1
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Thomasen FE, Skaalum T, Kumar A, Srinivasan S, Vanni S, Lindorff-Larsen K. Rescaling protein-protein interactions improves Martini 3 for flexible proteins in solution. Nat Commun 2024; 15:6645. [PMID: 39103332 DOI: 10.1038/s41467-024-50647-9] [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: 05/29/2023] [Accepted: 07/15/2024] [Indexed: 08/07/2024] Open
Abstract
Multidomain proteins with flexible linkers and disordered regions play important roles in many cellular processes, but characterizing their conformational ensembles is difficult. We have previously shown that the coarse-grained model, Martini 3, produces too compact ensembles in solution, that may in part be remedied by strengthening protein-water interactions. Here, we show that decreasing the strength of protein-protein interactions leads to improved agreement with experimental data on a wide set of systems. We show that the 'symmetry' between rescaling protein-water and protein-protein interactions breaks down when studying interactions with or within membranes; rescaling protein-protein interactions better preserves the binding specificity of proteins with lipid membranes, whereas rescaling protein-water interactions preserves oligomerization of transmembrane helices. We conclude that decreasing the strength of protein-protein interactions improves the accuracy of Martini 3 for IDPs and multidomain proteins, both in solution and in the presence of a lipid membrane.
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Affiliation(s)
- F Emil Thomasen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200, Copenhagen N, Denmark.
| | - Tórur Skaalum
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200, Copenhagen N, Denmark
| | - Ashutosh Kumar
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Swiss National Center for Competence in Research (NCCR) Bio-inspired Materials, University of Fribourg, Chemin des Verdiers 4, CH-1700, Fribourg, Switzerland
| | | | - Stefano Vanni
- Department of Biology, University of Fribourg, Fribourg, Switzerland.
- Swiss National Center for Competence in Research (NCCR) Bio-inspired Materials, University of Fribourg, Chemin des Verdiers 4, CH-1700, Fribourg, Switzerland.
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200, Copenhagen N, Denmark.
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2
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Wasim A, Menon S, Mondal J. Modulation of α-synuclein aggregation amid diverse environmental perturbation. eLife 2024; 13:RP95180. [PMID: 39087984 PMCID: PMC11293868 DOI: 10.7554/elife.95180] [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] [Indexed: 08/02/2024] Open
Abstract
Intrinsically disordered protein α-synuclein (αS) is implicated in Parkinson's disease due to its aberrant aggregation propensity. In a bid to identify the traits of its aggregation, here we computationally simulate the multi-chain association process of αS in aqueous as well as under diverse environmental perturbations. In particular, the aggregation of αS in aqueous and varied environmental condition led to marked concentration differences within protein aggregates, resembling liquid-liquid phase separation (LLPS). Both saline and crowded settings enhanced the LLPS propensity. However, the surface tension of αS droplet responds differently to crowders (entropy-driven) and salt (enthalpy-driven). Conformational analysis reveals that the IDP chains would adopt extended conformations within aggregates and would maintain mutually perpendicular orientations to minimize inter-chain electrostatic repulsions. The droplet stability is found to stem from a diminished intra-chain interactions in the C-terminal regions of αS, fostering inter-chain residue-residue interactions. Intriguingly, a graph theory analysis identifies small-world-like networks within droplets across environmental conditions, suggesting the prevalence of a consensus interaction patterns among the chains. Together these findings suggest a delicate balance between molecular grammar and environment-dependent nuanced aggregation behavior of αS.
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Affiliation(s)
- Abdul Wasim
- Tata Institute of Fundamental ResearchHyderabadIndia
| | - Sneha Menon
- Tata Institute of Fundamental ResearchHyderabadIndia
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3
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Varenyk Y, Theodorakis PE, Pham DQH, Li MS, Krupa P. Exploring Structural Insights of Aβ42 and α-Synuclein Monomers and Heterodimer: A Comparative Study Using Implicit and Explicit Solvent Simulations. J Phys Chem B 2024; 128:4655-4669. [PMID: 38700150 PMCID: PMC11103699 DOI: 10.1021/acs.jpcb.4c00503] [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: 01/24/2024] [Revised: 04/10/2024] [Accepted: 04/16/2024] [Indexed: 05/05/2024]
Abstract
Protein misfolding, aggregation, and fibril formation play a central role in the development of severe neurological disorders, including Alzheimer's and Parkinson's diseases. The structural stability of mature fibrils in these diseases is of great importance, as organisms struggle to effectively eliminate amyloid plaques. To address this issue, it is crucial to investigate the early stages of fibril formation when monomers aggregate into small, toxic, and soluble oligomers. However, these structures are inherently disordered, making them challenging to study through experimental approaches. Recently, it has been shown experimentally that amyloid-β 42 (Aβ42) and α-synuclein (α-Syn) can coassemble. This has motivated us to investigate the interaction between their monomers as a first step toward exploring the possibility of forming heterodimeric complexes. In particular, our study involves the utilization of various Amber and CHARMM force-fields, employing both implicit and explicit solvent models in replica exchange and conventional simulation modes. This comprehensive approach allowed us to assess the strengths and weaknesses of these solvent models and force fields in comparison to experimental and theoretical findings, ensuring the highest level of robustness. Our investigations revealed that Aβ42 and α-Syn monomers can indeed form stable heterodimers, and the resulting heterodimeric model exhibits stronger interactions compared to the Aβ42 dimer. The binding of α-Syn to Aβ42 reduces the propensity of Aβ42 to adopt fibril-prone conformations and induces significant changes in its conformational properties. Notably, in AMBER-FB15 and CHARMM36m force fields with the use of explicit solvent, the presence of Aβ42 significantly increases the β-content of α-Syn, consistent with the experiments showing that Aβ42 triggers α-Syn aggregation. Our analysis clearly shows that although the use of implicit solvent resulted in too large compactness of monomeric α-Syn, structural properties of monomeric Aβ42 and the heterodimer were preserved in explicit-solvent simulations. We anticipate that our study sheds light on the interaction between α-Syn and Aβ42 proteins, thus providing the atom-level model required to assess the initial stage of aggregation mechanisms related to Alzheimer's and Parkinson's diseases.
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Affiliation(s)
- Yuliia Varenyk
- Institute
of Physics Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
- Department
of Theoretical Chemistry, University of
Vienna, Vienna 1090, Austria
| | | | - Dinh Q. H. Pham
- Institute
of Physics Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
| | - Mai Suan Li
- Institute
of Physics Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
| | - Paweł Krupa
- Institute
of Physics Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
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4
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Pietrek LM, Stelzl LS, Hummer G. Hierarchical Assembly of Single-Stranded RNA. J Chem Theory Comput 2024; 20:2246-2260. [PMID: 38361440 PMCID: PMC10938505 DOI: 10.1021/acs.jctc.3c01049] [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: 09/22/2023] [Revised: 12/09/2023] [Accepted: 01/25/2024] [Indexed: 02/17/2024]
Abstract
Single-stranded RNA (ssRNA) plays a major role in the flow of genetic information-most notably, in the form of messenger RNA (mRNA)-and in the regulation of biological processes. The highly dynamic nature of chains of unpaired nucleobases challenges structural characterizations of ssRNA by experiments or molecular dynamics (MD) simulations alike. Here, we use hierarchical chain growth (HCG) to construct ensembles of ssRNA chains. HCG assembles the structures of protein and nucleic acid chains from fragment libraries created by MD simulations. Applied to homo- and heteropolymeric ssRNAs of different lengths, we find that HCG produces structural ensembles that overall are in good agreement with diverse experiments, including nuclear magnetic resonance (NMR), small-angle X-ray scattering (SAXS), and single-molecule Förster resonance energy transfer (FRET). The agreement can be further improved by ensemble refinement using Bayesian inference of ensembles (BioEn). HCG can also be used to assemble RNA structures that combine base-paired and base-unpaired regions, as illustrated for the 5' untranslated region (UTR) of SARS-CoV-2 RNA.
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Affiliation(s)
- Lisa M. Pietrek
- Department
of Theoretical Biophysics, Max Planck Institute
of Biophysics, Max-von-Laue-Straße 3, 60438 Frankfurt am Main, Germany
| | - Lukas S. Stelzl
- Faculty
of Biology, Johannes Gutenberg University
Mainz, Gresemundweg 2, 55128 Mainz, Germany
- KOMET
1, Institute of Physics, Johannes Gutenberg
University Mainz, 55099 Mainz, Germany
- Institute
of Molecular Biology (IMB), 55128 Mainz, Germany
| | - Gerhard Hummer
- Department
of Theoretical Biophysics, Max Planck Institute
of Biophysics, Max-von-Laue-Straße 3, 60438 Frankfurt am Main, Germany
- Institute
for Biophysics, Goethe University, Max-von-Laue-Straße 9, 60438 Frankfurt am Main, Germany
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5
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Kharche S, Yadav M, Hande V, Prakash S, Sengupta D. Improved Protein Dynamics and Hydration in the Martini3 Coarse-Grain Model. J Chem Inf Model 2024; 64:837-850. [PMID: 38291973 DOI: 10.1021/acs.jcim.3c00802] [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: 02/01/2024]
Abstract
The Martini coarse-grain force-field has emerged as an important framework to probe cellular processes at experimentally relevant time- and length-scales. However, the recently developed version, the Martini3 force-field with the implemented Go̅ model (Martini3Go̅), as well as previous variants of the Martini model have not been benchmarked and rigorously tested for globular proteins. In this study, we consider three globular proteins, ubiquitin, lysozyme, and cofilin, and compare protein dynamics and hydration with observables from experiments and all-atom simulations. We show that the Martini3Go̅ model is able to accurately model the structural and dynamic features of small globular proteins. Overall, the structural integrity of the proteins is maintained, as validated by contact maps, radii of gyration (Rg), and SAXS profiles. The chemical shifts predicted from the ensemble sampled in the simulations are consistent with the experimental data. Further, a good match is observed in the protein-water interaction energetics, and the hydration levels of the residues are similar to atomistic simulations. However, the protein-water interaction dynamics is not accurately represented and appears to depend on the protein structural complexity, residue specificity, and water dynamics. Our work is a step toward testing and assessing the Martini3Go̅ model and provides insights into future efforts to refine Martini models with improved solvation effects and better correspondence to the underlying all-atom systems.
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Affiliation(s)
- Shalmali Kharche
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Manjul Yadav
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Vrushali Hande
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Shikha Prakash
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Durba Sengupta
- CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
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6
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Tolstova AP, Makarov AA, Adzhubei AA. Structure Comparison of Beta Amyloid Peptide Aβ 1-42 Isoforms. Molecular Dynamics Modeling. J Chem Inf Model 2024; 64:918-932. [PMID: 38241093 DOI: 10.1021/acs.jcim.3c01624] [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: 01/21/2024]
Abstract
Beta amyloid peptide Aβ 1-42 (Aβ42) has a unique dual role in the human organism, as both the peptide with an important physiological function and one of the most toxic biological compounds provoking Alzheimer's disease (AD). There are several known Aβ42 isoforms that we discuss here that are highly neurotoxic and lead to the early onset of AD. Aβ42 is an intrinsically disordered protein with no experimentally solved structure under physiological conditions. The objective of this research was to establish the appropriate molecular dynamics (MD) methodology and model a uniform set of structures for the Aβ42 isoforms that form the core of this study. For that purpose, force field selection and verification including convergence testing for MD simulations was made. Replica exchange MD and conventional MD modeling of several Aβ42 and Aβ16 isoforms that have neurotoxic and amyloidogenic effects impacting the severity of Alzheimer's disease were carried out with the optimal force field and solvent parameters. A standardized ensemble of structures for the Aβ42 and Aβ16 isoforms covering 30-50% of the conformational ensembles extracted from the free energy minima was calculated from MD trajectories. The resulting data set of modeled structures includes Aβ42 wild type, isoD7, pS8, D7H, and H6R-Aβ42 and Aβ16 wild type, isoD7, pS8, D7H, and H6R-Aβ16. The representative structures are given in the Supporting Information; they are open for public access. In the study, we also evaluated the differences between the structures of Aβ42 isoforms and speculate on their possible relevance to the known functions. Utilizing several representative structures for a single disordered protein for docking, with their subsequent averaging by conformations, would markedly increase the reliability of docking results.
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Affiliation(s)
- Anna P Tolstova
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia
| | - Alexander A Makarov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia
| | - Alexei A Adzhubei
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia
- Washington University School of Medicine and Health Sciences, Washington 20052, D.C., United States
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7
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Ballabio F, Paissoni C, Bollati M, de Rosa M, Capelli R, Camilloni C. Accurate and Efficient SAXS/SANS Implementation Including Solvation Layer Effects Suitable for Molecular Simulations. J Chem Theory Comput 2023; 19:8401-8413. [PMID: 37923304 PMCID: PMC10687869 DOI: 10.1021/acs.jctc.3c00864] [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: 08/07/2023] [Revised: 10/11/2023] [Accepted: 10/24/2023] [Indexed: 11/07/2023]
Abstract
Small-angle X-ray and neutron scattering (SAXS/SANS) provide valuable insights into the structure and dynamics of biomolecules in solution, complementing a wide range of structural techniques, including molecular dynamics simulations. As contrast-based methods, they are sensitive not only to structural properties but also to solvent-solute interactions. Their use in molecular dynamics simulations requires a forward model that should be as fast and accurate as possible. In this work, we demonstrate the feasibility of calculating SAXS and SANS intensities using a coarse-grained representation consisting of one bead per amino acid and three beads per nucleic acid, with form factors that can be corrected on the fly to account for solvation effects at no additional computational cost. By coupling this forward model with molecular dynamics simulations restrained with SAS data, it is possible to determine conformational ensembles or refine the structure and dynamics of proteins and nucleic acids in agreement with the experimental results. To assess the robustness of this approach, we applied it to gelsolin, for which we acquired SAXS data on its closed state, and to a UP1-microRNA complex, for which we used previously collected measurements. Our hybrid-resolution small-angle scattering (hySAS) implementation, being distributed in PLUMED, can be used with atomistic and coarse-grained simulations using diverse restraining strategies.
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Affiliation(s)
- Federico Ballabio
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
| | - Cristina Paissoni
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
| | - Michela Bollati
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
- Istituto
di Biofisica, Consiglio Nazionale delle
Ricerche (IBF-CNR), via
Alfonso Corti 12, 20133 Milano, Italy
| | - Matteo de Rosa
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
- Istituto
di Biofisica, Consiglio Nazionale delle
Ricerche (IBF-CNR), via
Alfonso Corti 12, 20133 Milano, Italy
| | - Riccardo Capelli
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
| | - Carlo Camilloni
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, via Celoria 26, 20133 Milano, Italy
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8
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Faidon Brotzakis Z, Löhr T, Truong S, Hoff S, Bonomi M, Vendruscolo M. Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy. Biochemistry 2023; 62:2407-2416. [PMID: 37477459 PMCID: PMC10433526 DOI: 10.1021/acs.biochem.3c00010] [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: 01/10/2023] [Revised: 06/03/2023] [Indexed: 07/22/2023]
Abstract
In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomistic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modeling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril, the side chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-β structure of amyloid fibrils.
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Affiliation(s)
- Z. Faidon Brotzakis
- Centre
for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, U.K.
| | - Thomas Löhr
- Centre
for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, U.K.
| | - Steven Truong
- Centre
for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, U.K.
| | - Samuel Hoff
- Department
of Structural Biology and Chemistry, Institut
Pasteur, Université Paris Cité CNRS UMR 3528, 75015 Paris, France
| | - Massimiliano Bonomi
- Department
of Structural Biology and Chemistry, Institut
Pasteur, Université Paris Cité CNRS UMR 3528, 75015 Paris, France
| | - Michele Vendruscolo
- Centre
for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, U.K.
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9
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Fagerberg E, Skepö M. Comparative Performance of Computer Simulation Models of Intrinsically Disordered Proteins at Different Levels of Coarse-Graining. J Chem Inf Model 2023; 63:4079-4087. [PMID: 37339604 PMCID: PMC10336962 DOI: 10.1021/acs.jcim.3c00113] [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: 01/24/2023] [Indexed: 06/22/2023]
Abstract
Coarse-graining is commonly used to decrease the computational cost of simulations. However, coarse-grained models are also considered to have lower transferability, with lower accuracy for systems outside the original scope of parametrization. Here, we benchmark a bead-necklace model and a modified Martini 2 model, both coarse-grained models, for a set of intrinsically disordered proteins, with the different models having different degrees of coarse-graining. The SOP-IDP model has earlier been used for this set of proteins; thus, those results are included in this study to compare how models with different levels of coarse-graining compare. The sometimes naive expectation of the least coarse-grained model performing best does not hold true for the experimental pool of proteins used here. Instead, it showed the least good agreement, indicating that one should not necessarily trust the otherwise intuitive notion of a more advanced model inherently being better in model choice.
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Affiliation(s)
- Eric Fagerberg
- Theoretical
Chemistry, Lund University, POB 124, SE-221 00 Lund, Sweden
| | - Marie Skepö
- Theoretical
Chemistry, Lund University, POB 124, SE-221 00 Lund, Sweden
- LINXS
- Institute of Advanced Neutron and X-ray Science, Scheelevägen 19, SE-223 70 Lund, Sweden
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10
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Devlin T, Fleming PJ, Loza N, Fleming KG. Generation of unfolded outer membrane protein ensembles defined by hydrodynamic properties. EUROPEAN BIOPHYSICS JOURNAL : EBJ 2023; 52:415-425. [PMID: 36899114 DOI: 10.1007/s00249-023-01639-y] [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: 10/31/2022] [Revised: 01/23/2023] [Accepted: 02/20/2023] [Indexed: 03/12/2023]
Abstract
Outer membrane proteins (OMPs) must exist as an unfolded ensemble while interacting with a chaperone network in the periplasm of Gram-negative bacteria. Here, we developed a method to model unfolded OMP (uOMP) conformational ensembles using the experimental properties of two well-studied OMPs. The overall sizes and shapes of the unfolded ensembles in the absence of a denaturant were experimentally defined by measuring the sedimentation coefficient as a function of urea concentration. We used these data to model a full range of unfolded conformations by parameterizing a targeted coarse-grained simulation protocol. The ensemble members were further refined by short molecular dynamics simulations to reflect proper torsion angles. The final conformational ensembles have polymer properties different from unfolded soluble and intrinsically disordered proteins and reveal inherent differences in the unfolded states that necessitate further investigation. Building these uOMP ensembles advances the understanding of OMP biogenesis and provides essential information for interpreting structures of uOMP-chaperone complexes.
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Affiliation(s)
- Taylor Devlin
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Patrick J Fleming
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Nicole Loza
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Karen G Fleming
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, 21218, USA.
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11
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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: 10] [Impact Index Per Article: 10.0] [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.
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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
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12
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Menon S, Mondal J. Conformational Plasticity in α-Synuclein and How Crowded Environment Modulates It. J Phys Chem B 2023; 127:4032-4049. [PMID: 37114769 DOI: 10.1021/acs.jpcb.3c00982] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
A 140-residue intrinsically disordered protein (IDP), α-synuclein (αS), is known to adopt conformations that are vastly plastic and susceptible to environmental cues and crowders. However, the inherently heterogeneous nature of αS has precluded a clear demarcation of its monomeric precursor between aggregation-prone and functionally relevant aggregation-resistant states and how a crowded environment could modulate their mutual dynamic equilibrium. Here, we identify an optimal set of distinct metastable states of αS in aqueous media by dissecting a 73 μs-long molecular dynamics ensemble via building a comprehensive Markov state model (MSM). Notably, the most populated metastable state corroborates with the dimension obtained from PRE-NMR studies of αS monomer, and it undergoes kinetic transition at diverse time scales with a weakly populated random-coil-like ensemble and a globular protein-like state. However, subjecting αS to a crowded environment results in a nonmonotonic compaction of these metastable conformations, thereby skewing the ensemble by either introducing new tertiary contacts or by reinforcing the innate contacts. The early stage of dimerization process is found to be considerably expedited in the presence of crowders, albeit promoting nonspecific interactions. Together with this, using an extensively sampled ensemble of αS, this exposition demonstrates that crowded environments can potentially modulate the conformational preferences of IDP that can either promote or inhibit aggregation events.
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Affiliation(s)
- Sneha Menon
- Tata Institute of Fundamental Research Hyderabad, Telangana 500046, India
| | - Jagannath Mondal
- Tata Institute of Fundamental Research Hyderabad, Telangana 500046, India
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13
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Sun X, Dyson HJ, Wright PE. Role of conformational dynamics in pathogenic protein aggregation. Curr Opin Chem Biol 2023; 73:102280. [PMID: 36878172 PMCID: PMC10033434 DOI: 10.1016/j.cbpa.2023.102280] [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: 11/22/2022] [Revised: 01/13/2023] [Accepted: 02/02/2023] [Indexed: 03/06/2023]
Abstract
The accumulation of pathogenic protein oligomers and aggregates is associated with several devastating amyloid diseases. As protein aggregation is a multi-step nucleation-dependent process beginning with unfolding or misfolding of the native state, it is important to understand how innate protein dynamics influence aggregation propensity. Kinetic intermediates composed of heterogeneous ensembles of oligomers are frequently formed on the aggregation pathway. Characterization of the structure and dynamics of these intermediates is critical to the understanding of amyloid diseases since oligomers appear to be the main cytotoxic agents. In this review, we highlight recent biophysical studies of the roles of protein dynamics in driving pathogenic protein aggregation, yielding new mechanistic insights that can be leveraged for design of aggregation inhibitors.
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Affiliation(s)
- Xun Sun
- Department of Integrative Structural and Computational Biology and Skaggs Institute of Chemical Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, 92037, USA
| | - H Jane Dyson
- Department of Integrative Structural and Computational Biology and Skaggs Institute of Chemical Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, 92037, USA
| | - Peter E Wright
- Department of Integrative Structural and Computational Biology and Skaggs Institute of Chemical Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, 92037, USA.
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14
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Structural ensembles of disordered proteins from hierarchical chain growth and simulation. Curr Opin Struct Biol 2023; 78:102501. [PMID: 36463772 DOI: 10.1016/j.sbi.2022.102501] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/26/2022] [Accepted: 10/28/2022] [Indexed: 12/03/2022]
Abstract
Disordered proteins and nucleic acids play key roles in cellular function and disease. Here, we review recent advances in the computational exploration of the conformational dynamics of flexible biomolecules. While atomistic molecular dynamics (MD) simulation has seen a lot of improvement in recent years, large-scale computing resources and careful validation are required to simulate full-length disordered biopolymers in solution. As a computationally efficient alternative, hierarchical chain growth (HCG) combines pre-sampled chain fragments in a statistically reproducible manner into ensembles of full-length atomically detailed biomolecular structures. Experimental data can be integrated during and after chain assembly. Applications to the neurodegeneration-linked proteins α-synuclein, tau, and TDP-43, including as condensate, illustrate the use of HCG. We conclude by highlighting the emerging connections to AI-based structural modeling including AlphaFold2.
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15
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Savva L, Platts JA. How Cu(II) binding affects structure and dynamics of α-synuclein revealed by molecular dynamics simulations. J Inorg Biochem 2023; 239:112068. [PMID: 36403437 DOI: 10.1016/j.jinorgbio.2022.112068] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/08/2022] [Accepted: 11/08/2022] [Indexed: 11/15/2022]
Abstract
We report accelerated molecular dynamics simulations of α-Synuclein and its complex with two Cu(II) ions bound to experimentally determined binding sites. Adding two Cu(II) ions, one bound to the N-terminal region and one to the C-terminus, decreases size and flexibility of the peptide while introducing significant new contacts within and between N-terminus and non-Aβ component (NAC). Cu(II) ions also alter the pattern of secondary structure within the peptide, inducing more and longer-lasting elements of secondary structure such as β-strands and hairpins. Free energy surfaces, obtained from reweighting the accelerated molecular dynamics boost potential, further demonstrate the restriction on size and flexibility that results from binding of copper ions.
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Affiliation(s)
- Loizos Savva
- School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, UK
| | - James A Platts
- School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, UK..
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16
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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: 14] [Impact Index Per Article: 14.0] [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.
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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
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17
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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.
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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.
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18
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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.
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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
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19
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Pedersen KB, Flores-Canales JC, Schiøtt B. Predicting molecular properties of α-synuclein using force fields for intrinsically disordered proteins. Proteins 2023; 91:47-61. [PMID: 35950933 PMCID: PMC10087257 DOI: 10.1002/prot.26409] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 06/17/2022] [Accepted: 07/12/2022] [Indexed: 12/29/2022]
Abstract
Independent force field validation is an essential practice to keep track of developments and for performing meaningful Molecular Dynamics simulations. In this work, atomistic force fields for intrinsically disordered proteins (IDP) are tested by simulating the archetypical IDP α-synuclein in solution for 2.5 μs. Four combinations of protein and water force fields were tested: ff19SB/OPC, ff19SB/TIP4P-D, ff03CMAP/TIP4P-D, and a99SB-disp/TIP4P-disp, with four independent repeat simulations for each combination. We compare our simulations to the results of a 73 μs simulation using the a99SB-disp/TIP4P-disp combination, provided by D. E. Shaw Research. From the trajectories, we predict a range of experimental observations of α-synuclein and compare them to literature data. This includes protein radius of gyration and hydration, intramolecular distances, NMR chemical shifts, and 3 J-couplings. Both ff19SB/TIP4P-D and a99SB-disp/TIP4P-disp produce extended conformational ensembles of α-synuclein that agree well with experimental radius of gyration and intramolecular distances while a99SB-disp/TIP4P-disp reproduces a balanced α-synuclein secondary structure content. It was found that ff19SB/OPC and ff03CMAP/TIP4P-D produce overly compact conformational ensembles and show discrepancies in the secondary structure content compared to the experimental data.
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Affiliation(s)
| | | | - Birgit Schiøtt
- Department of Chemistry, Aarhus University, Aarhus C, Denmark.,Interdisciplinary Nanoscience Center, Aarhus University, Aarhus C, Denmark
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20
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Langkilde AE, Vestergaard B. Protein fibrillation from another small angle-SAXS data analysis of developing systems. Methods Enzymol 2022; 678:377-409. [PMID: 36641215 DOI: 10.1016/bs.mie.2022.09.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
During the fibrillation process amyloid proteins undergo structural changes at very different length and time scales. Small angle X-ray scattering (SAXS) is a method that is uniquely suitable for the structural analysis of this process. Careful measures must, however, be taken both in the sample preparation, data collection and data analysis procedures to ensure proper data quality, coverage of the process and reliable interpretation. With this chapter, we provide many details about the data analysis of such developing systems. The recommendations are based on our own experience with analysis of data from several amyloid and amyloid-like proteins, with data decomposition being a central point in the procedure. We focus on two alternative approaches, one being a laborious, hands-on, iterative approach, the other being more automated, applying a chemometrics based software, developed for the purpose. Both methods can equally well be applied to other developing mixtures, but specific recommendations for amyloid samples are emphasized in this chapter.
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Affiliation(s)
- Annette Eva Langkilde
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.
| | - Bente Vestergaard
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.
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21
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Dey S, MacAinsh M, Zhou HX. Sequence-Dependent Backbone Dynamics of Intrinsically Disordered Proteins. J Chem Theory Comput 2022; 18:6310-6323. [PMID: 36084347 PMCID: PMC9561007 DOI: 10.1021/acs.jctc.2c00328] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
For intrinsically disordered proteins (IDPs), a pressing question is how sequence codes for function. Dynamics serves as a crucial link, reminiscent of the role of structure in sequence-function relations of structured proteins. To define general rules governing sequence-dependent backbone dynamics, we carried out long molecular dynamics simulations of eight IDPs. Blocks of residues exhibiting large amplitudes in slow dynamics are rigidified by local inter-residue interactions or secondary structures. A long region or an entire IDP can be slowed down by long-range contacts or secondary-structure packing. On the other hand, glycines promote fast dynamics and either demarcate rigid blocks or facilitate multiple modes of local and long-range inter-residue interactions. The sequence-dependent backbone dynamics endows IDPs with versatile response to binding partners, with some blocks recalcitrant while others readily adapting to intermolecular interactions.
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Affiliation(s)
- Souvik Dey
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Matthew MacAinsh
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Huan-Xiang Zhou
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL 60607, USA
- Department of Physics, University of Illinois at Chicago, Chicago, IL 60607, USA
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22
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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.
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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:
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23
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Teixeira JMC, Liu ZH, Namini A, Li J, Vernon RM, Krzeminski M, Shamandy AA, Zhang O, Haghighatlari M, Yu L, Head-Gordon T, Forman-Kay JD. IDPConformerGenerator: A Flexible Software Suite for Sampling the Conformational Space of Disordered Protein States. J Phys Chem A 2022; 126:5985-6003. [PMID: 36030416 PMCID: PMC9465686 DOI: 10.1021/acs.jpca.2c03726] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 08/08/2022] [Indexed: 11/29/2022]
Abstract
The power of structural information for informing biological mechanisms is clear for stable folded macromolecules, but similar structure-function insight is more difficult to obtain for highly dynamic systems such as intrinsically disordered proteins (IDPs) which must be described as structural ensembles. Here, we present IDPConformerGenerator, a flexible, modular open-source software platform for generating large and diverse ensembles of disordered protein states that builds conformers that obey geometric, steric, and other physical restraints on the input sequence. IDPConformerGenerator samples backbone phi (φ), psi (ψ), and omega (ω) torsion angles of relevant sequence fragments from loops and secondary structure elements extracted from folded protein structures in the RCSB Protein Data Bank and builds side chains from robust Monte Carlo algorithms using expanded rotamer libraries. IDPConformerGenerator has many user-defined options enabling variable fractional sampling of secondary structures, supports Bayesian models for assessing the agreement of IDP ensembles for consistency with experimental data, and introduces a machine learning approach to transform between internal and Cartesian coordinates with reduced error. IDPConformerGenerator will facilitate the characterization of disordered proteins to ultimately provide structural insights into these states that have key biological functions.
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Affiliation(s)
- João M. C. Teixeira
- Molecular
Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department
of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - 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
| | - Ashley Namini
- Molecular
Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Jie Li
- Pitzer Center for Theoretical Chemistry, Department of Chemistry, Department of Chemical
and Biomolecular Engineering, and Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Robert M. Vernon
- Molecular
Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Mickaël Krzeminski
- Molecular
Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Alaa A. Shamandy
- Molecular
Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department
of Computer Science, University of Toronto, Toronto, Ontario M5S 2E4, Canada
| | - Oufan Zhang
- Pitzer Center for Theoretical Chemistry, Department of Chemistry, Department of Chemical
and Biomolecular Engineering, and Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Mojtaba Haghighatlari
- Pitzer Center for Theoretical Chemistry, Department of Chemistry, Department of Chemical
and Biomolecular Engineering, and Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Lei Yu
- Pitzer Center for Theoretical Chemistry, Department of Chemistry, Department of Chemical
and Biomolecular Engineering, and Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Teresa Head-Gordon
- Pitzer Center for Theoretical Chemistry, Department of Chemistry, Department of Chemical
and Biomolecular Engineering, and Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - 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
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24
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Privat C, Madurga S, Mas F, Rubio-Martinez J. Molecular dynamics simulations of an α-synuclein NAC domain fragment with a ff14IDPSFF IDP-specific force field suggest β-sheet intermediate states of fibrillation. Phys Chem Chem Phys 2022; 24:18841-18853. [PMID: 35912724 DOI: 10.1039/d2cp02042d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
For the discovery of treatments against synucleinopathies, it is necessary to unravel and fully understand the mechanism of fibrillation of proteins involved. Among them, α-synuclein (αS) plays a key role in the development of these diseases through its aggregation into oligomers found in Lewy bodies. However, its structural disorder as an intrinsically disordered protein (IDP) makes its characterization by experimental techniques arduously difficult. Atomistic simulations aim to provide insights into this blank canvas and, fortunately, some studies have already suggested promising mechanisms. Still, it is urgent to consider the IDP features in simulations, so recently a lot of force fields designed to deal with IDPs have been developed. In this study, we have carried out a total of 12 μs simulations of an αS core fragment using a popular ff14SB AMBER force field and the ff14IDPSFF variation that includes a grid-based energy correction map (CMAP) method. The predicted chemical shifts from the simulations and those measured from the αS protein in the NMR solution indicate that ff14IDPSFF reproduces the experimental data more accurately. Moreover, structural analysis exhibits opposite trends between secondary structure propensities. The ff14SB force field preserves the α-helices found in the micelle-bound αS structure, which is used as an initial conformation, while ff14IDPSFF stands out with increased structural disorder and the formation of β-sheets, which suggests that the IDP-specific force field can capture more suitable conformations representing the possible intermediate states of the fibrillation process.
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Affiliation(s)
- Cristian Privat
- Department of Material Science and Physical Chemistry & Research Institute of Theoretical and Computational Chemistry (IQTCUB), University of Barcelona, C/Martí i Franquès 1, 08028, Barcelona, Spain.
| | - Sergio Madurga
- Department of Material Science and Physical Chemistry & Research Institute of Theoretical and Computational Chemistry (IQTCUB), University of Barcelona, C/Martí i Franquès 1, 08028, Barcelona, Spain.
| | - Francesc Mas
- Department of Material Science and Physical Chemistry & Research Institute of Theoretical and Computational Chemistry (IQTCUB), University of Barcelona, C/Martí i Franquès 1, 08028, Barcelona, Spain.
| | - Jaime Rubio-Martinez
- Department of Material Science and Physical Chemistry & Research Institute of Theoretical and Computational Chemistry (IQTCUB), University of Barcelona, C/Martí i Franquès 1, 08028, Barcelona, Spain.
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25
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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.
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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,
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26
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Shimizu M, Okuda A, Morishima K, Inoue R, Sato N, Yunoki Y, Urade R, Sugiyama M. Extracting time series matching a small-angle X-ray scattering profile from trajectories of molecular dynamics simulations. Sci Rep 2022; 12:9970. [PMID: 35705644 PMCID: PMC9200744 DOI: 10.1038/s41598-022-13982-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 05/31/2022] [Indexed: 11/30/2022] Open
Abstract
Solving structural ensembles of flexible biomolecules is a challenging research area. Here, we propose a method to obtain possible structural ensembles of a biomolecule based on small-angle X-ray scattering (SAXS) and molecular dynamics simulations. Our idea is to clip a time series that matches a SAXS profile from a simulation trajectory. To examine its practicability, we applied our idea to a multi-domain protein ER-60 and successfully extracted time series longer than 1 micro second from trajectories of coarse-grained molecular dynamics simulations. In the extracted time series, the domain conformation was distributed continuously and smoothly in a conformational space. Preferred domain conformations were also observed. Diversity among scattering curves calculated from each ER-60 structure was interpreted to reflect an open-close motion of the protein. Although our approach did not provide a unique solution for the structural ensemble of the biomolecule, each extracted time series can be an element of the real behavior of ER-60. Considering its low computational cost, our approach will play a key role to identify biomolecular dynamics by integrating SAXS, simulations, and other experiments.
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Affiliation(s)
- Masahiro Shimizu
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan.
| | - Aya Okuda
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Ken Morishima
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Rintaro Inoue
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Nobuhiro Sato
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Yasuhiro Yunoki
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Reiko Urade
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Masaaki Sugiyama
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan.
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27
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Savva L, Platts JA. Evaluation of implicit solvent models in molecular dynamics simulation of α-Synuclein. J Biomol Struct Dyn 2022:1-16. [PMID: 35670576 DOI: 10.1080/07391102.2022.2082534] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
We report conventional and accelerated molecular dynamics simulations of α-Synuclein, designed to assess performance of using different starting conformation, solvation environment and force field combination. Backbone and sidechain chemical shifts, radius of gyration, presence of β-hairpin structures in KTK(E/Q)GV repeats and secondary structure percentages were used to evaluate how variations in forcefield, solvation model and simulation protocol provide results that correlate with experimental findings. We show that with suitable choice of forcefield and solvent, ff03ws and OBC implicit model, respectively, acceptable reproduction of experimental data on size and secondary structure is obtained by both conventional and accelerated MD. In contrast to the implicit solvent model, simulations in explicit TIP4P/2005 solvent do not properly represent size or secondary structure of α-Synuclein.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Loizos Savva
- School of Chemistry, Cardiff University, Cardiff, UK
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28
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Palomino-Hernandez O, Santambrogio C, Rossetti G, Fernandez CO, Grandori R, Carloni P. Molecular Dynamics-Assisted Interpretation of Experimentally Determined Intrinsically Disordered Protein Conformational Components: The Case of Human α-Synuclein. J Phys Chem B 2022; 126:3632-3639. [PMID: 35543707 DOI: 10.1021/acs.jpcb.1c10954] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Mass spectrometry and single molecule force microscopy are two experimental approaches able to provide structural information on intrinsically disordered proteins (IDPs). These techniques allow the dissection of conformational ensembles in their main components, although at a low-resolution level. In this work, we interpret the results emerging from these experimental approaches on human alpha synuclein (AS) by analyzing a previously published 73 μs-long molecular-dynamics (MD) simulation of the protein in explicit solvent. We further compare MD-based predictions of single molecule Förster resonance energy transfer (smFRET) data of AS in solution with experimental data. The combined theoretical and experimental data provide a description of AS main conformational ensemble, shedding light into its intramolecular interactions and overall structural compactness. This analysis could be easily transferred to other IDPs.
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Affiliation(s)
- Oscar Palomino-Hernandez
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany.,Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen, 52425 Aachen, Germany.,Computation-Based Science and Technology Research Center, The Cyprus Institute, 2121 Nicosia, Cyprus.,Institute of Life Science, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel
| | - Carlo Santambrogio
- Department of Biotechnology and Biosciences, University of Milan-Bicocca, 20126 Milan, Italy
| | - Giulia Rossetti
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany.,Department of Neurology, University Hospital Aachen, RWTH Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany.,Jülich Supercomputing Center (JSC), Forschungszentrum Jülich, 52425 Jülich, Germany
| | - Claudio O Fernandez
- Max Planck Laboratory for Structural Biology, Chemistry and Molecular Biophysics of Rosario (MPLbioR, UNR-MPI-NAT). Partner Laboratory of the Max Planck Institute for Biophysical Chemistry (MPI-NAT, MPG). Centro de Estudios Interdisciplinarios, Universidad Nacional de Rosario, Rosario, Argentina S2002LRK Rosario, Argentina
| | - Rita Grandori
- Department of Biotechnology and Biosciences, University of Milan-Bicocca, 20126 Milan, Italy
| | - Paolo Carloni
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany.,Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen, 52425 Aachen, Germany.,Institute for Neuroscience and Medicine (INM-11) Forschungszentrum Jülich, 52425 Jülich, Germany
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29
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Wilson CJ, Choy WY, Karttunen M. AlphaFold2: A Role for Disordered Protein/Region Prediction? Int J Mol Sci 2022; 23:4591. [PMID: 35562983 PMCID: PMC9104326 DOI: 10.3390/ijms23094591] [Citation(s) in RCA: 57] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 01/27/2023] Open
Abstract
The development of AlphaFold2 marked a paradigm-shift in the structural biology community. Herein, we assess the ability of AlphaFold2 to predict disordered regions against traditional sequence-based disorder predictors. We find that AlphaFold2 performs well at discriminating disordered regions, but also note that the disorder predictor one constructs from an AlphaFold2 structure determines accuracy. In particular, a naïve, but non-trivial assumption that residues assigned to helices, strands, and H-bond stabilized turns are likely ordered and all other residues are disordered results in a dramatic overestimation in disorder; conversely, the predicted local distance difference test (pLDDT) provides an excellent measure of residue-wise disorder. Furthermore, by employing molecular dynamics (MD) simulations, we note an interesting relationship between the pLDDT and secondary structure, that may explain our observations and suggests a broader application of the pLDDT for characterizing the local dynamics of intrinsically disordered proteins and regions (IDPs/IDRs).
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Affiliation(s)
- Carter J. Wilson
- Department of Mathematics, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada;
- Centre for Advanced Materials and Biomaterials Research, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
| | - Wing-Yiu Choy
- Department of Biochemistry, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5C1, Canada
| | - Mikko Karttunen
- Centre for Advanced Materials and Biomaterials Research, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
- Department of Physics and Astronomy, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
- Department of Chemistry, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 3K7, Canada
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30
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Thomasen FE, Pesce F, Roesgaard MA, Tesei G, Lindorff-Larsen K. Improving Martini 3 for Disordered and Multidomain Proteins. J Chem Theory Comput 2022; 18:2033-2041. [PMID: 35377637 DOI: 10.1021/acs.jctc.1c01042] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Coarse-grained molecular dynamics simulations are a useful tool to determine conformational ensembles of proteins. Here, we show that the coarse-grained force field Martini 3 underestimates the global dimensions of intrinsically disordered proteins (IDPs) and multidomain proteins when compared with small-angle X-ray scattering (SAXS) data and that increasing the strength of protein-water interactions favors more expanded conformations. We find that increasing the strength of interactions between protein and water by ca. 10% results in improved agreement with the SAXS data for IDPs and multidomain proteins. We also show that this correction results in a more accurate description of self-association of IDPs and folded proteins and better agreement with paramagnetic relaxation enhancement data for most IDPs. While simulations with this revised force field still show deviations to experiments for some systems, our results suggest that it is overall a substantial improvement for coarse-grained simulations of soluble proteins.
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Affiliation(s)
- F Emil Thomasen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Francesco Pesce
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Mette Ahrensback Roesgaard
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Giulio Tesei
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
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31
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Karamanos TK, Kalverda AP, Radford SE. Generating Ensembles of Dynamic Misfolding Proteins. Front Neurosci 2022; 16:881534. [PMID: 35431773 PMCID: PMC9008329 DOI: 10.3389/fnins.2022.881534] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 03/08/2022] [Indexed: 01/09/2023] Open
Abstract
The early stages of protein misfolding and aggregation involve disordered and partially folded protein conformers that contain a high degree of dynamic disorder. These dynamic species may undergo large-scale intra-molecular motions of intrinsically disordered protein (IDP) precursors, or flexible, low affinity inter-molecular binding in oligomeric assemblies. In both cases, generating atomic level visualization of the interconverting species that captures the conformations explored and their physico-chemical properties remains hugely challenging. How specific sub-ensembles of conformers that are on-pathway to aggregation into amyloid can be identified from their aggregation-resilient counterparts within these large heterogenous pools of rapidly moving molecules represents an additional level of complexity. Here, we describe current experimental and computational approaches designed to capture the dynamic nature of the early stages of protein misfolding and aggregation, and discuss potential challenges in describing these species because of the ensemble averaging of experimental restraints that arise from motions on the millisecond timescale. We give a perspective of how machine learning methods can be used to extract aggregation-relevant sub-ensembles and provide two examples of such an approach in which specific interactions of defined species within the dynamic ensembles of α-synuclein (αSyn) and β2-microgloblulin (β2m) can be captured and investigated.
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Affiliation(s)
- Theodoros K. Karamanos
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom
| | | | - Sheena E. Radford
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom
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32
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Kulkarni P, Leite VBP, Roy S, Bhattacharyya S, Mohanty A, Achuthan S, Singh D, Appadurai R, Rangarajan G, Weninger K, Orban J, Srivastava A, Jolly MK, Onuchic JN, Uversky VN, Salgia R. Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma. BIOPHYSICS REVIEWS 2022; 3:011306. [PMID: 38505224 PMCID: PMC10903413 DOI: 10.1063/5.0080512] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/17/2022] [Indexed: 03/21/2024]
Abstract
Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.
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Affiliation(s)
- Prakash Kulkarni
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Vitor B. P. Leite
- Departamento de Física, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista (UNESP), São José do Rio Preto, São Paulo 15054-000, Brazil
| | - Susmita Roy
- Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
| | - Supriyo Bhattacharyya
- Translational Bioinformatics, Center for Informatics, Department of Computational and Quantitative Medicine, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Atish Mohanty
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Srisairam Achuthan
- Center for Informatics, Division of Research Informatics, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Divyoj Singh
- Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Rajeswari Appadurai
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India
| | - Govindan Rangarajan
- Department of Mathematics, Indian Institute of Science, Bangalore 560012, India
| | - Keith Weninger
- Department of Physics, North Carolina State University, Raleigh, North Carolina 27695, USA
| | | | - Anand Srivastava
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India
| | - Mohit Kumar Jolly
- Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Jose N. Onuchic
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005-1892, USA
| | | | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California 91010, USA
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33
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Fagerberg E, Lenton S, Nylander T, Seydel T, Skepö M. Self-Diffusive Properties of the Intrinsically Disordered Protein Histatin 5 and the Impact of Crowding Thereon: A Combined Neutron Spectroscopy and Molecular Dynamics Simulation Study. J Phys Chem B 2022; 126:789-801. [PMID: 35044776 PMCID: PMC8819652 DOI: 10.1021/acs.jpcb.1c08976] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
![]()
Intrinsically disordered
proteins (IDPs) are proteins that, in
comparison with globular/structured proteins, lack a distinct tertiary
structure. Here, we use the model IDP, Histatin 5, for studying its
dynamical properties under self-crowding conditions with quasi-elastic
neutron scattering in combination with full atomistic molecular dynamics
(MD) simulations. The aim is to determine the effects of crowding
on the center-of-mass diffusion as well as the internal diffusive
behavior. The diffusion was found to decrease significantly, which
we hypothesize can be attributed to some degree of aggregation at
higher protein concentrations, (≥100 mg/mL), as indicated by
recent small-angle X-ray scattering studies. Temperature effects are
also considered and found to, largely, follow Stokes–Einstein
behavior. Simple geometric considerations fail to accurately predict
the rates of diffusion, while simulations show semiquantitative agreement
with experiments, dependent on assumptions of the ratio between translational
and rotational diffusion. A scaling law that previously was found
to successfully describe the behavior of globular proteins was found
to be inadequate for the IDP, Histatin 5. Analysis of the MD simulations
show that the width of the distribution with respect to diffusion
is not a simplistic mirroring of the distribution of radius of gyration,
hence, displaying the particular features of IDPs that need to be
accounted for.
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Affiliation(s)
- Eric Fagerberg
- Theoretical Chemistry, Lund University, POB 124, SE-221 00 Lund, Sweden
| | - Samuel Lenton
- Physical Chemistry, Lund University, POB 124, SE-221 00 Lund, Sweden
| | - Tommy Nylander
- Physical Chemistry, Lund University, POB 124, SE-221 00 Lund, Sweden
| | - Tilo Seydel
- Institut Max von Laue - Paul Langevin, 71 avenue des Martyrs, CS 20156, F-38042 Grenoble, France
| | - Marie Skepö
- Theoretical Chemistry, Lund University, POB 124, SE-221 00 Lund, Sweden.,LINXS - Lund Institute of Advanced Neutron and X-ray Science, Scheelevägen 19, SE-223 70 Lund, Sweden
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34
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Pesce F, Lindorff-Larsen K. Refining conformational ensembles of flexible proteins against small-angle x-ray scattering data. Biophys J 2021; 120:5124-5135. [PMID: 34627764 PMCID: PMC8633713 DOI: 10.1016/j.bpj.2021.10.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 09/09/2021] [Accepted: 10/04/2021] [Indexed: 01/30/2023] Open
Abstract
Intrinsically disordered proteins and flexible regions in multidomain proteins display substantial conformational heterogeneity. Characterizing the conformational ensembles of these proteins in solution typically requires combining one or more biophysical techniques with computational modeling or simulations. Experimental data can either be used to assess the accuracy of a computational model or to refine the computational model to get a better agreement with the experimental data. In both cases, one generally needs a so-called forward model (i.e., an algorithm to calculate experimental observables from individual conformations or ensembles). In many cases, this involves one or more parameters that need to be set, and it is not always trivial to determine the optimal values or to understand the impact on the choice of parameters. For example, in the case of small-angle x-ray scattering (SAXS) experiments, many forward models include parameters that describe the contribution of the hydration layer and displaced solvent to the background-subtracted experimental data. Often, one also needs to fit a scale factor and a constant background for the SAXS data but across the entire ensemble. Here, we present a protocol to dissect the effect of the free parameters on the calculated SAXS intensities and to identify a reliable set of values. We have implemented this procedure in our Bayesian/maximum entropy framework for ensemble refinement and demonstrate the results on four intrinsically disordered proteins and a protein with three domains connected by flexible linkers. Our results show that the resulting ensembles can depend on the parameters used for solvent effects and suggest that these should be chosen carefully. We also find a set of parameters that work robustly across all proteins.
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Affiliation(s)
- Francesco Pesce
- 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.
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35
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Tesei G, Schulze TK, Crehuet R, Lindorff-Larsen K. Accurate model of liquid-liquid phase behavior of intrinsically disordered proteins from optimization of single-chain properties. Proc Natl Acad Sci U S A 2021; 118:2111696118. [PMID: 34716273 DOI: 10.1101/2021.06.23.449550] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 09/15/2021] [Indexed: 05/25/2023] Open
Abstract
Many intrinsically disordered proteins (IDPs) may undergo liquid-liquid phase separation (LLPS) and participate in the formation of membraneless organelles in the cell, thereby contributing to the regulation and compartmentalization of intracellular biochemical reactions. The phase behavior of IDPs is sequence dependent, and its investigation through molecular simulations requires protein models that combine computational efficiency with an accurate description of intramolecular and intermolecular interactions. We developed a general coarse-grained model of IDPs, with residue-level detail, based on an extensive set of experimental data on single-chain properties. Ensemble-averaged experimental observables are predicted from molecular simulations, and a data-driven parameter-learning procedure is used to identify the residue-specific model parameters that minimize the discrepancy between predictions and experiments. The model accurately reproduces the experimentally observed conformational propensities of a set of IDPs. Through two-body as well as large-scale molecular simulations, we show that the optimization of the intramolecular interactions results in improved predictions of protein self-association and LLPS.
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Affiliation(s)
- Giulio Tesei
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark;
| | - Thea K Schulze
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Ramon Crehuet
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark
- CSIC-Institute for Advanced Chemistry of Catalonia (IQAC), E-08034 Barcelona, Spain
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark;
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36
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Tesei G, Schulze TK, Crehuet R, Lindorff-Larsen K. Accurate model of liquid-liquid phase behavior of intrinsically disordered proteins from optimization of single-chain properties. Proc Natl Acad Sci U S A 2021; 118:e2111696118. [PMID: 34716273 PMCID: PMC8612223 DOI: 10.1073/pnas.2111696118] [Citation(s) in RCA: 115] [Impact Index Per Article: 38.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 09/15/2021] [Indexed: 11/18/2022] Open
Abstract
Many intrinsically disordered proteins (IDPs) may undergo liquid-liquid phase separation (LLPS) and participate in the formation of membraneless organelles in the cell, thereby contributing to the regulation and compartmentalization of intracellular biochemical reactions. The phase behavior of IDPs is sequence dependent, and its investigation through molecular simulations requires protein models that combine computational efficiency with an accurate description of intramolecular and intermolecular interactions. We developed a general coarse-grained model of IDPs, with residue-level detail, based on an extensive set of experimental data on single-chain properties. Ensemble-averaged experimental observables are predicted from molecular simulations, and a data-driven parameter-learning procedure is used to identify the residue-specific model parameters that minimize the discrepancy between predictions and experiments. The model accurately reproduces the experimentally observed conformational propensities of a set of IDPs. Through two-body as well as large-scale molecular simulations, we show that the optimization of the intramolecular interactions results in improved predictions of protein self-association and LLPS.
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Affiliation(s)
- Giulio Tesei
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark;
| | - Thea K Schulze
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Ramon Crehuet
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark
- CSIC-Institute for Advanced Chemistry of Catalonia (IQAC), E-08034 Barcelona, Spain
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark;
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37
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Yagi K, Re S, Mori T, Sugita Y. Weight average approaches for predicting dynamical properties of biomolecules. Curr Opin Struct Biol 2021; 72:88-94. [PMID: 34592697 DOI: 10.1016/j.sbi.2021.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 08/21/2021] [Accepted: 08/24/2021] [Indexed: 11/16/2022]
Abstract
Recent advances in atomistic molecular dynamics (MD) simulations of biomolecules allow us to explore their conformational spaces widely, observing large-scale conformational fluctuations or transitions between distinct structures. To reproduce or refine experimental data using MD simulations, structure ensembles, which are characterized by multiple structures and their statistical weights on the rugged free-energy landscapes, are often used. Here, we summarize weight average approaches for various experimental measurements. Weight average approaches are now applied to hybrid quantum mechanics/molecular mechanics MD simulations to predict fast vibrational motions in a protein with a high accuracy for better understanding of molecular functions from atomic structures.
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Affiliation(s)
- Kiyoshi Yagi
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Suyong Re
- RIKEN Center for Biosystems Dynamics Research, 1-6-5 Minatojima-Minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health, and Nutrition 7-6-8, Saito-Asagi, Ibaraki, Osaka, 567-0085, Japan
| | - Takaharu Mori
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Yuji Sugita
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan; RIKEN Center for Biosystems Dynamics Research, 1-6-5 Minatojima-Minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
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38
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Lindorff-Larsen K, Kragelund BB. On the potential of machine learning to examine the relationship between sequence, structure, dynamics and function of intrinsically disordered proteins. J Mol Biol 2021; 433:167196. [PMID: 34390736 DOI: 10.1016/j.jmb.2021.167196] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 08/03/2021] [Accepted: 08/04/2021] [Indexed: 11/29/2022]
Abstract
Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and many diverging properties. IDPs-and intrinsically disordered regions (IDRs) interspersed between folded domains-are generally characterized as having no persistent tertiary structure; instead they interconvert between a large number of different and often expanded structures. IDPs and IDRs are involved in an enormously wide range of biological functions and reveal novel mechanisms of interactions, and while they defy the common structure-function paradigm of folded proteins, their structural preferences and dynamics are important for their function. We here discuss open questions in the field of IDPs and IDRs, focusing on areas where machine learning and other computational methods play a role. We discuss computational methods aimed to predict transiently formed local and long-range structure, including methods for integrative structural biology. We discuss the many different ways in which IDPs and IDRs can bind to other molecules, both via short linear motifs, as well as in the formation of larger dynamic complexes such as biomolecular condensates. We discuss how experiments are providing insight into such complexes and may enable more accurate predictions. Finally, we discuss the role of IDPs in disease and how new methods are needed to interpret the mechanistic effects of genomic variants in IDPs.
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Affiliation(s)
- Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory & Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen. Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark.
| | - Birthe B Kragelund
- Structural Biology and NMR Laboratory & Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen. Ole Maaløes Vej 5, DK-2200 Copenhagen N, Denmark.
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39
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Paissoni C, Camilloni C. How to Determine Accurate Conformational Ensembles by Metadynamics Metainference: A Chignolin Study Case. Front Mol Biosci 2021; 8:694130. [PMID: 34124166 PMCID: PMC8187852 DOI: 10.3389/fmolb.2021.694130] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 05/14/2021] [Indexed: 11/13/2022] Open
Abstract
The reliability and usefulness of molecular dynamics simulations of equilibrium processes rests on their statistical precision and their capability to generate conformational ensembles in agreement with available experimental knowledge. Metadynamics Metainference (M&M), coupling molecular dynamics with the enhanced sampling ability of Metadynamics and with the ability to integrate experimental information of Metainference, can in principle achieve both goals. Here we show that three different Metadynamics setups provide converged estimate of the populations of the three-states populated by a model peptide. Errors are estimated correctly by block averaging, but higher precision is obtained by performing independent replicates. One effect of Metadynamics is that of dramatically decreasing the number of effective frames resulting from the simulations and this is relevant for M&M where the number of replicas should be large enough to capture the conformational heterogeneity behind the experimental data. Our simulations allow also us to propose that monitoring the relative error associated with conformational averaging can help to determine the minimum number of replicas to be simulated in the context of M&M simulations. Altogether our data provides useful indication on how to generate sound conformational ensemble in agreement with experimental data.
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Affiliation(s)
- Cristina Paissoni
- Dipartimento di Bioscienze, Università degli Studi di Milano, Milan, Italy
| | - Carlo Camilloni
- Dipartimento di Bioscienze, Università degli Studi di Milano, Milan, Italy
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