1
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Latham AP, Tempkin JOB, Otsuka S, Zhang W, Ellenberg J, Sali A. Integrative spatiotemporal modeling of biomolecular processes: application to the assembly of the Nuclear Pore Complex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.06.606842. [PMID: 39149317 PMCID: PMC11326192 DOI: 10.1101/2024.08.06.606842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. We first compute integrative structure models at fixed time points and then optimally select and connect these snapshots into a series of trajectories that optimize the likelihood of both the snapshots and transitions between them. The method is demonstrated by application to the assembly process of the human Nuclear Pore Complex in the context of the reforming nuclear envelope during mitotic cell division, based on live-cell correlated electron tomography, bulk fluorescence correlation spectroscopy-calibrated quantitative live imaging, and a structural model of the fully-assembled Nuclear Pore Complex. Modeling of the assembly process improves the model precision over static integrative structure modeling alone. The method is applicable to a wide range of time-dependent systems in cell biology, and is available to the broader scientific community through an implementation in the open source Integrative Modeling Platform software.
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Affiliation(s)
- Andrew P Latham
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jeremy O B Tempkin
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Shotaro Otsuka
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Wanlu Zhang
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jan Ellenberg
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94143, USA
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2
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Liu S, Athreya A, Lao Z, Zhang B. From Nucleosomes to Compartments: Physicochemical Interactions Underlying Chromatin Organization. Annu Rev Biophys 2024; 53:221-245. [PMID: 38346246 PMCID: PMC11369498 DOI: 10.1146/annurev-biophys-030822-032650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2024]
Abstract
Chromatin organization plays a critical role in cellular function by regulating access to genetic information. However, understanding chromatin folding is challenging due to its complex, multiscale nature. Significant progress has been made in studying in vitro systems, uncovering the structure of individual nucleosomes and their arrays, and elucidating the role of physicochemical forces in stabilizing these structures. Additionally, remarkable advancements have been achieved in characterizing chromatin organization in vivo, particularly at the whole-chromosome level, revealing important features such as chromatin loops, topologically associating domains, and nuclear compartments. However, bridging the gap between in vitro and in vivo studies remains challenging. The resemblance between in vitro and in vivo chromatin conformations and the relevance of internucleosomal interactions for chromatin folding in vivo are subjects of debate. This article reviews experimental and computational studies conducted at various length scales, highlighting the significance of intrinsic interactions between nucleosomes and their roles in chromatin folding in vivo.
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Affiliation(s)
- Shuming Liu
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;
| | - Advait Athreya
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;
| | - Zhuohan Lao
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;
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3
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Latham AP, Zhu L, Sharon DA, Ye S, Willard AP, Zhang X, Zhang B. Microphase Separation Produces Interfacial Environment within Diblock Biomolecular Condensates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.30.534967. [PMID: 37034777 PMCID: PMC10081284 DOI: 10.1101/2023.03.30.534967] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
The phase separation of intrinsically disordered proteins is emerging as an important mechanism for cellular organization. However, efforts to connect protein sequences to the physical properties of condensates, i.e., the molecular grammar, are hampered by a lack of effective approaches for probing high-resolution structural details. Using a combination of multiscale simulations and fluorescence lifetime imaging microscopy experiments, we systematically explored a series of systems consisting of diblock elastin-like polypeptides (ELP). The simulations succeeded in reproducing the variation of condensate stability upon amino acid substitution and revealed different microenvironments within a single condensate, which we verified with environmentally sensitive fluorophores. The interspersion of hydrophilic and hydrophobic residues and a lack of secondary structure formation result in an interfacial environment, which explains both the strong correlation between ELP condensate stability and interfacial hydrophobicity scales, as well as the prevalence of protein-water hydrogen bonds. Our study uncovers new mechanisms for condensate stability and organization that may be broadly applicable.
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Affiliation(s)
- Andrew P Latham
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Longchen Zhu
- Department of Chemistry, School of Science and Research Center for Industries of the Future, Westlake University, 600 Dunyu Road, Hangzhou 310030, Zhejiang Province, China
- Westlake Laboratory of Life Sciences and Biomedicine, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Dina A Sharon
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Songtao Ye
- Department of Chemistry, School of Science and Research Center for Industries of the Future, Westlake University, 600 Dunyu Road, Hangzhou 310030, Zhejiang Province, China
- Westlake Laboratory of Life Sciences and Biomedicine, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Adam P Willard
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Xin Zhang
- Department of Chemistry, School of Science and Research Center for Industries of the Future, Westlake University, 600 Dunyu Road, Hangzhou 310030, Zhejiang Province, China
- Westlake Laboratory of Life Sciences and Biomedicine, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139
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4
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Airas J, Ding X, Zhang B. Transferable Implicit Solvation via Contrastive Learning of Graph Neural Networks. ACS CENTRAL SCIENCE 2023; 9:2286-2297. [PMID: 38161379 PMCID: PMC10755853 DOI: 10.1021/acscentsci.3c01160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/26/2023] [Accepted: 10/31/2023] [Indexed: 01/03/2024]
Abstract
Implicit solvent models are essential for molecular dynamics simulations of biomolecules, striking a balance between computational efficiency and biological realism. Efforts are underway to develop accurate and transferable implicit solvent models and coarse-grained (CG) force fields in general, guided by a bottom-up approach that matches the CG energy function with the potential of mean force (PMF) defined by the finer system. However, practical challenges arise due to the lack of analytical expressions for the PMF and algorithmic limitations in parameterizing CG force fields. To address these challenges, a machine learning-based approach is proposed, utilizing graph neural networks (GNNs) to represent the solvation free energy and potential contrasting for parameter optimization. We demonstrate the effectiveness of the approach by deriving a transferable GNN implicit solvent model using 600,000 atomistic configurations of six proteins obtained from explicit solvent simulations. The GNN model provides solvation free energy estimations much more accurately than state-of-the-art implicit solvent models, reproducing configurational distributions of explicit solvent simulations. We also demonstrate the reasonable transferability of the GNN model outside of the training data. Our study offers valuable insights for deriving systematically improvable implicit solvent models and CG force fields from a bottom-up perspective.
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Affiliation(s)
- Justin Airas
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, United
States
| | - Xinqiang Ding
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, United
States
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, United
States
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5
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Borges-Araújo L, Patmanidis I, Singh AP, Santos LHS, Sieradzan AK, Vanni S, Czaplewski C, Pantano S, Shinoda W, Monticelli L, Liwo A, Marrink SJ, Souza PCT. Pragmatic Coarse-Graining of Proteins: Models and Applications. J Chem Theory Comput 2023; 19:7112-7135. [PMID: 37788237 DOI: 10.1021/acs.jctc.3c00733] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.
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Affiliation(s)
- Luís Borges-Araújo
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
| | - Ilias Patmanidis
- Department of Chemistry, Aarhus University, Langelandsgade 140, 8000 Aarhus C, Denmark
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Akhil P Singh
- Department of Biology, University of Fribourg, Chemin du Musée 10, Fribourg CH-1700, Switzerland
| | - Lucianna H S Santos
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay
| | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Stefano Vanni
- Department of Biology, University of Fribourg, Chemin du Musée 10, Fribourg CH-1700, Switzerland
- Institut de Pharmacologie Moléculaire et Cellulaire, Université Côte d'Azur, Inserm, CNRS, 06560 Valbonne, France
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Sergio Pantano
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay
| | - Wataru Shinoda
- Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita, Okayama 700-8530, Japan
| | - Luca Monticelli
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
| | - Adam Liwo
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Paulo C T Souza
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
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6
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Liu F, Wang J. ATP Acts as a Hydrotrope to Regulate the Phase Separation of NBDY Clusters. JACS AU 2023; 3:2578-2585. [PMID: 37772172 PMCID: PMC10523361 DOI: 10.1021/jacsau.3c00391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 08/16/2023] [Accepted: 08/25/2023] [Indexed: 09/30/2023]
Abstract
Nonannotated P-body dissociating polypeptide (NBDY) is a recently discovered human microprotein that has been found to be a novel component of the mRNA decapping complex. Previous studies have shown that the phosphorylation of NBDY promotes the liquid phase of the NBDY remixing in vitro. Typically, during the process of phosphorylation, a phosphate group is added to the protein through adenosine triphosphate (ATP) hydrolysis. It has been shown that ATP acts as a biological hydrotrope, affecting the phase separation of proteins in solution. In this study, we utilized simulation methods to investigate the dynamic properties of the NBDY clusters at various ATP concentrations. Our findings demonstrate that ATP can regulate the phase separation of NBDY clusters. Specifically, we identified a critical point in the concentration ratio between ATP and NBDY that exhibits a dual effect on the phase separation of NBDY. We observed that the nonsaturated ATP concentration can facilitate the formation of phase separation, while oversaturated ATP concentration promotes the diffusion of NBDY, and the oversaturated ATP-NBDY interaction impedes the phase separation of NBDY. Additionally, we found that ATPs can bind to the protein surface by aggregating into ATP clusters, which further hinders the diffusion of NBDY clusters. Our work provides general insight into the role of ATP in the phase separation of protein condensates.
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Affiliation(s)
- Fei Liu
- Wenzhou
Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China
| | - Jin Wang
- Wenzhou
Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China
- Department
of Chemistry and Physics, State University
of New York at Stony Brook, Stony Brook New York 11794, United States
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7
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Airas J, Ding X, Zhang B. Transferable Coarse Graining via Contrastive Learning of Graph Neural Networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.08.556923. [PMID: 37745447 PMCID: PMC10515757 DOI: 10.1101/2023.09.08.556923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Coarse-grained (CG) force fields are essential for molecular dynamics simulations of biomolecules, striking a balance between computational efficiency and biological realism. These simulations employ simplified models grouping atoms into interaction sites, enabling the study of complex biomolecular systems over biologically relevant timescales. Efforts are underway to develop accurate and transferable CG force fields, guided by a bottom-up approach that matches the CG energy function with the potential of mean force (PMF) defined by the finer system. However, practical challenges arise due to many-body effects, lack of analytical expressions for the PMF, and limitations in parameterizing CG force fields. To address these challenges, a machine learning-based approach is proposed, utilizing graph neural networks (GNNs) to represent CG force fields and potential contrasting for parameterization from atomistic simulation data. We demonstrate the effectiveness of the approach by deriving a transferable GNN implicit solvent model using 600,000 atomistic configurations of six proteins obtained from explicit solvent simulations. The GNN model provides solvation free energy estimations much more accurately than state-of-the-art implicit solvent models, reproducing configurational distributions of explicit solvent simulations. We also demonstrate the reasonable transferability of the GNN model outside the training data. Our study offers valuable insights for building accurate coarse-grained models bottom-up.
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Affiliation(s)
- Justin Airas
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Xinqiang Ding
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
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8
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Schuette G, Ding X, Zhang B. Efficient Hi-C inversion facilitates chromatin folding mechanism discovery and structure prediction. Biophys J 2023; 122:3425-3438. [PMID: 37496267 PMCID: PMC10502442 DOI: 10.1016/j.bpj.2023.07.017] [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: 03/17/2023] [Revised: 07/10/2023] [Accepted: 07/24/2023] [Indexed: 07/28/2023] Open
Abstract
Genome-wide chromosome conformation capture (Hi-C) experiments have revealed many structural features of chromatin across multiple length scales. Further understanding genome organization requires relating these discoveries to the mechanisms that establish chromatin structures and reconstructing these structures in three dimensions, but both objectives are difficult to achieve with existing algorithms that are often computationally expensive. To alleviate this challenge, we present an algorithm that efficiently converts Hi-C data into contact energies, which measure the interaction strength between genomic loci brought into proximity. Contact energies are local quantities unaffected by the topological constraints that correlate Hi-C contact probabilities. Thus, extracting contact energies from Hi-C contact probabilities distills the biologically unique information contained in the data. We show that contact energies reveal the location of chromatin loop anchors, support a phase separation mechanism for genome compartmentalization, and parameterize polymer simulations that predict three-dimensional chromatin structures. Therefore, we anticipate that contact energy extraction will unleash the full potential of Hi-C data and that our inversion algorithm will facilitate the widespread adoption of contact energy analysis.
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Affiliation(s)
- Greg Schuette
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Xinqiang Ding
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts.
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9
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Liu S, Wang C, Latham AP, Ding X, Zhang B. OpenABC enables flexible, simplified, and efficient GPU accelerated simulations of biomolecular condensates. PLoS Comput Biol 2023; 19:e1011442. [PMID: 37695778 PMCID: PMC10513381 DOI: 10.1371/journal.pcbi.1011442] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 09/21/2023] [Accepted: 08/19/2023] [Indexed: 09/13/2023] Open
Abstract
Biomolecular condensates are important structures in various cellular processes but are challenging to study using traditional experimental techniques. In silico simulations with residue-level coarse-grained models strike a balance between computational efficiency and chemical accuracy. They could offer valuable insights by connecting the emergent properties of these complex systems with molecular sequences. However, existing coarse-grained models often lack easy-to-follow tutorials and are implemented in software that is not optimal for condensate simulations. To address these issues, we introduce OpenABC, a software package that greatly simplifies the setup and execution of coarse-grained condensate simulations with multiple force fields using Python scripting. OpenABC seamlessly integrates with the OpenMM molecular dynamics engine, enabling efficient simulations with performance on a single GPU that rivals the speed achieved by hundreds of CPUs. We also provide tools that convert coarse-grained configurations to all-atom structures for atomistic simulations. We anticipate that OpenABC will significantly facilitate the adoption of in silico simulations by a broader community to investigate the structural and dynamical properties of condensates.
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Affiliation(s)
- Shuming Liu
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Cong Wang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Andrew P. Latham
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, California, United States of America
| | - Xinqiang Ding
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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10
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Zaporozhets I, Clementi C. Multibody Terms in Protein Coarse-Grained Models: A Top-Down Perspective. J Phys Chem B 2023; 127:6920-6927. [PMID: 37499123 DOI: 10.1021/acs.jpcb.3c04493] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Coarse-grained models allow computational investigation of biomolecular processes occurring on long time and length scales, intractable with atomistic simulation. Traditionally, many coarse-grained models rely mostly on pairwise interaction potentials. However, the decimation of degrees of freedom should, in principle, lead to a complex many-body effective interaction potential. In this work, we use experimental data on mutant stability to parametrize coarse-grained models for two proteins with and without many-body terms. We demonstrate that many-body terms are necessary to reproduce quantitatively the effects of point mutations on protein stability, particularly to implicitly take into account the effect of the solvent.
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Affiliation(s)
- Iryna Zaporozhets
- Department of Chemistry, Rice University, 6100 Main Street, Houston, Texas 77005, United States
- Center for Theoretical Biological Physics, Rice University, 6100 Main Street, Houston, Texas 77005, United States
- Department of Physics, Freie Universität, Arnimallee 12, Berlin 14195, Germany
| | - Cecilia Clementi
- Department of Chemistry, Rice University, 6100 Main Street, Houston, Texas 77005, United States
- Center for Theoretical Biological Physics, Rice University, 6100 Main Street, Houston, Texas 77005, United States
- Department of Physics, Freie Universität, Arnimallee 12, Berlin 14195, Germany
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11
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Schuette G, Ding X, Zhang B. Efficient Hi-C inversion facilitates chromatin folding mechanism discovery and structure prediction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.17.533194. [PMID: 36993500 PMCID: PMC10055272 DOI: 10.1101/2023.03.17.533194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
Genome-wide chromosome conformation capture (Hi-C) experiments have revealed many structural features of chromatin across multiple length scales. Further understanding genome organization requires relating these discoveries to the mechanisms that establish chromatin structures and reconstructing these structures in three dimensions, but both objectives are difficult to achieve with existing algorithms that are often computationally expensive. To alleviate this challenge, we present an algorithm that efficiently converts Hi-C data into contact energies, which measure the interaction strength between genomic loci brought into proximity. Contact energies are local quantities unaffected by the topological constraints that correlate Hi-C contact probabilities. Thus, extracting contact energies from Hi-C contact probabilities distills the biologically unique information contained in the data. We show that contact energies reveal the location of chromatin loop anchors, support a phase separation mechanism for genome compartmentalization, and parameterize polymer simulations that predict three-dimensional chromatin structures. Therefore, we anticipate that contact energy extraction will unleash the full potential of Hi-C data and that our inversion algorithm will facilitate the widespread adoption of contact energy analysis.
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Affiliation(s)
- Greg Schuette
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Xinqiang Ding
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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12
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Liu S, Wang C, Latham A, Ding X, Zhang B. OpenABC Enables Flexible, Simplified, and Efficient GPU Accelerated Simulations of Biomolecular Condensates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.19.537533. [PMID: 37131742 PMCID: PMC10153273 DOI: 10.1101/2023.04.19.537533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Biomolecular condensates are important structures in various cellular processes but are challenging to study using traditional experimental techniques. In silico simulations with residue-level coarse-grained models strike a balance between computational efficiency and chemical accuracy. They could offer valuable insights by connecting the emergent properties of these complex systems with molecular sequences. However, existing coarse-grained models often lack easy-to-follow tutorials and are implemented in software that is not optimal for condensate simulations. To address these issues, we introduce OpenABC, a software package that greatly simplifies the setup and execution of coarse-grained condensate simulations with multiple force fields using Python scripting. OpenABC seamlessly integrates with the OpenMM molecular dynamics engine, enabling efficient simulations with performances on a single GPU that rival the speed achieved by hundreds of CPUs. We also provide tools that convert coarse-grained configurations to all-atom structures for atomistic simulations. We anticipate that Open-ABC will significantly facilitate the adoption of in silico simulations by a broader community to investigate the structural and dynamical properties of condensates. Open-ABC is available at https://github.com/ZhangGroup-MITChemistry/OpenABC.
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Affiliation(s)
- Shuming Liu
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cong Wang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Andrew Latham
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Xinqiang Ding
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
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13
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Kamat K, Lao Z, Qi Y, Wang Y, Ma J, Zhang B. Compartmentalization with nuclear landmarks yields random, yet precise, genome organization. Biophys J 2023; 122:1376-1389. [PMID: 36871158 PMCID: PMC10111368 DOI: 10.1016/j.bpj.2023.03.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 02/19/2023] [Accepted: 03/01/2023] [Indexed: 03/06/2023] Open
Abstract
The 3D organization of eukaryotic genomes plays an important role in genome function. While significant progress has been made in deciphering the folding mechanisms of individual chromosomes, the principles of the dynamic large-scale spatial arrangement of all chromosomes inside the nucleus are poorly understood. We use polymer simulations to model the diploid human genome compartmentalization relative to nuclear bodies such as nuclear lamina, nucleoli, and speckles. We show that a self-organization process based on a cophase separation between chromosomes and nuclear bodies can capture various features of genome organization, including the formation of chromosome territories, phase separation of A/B compartments, and the liquid property of nuclear bodies. The simulated 3D structures quantitatively reproduce both sequencing-based genomic mapping and imaging assays that probe chromatin interaction with nuclear bodies. Importantly, our model captures the heterogeneous distribution of chromosome positioning across cells while simultaneously producing well-defined distances between active chromatin and nuclear speckles. Such heterogeneity and preciseness of genome organization can coexist due to the nonspecificity of phase separation and the slow chromosome dynamics. Together, our work reveals that the cophase separation provides a robust mechanism for us to produce functionally important 3D contacts without requiring thermodynamic equilibration that can be difficult to achieve.
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Affiliation(s)
- Kartik Kamat
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Zhuohan Lao
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Yifeng Qi
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Yuchuan Wang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Jian Ma
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts.
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14
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Wohl S, Zheng W. Interpreting Transient Interactions of Intrinsically Disordered Proteins. J Phys Chem B 2023; 127:2395-2406. [PMID: 36917561 PMCID: PMC10038935 DOI: 10.1021/acs.jpcb.3c00096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
The flexible nature of intrinsically disordered proteins (IDPs) gives rise to a conformational ensemble with a diverse set of conformations. The simplest way to describe this ensemble is through a homopolymer model without any specific interactions. However, there has been growing evidence that the conformational properties of IDPs and their relevant functions can be affected by transient interactions between specific and even nonlocal pairs of amino acids. Interpreting these interactions from experimental methods, each of which is most sensitive to a different distance regime referred to as probing length, remains a challenging and unsolved problem. Here, we first show that transient interactions can be realized between short fragments of charged amino acids by generating conformational ensembles using model disordered peptides and coarse-grained simulations. Using these ensembles, we investigate how sensitive different types of experimental measurements are to the presence of transient interactions. We find methods with shorter probing lengths to be more appropriate for detecting these transient interactions, but one experimental method is not sufficient due to the existence of other weak interactions typically seen in IDPs. Finally, we develop an adjusted polymer model with an additional short-distance peak which can robustly reproduce the distance distribution function from two experimental measurements with complementary short and long probing lengths. This new model can suggest whether a homopolymer model is insufficient for describing a specific IDP and meets the challenge of quantitatively identifying specific, transient interactions from a background of nonspecific, weak interactions.
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Affiliation(s)
- Samuel Wohl
- Department of Physics, Arizona State University, Tempe, Arizona 85287, United States
| | - Wenwei Zheng
- College of Integrative Sciences and Arts, Arizona State University, Mesa, Arizona 85212, United States
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15
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Luo S, Wohl S, Zheng W, Yang S. Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery. Biomolecules 2023; 13:biom13030530. [PMID: 36979465 PMCID: PMC10046839 DOI: 10.3390/biom13030530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/07/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023] Open
Abstract
Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.
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Affiliation(s)
- Shuqi Luo
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Samuel Wohl
- Department of Physics, Arizona State University, Tempe, AZ 85287, USA
| | - Wenwei Zheng
- College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ 85212, USA
- Correspondence: (W.Z.); (S.Y.)
| | - Sichun Yang
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA
- Correspondence: (W.Z.); (S.Y.)
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16
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Abstract
Coarse-grained models have proven helpful for simulating complex systems over long time scales to provide molecular insights into various processes. Methodologies for systematic parametrization of the underlying energy function or force field that describes the interactions among different components of the system are of great interest for ensuring simulation accuracy. We present a new method, potential contrasting, to enable efficient learning of force fields that can accurately reproduce the conformational distribution produced with all-atom simulations. Potential contrasting generalizes the noise contrastive estimation method with umbrella sampling to better learn the complex energy landscape of molecular systems. When applied to the Trp-cage protein, we found that the technique produces force fields that thoroughly capture the thermodynamics of the folding process despite the use of only α-carbons in the coarse-grained model. We further showed that potential contrasting could be applied over large data sets that combine the conformational ensembles of many proteins to improve force field transferability. We anticipate potential contrasting as a powerful tool for building general-purpose coarse-grained force fields.
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Affiliation(s)
- Xinqiang Ding
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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17
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Abstract
The human genome is arranged in the cell nucleus nonrandomly, and phase separation has been proposed as an important driving force for genome organization. However, the cell nucleus is an active system, and the contribution of nonequilibrium activities to phase separation and genome structure and dynamics remains to be explored. We simulated the genome using an energy function parametrized with chromosome conformation capture (Hi-C) data with the presence of active, nondirectional forces that break the detailed balance. We found that active forces that may arise from transcription and chromatin remodeling can dramatically impact the spatial localization of heterochromatin. When applied to euchromatin, active forces can drive heterochromatin to the nuclear envelope and compete with passive interactions among heterochromatin that tend to pull them in opposite directions. Furthermore, active forces induce long-range spatial correlations among genomic loci beyond single chromosome territories. We further showed that the impact of active forces could be understood from the effective temperature defined as the fluctuation-dissipation ratio. Our study suggests that nonequilibrium activities can significantly impact genome structure and dynamics, producing unexpected collective phenomena.
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Affiliation(s)
- Zhongling Jiang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, United States
| | - Yifeng Qi
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, United States
| | - Kartik Kamat
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, United States
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, United States
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18
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Latham AP, Zhang B. On the stability and layered organization of protein-DNA condensates. Biophys J 2022; 121:1727-1737. [PMID: 35364104 PMCID: PMC9117872 DOI: 10.1016/j.bpj.2022.03.028] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 12/02/2021] [Accepted: 03/24/2022] [Indexed: 11/17/2022] Open
Abstract
Multi-component phase separation is emerging as a key mechanism for the formation of biological condensates that play essential roles in signal sensing and transcriptional regulation. The molecular factors that dictate these condensates' stability and spatial organization are not fully understood, and it remains challenging to predict their microstructures. Using a near-atomistic, chemically accurate force field, we studied the phase behavior of chromatin regulators that are crucial for heterochromatin organization and their interactions with DNA. Our computed phase diagrams recapitulated previous experimental findings on different proteins. They revealed a strong dependence of condensate stability on the protein-DNA mixing ratio as a result of balancing protein-protein interactions and charge neutralization. Notably, a layered organization was observed in condensates formed by mixing HP1, histone H1, and DNA. This layered organization may be of biological relevance, as it enables cooperative DNA packaging between the two chromatin regulators: histone H1 softens the DNA to facilitate the compaction induced by HP1 droplets. Our study supports near-atomistic models as a valuable tool for characterizing the structure and stability of biological condensates.
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Affiliation(s)
- Andrew P Latham
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts.
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19
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Latham AP, Zhang B. Unifying coarse-grained force fields for folded and disordered proteins. Curr Opin Struct Biol 2022; 72:63-70. [PMID: 34536913 PMCID: PMC9057422 DOI: 10.1016/j.sbi.2021.08.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/08/2021] [Accepted: 08/17/2021] [Indexed: 12/22/2022]
Abstract
Liquid-liquid phase separation drives the formation of biological condensates that play essential roles in transcriptional regulation and signal sensing. Computational modeling could provide high-resolution structural characterizations of these condensates and help uncover physicochemical interactions that dictate their stability. However, many protein molecules involved in phase separation often contain multiple ordered domains connected with flexible, structureless linkers. Simulating such proteins necessitates force fields with consistent accuracy for both folded and disordered proteins. We provide a critical review of existing coarse-grained force fields for disordered proteins and highlight the challenges in their application to folded proteins. After discussing existing algorithms for force field parameterization, we propose an optimization strategy that should lead to computer models with improved transferability across protein types.
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Affiliation(s)
- Andrew P Latham
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.
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20
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Lin X, Qi Y, Latham AP, Zhang B. Multiscale modeling of genome organization with maximum entropy optimization. J Chem Phys 2021; 155:010901. [PMID: 34241389 PMCID: PMC8253599 DOI: 10.1063/5.0044150] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 04/28/2021] [Indexed: 12/15/2022] Open
Abstract
Three-dimensional (3D) organization of the human genome plays an essential role in all DNA-templated processes, including gene transcription, gene regulation, and DNA replication. Computational modeling can be an effective way of building high-resolution genome structures and improving our understanding of these molecular processes. However, it faces significant challenges as the human genome consists of over 6 × 109 base pairs, a system size that exceeds the capacity of traditional modeling approaches. In this perspective, we review the progress that has been made in modeling the human genome. Coarse-grained models parameterized to reproduce experimental data via the maximum entropy optimization algorithm serve as effective means to study genome organization at various length scales. They have provided insight into the principles of whole-genome organization and enabled de novo predictions of chromosome structures from epigenetic modifications. Applications of these models at a near-atomistic resolution further revealed physicochemical interactions that drive the phase separation of disordered proteins and dictate chromatin stability in situ. We conclude with an outlook on the opportunities and challenges in studying chromosome dynamics.
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Affiliation(s)
- Xingcheng Lin
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Yifeng Qi
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Andrew P. Latham
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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21
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Latham AP, Zhang B. Consistent Force Field Captures Homologue-Resolved HP1 Phase Separation. J Chem Theory Comput 2021; 17:3134-3144. [PMID: 33826337 PMCID: PMC8119372 DOI: 10.1021/acs.jctc.0c01220] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Many proteins have been shown to function via liquid-liquid phase separation. Computational modeling could offer much needed structural details of protein condensates and reveal the set of molecular interactions that dictate their stability. However, the presence of both ordered and disordered domains in these proteins places a high demand on the model accuracy. Here, we present an algorithm to derive a coarse-grained force field, MOFF, which can model both ordered and disordered proteins with consistent accuracy. It combines maximum entropy biasing, least-squares fitting, and basic principles of energy landscape theory to ensure that MOFF recreates experimental radii of gyration while predicting the folded structures for globular proteins with lower energy. The theta temperature determined from MOFF separates ordered and disordered proteins at 300 K and exhibits a strikingly linear relationship with amino acid sequence composition. We further applied MOFF to study the phase behavior of HP1, an essential protein for post-translational modification and spatial organization of chromatin. The force field successfully resolved the structural difference of two HP1 homologues despite their high sequence similarity. We carried out large-scale simulations with hundreds of proteins to determine the critical temperature of phase separation and uncover multivalent interactions that stabilize higher-order assemblies. In all, our work makes significant methodological strides to connect theories of ordered and disordered proteins and provides a powerful tool for studying liquid-liquid phase separation with near-atomistic details.
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Affiliation(s)
- Andrew P Latham
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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22
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Bari KJ, Prakashchand DD. Fundamental Challenges and Outlook in Simulating Liquid-Liquid Phase Separation of Intrinsically Disordered Proteins. J Phys Chem Lett 2021; 12:1644-1656. [PMID: 33555894 DOI: 10.1021/acs.jpclett.0c03404] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Intrinsically disordered proteins (IDPs) populate an ensemble of dynamic conformations, making their structural characterization by experiments challenging. Many IDPs undergo liquid-liquid phase separation into dense membraneless organelles with myriad cellular functions. Multivalent interactions in low-complexity IDPs promote the formation of these subcellular coacervates. While solution NMR, Förster resonance energy transfer (FRET), and small-angle X-ray scattering (SAXS) studies on IDPs have their own challenges, recent computational methods draw a rational trade-off to characterize the driving forces underlying phase separation. In this Perspective, we critically evaluate the scope of approximation-free field theoretic simulations, well-tempered ensemble methods, enhanced sampling techniques, coarse-grained force fields, and slab simulation approaches to offer an improved understanding of phase separation. A synergy between simulation length scale and model resolution would reduce the existing caveats and enable theories of polymer physics to elucidate finer details of liquid-liquid phase separation (LLPS). These computational advances offer promise for rigorous characterization of the IDP proteome and designing peptides with tunable material and self-assembly properties.
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Affiliation(s)
- Khandekar Jishan Bari
- Center for Interdisciplinary Sciences, Tata Institute of Fundamental Research, Gopanpally, Hyderabad 500107, India
- Department of Chemical Sciences, Indian Institute of Science Education and Research, Berhampur, Odisha 760010, India
| | - Dube Dheeraj Prakashchand
- Center for Interdisciplinary Sciences, Tata Institute of Fundamental Research, Gopanpally, Hyderabad 500107, India
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23
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Mu J, Liu H, Zhang J, Luo R, Chen HF. Recent Force Field Strategies for Intrinsically Disordered Proteins. J Chem Inf Model 2021; 61:1037-1047. [PMID: 33591749 PMCID: PMC8256680 DOI: 10.1021/acs.jcim.0c01175] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Intrinsically disordered proteins (IDPs) are widely distributed across eukaryotic cells, playing important roles in molecular recognition, molecular assembly, post-translational modification, and other biological processes. IDPs are also associated with many diseases such as cancers, cardiovascular diseases, and neurodegenerative diseases. Due to their structural flexibility, conventional experimental methods cannot reliably capture their heterogeneous structures. Molecular dynamics simulation becomes an important complementary tool to quantify IDP structures. This review covers recent force field strategies proposed for more accurate molecular dynamics simulations of IDPs. The strategies include adjusting dihedral parameters, adding grid-based energy correction map (CMAP) parameters, refining protein-water interactions, and others. Different force fields were found to perform well on specific observables of specific IDPs but also are limited in reproducing all available experimental observables consistently for all tested IDPs. We conclude the review with perspective areas for improvements for future force fields for IDPs.
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Affiliation(s)
- Junxi Mu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hao Liu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jian Zhang
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, School of Medicine, Shanghai Jiao Tong University, Shanghai 20025, China
| | - Ray Luo
- Departments of Molecular Biology and Biochemistry, Chemical and Molecular Engineering, Materials Science and Engineering, and Biomedical Engineering, University of California, Irvine, California 92697-3900, United States
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
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24
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Mammen Regy R, Zheng W, Mittal J. Using a sequence-specific coarse-grained model for studying protein liquid-liquid phase separation. Methods Enzymol 2020; 646:1-17. [PMID: 33453922 DOI: 10.1016/bs.mie.2020.07.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
The formation of membraneless organelles (MLOs) via liquid-liquid phase separation (LLPS) of biomolecules is a topic that has garnered significant attention in the scientific community recently. Experimental studies have revealed that intrinsically disordered proteins (IDPs) may play a major role in driving the formation of these droplets via LLPS by forming multivalent interactions between amino acids. To quantify these interactions is an arduous task as it is difficult to investigate these interactions at the amino acid level using currently available experimental tools. It becomes necessary to complement experimental studies using appropriate computational methods such as coarse-grained models of IDPs that can allow one to simulate biomolecular LLPS using general-purpose hardware. Here, we summarize our coarse-grained modeling framework that uses a single bead per amino acid resolution and the co-existence sampling technique to study sequence-specific protein phase separation using molecular dynamics simulations. We further discuss the caveats and technicalities, which one must consider while using this method to obtain thermodynamic phase diagrams. To ease the learning curve, we provide our implementations of the coarse-grained potentials in the HOOMD-Blue simulation package and associated python scripts to run such simulations.
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Affiliation(s)
- Roshan Mammen Regy
- Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA, United States
| | - Wenwei Zheng
- College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ, United States
| | - Jeetain Mittal
- Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA, United States.
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25
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Kilgore HR, Latham AP, Ressler VT, Zhang B, Raines RT. Structure and Dynamics of N-Glycosylated Human Ribonuclease 1. Biochemistry 2020; 59:3148-3156. [PMID: 32544330 DOI: 10.1021/acs.biochem.0c00191] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Glycosylation is a common modification that can endow proteins with altered physical and biological properties. Ribonuclease 1 (RNase 1), which is the human homologue of the archetypal enzyme RNase A, undergoes N-linked glycosylation at asparagine residues 34, 76, and 88. We have produced the three individual glycoforms that display the core heptasaccharide, Man5GlcNAc2, and analyzed the structure of each glycoform by using small-angle X-ray scattering along with molecular dynamics simulations. The glycan on Asn34 is relatively compact and rigid, donates hydrogen bonds that "cap" the carbonyl groups at the C-terminus of an α-helix, and enhances protein thermostability. In contrast, the glycan on Asn88 is flexible and can even enter the enzymic active site, hindering catalysis. The N-glycosylation of Asn76 has less pronounced consequences. These data highlight the diverse behaviors of Man5GlcNAc2 pendants and provide a structural underpinning to the functional consequences of protein glycosylation.
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Affiliation(s)
- Henry R Kilgore
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Andrew P Latham
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Valerie T Ressler
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Ronald T Raines
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
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26
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Zhai C, Li T, Shi H, Yeo J. Discovery and design of soft polymeric bio-inspired materials with multiscale simulations and artificial intelligence. J Mater Chem B 2020; 8:6562-6587. [DOI: 10.1039/d0tb00896f] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Establishing the “Materials 4.0” paradigm requires intimate knowledge of the virtual space in materials design.
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Affiliation(s)
- Chenxi Zhai
- J2 Lab for Engineering Living Materials
- Sibley School of Mechanical and Aerospace Engineering
- Cornell University
- Ithaca
- USA
| | - Tianjiao Li
- J2 Lab for Engineering Living Materials
- Sibley School of Mechanical and Aerospace Engineering
- Cornell University
- Ithaca
- USA
| | - Haoyuan Shi
- J2 Lab for Engineering Living Materials
- Sibley School of Mechanical and Aerospace Engineering
- Cornell University
- Ithaca
- USA
| | - Jingjie Yeo
- J2 Lab for Engineering Living Materials
- Sibley School of Mechanical and Aerospace Engineering
- Cornell University
- Ithaca
- USA
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27
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Latham AP, Zhang B. Maximum Entropy Optimized Force Field for Intrinsically Disordered Proteins. J Chem Theory Comput 2019; 16:773-781. [PMID: 31756104 DOI: 10.1021/acs.jctc.9b00932] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Intrinsically disordered proteins (IDPs) constitute a significant fraction of eukaryotic proteomes. High-resolution characterization of IDP conformational ensembles can help elucidate their roles in a wide range of biological processes but remains challenging both experimentally and computationally. Here, we present a generic algorithm to improve the accuracy of coarse-grained IDP models using a diverse set of experimental measurements. It combines maximum entropy optimization and least-squares regression to systematically adjust model parameters and improve the agreement between simulation and experiment. We successfully applied the algorithm to derive a transferable force field, which we term the maximum entropy optimized force field (MOFF), for de novo prediction of IDP structures. Statistical analysis of force field parameters reveals features of amino acid interactions not captured by potentials designed to work well for folded proteins. We anticipate its combination of efficiency and accuracy will make MOFF useful for studying the phase separation of IDPs, which drives the formation of various biological compartments.
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Affiliation(s)
- Andrew P Latham
- Department of Chemistry , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
| | - Bin Zhang
- Department of Chemistry , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
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28
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Parsons T, Zhang B. Critical role of histone tail entropy in nucleosome unwinding. J Chem Phys 2019; 150:185103. [PMID: 31091895 DOI: 10.1063/1.5085663] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The nucleosome is the fundamental packaging unit for the genome. It must remain tightly wound to ensure genome stability while simultaneously being flexible enough to keep the DNA molecule accessible for genome function. The set of physicochemical interactions responsible for the delicate balance between these naturally opposed processes have not been determined due to challenges in resolving partially unwound nucleosome configurations at atomic resolution. Using a near atomistic protein-DNA model and advanced sampling techniques, we calculate the free energy cost of nucleosome DNA unwinding. Our simulations identify a large energetic barrier that decouples the outer and the inner DNA unwinding into two separate processes, occurring on different time scales. This dynamical decoupling allows the exposure of outer DNA at a modest cost to ensure accessibility while keeping the inner DNA and the histone core intact to maintain stability. We also reveal that this energetic barrier arises from a delayed loss of contacts between disordered histone tails and the DNA and is, surprisingly, largely offset by an entropic contribution from these tails. Implications of this enthalpy entropy compensation for the regulation of nucleosome stability and genome function are discussed.
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Affiliation(s)
- Thomas Parsons
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139-4307, USA
| | - Bin Zhang
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139-4307, USA
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29
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Structural and Dynamical Order of a Disordered Protein: Molecular Insights into Conformational Switching of PAGE4 at the Systems Level. Biomolecules 2019; 9:biom9020077. [PMID: 30813315 PMCID: PMC6406393 DOI: 10.3390/biom9020077] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 02/10/2019] [Accepted: 02/10/2019] [Indexed: 01/10/2023] Open
Abstract
Folded proteins show a high degree of structural order and undergo (fairly constrained) collective motions related to their functions. On the other hand, intrinsically disordered proteins (IDPs), while lacking a well-defined three-dimensional structure, do exhibit some structural and dynamical ordering, but are less constrained in their motions than folded proteins. The larger structural plasticity of IDPs emphasizes the importance of entropically driven motions. Many IDPs undergo function-related disorder-to-order transitions driven by their interaction with specific binding partners. As experimental techniques become more sensitive and become better integrated with computational simulations, we are beginning to see how the modest structural ordering and large amplitude collective motions of IDPs endow them with an ability to mediate multiple interactions with different partners in the cell. To illustrate these points, here, we use Prostate-associated gene 4 (PAGE4), an IDP implicated in prostate cancer (PCa) as an example. We first review our previous efforts using molecular dynamics simulations based on atomistic AWSEM to study the conformational dynamics of PAGE4 and how its motions change in its different physiologically relevant phosphorylated forms. Our simulations quantitatively reproduced experimental observations and revealed how structural and dynamical ordering are encoded in the sequence of PAGE4 and can be modulated by different extents of phosphorylation by the kinases HIPK1 and CLK2. This ordering is reflected in changing populations of certain secondary structural elements as well as in the regularity of its collective motions. These ordered features are directly correlated with the functional interactions of WT-PAGE4, HIPK1-PAGE4 and CLK2-PAGE4 with the AP-1 signaling axis. These interactions give rise to repeated transitions between (high HIPK1-PAGE4, low CLK2-PAGE4) and (low HIPK1-PAGE4, high CLK2-PAGE4) cell phenotypes, which possess differing sensitivities to the standard PCa therapies, such as androgen deprivation therapy (ADT). We argue that, although the structural plasticity of an IDP is important in promoting promiscuous interactions, the modulation of the structural ordering is important for sculpting its interactions so as to rewire with agility biomolecular interaction networks with significant functional consequences.
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