80131 Naples, Italy
| | - Giuseppe Graziano
- Department of Science and Technology, University of Sannio, via Francesco de Sanctis snc, 82100 Benevento, Italy
| |
Collapse
|
31
|
Zhang O, Haghighatlari M, Li J, Liu ZH, Namini A, Teixeira JMC, Forman-Kay JD, Head-Gordon T. Learning to evolve structural ensembles of unfolded and disordered proteins using experimental solution data. J Chem Phys 2023; 158:174113. [PMID: 37144719 PMCID: PMC10163956 DOI: 10.1063/5.0141474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 04/11/2023] [Indexed: 05/06/2023] Open
Abstract
The structural characterization of proteins with a disorder requires a computational approach backed by experiments to model their diverse and dynamic structural ensembles. The selection of conformational ensembles consistent with solution experiments of disordered proteins highly depends on the initial pool of conformers, with currently available tools limited by conformational sampling. We have developed a Generative Recurrent Neural Network (GRNN) that uses supervised learning to bias the probability distributions of torsions to take advantage of experimental data types such as nuclear magnetic resonance J-couplings, nuclear Overhauser effects, and paramagnetic resonance enhancements. We show that updating the generative model parameters according to the reward feedback on the basis of the agreement between experimental data and probabilistic selection of torsions from learned distributions provides an alternative to existing approaches that simply reweight conformers of a static structural pool for disordered proteins. Instead, the biased GRNN, DynamICE, learns to physically change the conformations of the underlying pool of the disordered protein to those that better agree with experiments.
Collapse
Affiliation(s)
- Oufan Zhang
- Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Mojtaba Haghighatlari
- Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Jie Li
- Kenneth S. Pitzer Theory Center and Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | - Ashley Namini
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5S 1A8, Canada
| | | | | | | |
Collapse
|
32
|
Luo S, Wohl S, Zheng W, Yang S. Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery. Biomolecules 2023; 13:biom13030530. [PMID: 36979465 PMCID: PMC10046839 DOI: 10.3390/biom13030530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/07/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023] Open
Abstract
Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.
Collapse
Affiliation(s)
- Shuqi Luo
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Samuel Wohl
- Department of Physics, Arizona State University, Tempe, AZ 85287, USA
| | - Wenwei Zheng
- College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ 85212, USA
- Correspondence: (W.Z.); (S.Y.)
| | - Sichun Yang
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA
- Correspondence: (W.Z.); (S.Y.)
| |
Collapse
|
33
|
Alston JJ, Ginell GM, Soranno A, Holehouse AS. The analytical Flory random coil is a simple-to-use reference model for unfolded and disordered proteins. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.12.531990. [PMID: 36993592 PMCID: PMC10054940 DOI: 10.1101/2023.03.12.531990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Denatured, unfolded, and intrinsically disordered proteins (collectively referred to here as unfolded proteins) can be described using analytical polymer models. These models capture various polymeric properties and can be fit to simulation results or experimental data. However, the model parameters commonly require users' decisions, making them useful for data interpretation but less clearly applicable as stand-alone reference models. Here we use all-atom simulations of polypeptides in conjunction with polymer scaling theory to parameterize an analytical model of unfolded polypeptides that behave as ideal chains (ν = 0.50). The model, which we call the analytical Flory Random Coil (AFRC), requires only the amino acid sequence as input and provides direct access to probability distributions of global and local conformational order parameters. The model defines a specific reference state to which experimental and computational results can be compared and normalized. As a proof-of-concept, we use the AFRC to identify sequence-specific intramolecular interactions in simulations of disordered proteins. We also use the AFRC to contextualize a curated set of 145 different radii of gyration obtained from previously published small-angle X-ray scattering experiments of disordered proteins. The AFRC is implemented as a stand-alone software package and is also available via a Google colab notebook. In summary, the AFRC provides a simple-to-use reference polymer model that can guide intuition and aid in interpreting experimental or simulation results.
Collapse
Affiliation(s)
- Jhullian J. Alston
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Garrett M. Ginell
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Andrea Soranno
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| | - Alex S. Holehouse
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA
| |
Collapse
|
34
|
Lalmansingh JM, Keeley AT, Ruff KM, Pappu RV, Holehouse AS. SOURSOP: A Python package for the analysis of simulations of intrinsically disordered proteins. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.16.528879. [PMID: 36824878 PMCID: PMC9949127 DOI: 10.1101/2023.02.16.528879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite SOURSOP, an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.
Collapse
|
35
|
Tesei G, Lindorff-Larsen K. Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range. OPEN RESEARCH EUROPE 2023; 2:94. [PMID: 37645312 PMCID: PMC10450847 DOI: 10.12688/openreseurope.14967.2] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/16/2022] [Indexed: 08/31/2023]
Abstract
The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.
Collapse
Affiliation(s)
- Giulio Tesei
- Structural Biology and NMR Laboratory & the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory & the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
36
|
Pesce F, Newcombe EA, Seiffert P, Tranchant EE, Olsen JG, Grace CR, Kragelund BB, Lindorff-Larsen K. Assessment of models for calculating the hydrodynamic radius of intrinsically disordered proteins. Biophys J 2023; 122:310-321. [PMID: 36518077 PMCID: PMC9892621 DOI: 10.1016/j.bpj.2022.12.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 11/18/2022] [Accepted: 12/09/2022] [Indexed: 12/15/2022] Open
Abstract
Diffusion measurements by pulsed-field gradient NMR and fluorescence correlation spectroscopy can be used to probe the hydrodynamic radius of proteins, which contains information about the overall dimension of a protein in solution. The comparison of this value with structural models of intrinsically disordered proteins is nonetheless impaired by the uncertainty of the accuracy of the methods for computing the hydrodynamic radius from atomic coordinates. To tackle this issue, we here build conformational ensembles of 11 intrinsically disordered proteins that we ensure are in agreement with measurements of compaction by small-angle x-ray scattering. We then use these ensembles to identify the forward model that more closely fits the radii derived from pulsed-field gradient NMR diffusion experiments. Of the models we examined, we find that the Kirkwood-Riseman equation provides the best description of the hydrodynamic radius probed by pulsed-field gradient NMR experiments. While some minor discrepancies remain, our results enable better use of measurements of the hydrodynamic radius in integrative modeling and for force field benchmarking and parameterization.
Collapse
Affiliation(s)
- Francesco Pesce
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Estella A Newcombe
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Pernille Seiffert
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Emil E Tranchant
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Johan G Olsen
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Christy R Grace
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Birthe B Kragelund
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| |
Collapse
|
37
|
Tesei G, Lindorff-Larsen K. Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range. OPEN RESEARCH EUROPE 2023; 2:94. [PMID: 37645312 PMCID: PMC10450847 DOI: 10.12688/openreseurope.14967.1] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/16/2022] [Indexed: 02/13/2024]
Abstract
The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.
Collapse
Affiliation(s)
- Giulio Tesei
- Structural Biology and NMR Laboratory & the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory & the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
38
|
Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology. Biomolecules 2023; 13:biom13010124. [PMID: 36671509 PMCID: PMC9856150 DOI: 10.3390/biom13010124] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/01/2023] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
Intense study of intrinsically disordered proteins (IDPs) did not begin in earnest until the late 1990s when a few groups, working independently, convinced the community that these 'weird' proteins could have important functions. Over the past two decades, it has become clear that IDPs play critical roles in a multitude of biological phenomena with prominent examples including coordination in signaling hubs, enabling gene regulation, and regulating ion channels, just to name a few. One contributing factor that delayed appreciation of IDP functional significance is the experimental difficulty in characterizing their dynamic conformations. The combined application of multiple methods, termed integrative structural biology, has emerged as an essential approach to understanding IDP phenomena. Here, we review some of the recent applications of the integrative structural biology philosophy to study IDPs.
Collapse
|
39
|
Das D, Mukhopadhyay S. Molecular Origin of Internal Friction in Intrinsically Disordered Proteins. Acc Chem Res 2022; 55:3470-3480. [PMID: 36346711 DOI: 10.1021/acs.accounts.2c00528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Protein folding and dynamics are controlled by an interplay of thermal and viscosity effects. The effect of viscous drag through the solvent molecules is described by the classic Kramers theory in the high friction limit, which considers the dampening of the reactant molecules in the solution and quantifies the dependence of the reaction rate on the frictional drag. In addition to the external energy dissipation originating from the surrounding solvent molecules, there is an additional mode of internal energy dissipative force operative within the polypeptide chain reflecting the internal resistance of the chain to its conformational alterations. This dry, solvent-independent intrinsic frictional drag is termed internal friction. In the case of natively folded proteins, the physical origin of internal friction is primarily attributed to the intrachain interactions or other nonnative interactions in their compact states. However, the molecular origin of internal friction in intrinsically disordered proteins (IDPs) remains elusive.In this Account, we address this fundamental issue: what are the principal drivers of viscosity-independent (dry) friction in highly solvated, expanded, conformationally flexible, rapidly fluctuating IDPs that do not possess persistent intrachain interactions? IDPs exhibit diffusive conformational dynamics that is predominantly dominated by the segmental motion of the backbone arising due to the dihedral rotations in the Ramachandran Φ-Ψ space. The physical origin of friction in a complex biopolymeric system such as IDPs can be described by classic polymer models, namely, Rouse/Zimm models with internal friction. These one-dimensional models do not invoke torsional fluctuation components. Kuhn's classic description includes the connection between internal friction and microscopic dihedral hopping. Based on our time-resolved fluorescence anisotropy results, we describe that the sequence-dependent, collective, short-range backbone dihedral rotations govern localized internal friction in an archetypal IDP, namely, α-synuclein. The highly sensitive, residue-specific fluorescence depolarization kinetics offers a potent methodology to characterize and quantify the directional decorrelation engendered due to the short-range dihedral relaxation of the polypeptide backbone in the dihedral space. We utilized this characteristic relaxation time scale as our dynamic readout to quantify the site-specific frictional component. Our linear viscosity-dependent model of torsional relaxation time scale furnished a finite nonzero time constant at the zero solvent viscosity representing the solvent-independent internal friction. These results unveil the effect of the degree of dihedral restraining parameter on the internal friction component by showing that a restrained proline residue imparts higher torsional stiffness in the chain segments and, therefore, exhibits higher internal friction. This Account sheds light on the molecular underpinning of the sequence-specific internal friction in IDPs and will be of interest to unmask the role of internal friction in a diverse range of biomolecular processes involving binding-induced folding, allosteric interaction, protein misfolding and aggregation, and biomolecular condensation via phase separation.
Collapse
Affiliation(s)
- Debapriya Das
- Centre for Protein Science, Design and Engineering, Indian Institute of Science Education and Research (IISER) Mohali, Knowledge City, Sector 81, SAS Nagar, Mohali, Punjab 140306, India.,Department of Chemical Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Knowledge City, Sector 81, SAS Nagar, Mohali, Punjab 140306, India
| | - Samrat Mukhopadhyay
- Centre for Protein Science, Design and Engineering, Indian Institute of Science Education and Research (IISER) Mohali, Knowledge City, Sector 81, SAS Nagar, Mohali, Punjab 140306, India.,Department of Chemical Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Knowledge City, Sector 81, SAS Nagar, Mohali, Punjab 140306, India.,Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Knowledge City, Sector 81, SAS Nagar, Mohali, Punjab 140306, India
| |
Collapse
|
40
|
The biophysics of disordered proteins from the point of view of single-molecule fluorescence spectroscopy. Essays Biochem 2022; 66:875-890. [PMID: 36416865 PMCID: PMC9760427 DOI: 10.1042/ebc20220065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 10/10/2022] [Accepted: 10/11/2022] [Indexed: 11/24/2022]
Abstract
Intrinsically disordered proteins (IDPs) and regions (IDRs) have emerged as key players across many biological functions and diseases. Differently from structured proteins, disordered proteins lack stable structure and are particularly sensitive to changes in the surrounding environment. Investigation of disordered ensembles requires new approaches and concepts for quantifying conformations, dynamics, and interactions. Here, we provide a short description of the fundamental biophysical properties of disordered proteins as understood through the lens of single-molecule fluorescence observations. Single-molecule Förster resonance energy transfer (FRET) and fluorescence correlation spectroscopy (FCS) provides an extensive and versatile toolbox for quantifying the characteristics of conformational distributions and the dynamics of disordered proteins across many different solution conditions, both in vitro and in living cells.
Collapse
|
41
|
Gama Lima Costa R, Fushman D. Reweighting methods for elucidation of conformation ensembles of proteins. Curr Opin Struct Biol 2022; 77:102470. [PMID: 36183447 PMCID: PMC9771963 DOI: 10.1016/j.sbi.2022.102470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/24/2022] [Accepted: 08/28/2022] [Indexed: 12/24/2022]
Abstract
Proteins are inherently dynamic macromolecules that exist in equilibrium among multiple conformational states, and motions of protein backbone and side chains are fundamental to biological function. The ability to characterize the conformational landscape is particularly important for intrinsically disordered proteins, multidomain proteins, and weakly bound complexes, where single-structure representations are inadequate. As the focus of structural biology shifts from relatively rigid macromolecules toward larger and more complex systems and molecular assemblies, there is a need for structural approaches that can paint a more realistic picture of such conformationally heterogeneous systems. Here, we review reweighting methods for elucidation of structural ensembles based on experimental data, with the focus on applications to multidomain proteins.
Collapse
Affiliation(s)
- Raquel Gama Lima Costa
- Chemical Physics Program, Institute for Physical Sciences and Technology, University of Maryland, College Park, 20742, MD, USA.
| | - David Fushman
- Chemical Physics Program, Institute for Physical Sciences and Technology, University of Maryland, College Park, 20742, MD, USA; Department of Chemistry and Biochemistry, Center for Biomolecular Structure and Organization, University of Maryland, College Park, 20742, MD, USA.
| |
Collapse
|
42
|
Zheng W, Du Z, Ko SB, Wickramasinghe NP, Yang S. Incorporation of D 2O-Induced Fluorine Chemical Shift Perturbations into Ensemble-Structure Characterization of the ERalpha Disordered Region. J Phys Chem B 2022; 126:9176-9186. [PMID: 36331868 PMCID: PMC10066504 DOI: 10.1021/acs.jpcb.2c05456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Structural characterization of intrinsically disordered proteins (IDPs) requires a concerted effort between experiments and computations by accounting for their conformational heterogeneity. Given the diversity of experimental tools providing local and global structural information, constructing an experimental restraint-satisfying structural ensemble remains challenging. Here, we use the disordered N-terminal domain (NTD) of the estrogen receptor alpha (ERalpha) as a model system to combine existing small-angle X-ray scattering (SAXS) and hydroxyl radical protein footprinting (HRPF) data and newly acquired solvent accessibility data via D2O-induced fluorine chemical shifting (DFCS) measurements. A new set of DFCS data for the solvent exposure of a set of 12 amino acid positions were added to complement previously acquired HRPF measurements for the solvent exposure of the other 16 nonoverlapping amino acids, thereby improving the NTD ensemble characterization considerably. We also found that while choosing an initial ensemble of structures generated from a different atomic-level force field or sampling/modeling method can lead to distinct contact maps even when the same sets of experimental measurements were used for ensemble-fitting, comparative analyses from these initial ensembles reveal commonly recurring structural features in their ensemble-averaged contact map. Specifically, nonlocal or long-range transient interactions were found consistently between the N-terminal segments and the central region, sufficient to mediate the conformational ensemble and regulate how the NTD interacts with its coactivator proteins.
Collapse
Affiliation(s)
- Wenwei Zheng
- College of Integrative Sciences and Arts, Arizona State University, Mesa, Arizona 85212, United States
| | - Zhanwen Du
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106, United States
| | - Soo Bin Ko
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106, United States
| | | | - Sichun Yang
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106, United States
| |
Collapse
|
43
|
Förster D, Idier J, Liberti L, Mucherino A, Lin JH, Malliavin TE. Low-resolution description of the conformational space for intrinsically disordered proteins. Sci Rep 2022; 12:19057. [PMID: 36352011 PMCID: PMC9646904 DOI: 10.1038/s41598-022-21648-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 09/29/2022] [Indexed: 11/11/2022] Open
Abstract
Intrinsically disordered proteins (IDP) are at the center of numerous biological processes, and attract consequently extreme interest in structural biology. Numerous approaches have been developed for generating sets of IDP conformations verifying a given set of experimental measurements. We propose here to perform a systematic enumeration of protein conformations, carried out using the TAiBP approach based on distance geometry. This enumeration was performed on two proteins, Sic1 and pSic1, corresponding to unphosphorylated and phosphorylated states of an IDP. The relative populations of the obtained conformations were then obtained by fitting SAXS curves as well as Ramachandran probability maps, the original finite mixture approach RamaMix being developed for this second task. The similarity between profiles of local gyration radii provides to a certain extent a converged view of the Sic1 and pSic1 conformational space. Profiles and populations are thus proposed for describing IDP conformations. Different variations of the resulting gyration radius between phosphorylated and unphosphorylated states are observed, depending on the set of enumerated conformations as well as on the methods used for obtaining the populations.
Collapse
Affiliation(s)
- Daniel Förster
- grid.112485.b0000 0001 0217 6921UMR7374 Interfaces, Confinement, Matériaux et Nanostructures, Université d’Orléans, Orléans, France
| | - Jérôme Idier
- grid.503212.70000 0000 9563 6044UMR6004 Laboratoire des Sciences du Numérique de Nantes, Nantes, France
| | - Leo Liberti
- grid.508893.fLIX UMR 7161 CNRS École Polytechnique, Institut Polytechnique de Paris, 91128 Palaiseau, France
| | - Antonio Mucherino
- grid.420225.30000 0001 2298 7270IRISA, University of Rennes 1, Rennes, France
| | - Jung-Hsin Lin
- grid.509455.8Biomedical Translation Research Center, Academia Sinica, Taipei, Taiwan
| | - Thérèse E. Malliavin
- grid.428999.70000 0001 2353 6535Institut Pasteur, Université Paris Cité, CNRS UMR3528, Unité de Bioinformatique Structurale, F-75015 Paris, France ,grid.29172.3f0000 0001 2194 6418Université de Lorraine, CNRS UMR7019, LPCT, F-54000 Nancy, France
| |
Collapse
|
44
|
Lenard AJ, Mulder FAA, Madl T. Solvent paramagnetic relaxation enhancement as a versatile method for studying structure and dynamics of biomolecular systems. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2022; 132-133:113-139. [PMID: 36496256 DOI: 10.1016/j.pnmrs.2022.09.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 09/14/2022] [Accepted: 09/15/2022] [Indexed: 06/17/2023]
Abstract
Solvent paramagnetic relaxation enhancement (sPRE) is a versatile nuclear magnetic resonance (NMR)-based method that allows characterization of the structure and dynamics of biomolecular systems through providing quantitative experimental information on solvent accessibility of NMR-active nuclei. Addition of soluble paramagnetic probes to the solution of a biomolecule leads to paramagnetic relaxation enhancement in a concentration-dependent manner. Here we review recent progress in the sPRE-based characterization of structural and dynamic properties of biomolecules and their complexes, and aim to deliver a comprehensive illustration of a growing number of applications of the method to various biological systems. We discuss the physical principles of sPRE measurements and provide an overview of available co-solute paramagnetic probes. We then explore how sPRE, in combination with complementary biophysical techniques, can further advance biomolecular structure determination, identification of interaction surfaces within protein complexes, and probing of conformational changes and low-population transient states, as well as deliver insights into weak, nonspecific, and transient interactions between proteins and co-solutes. In addition, we present examples of how the incorporation of solvent paramagnetic probes can improve the sensitivity of NMR experiments and discuss the prospects of applying sPRE to NMR metabolomics, drug discovery, and the study of intrinsically disordered proteins.
Collapse
Affiliation(s)
- Aneta J Lenard
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Ageing, Molecular Biology and Biochemistry, Research Unit Integrative Structural Biology, Medical University of Graz, 8010 Graz, Austria.
| | - Frans A A Mulder
- Interdisciplinary Nanoscience Center and Department of Chemistry, University of Aarhus, DK-8000 Aarhus, Denmark; Institute of Biochemistry, Johannes Kepler Universität Linz, 4040 Linz, Austria.
| | - Tobias Madl
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Ageing, Molecular Biology and Biochemistry, Research Unit Integrative Structural Biology, Medical University of Graz, 8010 Graz, Austria; BioTechMed-Graz, 8010 Graz, Austria.
| |
Collapse
|
45
|
Theillet FX, Luchinat E. In-cell NMR: Why and how? PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2022; 132-133:1-112. [PMID: 36496255 DOI: 10.1016/j.pnmrs.2022.04.002] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 04/19/2022] [Accepted: 04/27/2022] [Indexed: 06/17/2023]
Abstract
NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.
Collapse
Affiliation(s)
- Francois-Xavier Theillet
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France.
| | - Enrico Luchinat
- Dipartimento di Scienze e Tecnologie Agro-Alimentari, Alma Mater Studiorum - Università di Bologna, Piazza Goidanich 60, 47521 Cesena, Italy; CERM - Magnetic Resonance Center, and Neurofarba Department, Università degli Studi di Firenze, 50019 Sesto Fiorentino, Italy
| |
Collapse
|
46
|
Yu L, Brüschweiler R. Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins. PLoS Comput Biol 2022; 18:e1010036. [PMID: 36084124 PMCID: PMC9491582 DOI: 10.1371/journal.pcbi.1010036] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 09/21/2022] [Accepted: 08/03/2022] [Indexed: 12/29/2022] Open
Abstract
Intrinsically disordered proteins (IDPs) are highly dynamic systems that play an important role in cell signaling processes and their misfunction often causes human disease. Proper understanding of IDP function not only requires the realistic characterization of their three-dimensional conformational ensembles at atomic-level resolution but also of the time scales of interconversion between their conformational substates. Large sets of experimental data are often used in combination with molecular modeling to restrain or bias models to improve agreement with experiment. It is shown here for the N-terminal transactivation domain of p53 (p53TAD) and Pup, which are two IDPs that fold upon binding to their targets, how the latest advancements in molecular dynamics (MD) simulations methodology produces native conformational ensembles by combining replica exchange with series of microsecond MD simulations. They closely reproduce experimental data at the global conformational ensemble level, in terms of the distribution properties of the radius of gyration tensor, and at the local level, in terms of NMR properties including 15N spin relaxation, without the need for reweighting. Further inspection revealed that 10-20% of the individual MD trajectories display the formation of secondary structures not observed in the experimental NMR data. The IDP ensembles were analyzed by graph theory to identify dominant inter-residue contact clusters and characteristic amino-acid contact propensities. These findings indicate that modern MD force fields with residue-specific backbone potentials can produce highly realistic IDP ensembles sampling a hierarchy of nano- and picosecond time scales providing new insights into their biological function.
Collapse
Affiliation(s)
- Lei Yu
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio, United States of America
| | - Rafael Brüschweiler
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio, United States of America
- Department of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, Ohio, United States of America
- * E-mail:
| |
Collapse
|
47
|
Smyth S, Zhang Z, Bah A, Tsangaris TE, Dawson J, Forman-Kay JD, Gradinaru CC. Multisite phosphorylation and binding alter conformational dynamics of the 4E-BP2 protein. Biophys J 2022; 121:3049-3060. [PMID: 35841142 PMCID: PMC9463650 DOI: 10.1016/j.bpj.2022.07.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 05/19/2022] [Accepted: 07/11/2022] [Indexed: 11/02/2022] Open
Abstract
Intrinsically disordered proteins (IDPs) play critical roles in regulatory protein interactions, but detailed structural/dynamic characterization of their ensembles remain challenging, both in isolation and when they form dynamic "fuzzy" complexes. Such is the case for mRNA cap-dependent translation initiation, which is regulated by the interaction of the predominantly folded eukaryotic initiation factor 4E (eIF4E) with the intrinsically disordered eIF4E binding proteins (4E-BPs) in a phosphorylation-dependent manner. Single-molecule Förster resonance energy transfer showed that the conformational changes of 4E-BP2 induced by binding to eIF4E are non-uniform along the sequence; while a central region containing both motifs that bind to eIF4E expands and becomes stiffer, the C-terminal region is less affected. Fluorescence anisotropy decay revealed a non-uniform segmental flexibility around six different labeling sites along the chain. Dynamic quenching of these fluorescent probes by intrinsic aromatic residues measured via fluorescence correlation spectroscopy report on transient intra- and inter-molecular contacts on nanosecond-to-microsecond timescales. Upon hyperphosphorylation, which induces folding of ∼40 residues in 4E-BP2, the quenching rates decreased at most labeling sites. The chain dynamics around sites in the C-terminal region far away from the two binding motifs significantly increased upon binding to eIF4E, suggesting that this region is also involved in the highly dynamic 4E-BP2:eIF4E complex. Our time-resolved fluorescence data paint a sequence-level rigidity map of three states of 4E-BP2 differing in phosphorylation or binding status and distinguish regions that form contacts with eIF4E. This study adds complementary structural and dynamics information to recent studies of 4E-BP2, and it constitutes an important step toward a mechanistic understanding of this important IDP via integrative modeling.
Collapse
Affiliation(s)
- Spencer Smyth
- Department of Physics, University of Toronto, Toronto, Ontario, Canada; Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario, Canada
| | - Zhenfu Zhang
- Department of Physics, University of Toronto, Toronto, Ontario, Canada; Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario, Canada
| | - Alaji Bah
- Program in Molecular Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Thomas E Tsangaris
- Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario, Canada
| | - Jennifer Dawson
- Program in Molecular Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Julie D Forman-Kay
- Program in Molecular Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada
| | - Claudiu C Gradinaru
- Department of Physics, University of Toronto, Toronto, Ontario, Canada; Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario, Canada.
| |
Collapse
|
48
|
Gomes GNW, Namini A, Gradinaru CC. Integrative Conformational Ensembles of Sic1 Using Different Initial Pools and Optimization Methods. Front Mol Biosci 2022; 9:910956. [PMID: 35923464 PMCID: PMC9342850 DOI: 10.3389/fmolb.2022.910956] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 06/21/2022] [Indexed: 01/02/2023] Open
Abstract
Intrinsically disordered proteins play key roles in regulatory protein interactions, but their detailed structural characterization remains challenging. Here we calculate and compare conformational ensembles for the disordered protein Sic1 from yeast, starting from initial ensembles that were generated either by statistical sampling of the conformational landscape, or by molecular dynamics simulations. Two popular, yet contrasting optimization methods were used, ENSEMBLE and Bayesian Maximum Entropy, to achieve agreement with experimental data from nuclear magnetic resonance, small-angle X-ray scattering and single-molecule Förster resonance energy transfer. The comparative analysis of the optimized ensembles, including secondary structure propensity, inter-residue contact maps, and the distributions of hydrogen bond and pi interactions, revealed the importance of the physics-based generation of initial ensembles. The analysis also provides insights into designing new experiments that report on the least restrained features among the optimized ensembles. Overall, differences between ensembles optimized from different priors were greater than when using the same prior with different optimization methods. Generating increasingly accurate, reliable and experimentally validated ensembles for disordered proteins is an important step towards a mechanistic understanding of their biological function and involvement in various diseases.
Collapse
Affiliation(s)
- Gregory-Neal W. Gomes
- Department of Physics, University of Toronto, Toronto, ON, Canada
- *Correspondence: Gregory-Neal W. Gomes, ; Claudiu C. Gradinaru,
| | - Ashley Namini
- Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, ON, Canada
| | - Claudiu C. Gradinaru
- Department of Physics, University of Toronto, Toronto, ON, Canada
- Department of Chemical & Physical Sciences, University of Toronto Mississauga, Mississauga, ON, Canada
- *Correspondence: Gregory-Neal W. Gomes, ; Claudiu C. Gradinaru,
| |
Collapse
|
49
|
Ghosh K, Huihui J, Phillips M, Haider A. Rules of Physical Mathematics Govern Intrinsically Disordered Proteins. Annu Rev Biophys 2022; 51:355-376. [PMID: 35119946 PMCID: PMC9190209 DOI: 10.1146/annurev-biophys-120221-095357] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
In stark contrast to foldable proteins with a unique folded state, intrinsically disordered proteins and regions (IDPs) persist in perpetually disordered ensembles. Yet an IDP ensemble has conformational features-even when averaged-that are specific to its sequence. In fact, subtle changes in an IDP sequence can modulate its conformational features and its function. Recent advances in theoretical physics reveal a set of elegant mathematical expressions that describe the intricate relationships among IDP sequences, their ensemble conformations, and the regulation of their biological functions. These equations also describe the molecular properties of IDP sequences that predict similarities and dissimilarities in their functions and facilitate classification of sequences by function, an unmet challenge to traditional bioinformatics. These physical sequence-patterning metrics offer a promising new avenue for advancing synthetic biology at a time when multiple novel functional modes mediated by IDPs are emerging.
Collapse
Affiliation(s)
- Kingshuk Ghosh
- Department of Physics and Astronomy, University of Denver, Denver, Colorado, USA,Molecular and Cellular Biophysics Program, University of Denver, Denver, Colorado, USA
| | - Jonathan Huihui
- Department of Physics and Astronomy, University of Denver, Denver, Colorado, USA
| | - Michael Phillips
- Department of Physics and Astronomy, University of Denver, Denver, Colorado, USA
| | - Austin Haider
- Molecular and Cellular Biophysics Program, University of Denver, Denver, Colorado, USA
| |
Collapse
|
50
|
Camacho-Zarco AR, Schnapka V, Guseva S, Abyzov A, Adamski W, Milles S, Jensen MR, Zidek L, Salvi N, Blackledge M. NMR Provides Unique Insight into the Functional Dynamics and Interactions of Intrinsically Disordered Proteins. Chem Rev 2022; 122:9331-9356. [PMID: 35446534 PMCID: PMC9136928 DOI: 10.1021/acs.chemrev.1c01023] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
![]()
Intrinsically disordered
proteins are ubiquitous throughout all
known proteomes, playing essential roles in all aspects of cellular
and extracellular biochemistry. To understand their function, it is
necessary to determine their structural and dynamic behavior and to
describe the physical chemistry of their interaction trajectories.
Nuclear magnetic resonance is perfectly adapted to this task, providing
ensemble averaged structural and dynamic parameters that report on
each assigned resonance in the molecule, unveiling otherwise inaccessible
insight into the reaction kinetics and thermodynamics that are essential
for function. In this review, we describe recent applications of NMR-based
approaches to understanding the conformational energy landscape, the
nature and time scales of local and long-range dynamics and how they
depend on the environment, even in the cell. Finally, we illustrate
the ability of NMR to uncover the mechanistic basis of functional
disordered molecular assemblies that are important for human health.
Collapse
Affiliation(s)
| | - Vincent Schnapka
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | - Serafima Guseva
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | - Anton Abyzov
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | - Wiktor Adamski
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | - Sigrid Milles
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | | | - Lukas Zidek
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 5, 82500 Brno, Czech Republic.,Central European Institute of Technology, Masaryk University, Kamenice 5, 82500 Brno, Czech Republic
| | - Nicola Salvi
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | | |
Collapse
|