1
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Mazzaferro N, Sasmal S, Cossio P, Hocky GM. Good Rates From Bad Coordinates: The Exponential Average Time-dependent Rate Approach. J Chem Theory Comput 2024; 20:5901-5912. [PMID: 38954555 PMCID: PMC11270837 DOI: 10.1021/acs.jctc.4c00425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 07/04/2024]
Abstract
Our ability to calculate rate constants of biochemical processes using molecular dynamics simulations is severely limited by the fact that the time scales for reactions, or changes in conformational state, scale exponentially with the relevant free-energy barrier heights. In this work, we improve upon a recently proposed rate estimator that allows us to predict transition times with molecular dynamics simulations biased to rapidly explore one or several collective variables (CVs). This approach relies on the idea that not all bias goes into promoting transitions, and along with the rate, it estimates a concomitant scale factor for the bias termed the "CV biasing efficiency" γ. First, we demonstrate mathematically that our new formulation allows us to derive the commonly used Infrequent Metadynamics (iMetaD) estimator when using a perfect CV, where γ = 1. After testing it on a model potential, we then study the unfolding behavior of a previously well characterized coarse-grained protein, which is sufficiently complex that we can choose many different CVs to bias, but which is sufficiently simple that we are able to compute the unbiased rate directly. For this system, we demonstrate that predictions from our new Exponential Average Time-Dependent Rate (EATR) estimator converge to the true rate constant more rapidly as a function of bias deposition time than does the previous iMetaD approach, even for bias deposition times that are short. We also show that the γ parameter can serve as a good metric for assessing the quality of the biasing coordinate. We demonstrate that these results hold when applying the methods to an atomistic protein folding example. Finally, we demonstrate that our approach works when combining multiple less-than-optimal bias coordinates, and adapt our method to the related "OPES flooding" approach. Overall, our time-dependent rate approach offers a powerful framework for predicting rate constants from biased simulations.
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Affiliation(s)
- Nicodemo Mazzaferro
- Department
of Chemistry, New York University, New York, New York 10003, United States
| | - Subarna Sasmal
- Department
of Chemistry, New York University, New York, New York 10003, United States
| | - Pilar Cossio
- Center
for Computational Mathematics, Flatiron
Institute, New York, New York 10010, United States
- Center
for Computational Biology, Flatiron Institute, New York, New York 10010, United States
| | - Glen M. Hocky
- Department
of Chemistry, New York University, New York, New York 10003, United States
- Simons
Center for Computational Physical Chemistry, New York University, New York, New York 10003, United States
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2
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Sternke-Hoffmann R, Sun X, Menzel A, Pinto MDS, Venclovaite U, Wördehoff M, Hoyer W, Zheng W, Luo J. Phase Separation and Aggregation of α-Synuclein Diverge at Different Salt Conditions. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2308279. [PMID: 38973194 DOI: 10.1002/advs.202308279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 05/27/2024] [Indexed: 07/09/2024]
Abstract
The coacervation of alpha-synuclein (αSyn) into cytotoxic oligomers and amyloid fibrils are considered pathological hallmarks of Parkinson's disease. While aggregation is central to amyloid diseases, liquid-liquid phase separation (LLPS) and its interplay with aggregation have gained increasing interest. Previous work shows that factors promoting or inhibiting aggregation have similar effects on LLPS. This study provides a detailed scanning of a wide range of parameters, including protein, salt and crowding concentrations at multiple pH values, revealing different salt dependencies of aggregation and LLPS. The influence of salt on aggregation under crowding conditions follows a non-monotonic pattern, showing increased effects at medium salt concentrations. This behavior can be elucidated through a combination of electrostatic screening and salting-out effects on the intramolecular interactions between the N-terminal and C-terminal regions of αSyn. By contrast, this study finds a monotonic salt dependence of LLPS due to intermolecular interactions. Furthermore, it observes time evolution of the two distinct assembly states, with macroscopic fibrillar-like bundles initially forming at medium salt concentration but subsequently converting into droplets after prolonged incubation. The droplet state is therefore capable of inhibiting aggregation or even dissolving aggregates through heterotypic interactions, thus preventing αSyn from its dynamically arrested state.
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Affiliation(s)
- Rebecca Sternke-Hoffmann
- Center for Life Sciences, Paul Scherrer Institute, Forschungsstrasse 111, Villigen, 5232, Switzerland
| | - Xun Sun
- Center for Life Sciences, Paul Scherrer Institute, Forschungsstrasse 111, Villigen, 5232, Switzerland
| | - Andreas Menzel
- Center for Photon Science, Paul Scherrer Institute, Forschungsstrasse 111, Villigen, 5232, Switzerland
| | - Miriam Dos Santos Pinto
- Center for Life Sciences, Paul Scherrer Institute, Forschungsstrasse 111, Villigen, 5232, Switzerland
| | - Urte Venclovaite
- Center for Life Sciences, Paul Scherrer Institute, Forschungsstrasse 111, Villigen, 5232, Switzerland
| | - Michael Wördehoff
- Institut für Physikalische Biologie, Heinrich-Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Wolfgang Hoyer
- Institut für Physikalische Biologie, Heinrich-Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Wenwei Zheng
- College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ, 85212, USA
| | - Jinghui Luo
- Center for Life Sciences, Paul Scherrer Institute, Forschungsstrasse 111, Villigen, 5232, Switzerland
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3
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Jung J, Yagi K, Tan C, Oshima H, Mori T, Yu I, Matsunaga Y, Kobayashi C, Ito S, Ugarte La Torre D, Sugita Y. GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models. J Phys Chem B 2024; 128:6028-6048. [PMID: 38876465 PMCID: PMC11215777 DOI: 10.1021/acs.jpcb.4c02096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 05/15/2024] [Accepted: 05/21/2024] [Indexed: 06/16/2024]
Abstract
GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.
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Affiliation(s)
- Jaewoon Jung
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Kiyoshi Yagi
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Cheng Tan
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Hiraku Oshima
- Laboratory
for Biomolecular Function Simulation, RIKEN
Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
- Graduate
School of Life Science, University of Hyogo, Harima Science Park City, Hyogo 678-1297, Japan
| | - Takaharu Mori
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department
of Chemistry, Tokyo University of Science, Shinjuku-ku, Tokyo 162-8601, Japan
| | - Isseki Yu
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department
of Bioinformatics, Maebashi Institute of
Technology, Maebashi, Gunma 371-0816, Japan
| | - Yasuhiro Matsunaga
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
- Graduate
School of Science and Engineering, Saitama
University, Saitama 338-8570, Japan
| | - Chigusa Kobayashi
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Shingo Ito
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Diego Ugarte La Torre
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
- Laboratory
for Biomolecular Function Simulation, RIKEN
Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
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4
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Sternke-Hoffmann R, Sun X, Menzel A, Pinto MDS, Venclovaitė U, Wördehoff M, Hoyer W, Zheng W, Luo J. Phase Separation and Aggregation of α-Synuclein Diverge at Different Salt Conditions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.01.582895. [PMID: 38464093 PMCID: PMC10925286 DOI: 10.1101/2024.03.01.582895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
The coacervation and structural rearrangement of the protein alpha-synuclein (αSyn) into cytotoxic oligomers and amyloid fibrils are considered pathological hallmarks of Parkinson's disease. While aggregation is recognized as the key element of amyloid diseases, liquid-liquid phase separation (LLPS) and its interplay with aggregation have gained increasing interest. Previous work showed that factors promoting or inhibiting amyloid formation have similar effects on phase separation. Here, we provide a detailed scanning of a wide range of parameters including protein, salt and crowding concentrations at multiple pH values, revealing different salt dependencies of aggregation and phase separation. The influence of salt on aggregation under crowded conditions follows a non-monotonic pattern, showing increased effects at medium salt concentrations. This behavior can be elucidated through a combination of electrostatic screening and salting-out effects on the intramolecular interactions between the N-terminal and C-terminal regions of αSyn. By contrast, we find a monotonic salt dependence of phase separation due to the intermolecular interaction. Furthermore, we observe the time evolution of the two distinct assembly states, with macroscopic fibrillar-like bundles initially forming at medium salt concentration but subsequently converting into droplets after prolonged incubation. The droplet state is therefore capable of inhibiting aggregation or even dissolving the aggregates through a variety of heterotypic interactions, thus preventing αSyn from its dynamically arrested state.
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Affiliation(s)
- Rebecca Sternke-Hoffmann
- Department of Biology and Chemistry, Paul Scherrer Institute, Forschungsstrasse 111, 5232 Villigen PSI, Switzerland
| | - Xun Sun
- Department of Biology and Chemistry, Paul Scherrer Institute, Forschungsstrasse 111, 5232 Villigen PSI, Switzerland
| | - Andreas Menzel
- Photon Science Division, Paul Scherrer Institute, Forschungsstrasse 111, 5232 Villigen PSI, Switzerland
| | - Miriam Dos Santos Pinto
- Department of Biology and Chemistry, Paul Scherrer Institute, Forschungsstrasse 111, 5232 Villigen PSI, Switzerland
| | - Urtė Venclovaitė
- Department of Biology and Chemistry, Paul Scherrer Institute, Forschungsstrasse 111, 5232 Villigen PSI, Switzerland
| | - Michael Wördehoff
- Institut für Physikalische Biologie, Heinrich-Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Wolfgang Hoyer
- Institut für Physikalische Biologie, Heinrich-Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Wenwei Zheng
- College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ, 85212, United States
| | - Jinghui Luo
- Department of Biology and Chemistry, Paul Scherrer Institute, Forschungsstrasse 111, 5232 Villigen PSI, Switzerland
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5
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Bjarnason S, McIvor JAP, Prestel A, Demény KS, Bullerjahn JT, Kragelund BB, Mercadante D, Heidarsson PO. DNA binding redistributes activation domain ensemble and accessibility in pioneer factor Sox2. Nat Commun 2024; 15:1445. [PMID: 38365983 PMCID: PMC10873366 DOI: 10.1038/s41467-024-45847-2] [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: 07/13/2023] [Accepted: 02/01/2024] [Indexed: 02/18/2024] Open
Abstract
More than 1600 human transcription factors orchestrate the transcriptional machinery to control gene expression and cell fate. Their function is conveyed through intrinsically disordered regions (IDRs) containing activation or repression domains but lacking quantitative structural ensemble models prevents their mechanistic decoding. Here we integrate single-molecule FRET and NMR spectroscopy with molecular simulations showing that DNA binding can lead to complex changes in the IDR ensemble and accessibility. The C-terminal IDR of pioneer factor Sox2 is highly disordered but its conformational dynamics are guided by weak and dynamic charge interactions with the folded DNA binding domain. Both DNA and nucleosome binding induce major rearrangements in the IDR ensemble without affecting DNA binding affinity. Remarkably, interdomain interactions are redistributed in complex with DNA leading to variable exposure of two activation domains critical for transcription. Charged intramolecular interactions allowing for dynamic redistributions may be common in transcription factors and necessary for sensitive tuning of structural ensembles.
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Affiliation(s)
- Sveinn Bjarnason
- Department of Biochemistry, Science Institute, University of Iceland, Sturlugata 7, 102, Reykjavík, Iceland
| | - Jordan A P McIvor
- School of Chemical Science, University of Auckland, Auckland, New Zealand
| | - Andreas Prestel
- Department of Biology, REPIN and Structural Biology and NMR Laboratory, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Kinga S Demény
- Department of Biochemistry, Science Institute, University of Iceland, Sturlugata 7, 102, Reykjavík, Iceland
| | - Jakob T Bullerjahn
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max-von-Laue-Straße 3, 60438, Frankfurt am Main, Germany
| | - Birthe B Kragelund
- Department of Biology, REPIN and Structural Biology and NMR Laboratory, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Davide Mercadante
- School of Chemical Science, University of Auckland, Auckland, New Zealand.
| | - Pétur O Heidarsson
- Department of Biochemistry, Science Institute, University of Iceland, Sturlugata 7, 102, Reykjavík, Iceland.
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6
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Barati F, Hosseini F, Vafaee R, Sabouri Z, Ghadam P, Arab SS, Shadfar N, Piroozmand F. In silico approaches to investigate enzyme immobilization: a comprehensive systematic review. Phys Chem Chem Phys 2024; 26:5744-5761. [PMID: 38294035 DOI: 10.1039/d3cp03989g] [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
Enzymes are popular catalysts with many applications, especially in industry. Biocatalyst usage on a large scale is facing some limitations, such as low operational stability, low recyclability, and high enzyme cost. Enzyme immobilization is a beneficial strategy to solve these problems. Bioinformatics tools can often correctly predict immobilization outcomes, resulting in a cost-effective experimental phase with the least time consumed. This study provides an overview of in silico methods predicting immobilization processes via a comprehensive systematic review of published articles till 11 December 2022. It also mentions the strengths and weaknesses of the processes and explains the computational analyses in each method that are required for immobilization assessment. In this regard, Web of Science and Scopus databases were screened to gain relevant publications. After screening the gathered documents (n = 3873), 60 articles were selected for the review. The selected papers have applied in silico procedures including only molecular dynamics (MD) simulations (n = 20), parallel tempering Monte Carlo (PTMC) and MD simulations (n = 3), MD and docking (n = 1), density functional theory (DFT) and MD (n = 1), only docking (n = 11), metal ion binding site prediction (MIB) server and docking (n = 2), docking and DFT (n = 1), docking and analysis of enzyme surfaces (n = 1), only DFT (n = 1), only MIB server (n = 2), analysis of an enzyme structure and surface (n = 12), rational design of immobilized derivatives (RDID) software (n = 3), and dissipative particle dynamics (DPD; n = 2). In most included studies (n = 51), enzyme immobilization was investigated experimentally in addition to in silico evaluation.
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Affiliation(s)
- Farzaneh Barati
- Department of Biotechnology, Faculty of Biological Sciences, Alzahra University, Tehran, Iran.
| | - Fakhrisadat Hosseini
- Department of Biotechnology, Faculty of Biological Sciences, Alzahra University, Tehran, Iran.
| | - Rayeheh Vafaee
- Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | - Zahra Sabouri
- Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran
| | - Parinaz Ghadam
- Department of Biotechnology, Faculty of Biological Sciences, Alzahra University, Tehran, Iran.
| | - Seyed Shahriar Arab
- Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | - Najmeh Shadfar
- Department of Biotechnology, Faculty of Biological Sciences, Alzahra University, Tehran, Iran.
| | - Firoozeh Piroozmand
- Department of Microbial Biotechnology, School of Biology and Center of Excellence in Phylogeny of Living Organisms, College of Science, University of Tehran, Tehran, Iran
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7
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Lan PD, Nissley DA, O’Brien EP, Nguyen TT, Li MS. Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2. J Chem Phys 2024; 160:055101. [PMID: 38310477 PMCID: PMC11223169 DOI: 10.1063/5.0188053] [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: 11/18/2023] [Accepted: 01/08/2024] [Indexed: 02/05/2024] Open
Abstract
The binding of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein to the host cell receptor angiotensin-converting enzyme 2 (ACE2) is the first step in human viral infection. Therefore, understanding the mechanism of interaction between RBD and ACE2 at the molecular level is critical for the prevention of COVID-19, as more variants of concern, such as Omicron, appear. Recently, atomic force microscopy has been applied to characterize the free energy landscape of the RBD-ACE2 complex, including estimation of the distance between the transition state and the bound state, xu. Here, using a coarse-grained model and replica-exchange umbrella sampling, we studied the free energy landscape of both the wild type and Omicron subvariants BA.1 and XBB.1.5 interacting with ACE2. In agreement with experiment, we find that the wild type and Omicron subvariants have similar xu values, but Omicron binds ACE2 more strongly than the wild type, having a lower dissociation constant KD.
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Affiliation(s)
| | - Daniel A. Nissley
- Department of Statistics, University of Oxford, Oxford Protein Bioinformatics Group, Oxford OX1 2JD, United Kingdom
| | | | - Toan T. Nguyen
- Key Laboratory for Multiscale Simulation of Complex Systems and Department of Theoretical Physics, Faculty of Physics, University of Science, Vietnam National University - Hanoi, 334 Nguyen Trai Street, Thanh Xuan District, Hanoi 11400, Vietnam
| | - Mai Suan Li
- Institute of Physics, Polish Academy of Sciences, al. Lotnikow 32/46, 02-668 Warsaw, Poland
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8
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Bačić Toplek F, Scalone E, Stegani B, Paissoni C, Capelli R, Camilloni C. Multi- eGO: Model Improvements toward the Study of Complex Self-Assembly Processes. J Chem Theory Comput 2024; 20:459-468. [PMID: 38153340 PMCID: PMC10782439 DOI: 10.1021/acs.jctc.3c01182] [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: 10/25/2023] [Revised: 12/16/2023] [Accepted: 12/18/2023] [Indexed: 12/29/2023]
Abstract
Structure-based models have been instrumental in simulating protein folding and suggesting hypotheses about the mechanisms involved. Nowadays, at least for fast-folding proteins, folding can be simulated in explicit solvent using classical molecular dynamics. However, other self-assembly processes, such as protein aggregation, are still far from being accessible. Recently, we proposed that a hybrid multistate structure-based model, multi-eGO, could help to bridge the gap toward the simulation of out-of-equilibrium, concentration-dependent self-assembly processes. Here, we further improve the model and show how multi-eGO can effectively and accurately learn the conformational ensemble of the amyloid β42 intrinsically disordered peptide, reproduce the well-established folding mechanism of the B1 immunoglobulin-binding domain of streptococcal protein G, and reproduce the aggregation as a function of the concentration of the transthyretin 105-115 amyloidogenic peptide. We envision that by learning from the dynamics of a few minima, multi-eGO can become a platform for simulating processes inaccessible to other simulation techniques.
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Affiliation(s)
- Fran Bačić Toplek
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, Via Celoria 26, 20133 Milano, Italy
| | - Emanuele Scalone
- Dipartimento
di Bioscienze, Università degli Studi
di Milano, Via Celoria 26, 20133 Milano, Italy
- Department
of Chemistry, Dartmouth College, Hanover, New Hampshire 03755, United States
| | - Bruno Stegani
- 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
| | - 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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9
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Nguyen H, Nguyen HL, Lan PD, Thai NQ, Sikora M, Li MS. Interaction of SARS-CoV-2 with host cells and antibodies: experiment and simulation. Chem Soc Rev 2023; 52:6497-6553. [PMID: 37650302 DOI: 10.1039/d1cs01170g] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the devastating global COVID-19 pandemic announced by WHO in March 2020. Through unprecedented scientific effort, several vaccines, drugs and antibodies have been developed, saving millions of lives, but the fight against COVID-19 continues as immune escape variants of concern such as Delta and Omicron emerge. To develop more effective treatments and to elucidate the side effects caused by vaccines and therapeutic agents, a deeper understanding of the molecular interactions of SARS-CoV-2 with them and human cells is required. With special interest in computational approaches, we will focus on the structure of SARS-CoV-2 and the interaction of its spike protein with human angiotensin-converting enzyme-2 (ACE2) as a prime entry point of the virus into host cells. In addition, other possible viral receptors will be considered. The fusion of viral and human membranes and the interaction of the spike protein with antibodies and nanobodies will be discussed, as well as the effect of SARS-CoV-2 on protein synthesis in host cells.
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Affiliation(s)
- Hung Nguyen
- Institute of Physics, Polish Academy of Sciences, al. Lotnikow 32/46, 02-668 Warsaw, Poland.
| | - Hoang Linh Nguyen
- Institute of Fundamental and Applied Sciences, Duy Tan University, Ho Chi Minh City 700000, Vietnam
- Faculty of Environmental and Natural Sciences, Duy Tan University, Da Nang 550000, Vietnam
| | - Pham Dang Lan
- Life Science Lab, Institute for Computational Science and Technology, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, 729110 Ho Chi Minh City, Vietnam
- Faculty of Physics and Engineering Physics, VNUHCM-University of Science, 227, Nguyen Van Cu Street, District 5, 749000 Ho Chi Minh City, Vietnam
| | - Nguyen Quoc Thai
- Dong Thap University, 783 Pham Huu Lau Street, Ward 6, Cao Lanh City, Dong Thap, Vietnam
| | - Mateusz Sikora
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany
| | - Mai Suan Li
- Institute of Physics, Polish Academy of Sciences, al. Lotnikow 32/46, 02-668 Warsaw, Poland.
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10
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Galvanetto N, Ivanović MT, Chowdhury A, Sottini A, Nüesch MF, Nettels D, Best RB, Schuler B. Extreme dynamics in a biomolecular condensate. Nature 2023:10.1038/s41586-023-06329-5. [PMID: 37468629 DOI: 10.1038/s41586-023-06329-5] [Citation(s) in RCA: 49] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 06/14/2023] [Indexed: 07/21/2023]
Abstract
Proteins and nucleic acids can phase-separate in the cell to form concentrated biomolecular condensates1-4. The functions of condensates span many length scales: they modulate interactions and chemical reactions at the molecular scale5, organize biochemical processes at the mesoscale6 and compartmentalize cells4. Understanding the underlying mechanisms of these processes will require detailed knowledge of the rich dynamics across these scales7. The mesoscopic dynamics of biomolecular condensates have been extensively characterized8, but their behaviour at the molecular scale has remained more elusive. Here, as an example of biomolecular phase separation, we study complex coacervates of two highly and oppositely charged disordered human proteins9. Their dense phase is 1,000 times more concentrated than the dilute phase, and the resulting percolated interaction network10 leads to a bulk viscosity 300 times greater than that of water. However, single-molecule spectroscopy optimized for measurements within individual droplets reveals that at the molecular scale, the disordered proteins remain exceedingly dynamic, with their chain configurations interconverting on submicrosecond timescales. Massive all-atom molecular dynamics simulations reproduce the experimental observations and explain this apparent discrepancy: the underlying interactions between individual charged side chains are short-lived and exchange on a pico- to nanosecond timescale. Our results indicate that, despite the high macroscopic viscosity of phase-separated systems, local biomolecular rearrangements required for efficient reactions at the molecular scale can remain rapid.
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Affiliation(s)
- Nicola Galvanetto
- Department of Biochemistry, University of Zurich, Zurich, Switzerland.
- Department of Physics, University of Zurich, Zurich, Switzerland.
| | - Miloš T Ivanović
- Department of Biochemistry, University of Zurich, Zurich, Switzerland.
| | - Aritra Chowdhury
- Department of Biochemistry, University of Zurich, Zurich, Switzerland
| | - Andrea Sottini
- Department of Biochemistry, University of Zurich, Zurich, Switzerland
| | - Mark F Nüesch
- Department of Biochemistry, University of Zurich, Zurich, Switzerland
| | - Daniel Nettels
- Department of Biochemistry, University of Zurich, Zurich, Switzerland
| | - Robert B Best
- Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
| | - Benjamin Schuler
- Department of Biochemistry, University of Zurich, Zurich, Switzerland.
- Department of Physics, University of Zurich, Zurich, Switzerland.
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11
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Halder R, Nissley DA, Sitarik I, Jiang Y, Rao Y, Vu QV, Li MS, Pritchard J, O'Brien EP. How soluble misfolded proteins bypass chaperones at the molecular level. Nat Commun 2023; 14:3689. [PMID: 37344452 DOI: 10.1038/s41467-023-38962-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 05/24/2023] [Indexed: 06/23/2023] Open
Abstract
Subpopulations of soluble, misfolded proteins can bypass chaperones within cells. The extent of this phenomenon and how it happens at the molecular level are unknown. Through a meta-analysis of the experimental literature we find that in all quantitative protein refolding studies there is always a subpopulation of soluble but misfolded protein that does not fold in the presence of one or more chaperones, and can take days or longer to do so. Thus, some misfolded subpopulations commonly bypass chaperones. Using multi-scale simulation models we observe that the misfolded structures that bypass various chaperones can do so because their structures are highly native like, leading to a situation where chaperones do not distinguish between the folded and near-native-misfolded states. More broadly, these results provide a mechanism by which long-time scale changes in protein structure and function can persist in cells because some misfolded states can bypass components of the proteostasis machinery.
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Affiliation(s)
- Ritaban Halder
- Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA
| | - Daniel A Nissley
- Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA
- Department of Statistics, University of Oxford, Oxford, OX1 3LB, UK
| | - Ian Sitarik
- Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA
| | - Yang Jiang
- Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA
| | - Yiyun Rao
- Molecular, Cellular and Integrative Biosciences Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA
| | - Quyen V Vu
- 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
- Institute for Computational Sciences and Technology; Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City, Vietnam
| | - Justin Pritchard
- Department of Biomedical Engineering, Pennsylvania State University, State College, PA, 16802, USA
- Huck Institute for the Life Sciences, Pennsylvania State University, State College, PA, 16802, USA
| | - Edward P O'Brien
- Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA.
- Bioinformatics and Genomics Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA.
- Institute for Computational and Data Sciences, Pennsylvania State University, University Park, PA, 16802, USA.
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12
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Development of hidden Markov modeling method for molecular orientations and structure estimation from high-speed atomic force microscopy time-series images. PLoS Comput Biol 2022; 18:e1010384. [PMID: 36580448 PMCID: PMC9833559 DOI: 10.1371/journal.pcbi.1010384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 01/11/2023] [Accepted: 12/20/2022] [Indexed: 12/30/2022] Open
Abstract
High-speed atomic force microscopy (HS-AFM) is a powerful technique for capturing the time-resolved behavior of biomolecules. However, structural information in HS-AFM images is limited to the surface geometry of a sample molecule. Inferring latent three-dimensional structures from the surface geometry is thus important for getting more insights into conformational dynamics of a target biomolecule. Existing methods for estimating the structures are based on the rigid-body fitting of candidate structures to each frame of HS-AFM images. Here, we extend the existing frame-by-frame rigid-body fitting analysis to multiple frames to exploit orientational correlations of a sample molecule between adjacent frames in HS-AFM data due to the interaction with the stage. In the method, we treat HS-AFM data as time-series data, and they are analyzed with the hidden Markov modeling. Using simulated HS-AFM images of the taste receptor type 1 as a test case, the proposed method shows a more robust estimation of molecular orientations than the frame-by-frame analysis. The method is applicable in integrative modeling of conformational dynamics using HS-AFM data.
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13
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Multivariate effects of pH, salt, and Zn 2+ ions on Aβ 40 fibrillation. Commun Chem 2022; 5:171. [PMID: 36697708 PMCID: PMC9814776 DOI: 10.1038/s42004-022-00786-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 11/23/2022] [Indexed: 12/15/2022] Open
Abstract
Amyloid-β (Aβ) peptide aggregation plays a central role in the progress of Alzheimer's disease (AD), of which Aβ-deposited extracellular amyloid plaques are a major hallmark. The brain micro-environmental variation in AD patients, like local acidification, increased ionic strength, or changed metal ion levels, cooperatively modulates the aggregation of the Aβ peptides. Here, we investigate the multivariate effects of varied pH, ionic strength and Zn2+ on Aβ40 fibrillation kinetics. Our results reveal that Aβ fibrillation kinetics are strongly affected by pH and ionic strength suggesting the importance of electrostatic interactions in regulating Aβ40 fibrillation. More interestingly, the presence of Zn2+ ions can further alter or even reserve the role of pH and ionic strength on the amyloid fibril kinetics, suggesting the importance of amino acids like Histidine that can interact with Zn2+ ions. Both pH and ionic strength regulate the secondary nucleation processes, however regardless of pH and Zn2+ ions, ionic strength can also modulate the morphology of Aβ40 aggregates. These multivariate effects in bulk solution provide insights into the correlation of pH-, ionic strength- or Zn2+ ions changes with amyloid deposits in AD brain and will deepen our understanding of the molecular pathology in the local brain microenvironment.
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14
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Rizuan A, Jovic N, Phan TM, Kim YC, Mittal J. Developing Bonded Potentials for a Coarse-Grained Model of Intrinsically Disordered Proteins. J Chem Inf Model 2022; 62:4474-4485. [PMID: 36066390 PMCID: PMC10165611 DOI: 10.1021/acs.jcim.2c00450] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Recent advances in residue-level coarse-grained (CG) computational models have enabled molecular-level insights into biological condensates of intrinsically disordered proteins (IDPs), shedding light on the sequence determinants of their phase separation. The existing CG models that treat protein chains as flexible molecules connected via harmonic bonds cannot populate common secondary-structure elements. Here, we present a CG dihedral angle potential between four neighboring beads centered at Cα atoms to faithfully capture the transient helical structures of IDPs. In order to parameterize and validate our new model, we propose Cα-based helix assignment rules based on dihedral angles that succeed in reproducing the atomistic helicity results of a polyalanine peptide and folded proteins. We then introduce sequence-dependent dihedral angle potential parameters (εd) and use experimentally available helical propensities of naturally occurring 20 amino acids to find their optimal values. The single-chain helical propensities from the CG simulations for commonly studied prion-like IDPs are in excellent agreement with the NMR-based α-helix fraction, demonstrating that the new HPS-SS model can accurately produce structural features of IDPs. Furthermore, this model can be easily implemented for large-scale assembly simulations due to its simplicity.
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Affiliation(s)
- Azamat Rizuan
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
| | - Nina Jovic
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
| | - Tien M Phan
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
| | - Young C Kim
- Center for Materials Physics and Technology, Naval Research Laboratory, Washington, District of Columbia 20375, United States
| | - Jeetain Mittal
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
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15
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Chang L, Perez A. Deciphering the Folding Mechanism of Proteins G and L and Their Mutants. J Am Chem Soc 2022; 144:14668-14677. [PMID: 35930769 DOI: 10.1021/jacs.2c04488] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Much of our understanding of folding mechanisms comes from interpretations of experimental ϕ and ψ value analysis, relating the differences in stability of the transition state ensemble (TSE) and folded state. We introduce a unified approach combining simulations and Bayesian inference to provide atomistic detail for the folding mechanism of proteins G and L and their mutants. Proteins G and L fold to similar topologies despite low sequence similarity, but differ in their folding pathways. A fast folding redesign of protein G, NuG2, switches folding pathways and folds through a similar pathway with protein L. A redesign of protein L also leads to faster folding, respecting the original folding pathway. Our Bayesian inference approach starts from the same prior on all systems and correctly identifies the folding mechanism for each of the four proteins, a success of the force field and sampling strategy. The approach is computationally efficient and correctly identifies the TSE and intermediate structures along the folding pathway in good agreement with experiments. We complement our findings by using two orthogonal approaches that differ in computational cost and interpretability. Adaptive sampling MD combined with the Markov state model provides a kinetic model that confirms the more complex folding mechanism of protein G and its mutant. Finally, a novel fragment decomposition approach using AlphaFold identifies preferences for secondary structure element combinations that follow the order of events observed in the folding pathways.
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Affiliation(s)
- Liwei Chang
- Department of Chemistry, University of Florida, Gainesville, Florida 32611, United States.,Quantum Theory Project, University of Florida, Gainesville, Florida 32611, United States
| | - Alberto Perez
- Department of Chemistry, University of Florida, Gainesville, Florida 32611, United States.,Quantum Theory Project, University of Florida, Gainesville, Florida 32611, United States
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16
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Oide M, Sugita Y. Protein Folding Intermediates on the Dimensionality Reduced Landscape with UMAP and Native Contact Likelihood. J Chem Phys 2022; 157:075101. [DOI: 10.1063/5.0099094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
To understand protein folding mechanisms from molecular dynamics (MD) simulations, it is important to explore not only folded/unfolded states but also representative intermediate structures on the conformational landscape. Here, we propose a novel approach to construct the landscape using the uniform manifold approximation and projection (UMAP) method, which reduces the dimensionality without losing data-point proximity. In the approach, native contact likelihood is used as feature variables rather than the conventional Cartesian coordinates or dihedral angles of protein structures. We tested the performance of UMAP for coarse-grained MD simulation trajectories of B1 domain in protein G and observed on-pathway transient structures and other metastable states on the UMAP conformational landscape. In contrast, these structures were not clearly distinguished on the dimensionality reduced landscape using principal component analysis (PCA) or time-lagged independent component analysis (tICA). This approach is also useful to obtain dynamical information through Markov State Modeling and would be applicable to large-scale conformational changes in many other biomacromolecules.
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Affiliation(s)
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN, Japan
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17
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Ooka K, Liu R, Arai M. The Wako-Saitô-Muñoz-Eaton Model for Predicting Protein Folding and Dynamics. Molecules 2022; 27:molecules27144460. [PMID: 35889332 PMCID: PMC9319528 DOI: 10.3390/molecules27144460] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/07/2022] [Accepted: 07/08/2022] [Indexed: 11/16/2022] Open
Abstract
Despite the recent advances in the prediction of protein structures by deep neutral networks, the elucidation of protein-folding mechanisms remains challenging. A promising theory for describing protein folding is a coarse-grained statistical mechanical model called the Wako-Saitô-Muñoz-Eaton (WSME) model. The model can calculate the free-energy landscapes of proteins based on a three-dimensional structure with low computational complexity, thereby providing a comprehensive understanding of the folding pathways and the structure and stability of the intermediates and transition states involved in the folding reaction. In this review, we summarize previous and recent studies on protein folding and dynamics performed using the WSME model and discuss future challenges and prospects. The WSME model successfully predicted the folding mechanisms of small single-domain proteins and the effects of amino-acid substitutions on protein stability and folding in a manner that was consistent with experimental results. Furthermore, extended versions of the WSME model were applied to predict the folding mechanisms of multi-domain proteins and the conformational changes associated with protein function. Thus, the WSME model may contribute significantly to solving the protein-folding problem and is expected to be useful for predicting protein folding, stability, and dynamics in basic research and in industrial and medical applications.
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Affiliation(s)
- Koji Ooka
- Department of Physics, Graduate School of Science, The University of Tokyo, 3-8-1 Komaba, Meguro, Tokyo 153-8902, Japan;
- Komaba Organization for Educational Excellence, College of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro, Tokyo 153-8902, Japan
| | - Runjing Liu
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro, Tokyo 153-8902, Japan;
| | - Munehito Arai
- Department of Physics, Graduate School of Science, The University of Tokyo, 3-8-1 Komaba, Meguro, Tokyo 153-8902, Japan;
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro, Tokyo 153-8902, Japan;
- Correspondence:
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18
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Sahoo A, Lee PY, Matysiak S. Transferable and Polarizable Coarse Grained Model for Proteins─ProMPT. J Chem Theory Comput 2022; 18:5046-5055. [PMID: 35793442 DOI: 10.1021/acs.jctc.2c00269] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The application of classical molecular dynamics (MD) simulations at atomic resolution (fine-grained level, FG), to most biomolecular processes, remains limited because of the associated computational complexity of representing all the atoms. This problem is magnified in the presence of protein-based biomolecular systems that have a very large conformational space, and MD simulations with fine-grained resolution have slow dynamics to explore this space. Current transferable coarse grained (CG) force fields in literature are either limited to only peptides with the environment encoded in an implicit form or cannot capture transitions into secondary/tertiary peptide structures from a primary sequence of amino acids. In this work, we present a transferable CG force field with an explicit representation of the environment for accurate simulations with proteins. The force field consists of a set of pseudoatoms representing different chemical groups that can be joined/associated together to create different biomolecular systems. This preserves the transferability of the force field to multiple environments and simulation conditions. We have added electronic polarization that can respond to environmental heterogeneity/fluctuations and couple it to protein's structural transitions. The nonbonded interactions are parametrized with physics-based features such as solvation and partitioning free energies determined by thermodynamic calculations and matched with experiments and/or atomistic simulations. The bonded potentials are inferred from corresponding distributions in nonredundant protein structure databases. We present validations of the CG model with simulations of well-studied aqueous protein systems with specific protein fold types─Trp-cage, Trpzip4, villin, WW-domain, and β-α-β. We also explore the applications of the force field to study aqueous aggregation of Aβ 16-22 peptides.
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Affiliation(s)
- Abhilash Sahoo
- Biophysics Program, University of Maryland, College Park, Maryland 20742, United States
| | - Pei-Yin Lee
- Chemical Physics Program, University of Maryland, College Park, Maryland 20742, United States
| | - Silvina Matysiak
- Fischell Department of Bioengineering, University of Maryland, College Park, Maryland 20742, United States
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19
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Multi-eGO: An in silico lens to look into protein aggregation kinetics at atomic resolution. Proc Natl Acad Sci U S A 2022; 119:e2203181119. [PMID: 35737839 PMCID: PMC9245614 DOI: 10.1073/pnas.2203181119] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 associated diseases that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the structural characterization of the transient oligomers formed during the process. Oligomers have been proven elusive to high-resolution structural techniques, while the large sizes and long time scales, typical of aggregation processes, have limited the use of computational methods to date. To surmount these limitations, we here present multi-eGO, an atomistic, hybrid structure-based model which, leveraging the knowledge of monomers conformational dynamics and of fibril structures, efficiently captures the essential structural and kinetics aspects of protein aggregation. Multi-eGO molecular dynamics simulations can describe the aggregation kinetics of thousands of monomers. The concentration dependence of the simulated kinetics, as well as the structural features of the resulting fibrils, are in qualitative agreement with in vitro experiments carried out on an amyloidogenic peptide from Transthyretin, a protein responsible for one of the most common cardiac amyloidoses. Multi-eGO simulations allow the formation of primary nuclei in a sea of transient lower-order oligomers to be observed over time and at atomic resolution, following their growth and the subsequent secondary nucleation events, until the maturation of multiple fibrils is achieved. Multi-eGO, combined with the many experimental techniques deployed to study protein aggregation, can provide the structural basis needed to advance the design of molecules targeting amyloidogenic diseases.
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20
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Tan C, Jung J, Kobayashi C, Torre DUL, Takada S, Sugita Y. Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations. PLoS Comput Biol 2022; 18:e1009578. [PMID: 35381009 PMCID: PMC9012402 DOI: 10.1371/journal.pcbi.1009578] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 04/15/2022] [Accepted: 03/26/2022] [Indexed: 12/28/2022] Open
Abstract
Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the Cα atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations.
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Affiliation(s)
- Cheng Tan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan
| | - Jaewoon Jung
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama, Japan
| | - Chigusa Kobayashi
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan
| | - Diego Ugarte La Torre
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan
| | - Shoji Takada
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | - Yuji Sugita
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama, Japan
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo, Japan
- * E-mail:
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21
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Effects of ionic strength on the folding and stability of SAMP1, a ubiquitin-like halophilic protein. Biophys J 2022; 121:552-564. [PMID: 35063455 PMCID: PMC8874027 DOI: 10.1016/j.bpj.2022.01.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 12/13/2021] [Accepted: 01/13/2022] [Indexed: 11/21/2022] Open
Abstract
Our knowledge of the folding behavior of proteins from extremophiles is limited at this time. These proteins may more closely resemble the primordial proteins selected in early evolution under extreme conditions. The small archaeal modifier protein 1 (SAMP1) studied in this report is an 87-residue protein with a β-grasp fold found in the halophile Haloferax volcanii from the Dead Sea. To gain insight into the effects of salt on the stability and folding mechanism of SAMP1, we conducted equilibrium and kinetic folding experiments as a function of sodium chloride concentration. The results revealed that increasing ionic strength accelerates refolding and slows down unfolding of SAMP1, giving rise to a pronounced salt-induced stabilization. With increasing NaCl concentration, the rate of folding observed via a combination of continuous-flow (0.1-2 ms time range) and stopped-flow measurements (>2 ms) exhibited a >100-fold increase between 0.1 and 1.5 M NaCl and leveled off at higher concentrations. Using the Linderström-Lang smeared charge formalism to model electrostatic interactions in ground and transition states encountered during folding, we showed that the observed salt dependence is dominated by Debye-Hückel screening of electrostatic repulsion among numerous negatively charged residues. Comparisons are also drawn with three well-studied mesophilic members of the β-grasp superfamily: protein G, protein L, and ubiquitin. Interestingly, the folding rate of SAMP1 in 3 M sodium chloride is comparable to that of protein G, ubiquitin, and protein L at lower ionic strength. The results indicate the important role of electrostatic interactions in protein folding and imply that proteins have evolved to minimize unfavorable charge-charge interactions under their specific native conditions.
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22
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Release of linker histone from the nucleosome driven by polyelectrolyte competition with a disordered protein. Nat Chem 2022; 14:224-231. [PMID: 34992286 DOI: 10.1038/s41557-021-00839-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 10/19/2021] [Indexed: 12/13/2022]
Abstract
Highly charged intrinsically disordered proteins are essential regulators of chromatin structure and transcriptional activity. Here we identify a surprising mechanism of molecular competition that relies on the pronounced dynamical disorder present in these polyelectrolytes and their complexes. The highly positively charged human linker histone H1.0 (H1) binds to nucleosomes with ultrahigh affinity, implying residence times incompatible with efficient biological regulation. However, we show that the disordered regions of H1 retain their large-amplitude dynamics when bound to the nucleosome, which enables the highly negatively charged and disordered histone chaperone prothymosin α to efficiently invade the H1-nucleosome complex and displace H1 via a competitive substitution mechanism, vastly accelerating H1 dissociation. By integrating experiments and simulations, we establish a molecular model that rationalizes the remarkable kinetics of this process structurally and dynamically. Given the abundance of polyelectrolyte sequences in the nuclear proteome, this mechanism is likely to be widespread in cellular regulation.
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23
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Santhakumar V, Manuel Mascarenhas N. The role of C-terminal helix in the conformational transition of an arginine binding protein. J Struct Biol X 2022; 6:100071. [PMID: 36035778 PMCID: PMC9402392 DOI: 10.1016/j.yjsbx.2022.100071] [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: 04/04/2022] [Accepted: 08/06/2022] [Indexed: 11/27/2022] Open
Abstract
Probe the role of C-ter. helix (CTH) in conformational transition of TmArgBP. Presence of CTH almost doubles the barrier to access the closed-state. In the absence of CTH, the protein can fluctuate between the two conformations. CTH not only constraints the open-state conformation but also guides in accessing it.
The thermotoga maritima arginine binding protein (TmArgBP) is a periplasmic binding protein that has a short helix at the C-terminal end (CTH), which is swapped between the two chains. We apply a coarse-grained structure-based model (SBM) and all-atom MD simulation on this protein to understand the mechanism and the role of CTH in the conformational transition. When the results of SBM simulations of TmArgBP in the presence and absence of CTH are compared, we find that CTH is strategically located at the back of the binding pocket restraining the open-state conformation thereby disengaging access to the closed-state. We also ran all-atom MD simulations of open-state TmArgBP with and without CTH and discovered that in the absence of CTH the protein could reach the closed-state within 250 ns, while in its presence, the protein remained predominantly in its open-state conformation. In the simulation started from unliganded closed-state conformation without CTH, the protein exhibited multiple transitions between the two states, suggesting CTH as an essential structural element to stabilize the open-state conformation. In another simulation that began with an unliganded closed-state conformation with CTH, the protein was able to access the open-state. In this simulation the CTH was observed to reorient itself to interact with the protein emphasizing its role in assisting the conformational change. Based on our findings, we believe that CTH not only acts as a structural element that constraints the protein in its open-state but it may also guide the protein back to its open-state conformation upon ligand unbinding.
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24
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Nguyen H, Lan PD, Nissley DA, O’Brien EP, Li MS. Electrostatic Interactions Explain the Higher Binding Affinity of the CR3022 Antibody for SARS-CoV-2 than the 4A8 Antibody. J Phys Chem B 2021; 125:7368-7379. [PMID: 34228472 PMCID: PMC8276604 DOI: 10.1021/acs.jpcb.1c03639] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 05/30/2021] [Indexed: 12/23/2022]
Abstract
A structural understanding of the mechanism by which antibodies bind SARS-CoV-2 at the atomic level is highly desirable as it can tell the development of more effective antibodies to treat Covid-19. Here, we use steered molecular dynamics (SMD) and coarse-grained simulations to estimate the binding affinity of the monoclonal antibodies CR3022 and 4A8 to the SARS-CoV-2 receptor-binding domain (RBD) and SARS-CoV-2 N-terminal domain (NTD). Consistent with experiments, our SMD and coarse-grained simulations both indicate that CR3022 has a higher affinity for SARS-CoV-2 RBD than 4A8 for the NTD, and the coarse-grained simulations indicate the former binds three times stronger to its respective epitope. This finding shows that CR3022 is a candidate for Covid-19 therapy and is likely a better choice than 4A8. Energetic decomposition of the interaction energies between these two complexes reveals that electrostatic interactions explain the difference in the observed binding affinity between the two complexes. This result could lead to a new approach for developing anti-Covid-19 antibodies in which good candidates must contain charged amino acids in the area of contact with the virus.
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Affiliation(s)
- Hung Nguyen
- Institute
of Physics, Polish Academy of Sciences, al. Lotnikow 32/46, 02-668 Warsaw, Poland
| | - Pham Dang Lan
- Life
Science Lab, Institute for Computational Science and Technology, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City, Vietnam
- Faculty
of Physics and Engineering Physics, VNUHCM-University
of Science, 227, Nguyen
Van Cu Street, District 5, Ho Chi Minh City, Vietnam
| | - Daniel A. Nissley
- Department
of Statistics, University of Oxford, Oxford
Protein Bioinformatics Group, Oxford OX1 2JD, United Kingdom
| | - Edward P. O’Brien
- Department
of Chemistry, Penn State University, University Park, Pennsylvania 16802, United States
- Bioinformatics
and Genomics Graduate Program, The Huck
Institutes of the Life Sciences, Penn State University, University Park, Pennsylvania 16802, United States
- Institute
for Computational and Data Sciences, Penn
State University, University Park, Pennsylvania 16802, United States
| | - Mai Suan Li
- Institute
of Physics, Polish Academy of Sciences, al. Lotnikow 32/46, 02-668 Warsaw, Poland
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25
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Giulini M, Rigoli M, Mattiotti G, Menichetti R, Tarenzi T, Fiorentini R, Potestio R. From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules. Front Mol Biosci 2021; 8:676976. [PMID: 34164432 PMCID: PMC8215203 DOI: 10.3389/fmolb.2021.676976] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 05/06/2021] [Indexed: 12/18/2022] Open
Abstract
The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.
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Affiliation(s)
- Marco Giulini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Marta Rigoli
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Giovanni Mattiotti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Roberto Menichetti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Thomas Tarenzi
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaele Fiorentini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaello Potestio
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
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26
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Shinobu A, Kobayashi C, Matsunaga Y, Sugita Y. Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins. J Chem Inf Model 2021; 61:2427-2443. [PMID: 33956432 DOI: 10.1021/acs.jcim.1c00286] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Large-scale conformational transitions in multi-domain proteins are often essential for their functions. To investigate the transitions, it is necessary to explore multiple potential pathways, which involve different intermediate structures. Here, we present a multi-basin (MB) coarse-grained (CG) structure-based Go̅ model for describing transitions in proteins with more than two moving domains. This model is an extension of our dual-basin Go̅ model in which system-dependent parameters are determined systematically using the multistate Bennett acceptance ratio method. In the MB Go̅ model for multi-domain proteins, we assume that intermediate structures may have partial inter-domain native contacts. This approach allows us to search multiple transition pathways that involve distinct intermediate structures using the CG molecular dynamics (MD) simulations. We apply this scheme to an enzyme, adenylate kinase (AdK), which has three major domains and can move along two different pathways. Using the optimized mixing parameters for each pathway, AdK shows frequent transitions between the Open, Closed, and the intermediate basins and samples a wide variety of conformations within each basin. The explored multiple transition pathways could be compared with experimental data and examined in more detail by atomistic MD simulations.
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Affiliation(s)
- Ai Shinobu
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
| | - Chigusa Kobayashi
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yasuhiro Matsunaga
- Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan
| | - Yuji Sugita
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan.,Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan.,Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
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27
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Bedford JT, Poutsma J, Diawara N, Greene LH. The nature of persistent interactions in two model β-grasp proteins reveals the advantage of symmetry in stability. J Comput Chem 2021; 42:600-607. [PMID: 33534913 DOI: 10.1002/jcc.26477] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 10/27/2020] [Accepted: 11/22/2020] [Indexed: 01/25/2023]
Abstract
Two proteins within the β-grasp superfamily, the B1-domain of protein G and the small archaeal modifier protein 1, were investigated to elucidate the key determinants of structural stability at the level of individual interactions. These symmetrical proteins both contain two β-hairpins which form a sheet flanked by a central α-helix. They were subjected to high temperature molecular dynamics simulations and the detailed behavior of each long-range interaction was characterized. The results revealed that in GB1 the most stable region was the C-terminal hairpin and in SAMP1 it was the opposite, the N-terminal hairpin. Experimental results for GB1 support this finding. In conclusion, it appears that the difference in the location and number of hydrophobic interactions dictate the differential stability which is accommodated due to structural symmetry of the β-grasp fold. Thus, the hairpins are interchangeable and in nature this lends itself to adaptability and flexibility.
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28
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Mahmood MI, Poma AB, Okazaki KI. Optimizing Gō-MARTINI Coarse-Grained Model for F-BAR Protein on Lipid Membrane. Front Mol Biosci 2021; 8:619381. [PMID: 33693028 PMCID: PMC7937874 DOI: 10.3389/fmolb.2021.619381] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 01/14/2021] [Indexed: 12/31/2022] Open
Abstract
Coarse-grained (CG) molecular dynamics (MD) simulations allow us to access much larger length and time scales than atomistic MD simulations, providing an attractive alternative to the conventional simulations. Based on the well-known MARTINI CG force field, the recently developed Gō-MARTINI model for proteins describes large-amplitude structural dynamics, which has not been possible with the commonly used elastic network model. Using the Gō-MARTINI model, we conduct MD simulations of the F-BAR Pacsin1 protein on lipid membrane. We observe that structural changes of the non-globular protein are largely dependent on the definition of the native contacts in the Gō model. To address this issue, we introduced a simple cutoff scheme and tuned the cutoff distance of the native contacts and the interaction strength of the Lennard-Jones potentials in the Gō-MARTINI model. With the optimized Gō-MARTINI model, we show that it reproduces structural fluctuations of the Pacsin1 dimer from atomistic simulations. We also show that two Pacsin1 dimers properly assemble through lateral interaction on the lipid membrane. Our work presents a first step towards describing membrane remodeling processes in the Gō-MARTINI CG framework by simulating a crucial step of protein assembly on the membrane.
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Affiliation(s)
- Md Iqbal Mahmood
- Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, National Institutes of Natural Sciences, Okazaki, Japan
| | - Adolfo B Poma
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
| | - Kei-Ichi Okazaki
- Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, National Institutes of Natural Sciences, Okazaki, Japan
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29
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Smith AK, Soltani M, Wilkerson JW, Timmerman BD, Zhao EL, Bundy BC, Knotts TA. Coarse-grained simulation of PEGylated and tethered protein devices at all experimentally accessible surface residues on β-lactamase for stability analysis and comparison. J Chem Phys 2021; 154:075102. [PMID: 33607875 DOI: 10.1063/5.0032019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
PEGylated and surface-tethered proteins are used in a variety of biotechnological applications, but traditional methods offer little control over the placement of the functionalization sites on the protein. Fortunately, recent experimental methods functionalize the protein at any location on the amino acid sequence, so the question becomes one of selecting the site that will result in the best protein function. This work shows how molecular simulation can be used to screen potential attachment sites for surface tethering or PEGylation. Previous simulation work has shown promise in this regard for a model protein, but these studies are limited to screening only a few of the surface-accessible sites or only considered surface tethering or PEGylation separately rather than their combined effects. This work is done to overcome these limitations by screening all surface-accessible functionalization sites on a protein of industrial and therapeutic importance (TEM-1) and to evaluate the effects of tethering and PEGylation simultaneously in an effort to create a more accurate screen. The results show that functionalization site effectiveness appears to be a function of super-secondary and tertiary structures rather than the primary structure, as is often currently assumed. Moreover, sites in the middle of secondary structure elements, and not only those in loops regions, are shown to be good options for functionalization-a fact not appreciated in current practice. Taken as a whole, the results show how rigorous molecular simulation can be done to identify candidate amino acids for functionalization on a protein to facilitate the rational design of protein devices.
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Affiliation(s)
- Addison K Smith
- Department of Chemical Engineering at Brigham Young University, Provo, Utah 84602, USA
| | - Mehran Soltani
- Department of Chemical Engineering at Brigham Young University, Provo, Utah 84602, USA
| | - Joshua W Wilkerson
- Department of Chemical Engineering at Brigham Young University, Provo, Utah 84602, USA
| | - Brandon D Timmerman
- Department of Chemical Engineering at Brigham Young University, Provo, Utah 84602, USA
| | - Emily Long Zhao
- Department of Chemical Engineering at Brigham Young University, Provo, Utah 84602, USA
| | - Bradley C Bundy
- Department of Chemical Engineering at Brigham Young University, Provo, Utah 84602, USA
| | - Thomas A Knotts
- Department of Chemical Engineering at Brigham Young University, Provo, Utah 84602, USA
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30
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Brotzakis ZF, Vendruscolo M, Bolhuis PG. A method of incorporating rate constants as kinetic constraints in molecular dynamics simulations. Proc Natl Acad Sci U S A 2021; 118:e2012423118. [PMID: 33376207 PMCID: PMC7812743 DOI: 10.1073/pnas.2012423118] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
From the point of view of statistical mechanics, a full characterization of a molecular system requires an accurate determination of its possible states, their populations, and the respective interconversion rates. Toward this goal, well-established methods increase the accuracy of molecular dynamics simulations by incorporating experimental information about states using structural restraints and about populations using thermodynamics restraints. However, it is still unclear how to include experimental knowledge about interconversion rates. Here, we introduce a method of imposing known rate constants as constraints in molecular dynamics simulations, which is based on a combination of the maximum-entropy and maximum-caliber principles. Starting from an existing ensemble of trajectories, obtained from either molecular dynamics or enhanced trajectory sampling, this method provides a minimally perturbed path distribution consistent with the kinetic constraints, as well as modified free energy and committor landscapes. We illustrate the application of the method to a series of model systems, including all-atom molecular simulations of protein folding. Our results show that by combining experimental rate constants and molecular dynamics simulations, this approach enables the determination of transition states, reaction mechanisms, and free energies. We anticipate that this method will extend the applicability of molecular simulations to kinetic studies in structural biology and that it will assist the development of force fields to reproduce kinetic and thermodynamic observables. Furthermore, this approach is generally applicable to a wide range of systems in biology, physics, chemistry, and material science.
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Affiliation(s)
- Z Faidon Brotzakis
- Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom
| | - Michele Vendruscolo
- Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom
| | - Peter G Bolhuis
- van't Hoff Institute for Molecular Sciences, University of Amsterdam, 1090 GD Amsterdam, The Netherlands
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31
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Ugarte La Torre D, Takada S. Coarse-grained implicit solvent lipid force field with a compatible resolution to the Cα protein representation. J Chem Phys 2020; 153:205101. [PMID: 33261497 DOI: 10.1063/5.0026342] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Biological membranes have been prominent targets for coarse-grained (CG) molecular dynamics simulations. While minimal CG lipid models with three beads per lipid and quantitative CG lipid models with >10 beads per lipid have been well studied, in between them, CG lipid models with a compatible resolution to residue-level CG protein models are much less developed. Here, we extended a previously developed three-bead lipid model into a five-bead model and parameterized it for two phospholipids, POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) and DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine). The developed model, iSoLF, reproduced the area per lipid, hydrophobic thickness, and phase behaviors of the target phospholipid bilayer membranes at the physiological temperature. The model POPC and DPPC membranes were in liquid and gel phases, respectively, in accordance with experiments. We further examined the spontaneous formation of a membrane bilayer, the temperature dependence of physical properties, the vesicle dynamics, and the POPC/DPPC two-component membrane dynamics of the CG lipid model, showing some promise. Once combined with standard Cα protein models, the iSoLF model will be a powerful tool to simulate large biological membrane systems made of lipids and proteins.
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Affiliation(s)
- Diego Ugarte La Torre
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | - Shoji Takada
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
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32
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Subramanian S, Golla H, Divakar K, Kannan A, de Sancho D, Naganathan AN. Slow Folding of a Helical Protein: Large Barriers, Strong Internal Friction, or a Shallow, Bumpy Landscape? J Phys Chem B 2020; 124:8973-8983. [PMID: 32955882 PMCID: PMC7659034 DOI: 10.1021/acs.jpcb.0c05976] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
![]()
The rate at which a protein molecule
folds is determined by opposing
energetic and entropic contributions to the free energy that shape
the folding landscape. Delineating the extent to which they impact
the diffusional barrier-crossing events, including the magnitude of
internal friction and barrier height, has largely been a challenging
task. In this work, we extract the underlying thermodynamic and dynamic
contributions to the folding rate of an unusually slow-folding helical
DNA-binding domain, PurR, which shares the characteristics of ultrafast
downhill-folding proteins but nonetheless appears to exhibit an apparent
two-state equilibrium. We combine equilibrium spectroscopy, temperature-viscosity-dependent
kinetics, statistical mechanical modeling, and coarse-grained simulations
to show that the conformational behavior of PurR is highly heterogeneous
characterized by a large spread in melting temperatures, marginal
thermodynamic barriers, and populated partially structured states.
PurR appears to be at the threshold of disorder arising from frustrated
electrostatics and weak packing that in turn slows down folding due
to a shallow, bumpy landscape and not due to large thermodynamic barriers
or strong internal friction. Our work highlights how a strong temperature
dependence on the pre-exponential could signal a shallow landscape
and not necessarily a slow-folding diffusion coefficient, thus determining
the folding timescales of even millisecond folding proteins and hints
at possible structural origins for the shallow landscape.
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Affiliation(s)
- Sandhyaa Subramanian
- Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
| | - Hemashree Golla
- Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
| | - Kalivarathan Divakar
- Department of Biotechnology, National Institute of Technology Warangal, Warangal 506004, India
| | - Adithi Kannan
- Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
| | - David de Sancho
- Polimero eta Material Aurreratuak: Fisika, Kimika eta Teknologia, Kimika Fakultatea, Euskal Herriko Unibertsitatea UPV/EHU, Donostia-San Sebastián 20080, Spain.,Donostia International Physics Center (DIPC), PK 1072, Donostia-San Sebastián 20080, Spain
| | - Athi N Naganathan
- Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
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33
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Avestan MS, Javidi A, Ganote LP, Brown JM, Stan G. Kinetic effects in directional proteasomal degradation of the green fluorescent protein. J Chem Phys 2020; 153:105101. [DOI: 10.1063/5.0015191] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Affiliation(s)
| | - Alex Javidi
- Data Sciences, Janssen Research and Development, Spring House, Pennsylvania 19477, USA
| | | | | | - George Stan
- Department of Chemistry, University of Cincinnati, Cincinnati, Ohio 45221, USA
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34
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Nguyen HL, Lan PD, Thai NQ, Nissley DA, O'Brien EP, Li MS. Does SARS-CoV-2 Bind to Human ACE2 More Strongly Than Does SARS-CoV? J Phys Chem B 2020; 124:7336-7347. [PMID: 32790406 PMCID: PMC7433338 DOI: 10.1021/acs.jpcb.0c04511] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
![]()
The
2019 novel coronavirus (SARS-CoV-2) epidemic, which was first
reported in December 2019 in Wuhan, China, was declared a pandemic
by the World Health Organization in March 2020. Genetically, SARS-CoV-2
is closely related to SARS-CoV, which caused a global epidemic with
8096 confirmed cases in more than 25 countries from 2002 to 2003.
Given the significant morbidity and mortality rate, the current pandemic
poses a danger to all of humanity, prompting us to understand the
activity of SARS-CoV-2 at the atomic level. Experimental studies have
revealed that spike proteins of both SARS-CoV-2 and SARS-CoV bind
to angiotensin-converting enzyme 2 (ACE2) before entering the cell
for replication. However, the binding affinities reported by different
groups seem to contradict each other. Wrapp et al. (Science2020, 367, 1260–1263) showed
that the spike protein of SARS-CoV-2 binds to the ACE2 peptidase domain
(ACE2-PD) more strongly than does SARS-CoV, and this fact may be associated
with a greater severity of the new virus. However, Walls et al. (Cell2020, 181, 281–292)
reported that SARS-CoV-2 exhibits a higher binding affinity, but the
difference between the two variants is relatively small. To understand
the binding mechnism and experimental results, we investigated how
the receptor binding domain (RBD) of SARS-CoV (SARS-CoV-RBD) and SARS-CoV-2
(SARS-CoV-2-RBD) interacts with a human ACE2-PD using molecular modeling.
We applied a coarse-grained model to calculate the dissociation constant
and found that SARS-CoV-2 displays a 2-fold higher binding affinity.
Using steered all-atom molecular dynamics simulations, we demonstrate
that, like a coarse-grained simulation, SARS-CoV-2-RBD was associated
with ACE2-PD more strongly than was SARS-CoV-RBD, as evidenced by
a higher rupture force and larger pulling work. We show that the binding
affinity of both viruses to ACE2 is driven by electrostatic interactions.
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Affiliation(s)
- Hoang Linh Nguyen
- Life Science Lab, Institute for Computational Science and Technology, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City, Vietnam
| | - Pham Dang Lan
- Life Science Lab, Institute for Computational Science and Technology, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City, Vietnam.,Faculty of Physics and Engineering Physics, VNUHCM-University of Science, 227, Nguyen Van Cu Street, District 5, Ho Chi Minh City, Vietnam
| | - Nguyen Quoc Thai
- Life Science Lab, Institute for Computational Science and Technology, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City, Vietnam.,Dong Thap University, 783 Pham Huu Lau Street, Ward 6, Cao Lanh City, Dong Thap, Vietnam
| | - Daniel A Nissley
- Department of Statistics, University of Oxford, Oxford OX1 2JD, United Kingdom
| | - Edward P O'Brien
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania 16802, United States.,Bioinformatics and Genomics Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, United States.,Institute for Computational and Data Sciences, Pennsylvania State University, University Park, Pennsylvania 16802,United States
| | - Mai Suan Li
- Institute of Physics, Polish Academy of Sciences, al. Lotnikow 32/46, 02-668 Warsaw, Poland
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35
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Protein mechanics probed using simple molecular models. Biochim Biophys Acta Gen Subj 2020; 1864:129613. [DOI: 10.1016/j.bbagen.2020.129613] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 03/06/2020] [Accepted: 04/08/2020] [Indexed: 01/14/2023]
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36
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Mioduszewski Ł, Różycki B, Cieplak M. Pseudo-Improper-Dihedral Model for Intrinsically Disordered Proteins. J Chem Theory Comput 2020; 16:4726-4733. [PMID: 32436706 PMCID: PMC7588027 DOI: 10.1021/acs.jctc.0c00338] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
We present a new coarse-grained Cα-based protein model with a nonradial multibody pseudo-improper-dihedral potential that is transferable, time-independent, and suitable for molecular dynamics. It captures the nature of backbone and side-chain interactions between amino acid residues by adapting a simple improper dihedral term for a one-bead-per-residue model. It is parameterized for intrinsically disordered proteins and applicable to simulations of such proteins and their assemblies on millisecond time scales.
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Affiliation(s)
- Łukasz Mioduszewski
- Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
| | - Bartosz Różycki
- Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
| | - Marek Cieplak
- Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
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37
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Lafita A, Tian P, Best RB, Bateman A. TADOSS: computational estimation of tandem domain swap stability. Bioinformatics 2020; 35:2507-2508. [PMID: 30500878 PMCID: PMC6612889 DOI: 10.1093/bioinformatics/bty974] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Revised: 10/13/2018] [Accepted: 11/28/2018] [Indexed: 11/17/2022] Open
Abstract
Summary Proteins with highly similar tandem domains have shown an increased propensity for misfolding and aggregation. Several molecular explanations have been put forward, such as swapping of adjacent domains, but there is a lack of computational tools to systematically analyze them. We present the TAndem DOmain Swap Stability predictor (TADOSS), a method to computationally estimate the stability of tandem domain-swapped conformations from the structures of single domains, based on previous coarse-grained simulation studies. The tool is able to discriminate domains susceptible to domain swapping and to identify structural regions with high propensity to form hinge loops. TADOSS is a scalable method and suitable for large scale analyses. Availability and implementation Source code and documentation are freely available under an MIT license on GitHub at https://github.com/lafita/tadoss. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Aleix Lafita
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Pengfei Tian
- Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Robert B Best
- Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Alex Bateman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
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38
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Taylor PA, Jayaraman A. Molecular Modeling and Simulations of Peptide–Polymer Conjugates. Annu Rev Chem Biomol Eng 2020; 11:257-276. [DOI: 10.1146/annurev-chembioeng-092319-083243] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Peptide–polymer conjugates are a class of soft materials composed of covalently linked blocks of protein/polypeptides and synthetic/natural polymers. These materials are practically useful in biological applications, such as drug delivery, DNA/gene delivery, and antimicrobial coatings, as well as nonbiological applications, such as electronics, separations, optics, and sensing. Given their broad applicability, there is motivation to understand the molecular and macroscale structure, dynamics, and thermodynamic behavior exhibited by such materials. We focus on the past and ongoing molecular simulation studies aimed at obtaining such fundamental understanding and predicting molecular design rules for the target function. We describe briefly the experimental work in this field that validates or motivates these computational studies. We also describe the various models (e.g., atomistic, coarse-grained, or hybrid) and simulation methods (e.g., stochastic versus deterministic, enhanced sampling) that have been used and the types of questions that have been answered using these computational approaches.
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Affiliation(s)
- Phillip A. Taylor
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, USA
| | - Arthi Jayaraman
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, USA
- Department of Materials Science and Engineering, University of Delaware, Newark, Delaware 19716, USA
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39
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Kimura R, Aumpuchin P, Hamaue S, Shimomura T, Kikuchi T. Analyses of the folding sites of irregular β-trefoil fold proteins through sequence-based techniques and Gō-model simulations. BMC Mol Cell Biol 2020; 21:28. [PMID: 32295515 PMCID: PMC7477875 DOI: 10.1186/s12860-020-00271-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 03/31/2020] [Indexed: 02/07/2023] Open
Abstract
Background The details of the folding mechanisms have not yet been fully understood for many proteins, and it is believed that the information on the folding mechanism of a protein is encoded in its amino acid sequence. β-trefoil proteins are known to have the same 3D scaffold, namely, a three-fold symmetric scaffold, despite the proteins’ low sequence identity among superfamilies. In this study, we extract an initial folding unit from the amino acid sequences of irregular β-trefoil proteins by constructing an average distance map (ADM) and utilizing inter-residue average distance statistics to determine the relative contact frequencies for residue pairs in terms of F values. We compare our sequence-based prediction results with the packing between hydrophobic residues in native 3D structures and a Gō-model simulation. Results The ADM and F-value analyses predict that the N-terminal and C-terminal regions are compact and that the hydrophobic residues at the central region can be regarded as an interaction center with other residues. These results correspond well to those of the Gō-model simulations. Moreover, our results indicate that the irregular parts in the β-trefoil proteins do not hinder the protein formation. Conserved hydrophobic residues on the β5 strand are always the interaction center of packing between the conserved hydrophobic residues in both regular and irregular β-trefoil proteins. Conclusions We revealed that the β5 strand plays an important role in β-trefoil protein structure construction. The sequence-based methods used in this study can extract the protein folding information from only amino acid sequence data, and well corresponded to 3D structure-based Gō-model simulation and available experimental results.
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Affiliation(s)
- Risako Kimura
- Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga, 525-8577, Japan
| | - Panyavut Aumpuchin
- National Center for Genetic Engineering and Biotechnology (BIOTEC), 113 Thailand Science Park, Phaholyothin Road, Klong Luang, Pathumthani, 12120, Thailand
| | - Shoya Hamaue
- Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga, 525-8577, Japan
| | - Takumi Shimomura
- Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga, 525-8577, Japan
| | - Takeshi Kikuchi
- Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga, 525-8577, Japan.
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40
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Nissley DA, Vu QV, Trovato F, Ahmed N, Jiang Y, Li MS, O'Brien EP. Electrostatic Interactions Govern Extreme Nascent Protein Ejection Times from Ribosomes and Can Delay Ribosome Recycling. J Am Chem Soc 2020; 142:6103-6110. [PMID: 32138505 DOI: 10.1021/jacs.9b12264] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The ejection of nascent proteins out of the ribosome exit tunnel, after their covalent bond to transfer-RNA has been broken, has not been experimentally studied due to challenges in sample preparation. Here, we investigate this process using a combination of multiscale modeling, ribosome profiling, and gene ontology analyses. Simulating the ejection of a representative set of 122 E. coli proteins we find a greater than 1000-fold variation in ejection times. Nascent proteins enriched in negatively charged residues near their C-terminus eject the fastest, while nascent chains enriched in positively charged residues tend to eject much more slowly. More work is required to pull slowly ejecting proteins out of the exit tunnel than quickly ejecting proteins, according to all-atom simulations. An energetic decomposition reveals, for slowly ejecting proteins, that this is due to the strong attractive electrostatic interactions between the nascent chain and the negatively charged ribosomal-RNA lining the exit tunnel, and for quickly ejecting proteins, it is due to their repulsive electrostatic interactions with the exit tunnel. Ribosome profiling data from E. coli reveals that the presence of slowly ejecting sequences correlates with ribosomes spending more time at stop codons, indicating that the ejection process might delay ribosome recycling. Proteins that have the highest positive charge density at their C-terminus are overwhelmingly ribosomal proteins, suggesting the possibility that this sequence feature may aid in the cotranslational assembly of ribosomes by delaying the release of nascent ribosomal proteins into the cytosol. Thus, nascent chain ejection times from the ribosome can vary greatly between proteins due to differential electrostatic interactions, can influence ribosome recycling, and could be particularly relevant to the synthesis and cotranslational behavior of some proteins.
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Affiliation(s)
| | - Quyen V Vu
- 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.,Institute for Computational Sciences and Technology, Ho Chi Minh City, Vietnam
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41
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Arsiccio A, McCarty J, Pisano R, Shea JE. Heightened Cold-Denaturation of Proteins at the Ice–Water Interface. J Am Chem Soc 2020; 142:5722-5730. [DOI: 10.1021/jacs.9b13454] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Andrea Arsiccio
- Department of Applied Science and Technology, Politecnico di Torino, 24 corso Duca degli Abruzzi, Torino 10129, Italy
| | - James McCarty
- Department of Chemistry, Western Washington University, Bellingham, Washington 98225, United States
| | - Roberto Pisano
- Department of Applied Science and Technology, Politecnico di Torino, 24 corso Duca degli Abruzzi, Torino 10129, Italy
| | - Joan-Emma Shea
- Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106, United States
- Department of Physics, University of California, Santa Barbara, California 93106, United States
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42
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Hussain S, Haji-Akbari A. Studying rare events using forward-flux sampling: Recent breakthroughs and future outlook. J Chem Phys 2020; 152:060901. [DOI: 10.1063/1.5127780] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Sarwar Hussain
- Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520, USA
| | - Amir Haji-Akbari
- Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520, USA
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43
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Wang Y, Brooks Iii CL. Electrostatic Forces Control the Negative Allosteric Regulation in a Disordered Protein Switch. J Phys Chem Lett 2020; 11:864-868. [PMID: 31940206 DOI: 10.1021/acs.jpclett.9b03618] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The transcriptional adaptor zinc-binding 1 (TAZ1) domain of the transcriptional coactivator CBP/P300 and two disordered peptides, HIF-1α and CITED2, form a delicate protein switch that regulates cellular hypoxic response. In hypoxia, HIF-1α binds TAZ1 to control the transcription of adaptive genes critical for the recovery from hypoxic stress. CITED2 acts as the negative feedback regulator to rapidly displace HIF-1α and efficiently attenuate the hypoxic response. Though CITED2 and HIF-1α have the same dissociation constant (Kd = 10 nM) in their binary complexes with TAZ1, CITED2 is much more competitive than HIF-1α upon binding the same target TAZ1 in ternary ( Berlow et al. Nature 2017 , 543 , 447 - 451 ). Here we demonstrate that a simple coarse-grained model can recapitulate this negative allosteric effect and provide detailed physical insights into the displacement mechanism. We find that long-range electrostatic forces are essential for the efficient displacement of HIF-1α by CITED2. The strong electrostatic interactions between CITED2 and TAZ1, along with the unique binding mode, make CITED2 much more competitive than HIF-1α in binding TAZ1.
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44
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Theoretical and computational advances in protein misfolding. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2020; 118:1-31. [PMID: 31928722 DOI: 10.1016/bs.apcsb.2019.08.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
Misfolded proteins escape the cellular quality control mechanism and fail to fold properly or remain correctly folded leading to a loss in their functional specificity. Thus misfolding of proteins cause a large number of very different diseases ranging from errors in metabolism to various types of complex neurodegenerative diseases. A theoretical and computational perspective of protein misfolding is presented with a special emphasis on its salient features, mechanism and consequences. These insights quantitatively analyze different determinants of misfolding, that may be applied to design disease specific molecular targets.
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45
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Ruiz-Ortiz I, De Sancho D. Competitive binding of HIF-1α and CITED2 to the TAZ1 domain of CBP from molecular simulations. Phys Chem Chem Phys 2020; 22:8118-8127. [DOI: 10.1039/d0cp00328j] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Many intrinsically disordered proteins (IDPs) are involved in complex signalling networks inside the cell.
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Affiliation(s)
- Irene Ruiz-Ortiz
- Donostia International Physics Center
- Donostia-San Sebastián
- Spain
| | - David De Sancho
- Donostia International Physics Center
- Donostia-San Sebastián
- Spain
- University of the Basque Country
- Faculty of Chemistry
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46
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Dima RI, Stan G. Computational Studies of Mechanical Remodeling of Substrate Proteins by AAA+ Biological Nanomachines. ACS SYMPOSIUM SERIES 2020. [DOI: 10.1021/bk-2020-1356.ch008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Ruxandra I. Dima
- Department of Chemistry, University of Cincinnati, P. O. Box 210172, Cincinnati, Ohio 45221, United States
| | - George Stan
- Department of Chemistry, University of Cincinnati, P. O. Box 210172, Cincinnati, Ohio 45221, United States
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47
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Wei S, Zou X, Tian J, Huang H, Guo W, Chen Z. Control of Protein Conformation and Orientation on Graphene. J Am Chem Soc 2019; 141:20335-20343. [PMID: 31774666 DOI: 10.1021/jacs.9b10705] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Graphene-based biosensors have attracted considerable attention due to their advantages of label-free detection and high sensitivity. Many such biosensors utilize noncovalent van der Waals force to attach proteins onto graphene surface while preserving graphene's high conductivity. Maintaining the protein structure without denaturation/substantial conformational change and controlling proper protein orientation on the graphene surface are critical for biosensing applications of these biosensors fabricated with proteins on graphene. Based on the knowledge we obtained from our previous experimental study and computer modeling of amino acid residual level interactions between graphene and peptides, here we systemically redesigned an important protein for better conformational stability and desirable orientation on graphene. In this paper, immunoglobulin G (IgG) antibody-binding domain of protein G (protein GB1) was studied to demonstrate how we can preserve the protein native structure and control the protein orientation on graphene surface by redesigning protein mutants. Various experimental tools including sum frequency generation vibrational spectroscopy, attenuated total refection-Fourier transform infrared spectroscopy, fluorescence spectroscopy, and circular dichroism spectroscopy were used to study the protein GB1 structure on graphene, supplemented by molecular dynamics simulations. By carefully designing the protein GB1 mutant, we can avoid strong unfavorable interactions between protein and graphene to preserve protein conformation and to enable the protein to adopt a preferred orientation. The methodology developed in this study is general and can be applied to study different proteins on graphene and beyond. With the knowledge obtained from this research, one could apply this method to optimize protein function on surfaces (e.g., to enhance biosensor sensitivity).
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Affiliation(s)
- Shuai Wei
- Department of Chemistry , University of Michigan , Ann Arbor , Michigan 48109 , United States
| | - Xingquan Zou
- Department of Chemistry , University of Michigan , Ann Arbor , Michigan 48109 , United States
| | - Jiayi Tian
- Department of Chemistry , University of Michigan , Ann Arbor , Michigan 48109 , United States
| | - Hao Huang
- Department of Chemistry , University of Michigan , Ann Arbor , Michigan 48109 , United States
| | - Wen Guo
- Department of Chemistry , University of Michigan , Ann Arbor , Michigan 48109 , United States
| | - Zhan Chen
- Department of Chemistry , University of Michigan , Ann Arbor , Michigan 48109 , United States
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48
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Schuler B, Borgia A, Borgia MB, Heidarsson PO, Holmstrom ED, Nettels D, Sottini A. Binding without folding - the biomolecular function of disordered polyelectrolyte complexes. Curr Opin Struct Biol 2019; 60:66-76. [PMID: 31874413 DOI: 10.1016/j.sbi.2019.12.006] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 11/29/2019] [Accepted: 12/05/2019] [Indexed: 12/16/2022]
Abstract
Recent evidence shows that oppositely charged intrinsically disordered proteins (IDPs) can form high-affinity complexes that involve neither the formation of secondary or tertiary structure nor site-specific interactions between individual residues. Similar electrostatically dominated interactions have also been identified for positively charged IDPs binding to nucleic acids. These highly disordered polyelectrolyte complexes constitute an extreme case within the spectrum of biomolecular interactions involving disorder. Such interactions are likely to be widespread, since sequence analysis predicts proteins with highly charged disordered regions to be surprisingly numerous. Here, we summarize the insights that have emerged from the highly disordered polyelectrolyte complexes identified so far, and we highlight recent developments and future challenges in (i) establishing models for the underlying highly dynamic structural ensembles, (ii) understanding the novel binding mechanisms associated with them, and (iii) identifying the functional consequences.
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Affiliation(s)
- Benjamin Schuler
- Department of Biochemistry, University of Zurich, Switzerland; Department of Physics, University of Zurich, Switzerland.
| | - Alessandro Borgia
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Madeleine B Borgia
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Pétur O Heidarsson
- Department of Biochemistry, Science Institute, University of Iceland, Dunhagi 3, 107 Reykjavík, Iceland
| | - Erik D Holmstrom
- Department of Molecular Biosciences, University of Kansas, 1200 Sunnyside, Lawrence, KS 66045, USA; Department of Chemistry, University of Kansas, 1200 Sunnyside, Lawrence, KS 66045, USA
| | - Daniel Nettels
- Department of Biochemistry, University of Zurich, Switzerland
| | - Andrea Sottini
- Department of Biochemistry, University of Zurich, Switzerland
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49
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Shinobu A, Kobayashi C, Matsunaga Y, Sugita Y. Building a macro-mixing dual-basin Gō model using the Multistate Bennett Acceptance Ratio. Biophys Physicobiol 2019; 16:310-321. [PMID: 31984186 PMCID: PMC6975896 DOI: 10.2142/biophysico.16.0_310] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Accepted: 08/02/2019] [Indexed: 12/01/2022] Open
Abstract
The dual-basin Gō-model is a structural-based coarsegrained model for simulating a conformational transition between two known structures of a protein. Two parameters are required to produce a dual-basin potential mixed using two single-basin potentials, although the determination of mixing parameters is usually not straightforward. Here, we have developed an efficient scheme to determine the mixing parameters using the Multistate Bennett Acceptance Ratio (MBAR) method after short simulations with a set of parameters. In the scheme, MBAR allows us to predict observables at various unsimulated conditions, which are useful to improve the mixing parameters in the next round of iterative simulations. The number of iterations that are necessary for obtaining the converged mixing parameters are significantly reduced in the scheme. We applied the scheme to two proteins, the glutamine binding protein and the ribose binding protein, for showing the effectiveness in the parameter determination. After obtaining the converged parameters, both proteins show frequent conformational transitions between open and closed states, providing the theoretical basis to investigate structure-dynamics-function relationships of the proteins.
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Affiliation(s)
- Ai Shinobu
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Chigusa Kobayashi
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yasuhiro Matsunaga
- Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan
| | - Yuji Sugita
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
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50
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Abstract
This review discusses Gō models broadly used in biomolecular simulations. I start with a brief description of the original lattice model study by Nobuhiro Gō. Then, the theory of protein folding behind Gō model, free energy approaches, and off-lattice Gō models are reviewed. I also mention a stringent test for the assumption in Gō models given from all-atom molecular dynamics simulations. Subsequently, I move to application of Gō models to protein dynamical functions. Various extension of Gō models is also reviewed. Finally, some publicly available tools to use Gō models are listed.
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Affiliation(s)
- Shoji Takada
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto 606-8502, Japan
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