1
|
Roccatano D. A molecular dynamics simulation study of glycine/serine octapeptides labeled with 2,3-diazabicyclo[2.2.2]oct-2-ene fluorophore. J Chem Phys 2024; 160:145101. [PMID: 38587229 DOI: 10.1063/5.0190073] [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: 12/03/2023] [Accepted: 03/19/2024] [Indexed: 04/09/2024] Open
Abstract
The compound 2,3-diazabicyclo[2.2.2]oct-2-ene (DBO) is a versatile fluorophore widely used in Förster resonance energy transfer (FRET) spectroscopy studies due to its remarkable sensitivity, enabling precise donor-acceptor distance measurements, even for short peptides. Integrating time-resolved and FRET spectroscopies with molecular dynamics simulations provides a robust approach to unravel the structure and dynamics of biopolymers in a solution. This study investigates the structural behavior of three octapeptide variants: Trp-(Gly-Ser)3-Dbo, Trp-(GlyGly)3-Dbo, and Trp-(SerSer)3-Dbo, where Dbo represents the DBO-containing modified aspartic acid, using molecular dynamics simulations. Glycine- and serine-rich amino acid fragments, common in flexible protein regions, play essential roles in functional properties. Results show excellent agreement between end-to-end distances, orientational factors from simulations, and the available experimental and theoretical data, validating the reliability of the GROMOS force field model. The end-to-end distribution, modeled using three Gaussian distributions, reveals a complex shape, confirmed by cluster analysis highlighting a limited number of significant conformations dominating the peptide landscape. All peptides predominantly adopt a disordered state in the solvent, yet exhibit a compact shape, aligning with the model of disordered polypeptide chains in poor solvents. Conformations show marginal dependence on chain composition, with Ser-only chains exhibiting slightly more elongation. This study enhances our understanding of peptide behavior, providing valuable insights into their structural dynamics in solution.
Collapse
Affiliation(s)
- Danilo Roccatano
- School of Mathematics and Physics, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, United Kingdom
| |
Collapse
|
2
|
Kuczera K, Szoszkiewicz R, Shaffer CL, Jas GS. GB1 hairpin kinetics: capturing the folding pathway with molecular dynamics, replica exchange and optimal dimensionality reduction. J Biomol Struct Dyn 2023; 41:11671-11680. [PMID: 36591705 DOI: 10.1080/07391102.2022.2163427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/22/2022] [Indexed: 01/03/2023]
Abstract
We have performed molecular dynamics (MD) and replica-exchange (REMD) simulations of folding of the GB1 hairpin peptide in aqueous solution. REMD results were consistent with a cooperative zipper folding model. 120 μ s MD trajectories at 320 K yielded relaxation times of 1.8 μ s and 100 ns, with the slower assigned to global folding. The MD folding/unfolding transitions also followed the cooperative zipper model, specifying nucleation at the central turn followed by consecutive hydrogen bond formation. Formation of hydrogen bonds and hydrophobic contacts were highly correlated. Coarse-grained kinetic models constructed with the Optimal Dimensionality Reduction (ODR) approach found a folding time of 3.3 μ s and unfolding time of 4.0 μ s . Additionally, relaxation times in the 130-170 ns range could be assigned to formation of the transition state and off-path intermediates. The unfolded state was the most highly populated and, significantly, most heterogenous, assembling the largest number of microstates, primarily composed of extended and turn structures. The folded state was also heterogenous, but a to a lesser degree, involving the fully folded and partially folded in-register hairpins at early stages of the zipper pathway. The transition state corresponded to the nucleated hairpin, with central turn and first beta-sheet hydrogen bond, while the off-path intermediates were off-register partial hairpins. Our simulation results were in excellent agreement with experimental data on folded fraction, relaxation time and folding mechanism. The new findings from this work suggest a highly cooperative zipper folding mechanism, nascent hairpin transition state and ∼100 ns relaxation related to intermediate formation.Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- Krzysztof Kuczera
- Department of Chemistry, The University of Kansas, Lawrence, KS, USA
- Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA
| | - Robert Szoszkiewicz
- Faculty of Chemistry, Biological and Chemical Research Centre University of Warsaw, Warsaw, Poland
| | - Christopher L Shaffer
- College of Pharmacy and Pediatric Clinical Pharmacology, University of Nebraska Medical Center, Omaha, NE, USA
| | - Gouri S Jas
- College of Pharmacy and Pediatric Clinical Pharmacology, University of Nebraska Medical Center, Omaha, NE, USA
| |
Collapse
|
3
|
Bandyopadhyay S, Mondal J. A deep autoencoder framework for discovery of metastable ensembles in biomacromolecules. J Chem Phys 2021; 155:114106. [PMID: 34551528 DOI: 10.1063/5.0059965] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Biomacromolecules manifest dynamic conformational fluctuation and involve mutual interconversion among metastable states. A robust mapping of their conformational landscape often requires the low-dimensional projection of the conformational ensemble along optimized collective variables (CVs). However, the traditional choice for the CV is often limited by user-intuition and prior knowledge about the system, and this lacks a rigorous assessment of their optimality over other candidate CVs. To address this issue, we propose an approach in which we first choose the possible combinations of inter-residue Cα-distances within a given macromolecule as a set of input CVs. Subsequently, we derive a non-linear combination of latent space embedded CVs via auto-encoding the unbiased molecular dynamics simulation trajectories within the framework of the feed-forward neural network. We demonstrate the ability of the derived latent space variables in elucidating the conformational landscape in four hierarchically complex systems. The latent space CVs identify key metastable states of a bead-in-a-spring polymer. The combination of the adopted dimensional reduction technique with a Markov state model, built on the derived latent space, reveals multiple spatially and kinetically well-resolved metastable conformations for GB1 β-hairpin. A quantitative comparison based on the variational approach-based scoring of the auto-encoder-derived latent space CVs with the ones obtained via independent component analysis (principal component analysis or time-structured independent component analysis) confirms the optimality of the former. As a practical application, the auto-encoder-derived CVs were found to predict the reinforced folding of a Trp-cage mini-protein in aqueous osmolyte solution. Finally, the protocol was able to decipher the conformational heterogeneities involved in a complex metalloenzyme, namely, cytochrome P450.
Collapse
Affiliation(s)
- Satyabrata Bandyopadhyay
- Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad 500046, India
| | - Jagannath Mondal
- Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad 500046, India
| |
Collapse
|
4
|
Cubuk J, Alston JJ, Incicco JJ, Singh S, Stuchell-Brereton MD, Ward MD, Zimmerman MI, Vithani N, Griffith D, Wagoner JA, Bowman GR, Hall KB, Soranno A, Holehouse AS. The SARS-CoV-2 nucleocapsid protein is dynamic, disordered, and phase separates with RNA. Nat Commun 2021; 12:1936. [PMID: 33782395 PMCID: PMC8007728 DOI: 10.1038/s41467-021-21953-3] [Citation(s) in RCA: 359] [Impact Index Per Article: 89.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 02/18/2021] [Indexed: 12/15/2022] Open
Abstract
The SARS-CoV-2 nucleocapsid (N) protein is an abundant RNA-binding protein critical for viral genome packaging, yet the molecular details that underlie this process are poorly understood. Here we combine single-molecule spectroscopy with all-atom simulations to uncover the molecular details that contribute to N protein function. N protein contains three dynamic disordered regions that house putative transiently-helical binding motifs. The two folded domains interact minimally such that full-length N protein is a flexible and multivalent RNA-binding protein. N protein also undergoes liquid-liquid phase separation when mixed with RNA, and polymer theory predicts that the same multivalent interactions that drive phase separation also engender RNA compaction. We offer a simple symmetry-breaking model that provides a plausible route through which single-genome condensation preferentially occurs over phase separation, suggesting that phase separation offers a convenient macroscopic readout of a key nanoscopic interaction.
Collapse
Affiliation(s)
- Jasmine Cubuk
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - Jhullian J Alston
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - J Jeremías Incicco
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - Sukrit Singh
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - Melissa D Stuchell-Brereton
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - Michael D Ward
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - Maxwell I Zimmerman
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - Neha Vithani
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Griffith
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - Jason A Wagoner
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
| | - Gregory R Bowman
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA
| | - Kathleen B Hall
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrea Soranno
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA.
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA.
| | - Alex S Holehouse
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA.
- Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO, USA.
| |
Collapse
|
5
|
Cubuk J, Alston JJ, Incicco JJ, Singh S, Stuchell-Brereton MD, Ward MD, Zimmerman MI, Vithani N, Griffith D, Wagoner JA, Bowman GR, Hall KB, Soranno A, Holehouse AS. The SARS-CoV-2 nucleocapsid protein is dynamic, disordered, and phase separates with RNA. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020:2020.06.17.158121. [PMID: 32587966 PMCID: PMC7310622 DOI: 10.1101/2020.06.17.158121] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/11/2023]
Abstract
The SARS-CoV-2 nucleocapsid (N) protein is an abundant RNA binding protein critical for viral genome packaging, yet the molecular details that underlie this process are poorly understood. Here we combine single-molecule spectroscopy with all-atom simulations to uncover the molecular details that contribute to N protein function. N protein contains three dynamic disordered regions that house putative transiently-helical binding motifs. The two folded domains interact minimally such that full-length N protein is a flexible and multivalent RNA binding protein. N protein also undergoes liquid-liquid phase separation when mixed with RNA, and polymer theory predicts that the same multivalent interactions that drive phase separation also engender RNA compaction. We offer a simple symmetry-breaking model that provides a plausible route through which single-genome condensation preferentially occurs over phase separation, suggesting that phase separation offers a convenient macroscopic readout of a key nanoscopic interaction.
Collapse
|
6
|
Soranno A. Physical basis of the disorder-order transition. Arch Biochem Biophys 2020; 685:108305. [DOI: 10.1016/j.abb.2020.108305] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Revised: 02/10/2020] [Accepted: 02/14/2020] [Indexed: 12/29/2022]
|
7
|
Michaelis M, Hildebrand N, Meißner RH, Wurzler N, Li Z, Hirst JD, Micsonai A, Kardos J, Delle Piane M, Colombi Ciacchi L. Impact of the Conformational Variability of Oligopeptides on the Computational Prediction of Their CD Spectra. J Phys Chem B 2019; 123:6694-6704. [DOI: 10.1021/acs.jpcb.9b03932] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- M. Michaelis
- Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, Hybrid Materials Interfaces Group, University of Bremen, Am Fallturm 1, Bremen 28359, Germany
- Biomolecular and Materials Interface Research Group, Interdisciplinary Biomedical Research Centre, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham NG11 8NS, United Kingdom
| | - N. Hildebrand
- Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, Hybrid Materials Interfaces Group, University of Bremen, Am Fallturm 1, Bremen 28359, Germany
| | - R. H. Meißner
- Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, Hybrid Materials Interfaces Group, University of Bremen, Am Fallturm 1, Bremen 28359, Germany
| | - N. Wurzler
- Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, Hybrid Materials Interfaces Group, University of Bremen, Am Fallturm 1, Bremen 28359, Germany
| | - Z. Li
- School of Chemistry, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - J. D. Hirst
- School of Chemistry, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - A. Micsonai
- Department of Biochemistry, ELTE Eötvös Loránd University, Pázmány Péter sétány 1/C, Budapest H-1117, Hungary
| | - J. Kardos
- Department of Biochemistry, ELTE Eötvös Loránd University, Pázmány Péter sétány 1/C, Budapest H-1117, Hungary
| | - M. Delle Piane
- Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, Hybrid Materials Interfaces Group, University of Bremen, Am Fallturm 1, Bremen 28359, Germany
| | - L. Colombi Ciacchi
- Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, Hybrid Materials Interfaces Group, University of Bremen, Am Fallturm 1, Bremen 28359, Germany
| |
Collapse
|