1
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Chen G, Jaffrelot Inizan T, Plé T, Lagardère L, Piquemal JP, Maday Y. Advancing Force Fields Parameterization: A Directed Graph Attention Networks Approach. J Chem Theory Comput 2024. [PMID: 38875012 DOI: 10.1021/acs.jctc.3c01421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2024]
Abstract
Force fields (FFs) are an established tool for simulating large and complex molecular systems. However, parametrizing FFs is a challenging and time-consuming task that relies on empirical heuristics, experimental data, and computational data. Recent efforts aim to automate the assignment of FF parameters using pre-existing databases and on-the-fly ab initio data. In this study, we propose a graph-based force field (GB-FFs) model to directly derive parameters for the Generalized Amber Force Field (GAFF) from chemical environments and research into the influence of functional forms. Our end-to-end parametrization approach predicts parameters by aggregating the basic information in directed molecular graphs, eliminating the need for expert-defined procedures and enhances the accuracy and transferability of GAFF across a broader range of molecular complexes. Simulation results are compared to the original GAFF parametrization. In practice, our results demonstrate an improved transferability of the model, showcasing its improved accuracy in modeling intermolecular and torsional interactions, as well as improved solvation free energies. The optimization approach developed in this work is fully applicable to other nonpolarizable FFs as well as to polarizable ones.
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Affiliation(s)
- Gong Chen
- Sorbonne Université, CNRS, Université Paris Cité, Laboratoire Jacques-Louis Lions (LJLL), UMR 7598 CNRS, 75005 Paris, France
| | - Théo Jaffrelot Inizan
- Sorbonne Université, Laboratoire de Chimie Théorique (LCT), UMR 7616 CNRS, 75005 Paris, France
| | - Thomas Plé
- Sorbonne Université, Laboratoire de Chimie Théorique (LCT), UMR 7616 CNRS, 75005 Paris, France
| | - Louis Lagardère
- Sorbonne Université, Laboratoire de Chimie Théorique (LCT), UMR 7616 CNRS, 75005 Paris, France
| | - Jean-Philip Piquemal
- Sorbonne Université, Laboratoire de Chimie Théorique (LCT), UMR 7616 CNRS, 75005 Paris, France
| | - Yvon Maday
- Sorbonne Université, CNRS, Université Paris Cité, Laboratoire Jacques-Louis Lions (LJLL), UMR 7598 CNRS, 75005 Paris, France
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2
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Giulini M, Fiorentini R, Tubiana L, Potestio R, Menichetti R. EXCOGITO, an Extensible Coarse-Graining Toolbox for the Investigation of Biomolecules by Means of Low-Resolution Representations. J Chem Inf Model 2024. [PMID: 38860513 DOI: 10.1021/acs.jcim.4c00490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Abstract
Bottom-up coarse-grained (CG) models proved to be essential to complement and sometimes even replace all-atom representations of soft matter systems and biological macromolecules. The development of low-resolution models takes the moves from the reduction of the degrees of freedom employed, that is, the definition of a mapping between a system's high-resolution description and its simplified counterpart. Even in the absence of an explicit parametrization and simulation of a CG model, the observation of the atomistic system in simpler terms can be informative: this idea is leveraged by the mapping entropy, a measure of the information loss inherent to the process of coarsening. Mapping entropy lies at the heart of the extensible coarse-graining toolbox, EXCOGITO, developed to perform a number of operations and analyses on molecular systems pivoting around the properties of mappings. EXCOGITO can process an all-atom trajectory to compute the mapping entropy, identify the mapping that minimizes it, and establish quantitative relations between a low-resolution representation and the geometrical, structural, and energetic features of the system. Here, the software, which is available free of charge under an open-source license, is presented and showcased to introduce potential users to its capabilities and usage.
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Affiliation(s)
- Marco Giulini
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
| | - Raffaele Fiorentini
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
| | - Luca Tubiana
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
| | - Raffaello Potestio
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
| | - Roberto Menichetti
- Physics Department, University of Trento, Via Sommarive, 14, Trento I-38123, Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento I-38123, Italy
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3
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Mayorga LS, Masone D. The Secret Ballet Inside Multivesicular Bodies. ACS NANO 2024. [PMID: 38830824 DOI: 10.1021/acsnano.4c01590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
Lipid bilayers possess the capacity for self-assembly due to the amphipathic nature of lipid molecules, which have both hydrophobic and hydrophilic regions. When confined, lipid bilayers exhibit astonishing versatility in their forms, adopting diverse shapes that are challenging to observe through experimental means. Exploiting this adaptability, lipid structures motivate the development of bio-inspired mechanomaterials and integrated nanobio-interfaces that could seamlessly merge with biological entities, ultimately bridging the gap between synthetic and biological systems. In this work, we demonstrate how, in numerical simulations of multivesicular bodies, a fascinating evolution unfolds from an initial semblance of order toward states of higher entropy over time. We observe dynamic rearrangements in confined vesicles that reveal unexpected limit shapes of distinct geometric patterns. We identify five structures as the basic building blocks that systematically repeat under various conditions of size and composition. Moreover, we observe more complex and less frequent shapes that emerge in confined spaces. Our results provide insights into the dynamics of multivesicular systems, offering a richer understanding of how confined lipid bodies spontaneously self-organize.
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Affiliation(s)
- Luis S Mayorga
- Instituto de Histología y Embriología de Mendoza (IHEM), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Cuyo (UNCuyo), 5500 Mendoza, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Cuyo (UNCuyo), 5500, Mendoza, Argentina
| | - Diego Masone
- Instituto de Histología y Embriología de Mendoza (IHEM), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Cuyo (UNCuyo), 5500 Mendoza, Argentina
- Facultad de Ingeniería, Universidad Nacional de Cuyo (UNCuyo), 5500 Mendoza, Argentina
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4
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Liu Z, Grigas AT, Sumner J, Knab E, Davis CM, O'Hern CS. Identifying the minimal sets of distance restraints for FRET-assisted protein structural modeling. ARXIV 2024:arXiv:2405.07983v1. [PMID: 38800659 PMCID: PMC11118665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Proteins naturally occur in crowded cellular environments and interact with other proteins, nucleic acids, and organelles. Since most previous experimental protein structure determination techniques require that proteins occur in idealized, non-physiological environments, the effects of realistic cellular environments on protein structure are largely unexplored. Recently, Förster resonance energy transfer (FRET) has been shown to be an effective experimental method for investigating protein structure in vivo. Inter-residue distances measured in vivo can be incorporated as restraints in molecular dynamics (MD) simulations to model protein structural dynamics in vivo. Since most FRET studies only obtain inter-residue separations for a small number of amino acid pairs, it is important to determine the minimum number of restraints in the MD simulations that are required to achieve a given root-mean-square deviation (RMSD) from the experimental structural ensemble. Further, what is the optimal method for selecting these inter-residue restraints? Here, we implement several methods for selecting the most important FRET pairs and determine the number of pairs N r that are needed to induce conformational changes in proteins between two experimentally determined structures. We find that enforcing only a small fraction of restraints, N r / N ≲ 0.08 , where N is the number of amino acids, can induce the conformational changes. These results establish the efficacy of FRET-assisted MD simulations for atomic scale structural modeling of proteins in vivo. Significance Determining protein structure in vivo is essential for understanding protein function. Most protein structures have been studied in non-physiological conditions using x-ray crystallography, NMR spectroscopy, and cryo-electron microscopy. Thus, we do not know whether the cellular environment significantly affects protein structure. We emphasize the benefits of FRET-assisted molecular dynamics simulations in characterizing protein structure in vivo at the atomic scale. We identify the minimum number of FRET pairs that can induce conformational changes in several proteins, including one that has been characterized using in-cell NMR.
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Affiliation(s)
- Zhuoyi Liu
- Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut, 06520, USA
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, 06520, USA
| | - Alex T Grigas
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, 06520, USA
- Graduate Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, 06520, USA
| | - Jacob Sumner
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, 06520, USA
- Graduate Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, 06520, USA
| | - Edward Knab
- Department of Chemistry, Yale University, New Haven, Connecticut, 06520, USA
| | - Caitlin M Davis
- Department of Chemistry, Yale University, New Haven, Connecticut, 06520, USA
| | - Corey S O'Hern
- Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut, 06520, USA
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, 06520, USA
- Graduate Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, 06520, USA
- Department of Physics, Yale University, New Haven, Connecticut, 06520, USA
- Department of Applied Physics, Yale University, New Haven, Connecticut, 06520, USA
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5
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Brown CM, Marrink SJ. Modeling membranes in situ. Curr Opin Struct Biol 2024; 87:102837. [PMID: 38744147 DOI: 10.1016/j.sbi.2024.102837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/26/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024]
Abstract
Molecular dynamics simulations of cellular membranes have come a long way-from simple model lipid bilayers to multicomponent systems capturing the crowded and complex nature of real cell membranes. In this opinionated minireview, we discuss the current challenge to simulate the dynamics of membranes in their native environment, in situ, with the prospect of reaching the level of whole cells and cell organelles using an integrative modeling framework.
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Affiliation(s)
- Chelsea M Brown
- Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, the Netherlands. https://twitter.com/chelseabrowncg
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, the Netherlands. s.j.marrinkrug.nl
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6
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Belghit H, Spivak M, Dauchez M, Baaden M, Jonquet-Prevoteau J. From complex data to clear insights: visualizing molecular dynamics trajectories. FRONTIERS IN BIOINFORMATICS 2024; 4:1356659. [PMID: 38665177 PMCID: PMC11043564 DOI: 10.3389/fbinf.2024.1356659] [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: 12/15/2023] [Accepted: 03/14/2024] [Indexed: 04/28/2024] Open
Abstract
Advances in simulations, combined with technological developments in high-performance computing, have made it possible to produce a physically accurate dynamic representation of complex biological systems involving millions to billions of atoms over increasingly long simulation times. The analysis of these computed simulations is crucial, involving the interpretation of structural and dynamic data to gain insights into the underlying biological processes. However, this analysis becomes increasingly challenging due to the complexity of the generated systems with a large number of individual runs, ranging from hundreds to thousands of trajectories. This massive increase in raw simulation data creates additional processing and visualization challenges. Effective visualization techniques play a vital role in facilitating the analysis and interpretation of molecular dynamics simulations. In this paper, we focus mainly on the techniques and tools that can be used for visualization of molecular dynamics simulations, among which we highlight the few approaches used specifically for this purpose, discussing their advantages and limitations, and addressing the future challenges of molecular dynamics visualization.
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Affiliation(s)
- Hayet Belghit
- Université de Reims Champagne-Ardenne, CNRS, MEDYC, Reims, France
| | - Mariano Spivak
- Université Paris Cité, CNRS, Laboratoire de Biochimie Théorique, Paris, France
| | - Manuel Dauchez
- Université de Reims Champagne-Ardenne, CNRS, MEDYC, Reims, France
| | - Marc Baaden
- Université Paris Cité, CNRS, Laboratoire de Biochimie Théorique, Paris, France
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7
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Harju J, Broedersz CP. Physical models of bacterial chromosomes. Mol Microbiol 2024. [PMID: 38578226 DOI: 10.1111/mmi.15257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 03/12/2024] [Accepted: 03/18/2024] [Indexed: 04/06/2024]
Abstract
The interplay between bacterial chromosome organization and functions such as transcription and replication can be studied in increasing detail using novel experimental techniques. Interpreting the resulting quantitative data, however, can be theoretically challenging. In this minireview, we discuss how connecting experimental observations to biophysical theory and modeling can give rise to new insights on bacterial chromosome organization. We consider three flavors of models of increasing complexity: simple polymer models that explore how physical constraints, such as confinement or plectoneme branching, can affect bacterial chromosome organization; bottom-up mechanistic models that connect these constraints to their underlying causes, for instance, chromosome compaction to macromolecular crowding, or supercoiling to transcription; and finally, data-driven methods for inferring interpretable and quantitative models directly from complex experimental data. Using recent examples, we discuss how biophysical models can both deepen our understanding of how bacterial chromosomes are structured and give rise to novel predictions about bacterial chromosome organization.
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Affiliation(s)
- Janni Harju
- Department of Physics and Astronomy, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Chase P Broedersz
- Department of Physics and Astronomy, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Physics, Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Ludwig-Maximilian-University Munich, Munich, Germany
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8
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Beck TL, Carloni P, Asthagiri DN. All-Atom Biomolecular Simulation in the Exascale Era. J Chem Theory Comput 2024; 20:1777-1782. [PMID: 38382017 DOI: 10.1021/acs.jctc.3c01276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Exascale supercomputers have opened the door to dynamic simulations, facilitated by AI/ML techniques, that model biomolecular motions over unprecedented length and time scales. This new capability holds the potential to revolutionize our understanding of fundamental biological processes. Here we report on some of the major advances that were discussed at a recent CECAM workshop in Pisa, Italy, on the topic with a primary focus on atomic-level simulations. First, we highlight examples of current large-scale biomolecular simulations and the future possibilities enabled by crossing the exascale threshold. Next, we discuss challenges to be overcome in optimizing the usage of these powerful resources. Finally, we close by listing several grand challenge problems that could be investigated with this new computer architecture.
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Affiliation(s)
- Thomas L Beck
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Paolo Carloni
- INM-9/IAS-5 Computational Biomedicine, Forschungszentrum Jülich, Wilhelm-Johnen-Straße, D-54245 Jülich, Germany
- Department of Physics, RWTH Aachen University, D-52078 Aachen, Germany
| | - Dilipkumar N Asthagiri
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
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9
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Kim K, Choe D, Cho S, Palsson B, Cho BK. Reduction-to-synthesis: the dominant approach to genome-scale synthetic biology. Trends Biotechnol 2024:S0167-7799(24)00037-4. [PMID: 38423803 DOI: 10.1016/j.tibtech.2024.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 03/02/2024]
Abstract
Advances in systems and synthetic biology have propelled the construction of reduced bacterial genomes. Genome reduction was initially focused on exploring properties of minimal genomes, but more recently it has been deployed as an engineering strategy to enhance strain performance. This review provides the latest updates on reduced genomes, focusing on dual-track approaches of top-down reduction and bottom-up synthesis for their construction. Using cases from studies that are based on established industrial workhorse strains, we discuss the construction of a series of synthetic phenotypes that are candidates for biotechnological applications. Finally, we address the possible uses of reduced genomes for biotechnological applications and the needed future research directions that may ultimately lead to the total synthesis of rationally designed genomes.
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Affiliation(s)
- Kangsan Kim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea; KI for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea
| | - Donghui Choe
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Suhyung Cho
- KI for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea
| | - Bernhard Palsson
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Kongens, Lyngby, Denmark
| | - Byung-Kwan Cho
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea; KI for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea; Graduate School of Engineering Biology, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
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10
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Wasim A, Bera P, Mondal J. Development of a Data-Driven Integrative Model of a Bacterial Chromosome. J Chem Theory Comput 2024; 20:1673-1688. [PMID: 37083406 DOI: 10.1021/acs.jctc.3c00118] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023]
Abstract
The chromosome of archetypal bacteria E. coli is known for a complex topology with a 4.6 × 106 base pairs (bp) long sequence of nucleotides packed within a micrometer-sized cellular confinement. The inherent organization underlying this chromosome eludes general consensus due to the lack of a high-resolution picture of its conformation. Here we present our development of an integrative model of E. coli at a 500 bp resolution (https://github.com/JMLab-tifrh/ecoli_finer), which optimally combines a set of multiresolution genome-wide experimentally measured data within a framework of polymer based architecture. In particular the model is informed with an intragenome contact probability map at 5000 bp resolution derived via the Hi-C experiment and RNA-sequencing data at 500 bp resolution. Via dynamical simulations, this data-driven polymer based model generates an appropriate conformational ensemble commensurate with chromosome architectures that E. coli adopts. As a key hallmark of the E. coli chromosome the model spontaneously self-organizes into a set of nonoverlapping macrodomains and suitably locates plectonemic loops near the cell membrane. As novel extensions, it predicts a contact probability map simulated at a higher resolution than precedent experiments and can demonstrate segregation of chromosomes in a partially replicating cell. Finally, the modular nature of the model helps us devise control simulations to quantify the individual role of key features in hierarchical organization of the bacterial chromosome.
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Affiliation(s)
- Abdul Wasim
- Tata Institute of Fundamental Research Hyderabad, Hyderabad, Telangana 500046, India
| | - Palash Bera
- Tata Institute of Fundamental Research Hyderabad, Hyderabad, Telangana 500046, India
| | - Jagannath Mondal
- Tata Institute of Fundamental Research Hyderabad, Hyderabad, Telangana 500046, India
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11
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Zhang Z, Zhao Q, Gong Z, Du R, Liu M, Zhang Y, Zhang L, Li C. Progress, Challenges and Opportunities of NMR and XL-MS for Cellular Structural Biology. JACS AU 2024; 4:369-383. [PMID: 38425916 PMCID: PMC10900494 DOI: 10.1021/jacsau.3c00712] [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: 11/14/2023] [Revised: 01/05/2024] [Accepted: 01/16/2024] [Indexed: 03/02/2024]
Abstract
The validity of protein structures and interactions, whether determined under ideal laboratory conditions or predicted by AI tools such as Alphafold2, to precisely reflect those found in living cells remains to be examined. Moreover, understanding the changes in protein structures and interactions in response to stimuli within living cells, under both normal and disease conditions, is key to grasping proteins' functionality and cellular processes. Nevertheless, achieving high-resolution identification of these protein structures and interactions within living cells presents a technical challenge. In this Perspective, we summarize the recent advancements in in-cell nuclear magnetic resonance (NMR) and in vivo cross-linking mass spectrometry (XL-MS) for studying protein structures and interactions within a cellular context. Additionally, we discuss the challenges, opportunities, and potential benefits of integrating in-cell NMR and in vivo XL-MS in future research to offer an exhaustive approach to studying proteins in their natural habitat.
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Affiliation(s)
- Zeting Zhang
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
| | - Qun Zhao
- CAS
Key Laboratory of Separation Science for Analytical Chemistry, National
Chromatographic R. & A. Center, State Key Laboratory of Medical
Proteomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Zhou Gong
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
| | - Ruichen Du
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
- University
of Chinese Academy of Sciences, Beijing 10049, China
| | - Maili Liu
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
| | - Yukui Zhang
- CAS
Key Laboratory of Separation Science for Analytical Chemistry, National
Chromatographic R. & A. Center, State Key Laboratory of Medical
Proteomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Lihua Zhang
- CAS
Key Laboratory of Separation Science for Analytical Chemistry, National
Chromatographic R. & A. Center, State Key Laboratory of Medical
Proteomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Conggang Li
- Key
Laboratory of Magnetic Resonance in Biological Systems, State Key
Laboratory of Magnetic Resonance and Atomic and Molecular Physics,
National Center for Magnetic Resonance in Wuhan, Wuhan Institute of
Physics and Mathematics, Innovation Academy of Precision Measurement, Chinese Academy of Sciences, Wuhan 430071, China
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12
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McCafferty CL, Klumpe S, Amaro RE, Kukulski W, Collinson L, Engel BD. Integrating cellular electron microscopy with multimodal data to explore biology across space and time. Cell 2024; 187:563-584. [PMID: 38306982 DOI: 10.1016/j.cell.2024.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/03/2024] [Accepted: 01/03/2024] [Indexed: 02/04/2024]
Abstract
Biology spans a continuum of length and time scales. Individual experimental methods only glimpse discrete pieces of this spectrum but can be combined to construct a more holistic view. In this Review, we detail the latest advancements in volume electron microscopy (vEM) and cryo-electron tomography (cryo-ET), which together can visualize biological complexity across scales from the organization of cells in large tissues to the molecular details inside native cellular environments. In addition, we discuss emerging methodologies for integrating three-dimensional electron microscopy (3DEM) imaging with multimodal data, including fluorescence microscopy, mass spectrometry, single-particle analysis, and AI-based structure prediction. This multifaceted approach fills gaps in the biological continuum, providing functional context, spatial organization, molecular identity, and native interactions. We conclude with a perspective on incorporating diverse data into computational simulations that further bridge and extend length scales while integrating the dimension of time.
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Affiliation(s)
| | - Sven Klumpe
- Research Group CryoEM Technology, Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany.
| | - Rommie E Amaro
- Department of Molecular Biology, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Wanda Kukulski
- Institute of Biochemistry and Molecular Medicine, University of Bern, Bühlstrasse 28, 3012 Bern, Switzerland.
| | - Lucy Collinson
- Electron Microscopy Science Technology Platform, Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.
| | - Benjamin D Engel
- Biozentrum, University of Basel, Spitalstrasse 41, 4056 Basel, Switzerland.
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13
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Hosseini AN, van der Spoel D. Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals? J Phys Chem Lett 2024; 15:1079-1088. [PMID: 38261634 PMCID: PMC10839907 DOI: 10.1021/acs.jpclett.4c00012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 01/18/2024] [Accepted: 01/19/2024] [Indexed: 01/25/2024]
Abstract
Computational chemistry is an important tool in numerous scientific disciplines, including drug discovery and structural biology. Coarse-grained models offer simple representations of molecular systems that enable simulations of large-scale systems. Because there has been an increase in the adoption of such models for simulations of biomolecular systems, critical evaluation is warranted. Here, the stability of the amyloid peptide and organic crystals is evaluated using the Martini 3 coarse-grained force field. The crystals change shape drastically during the simulations. Radial distribution functions show that the distance between backbone beads in β-sheets increases by ∼1 Å, breaking the crystals. The melting points of organic compounds are much too low in the Martini force field. This suggests that Martini 3 lacks the specific interactions needed to accurately simulate peptides or organic crystals without imposing artificial restraints. The problems may be exacerbated by the use of the 12-6 potential, suggesting that a softer potential could improve this model for crystal simulations.
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Affiliation(s)
- A. Najla Hosseini
- Department of Cell and Molecular
Biology, Uppsala University, Box 596, SE-75124 Uppsala, Sweden
| | - David van der Spoel
- Department of Cell and Molecular
Biology, Uppsala University, Box 596, SE-75124 Uppsala, Sweden
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14
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Hoff SE, Zinke M, Izadi-Pruneyre N, Bonomi M. Bonds and bytes: The odyssey of structural biology. Curr Opin Struct Biol 2024; 84:102746. [PMID: 38101027 DOI: 10.1016/j.sbi.2023.102746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 11/20/2023] [Accepted: 11/24/2023] [Indexed: 12/17/2023]
Abstract
Characterizing structural and dynamic properties of proteins and large macromolecular assemblies is crucial to understand the molecular mechanisms underlying biological functions. In the field of structural biology, no single method comprehensively reveals the behavior of biological systems across various spatiotemporal scales. Instead, we have a versatile toolkit of techniques, each contributing a piece to the overall puzzle. Integrative structural biology combines different techniques to create accurate and precise multi-scale models that expand our understanding of complex biological systems. This review outlines recent advancements in computational and experimental methods in structural biology, with special focus on recent Artificial Intelligence techniques, emphasizes integrative approaches that combine different types of data for precise spatiotemporal modeling, and provides an outlook into future directions of this field.
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Affiliation(s)
- S E Hoff
- Institut Pasteur, Université Paris Cité, CNRS UMR 3528, Structural Bioinformatics Unit, Paris, France
| | - M Zinke
- Institut Pasteur, Université Paris Cité, CNRS UMR 3528, Bacterial Transmembrane Systems Unit, Paris, France. https://twitter.com/ZinkeMaximilian
| | - N Izadi-Pruneyre
- Institut Pasteur, Université Paris Cité, CNRS UMR 3528, Bacterial Transmembrane Systems Unit, Paris, France.
| | - M Bonomi
- Institut Pasteur, Université Paris Cité, CNRS UMR 3528, Structural Bioinformatics Unit, Paris, France.
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15
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Pezeshkian W, Ipsen JH. Mesoscale simulation of biomembranes with FreeDTS. Nat Commun 2024; 15:548. [PMID: 38228588 PMCID: PMC10792169 DOI: 10.1038/s41467-024-44819-w] [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: 05/10/2023] [Accepted: 01/05/2024] [Indexed: 01/18/2024] Open
Abstract
We present FreeDTS software for performing computational research on biomembranes at the mesoscale. In this software, a membrane is represented by a dynamically triangulated surface equipped with vertex-based inclusions to integrate the effects of integral and peripheral membrane proteins. Several algorithms are included in the software to simulate complex membranes at different conditions such as framed membranes with constant tension, vesicles and high-genus membranes with various fixed volumes or constant pressure differences and applying external forces to membrane regions. Furthermore, the software allows the user to turn off the shape evolution of the membrane and focus solely on the organization of proteins. As a result, we can take realistic membrane shapes obtained from, for example, cryo-electron tomography and backmap them into a finer simulation model. In addition to many biomembrane applications, this software brings us a step closer to simulating realistic biomembranes with molecular resolution. Here we provide several interesting showcases of the power of the software but leave a wide range of potential applications for interested users.
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Affiliation(s)
- Weria Pezeshkian
- Niels Bohr International Academy, Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100, Copenhagen, Denmark.
| | - John H Ipsen
- MEMPHYS/PhyLife, Department of Physics, Chemistry and Pharmacy (FKF), University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark
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16
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Chen LH, Hu JN. Development of nano-delivery systems for loaded bioactive compounds: using molecular dynamics simulations. Crit Rev Food Sci Nutr 2024:1-22. [PMID: 38206576 DOI: 10.1080/10408398.2023.2301427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2024]
Abstract
Over the past decade, a remarkable surge in the development of functional nano-delivery systems loaded with bioactive compounds for healthcare has been witnessed. Notably, the demanding requirements of high solubility, prolonged circulation, high tissue penetration capability, and strong targeting ability of nanocarriers have posed interdisciplinary research challenges to the community. While extensive experimental studies have been conducted to understand the construction of nano-delivery systems and their metabolic behavior in vivo, less is known about these molecular mechanisms and kinetic pathways during their metabolic process in vivo, and lacking effective means for high-throughput screening. Molecular dynamics (MD) simulation techniques provide a reliable tool for investigating the design of nano-delivery carriers encapsulating these functional ingredients, elucidating the synthesis, translocation, and delivery of nanocarriers. This review introduces the basic MD principles, discusses how to apply MD simulation to design nanocarriers, evaluates the ability of nanocarriers to adhere to or cross gastrointestinal mucosa, and regulates plasma proteins in vivo. Moreover, we presented the critical role of MD simulation in developing delivery systems for precise nutrition and prospects for the future. This review aims to provide insights into the implications of MD simulation techniques for designing and optimizing nano-delivery systems in the healthcare food industry.
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Affiliation(s)
- Li-Hang Chen
- SKL of Marine Food Processing & Safety Control, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, School of Food Science and Technology, Dalian Polytechnic University, Dalian, China
| | - Jiang-Ning Hu
- SKL of Marine Food Processing & Safety Control, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, School of Food Science and Technology, Dalian Polytechnic University, Dalian, China
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17
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Beltrán D, Hospital A, Gelpí JL, Orozco M. A new paradigm for molecular dynamics databases: the COVID-19 database, the legacy of a titanic community effort. Nucleic Acids Res 2024; 52:D393-D403. [PMID: 37953362 PMCID: PMC10767965 DOI: 10.1093/nar/gkad991] [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: 08/14/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023] Open
Abstract
Molecular dynamics (MD) simulations are keeping computers busy around the world, generating a huge amount of data that is typically not open to the scientific community. Pioneering efforts to ensure the safety and reusability of MD data have been based on the use of simple databases providing a limited set of standard analyses on single-short trajectories. Despite their value, these databases do not offer a true solution for the current community of MD users, who want a flexible analysis pipeline and the possibility to address huge non-Markovian ensembles of large systems. Here we present a new paradigm for MD databases, resilient to large systems and long trajectories, and designed to be compatible with modern MD simulations. The data are offered to the community through a web-based graphical user interface (GUI), implemented with state-of-the-art technology, which incorporates system-specific analysis designed by the trajectory providers. A REST API and associated Jupyter Notebooks are integrated into the platform, allowing fully customized meta-analysis by final users. The new technology is illustrated using a collection of trajectories obtained by the community in the context of the effort to fight the COVID-19 pandemic. The server is accessible at https://bioexcel-cv19.bsc.es/#/. It is free and open to all users and there are no login requirements. It is also integrated into the simulations section of the BioExcel-MolSSI COVID-19 Molecular Structure and Therapeutics Hub: https://covid.molssi.org/simulations/ and is part of the MDDB effort (https://mddbr.eu).
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Affiliation(s)
- Daniel Beltrán
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Josep Lluís Gelpí
- Department of Biochemistry and Biomedicine. University of Barcelona, Barcelona, Spain
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Biochemistry and Biomedicine. University of Barcelona, Barcelona, Spain
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18
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Goodsell DS, Autin L. Integrative modeling of JCVI-Syn3A nucleoids with a modular approach. Curr Res Struct Biol 2023; 7:100121. [PMID: 38221989 PMCID: PMC10784680 DOI: 10.1016/j.crstbi.2023.100121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/15/2023] [Accepted: 12/18/2023] [Indexed: 01/16/2024] Open
Abstract
A lattice-based method is presented for creating 3D models of entire bacterial nucleoids integrating ultrastructural information cryoelectron tomography, genomic and proteomic data, and experimental atomic structures of biomolecules and assemblies. The method is used to generate models of the minimal genome bacterium JCVI-Syn3A, producing a series of models that test hypotheses about transcription, condensation, and overall distribution of the genome. Lattice models are also used to generate atomic models of an entire JCVI-Syn3A cell.
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Affiliation(s)
- David S. Goodsell
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037, USA
- Research Collaboratory for Structural Bioinformatics Protein Data and Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA
| | - Ludovic Autin
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037, USA
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19
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Samuel Russell PP, Alaeen S, Pogorelov TV. In-Cell Dynamics: The Next Focus of All-Atom Simulations. J Phys Chem B 2023; 127:9863-9872. [PMID: 37793083 PMCID: PMC10874638 DOI: 10.1021/acs.jpcb.3c05166] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
The cell is a crowded space where large biomolecules and metabolites are in continuous motion. Great strides have been made in in vitro studies of protein dynamics, folding, and protein-protein interactions, and much new data are emerging of how they differ in the cell. In this Perspective, we highlight the current progress in atomistic modeling of in-cell environments, both bacteria and mammals, with emphasis on classical all-atom molecular dynamics simulations. These simulations have been recently used to capture and characterize functional and non-functional protein-protein interactions, protein folding dynamics of small proteins with varied topologies, and dynamics of metabolites. We further discuss the challenges and efforts for updating modern force fields critical to the progress of cellular environment simulations. We also briefly summarize developments in relevant state-of-the-art experimental techniques. As computational and experimental methodologies continue to progress and produce more directly comparable data, we are poised to capture the complex atomistic picture of the cell.
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Affiliation(s)
- Premila P Samuel Russell
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Sepehr Alaeen
- Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Taras V Pogorelov
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
- Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
- School of Chemical Sciences, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
- National Center for Supercomputing Applications, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
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20
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Georgouli K, Yeom JS, Blake RC, Navid A. Multi-scale models of whole cells: progress and challenges. Front Cell Dev Biol 2023; 11:1260507. [PMID: 38020904 PMCID: PMC10661945 DOI: 10.3389/fcell.2023.1260507] [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: 07/18/2023] [Accepted: 10/19/2023] [Indexed: 12/01/2023] Open
Abstract
Whole-cell modeling is "the ultimate goal" of computational systems biology and "a grand challenge for 21st century" (Tomita, Trends in Biotechnology, 2001, 19(6), 205-10). These complex, highly detailed models account for the activity of every molecule in a cell and serve as comprehensive knowledgebases for the modeled system. Their scope and utility far surpass those of other systems models. In fact, whole-cell models (WCMs) are an amalgam of several types of "system" models. The models are simulated using a hybrid modeling method where the appropriate mathematical methods for each biological process are used to simulate their behavior. Given the complexity of the models, the process of developing and curating these models is labor-intensive and to date only a handful of these models have been developed. While whole-cell models provide valuable and novel biological insights, and to date have identified some novel biological phenomena, their most important contribution has been to highlight the discrepancy between available data and observations that are used for the parametrization and validation of complex biological models. Another realization has been that current whole-cell modeling simulators are slow and to run models that mimic more complex (e.g., multi-cellular) biosystems, those need to be executed in an accelerated fashion on high-performance computing platforms. In this manuscript, we review the progress of whole-cell modeling to date and discuss some of the ways that they can be improved.
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Affiliation(s)
- Konstantia Georgouli
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, United States
| | - Jae-Seung Yeom
- Center for Applied Scientific Computing, Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA, United States
| | - Robert C. Blake
- Center for Applied Scientific Computing, Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA, United States
| | - Ali Navid
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, United States
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21
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Khalid S, Brandner AF, Juraschko N, Newman KE, Pedebos C, Prakaash D, Smith IPS, Waller C, Weerakoon D. Computational microbiology of bacteria: Advancements in molecular dynamics simulations. Structure 2023; 31:1320-1327. [PMID: 37875115 DOI: 10.1016/j.str.2023.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/04/2023] [Accepted: 09/28/2023] [Indexed: 10/26/2023]
Abstract
Microbiology is traditionally considered within the context of wet laboratory methodologies. Computational techniques have a great potential to contribute to microbiology. Here, we describe our loose definition of "computational microbiology" and provide a short survey focused on molecular dynamics simulations of bacterial systems that fall within this definition. It is our contention that increased compositional complexity and realistic levels of molecular crowding within simulated systems are key for bridging the divide between experimental and computational microbiology.
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Affiliation(s)
- Syma Khalid
- Department of Biochemistry, University of Oxford, OX1 3QU Oxford, UK; School of Chemistry, University of Southampton, SO17 1BJ Southampton, UK.
| | - Astrid F Brandner
- Department of Biochemistry, University of Oxford, OX1 3QU Oxford, UK
| | - Nikolai Juraschko
- Department of Biochemistry, University of Oxford, OX1 3QU Oxford, UK; Artificial Intelligence and Informatics, The Rosalind Franklin Institute, Didcot, UK
| | - Kahlan E Newman
- School of Chemistry, University of Southampton, SO17 1BJ Southampton, UK
| | - Conrado Pedebos
- Department of Biochemistry, University of Oxford, OX1 3QU Oxford, UK; Programa de Pós-Graduação em Biociências (PPGBio), Universidade Federal de Ciências da Saúde de Porto Alegre - UFCSPA, Porto Alegre, Brazil
| | - Dheeraj Prakaash
- Department of Biochemistry, University of Oxford, OX1 3QU Oxford, UK
| | - Iain P S Smith
- School of Chemistry, University of Southampton, SO17 1BJ Southampton, UK
| | - Callum Waller
- School of Chemistry, University of Southampton, SO17 1BJ Southampton, UK
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22
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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: 3] [Impact Index Per Article: 3.0] [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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23
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Johnson GT, Agmon E, Akamatsu M, Lundberg E, Lyons B, Ouyang W, Quintero-Carmona OA, Riel-Mehan M, Rafelski S, Horwitz R. Building the next generation of virtual cells to understand cellular biology. Biophys J 2023; 122:3560-3569. [PMID: 37050874 PMCID: PMC10541477 DOI: 10.1016/j.bpj.2023.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 03/19/2023] [Accepted: 04/06/2023] [Indexed: 04/14/2023] Open
Abstract
Cell science has made significant progress by focusing on understanding individual cellular processes through reductionist approaches. However, the sheer volume of knowledge collected presents challenges in integrating this information across different scales of space and time to comprehend cellular behaviors, as well as making the data and methods more accessible for the community to tackle complex biological questions. This perspective proposes the creation of next-generation virtual cells, which are dynamic 3D models that integrate information from diverse sources, including simulations, biophysical models, image-based models, and evidence-based knowledge graphs. These virtual cells would provide statistically accurate and holistic views of real cells, bridging the gap between theoretical concepts and experimental data, and facilitating productive new collaborations among researchers across related fields.
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Affiliation(s)
| | - Eran Agmon
- Center for Cell Analysis and Modeling, University of Connecticut Health, Farmington, Connecticut
| | - Matthew Akamatsu
- Department of Biology, University of Washington, Seattle, Washington
| | - Emma Lundberg
- Department of Applied Physics, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden; Department of Bioengineering, Stanford University, Stanford, California; Department of Pathology, Stanford University, Stanford, California; Chan Zuckerberg Biohub, San Francisco, California
| | - Blair Lyons
- Allen Institute for Cell Science, Seattle, Washington
| | - Wei Ouyang
- Department of Applied Physics, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | | | | | - Rick Horwitz
- Allen Institute for Cell Science, Seattle, Washington.
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24
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Klein F, Soñora M, Helene Santos L, Nazareno Frigini E, Ballesteros-Casallas A, Rodrigo Machado M, Pantano S. The SIRAH force field: A suite for simulations of complex biological systems at the coarse-grained and multiscale levels. J Struct Biol 2023; 215:107985. [PMID: 37331570 DOI: 10.1016/j.jsb.2023.107985] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/18/2023] [Accepted: 06/13/2023] [Indexed: 06/20/2023]
Abstract
The different combinations of molecular dynamics simulations with coarse-grained representations have acquired considerable popularity among the scientific community. Especially in biocomputing, the significant speedup granted by simplified molecular models opened the possibility of increasing the diversity and complexity of macromolecular systems, providing realistic insights on large assemblies for more extended time windows. However, a holistic view of biological ensembles' structural and dynamic features requires a self-consistent force field, namely, a set of equations and parameters that describe the intra and intermolecular interactions among moieties of diverse chemical nature (i.e., nucleic and amino acids, lipids, solvent, ions, etc.). Nevertheless, examples of such force fields are scarce in the literature at the fully atomistic and coarse-grained levels. Moreover, the number of force fields capable of handling simultaneously different scales is restricted to a handful. Among those, the SIRAH force field, developed in our group, furnishes a set of topologies and tools that facilitate the setting up and running of molecular dynamics simulations at the coarse-grained and multiscale levels. SIRAH uses the same classical pairwise Hamiltonian function implemented in the most popular molecular dynamics software. In particular, it runs natively in AMBER and Gromacs engines, and porting it to other simulation packages is straightforward. This review describes the underlying philosophy behind the development of SIRAH over the years and across families of biological molecules, discussing current limitations and future implementations.
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Affiliation(s)
- Florencia Klein
- Laboratoire de Biochimie Théorique, UPR9080, CNRS, Paris, France
| | - Martín Soñora
- Institut Pasteur de Montevideo, Mataojo 2020, 11400, Montevideo, Uruguay
| | | | - Ezequiel Nazareno Frigini
- Instituto Multidisciplinario de Investigaciones Biológicas de San Luis (IMIBIO-SL), Universidad Nacional de San Luis - CONICET, San Luis, Argentina
| | - Andrés Ballesteros-Casallas
- Institut Pasteur de Montevideo, Mataojo 2020, 11400, Montevideo, Uruguay; Area Bioinformática, DETEMA, Facultad de Química, Universidad de la República, General Flores 2124, Montevideo, 11600, Uruguay
| | | | - Sergio Pantano
- Institut Pasteur de Montevideo, Mataojo 2020, 11400, Montevideo, Uruguay; Area Bioinformática, DETEMA, Facultad de Química, Universidad de la República, General Flores 2124, Montevideo, 11600, Uruguay.
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25
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Gilbert BR, Thornburg ZR, Brier TA, Stevens JA, Grünewald F, Stone JE, Marrink SJ, Luthey-Schulten Z. Dynamics of chromosome organization in a minimal bacterial cell. Front Cell Dev Biol 2023; 11:1214962. [PMID: 37621774 PMCID: PMC10445541 DOI: 10.3389/fcell.2023.1214962] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 07/10/2023] [Indexed: 08/26/2023] Open
Abstract
Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication and inheritance of genetic material. By creating a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics, we investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell-cycle. To achieve cell-scale chromosome structures that are realistic, we model the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. In addition, the conformations of the circular DNA must avoid overlapping with ribosomes identitied in cryo-electron tomograms. While Syn3A lacks the complex regulatory systems known to orchestrate chromosome segregation in other bacteria, its minimized genome retains essential loop-extruding structural maintenance of chromosomes (SMC) protein complexes (SMC-scpAB) and topoisomerases. Through implementing the effects of these proteins in our simulations of replicating chromosomes, we find that they alone are sufficient for simultaneous chromosome segregation across all generations within nested theta structures. This supports previous studies suggesting loop-extrusion serves as a near-universal mechanism for chromosome organization within bacterial and eukaryotic cells. Furthermore, we analyze ribosome diffusion under the influence of the chromosome and calculate in silico chromosome contact maps that capture inter-daughter interactions. Finally, we present a methodology to map the polymer model of the chromosome to a Martini coarse-grained representation to prepare molecular dynamics models of entire Syn3A cells, which serves as an ultimate means of validation for cell states predicted by the WCM.
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Affiliation(s)
- Benjamin R. Gilbert
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Zane R. Thornburg
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Troy A. Brier
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Jan A. Stevens
- Molecular Dynamics Group, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands
| | - Fabian Grünewald
- Molecular Dynamics Group, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands
| | - John E. Stone
- NVIDIA Corporation, Santa Clara, CA, United States
- NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Siewert J. Marrink
- Molecular Dynamics Group, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands
| | - Zaida Luthey-Schulten
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, United States
- NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States
- NSF Center for the Physics of Living Cells, Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, United States
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Corey RA, Baaden M, Chavent M. A brief history of visualizing membrane systems in molecular dynamics simulations. FRONTIERS IN BIOINFORMATICS 2023; 3:1149744. [PMID: 37213533 PMCID: PMC10196259 DOI: 10.3389/fbinf.2023.1149744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 03/13/2023] [Indexed: 05/23/2023] Open
Abstract
Understanding lipid dynamics and function, from the level of single, isolated molecules to large assemblies, is more than ever an intensive area of research. The interactions of lipids with other molecules, particularly membrane proteins, are now extensively studied. With advances in the development of force fields for molecular dynamics simulations (MD) and increases in computational resources, the creation of realistic and complex membrane systems is now common. In this perspective, we will review four decades of the history of molecular dynamics simulations applied to membranes and lipids through the prism of molecular graphics.
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Affiliation(s)
- R. A. Corey
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
| | - M. Baaden
- Centre Nationale de la Recherche Scientifique, Laboratoire de Biochimie Théorique, Université Paris Cité, Paris, France
| | - M. Chavent
- Institut de Pharmacologie et Biologie Structurale, CNRS, Université de Toulouse, Toulouse, France
- *Correspondence: M. Chavent,
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