1
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Schanda P, Haran G. NMR and Single-Molecule FRET Insights into Fast Protein Motions and Their Relation to Function. Annu Rev Biophys 2024; 53:247-273. [PMID: 38346243 DOI: 10.1146/annurev-biophys-070323-022428] [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] [Indexed: 07/18/2024]
Abstract
Proteins often undergo large-scale conformational transitions, in which secondary and tertiary structure elements (loops, helices, and domains) change their structures or their positions with respect to each other. Simple considerations suggest that such dynamics should be relatively fast, but the functional cycles of many proteins are often relatively slow. Sophisticated experimental methods are starting to tackle this dichotomy and shed light on the contribution of large-scale conformational dynamics to protein function. In this review, we focus on the contribution of single-molecule Förster resonance energy transfer and nuclear magnetic resonance (NMR) spectroscopies to the study of conformational dynamics. We briefly describe the state of the art in each of these techniques and then point out their similarities and differences, as well as the relative strengths and weaknesses of each. Several case studies, in which the connection between fast conformational dynamics and slower function has been demonstrated, are then introduced and discussed. These examples include both enzymes and large protein machines, some of which have been studied by both NMR and fluorescence spectroscopies.
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Affiliation(s)
- Paul Schanda
- Institute of Science and Technology Austria (ISTA), Klosterneuburg, Austria;
| | - Gilad Haran
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel;
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2
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Nam K, Shao Y, Major DT, Wolf-Watz M. Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development. ACS OMEGA 2024; 9:7393-7412. [PMID: 38405524 PMCID: PMC10883025 DOI: 10.1021/acsomega.3c09084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/15/2024] [Accepted: 01/19/2024] [Indexed: 02/27/2024]
Abstract
Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.
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Affiliation(s)
- Kwangho Nam
- Department
of Chemistry and Biochemistry, University
of Texas at Arlington, Arlington, Texas 76019, United States
| | - Yihan Shao
- Department
of Chemistry and Biochemistry, University
of Oklahoma, Norman, Oklahoma 73019-5251, United States
| | - Dan T. Major
- Department
of Chemistry and Institute for Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 52900, Israel
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3
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Nam K, Arattu Thodika AR, Grundström C, Sauer UH, Wolf-Watz M. Elucidating Dynamics of Adenylate Kinase from Enzyme Opening to Ligand Release. J Chem Inf Model 2024; 64:150-163. [PMID: 38117131 PMCID: PMC10778088 DOI: 10.1021/acs.jcim.3c01618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 12/01/2023] [Accepted: 12/07/2023] [Indexed: 12/21/2023]
Abstract
This study explores ligand-driven conformational changes in adenylate kinase (AK), which is known for its open-to-close conformational transitions upon ligand binding and release. By utilizing string free energy simulations, we determine the free energy profiles for both enzyme opening and ligand release and compare them with profiles from the apoenzyme. Results reveal a three-step ligand release process, which initiates with the opening of the adenosine triphosphate-binding subdomain (ATP lid), followed by ligand release and concomitant opening of the adenosine monophosphate-binding subdomain (AMP lid). The ligands then transition to nonspecific positions before complete dissociation. In these processes, the first step is energetically driven by ATP lid opening, whereas the second step is driven by ATP release. In contrast, the AMP lid opening and its ligand release make minor contributions to the total free energy for enzyme opening. Regarding the ligand binding mechanism, our results suggest that AMP lid closure occurs via an induced-fit mechanism triggered by AMP binding, whereas ATP lid closure follows conformational selection. This difference in the closure mechanisms provides an explanation with implications for the debate on ligand-driven conformational changes of AK. Additionally, we determine an X-ray structure of an AK variant that exhibits significant rearrangements in the stacking of catalytic arginines, explaining its reduced catalytic activity. In the context of apoenzyme opening, the sequence of events is different. Here, the AMP lid opens first while the ATP lid remains closed, and the free energy associated with ATP lid opening varies with orientation, aligning with the reported AK opening and closing rate heterogeneity. Finally, this study, in conjunction with our previous research, provides a comprehensive view of the intricate interplay between various structural elements, ligands, and catalytic residues that collectively contribute to the robust catalytic power of the enzyme.
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Affiliation(s)
- Kwangho Nam
- Department
of Chemistry and Biochemistry, University
of Texas at Arlington, Arlington, Texas 76019, United States
| | - Abdul Raafik Arattu Thodika
- Department
of Chemistry and Biochemistry, University
of Texas at Arlington, Arlington, Texas 76019, United States
| | | | - Uwe H. Sauer
- Department
of Chemistry, Umeå University, Umeå 90187, SE, Sweden
| | - Magnus Wolf-Watz
- Department
of Chemistry, Umeå University, Umeå 90187, SE, Sweden
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4
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Kim J, Moon S, Romo TD, Yang Y, Bae E, Phillips GN. Conformational dynamics of adenylate kinase in crystals. STRUCTURAL DYNAMICS (MELVILLE, N.Y.) 2024; 11:014702. [PMID: 38389978 PMCID: PMC10883716 DOI: 10.1063/4.0000205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 12/14/2023] [Indexed: 02/24/2024]
Abstract
Adenylate kinase is a ubiquitous enzyme in living systems and undergoes dramatic conformational changes during its catalytic cycle. For these reasons, it is widely studied by genetic, biochemical, and biophysical methods, both experimental and theoretical. We have determined the basic crystal structures of three differently liganded states of adenylate kinase from Methanotorrus igneus, a hyperthermophilic organism whose adenylate kinase is a homotrimeric oligomer. The multiple copies of each protomer in the asymmetric unit of the crystal provide a unique opportunity to study the variation in the structure and were further analyzed using advanced crystallographic refinement methods and analysis tools to reveal conformational heterogeneity and, thus, implied dynamic behaviors in the catalytic cycle.
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Affiliation(s)
- Junhyung Kim
- Department of Agricultural Biotechnology, Seoul National University, Seoul 08826, South Korea
| | - Sojin Moon
- Department of Agricultural Biotechnology, Seoul National University, Seoul 08826, South Korea
| | - Tod D Romo
- Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, New York 14642, USA
| | - Yifei Yang
- Departments of BioSciences, Rice University, Houston, Texas 77005, USA
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5
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Lichtinger SM, Biggin PC. Tackling Hysteresis in Conformational Sampling: How to Be Forgetful with MEMENTO. J Chem Theory Comput 2023. [PMID: 37285481 DOI: 10.1021/acs.jctc.3c00140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The structure of proteins has long been recognized to hold the key to understanding and engineering their function, and rapid advances in structural biology and protein structure prediction are now supplying researchers with an ever-increasing wealth of structural information. Most of the time, however, structures can only be determined in free energy minima, one at a time. While conformational flexibility may thus be inferred from static end-state structures, their interconversion mechanisms─a central ambition of structural biology─are often beyond the scope of direct experimentation. Given the dynamical nature of the processes in question, many studies have attempted to explore conformational transitions using molecular dynamics (MD). However, ensuring proper convergence and reversibility in the predicted transitions is extremely challenging. In particular, a commonly used technique to map out a path from a starting to a target conformation called steered MD (SMD) can suffer from starting-state dependence (hysteresis) when combined with techniques such as umbrella sampling (US) to compute the free energy profile of a transition. Here, we study this problem in detail on conformational changes of increasing complexity. We also present a new, history-independent approach that we term "MEMENTO" (Morphing End states by Modelling Ensembles with iNdependent TOpologies) to generate paths that alleviate hysteresis in the construction of conformational free energy profiles. MEMENTO utilizes template-based structure modelling to restore physically reasonable protein conformations based on coordinate interpolation (morphing) as an ensemble of plausible intermediates, from which a smooth path is picked. We compare SMD and MEMENTO on well-characterized test cases (the toy peptide deca-alanine and the enzyme adenylate kinase) before discussing its use in more complicated systems (the kinase P38α and the bacterial leucine transporter LeuT). Our work shows that for all but the simplest systems SMD paths should not in general be used to seed umbrella sampling or related techniques, unless the paths are validated by consistent results from biased runs in opposite directions. MEMENTO, on the other hand, performs well as a flexible tool to generate intermediate structures for umbrella sampling. We also demonstrate that extended end-state sampling combined with MEMENTO can aid the discovery of collective variables on a case-by-case basis.
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Affiliation(s)
| | - Philip C Biggin
- Department of Biochemistry, University of Oxford, Oxford OX1 3QU, U.K
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6
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Scheerer D, Adkar BV, Bhattacharyya S, Levy D, Iljina M, Riven I, Dym O, Haran G, Shakhnovich EI. Allosteric communication between ligand binding domains modulates substrate inhibition in adenylate kinase. Proc Natl Acad Sci U S A 2023; 120:e2219855120. [PMID: 37094144 PMCID: PMC10160949 DOI: 10.1073/pnas.2219855120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 03/22/2023] [Indexed: 04/26/2023] Open
Abstract
Enzymes play a vital role in life processes; they control chemical reactions and allow functional cycles to be synchronized. Many enzymes harness large-scale motions of their domains to achieve tremendous catalytic prowess and high selectivity for specific substrates. One outstanding example is provided by the three-domain enzyme adenylate kinase (AK), which catalyzes phosphotransfer between ATP to AMP. Here we study the phenomenon of substrate inhibition by AMP and its correlation with domain motions. Using single-molecule FRET spectroscopy, we show that AMP does not block access to the ATP binding site, neither by competitive binding to the ATP cognate site nor by directly closing the LID domain. Instead, inhibitory concentrations of AMP lead to a faster and more cooperative domain closure by ATP, leading in turn to an increased population of the closed state. The effect of AMP binding can be modulated through mutations throughout the structure of the enzyme, as shown by the screening of an extensive AK mutant library. The mutation of multiple conserved residues reduces substrate inhibition, suggesting that substrate inhibition is an evolutionary well conserved feature in AK. Combining these insights, we developed a model that explains the complex activity of AK, particularly substrate inhibition, based on the experimentally observed opening and closing rates. Notably, the model indicates that the catalytic power is affected by the microsecond balance between the open and closed states of the enzyme. Our findings highlight the crucial role of protein motions in enzymatic activity.
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Affiliation(s)
- David Scheerer
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Bharat V Adkar
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138
| | | | - Dorit Levy
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Marija Iljina
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Inbal Riven
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Orly Dym
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Gilad Haran
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138
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7
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Verkhivker G, Alshahrani M, Gupta G, Xiao S, Tao P. From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on "Allosteric Intersection" of Biochemical and Big Data Approaches. Int J Mol Sci 2023; 24:7747. [PMID: 37175454 PMCID: PMC10178073 DOI: 10.3390/ijms24097747] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 04/22/2023] [Accepted: 04/23/2023] [Indexed: 05/15/2023] Open
Abstract
The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric regulation, the emerging structural biology technologies and AI approaches remains largely unexplored, calling for the development of AI-augmented integrative structural biology. In this review, we focus on the latest remarkable progress in deep high-throughput mining and comprehensive mapping of allosteric protein landscapes and allosteric regulatory mechanisms as well as on the new developments in AI methods for prediction and characterization of allosteric binding sites on the proteome level. We also discuss new AI-augmented structural biology approaches that expand our knowledge of the universe of protein dynamics and allostery. We conclude with an outlook and highlight the importance of developing an open science infrastructure for machine learning studies of allosteric regulation and validation of computational approaches using integrative studies of allosteric mechanisms. The development of community-accessible tools that uniquely leverage the existing experimental and simulation knowledgebase to enable interrogation of the allosteric functions can provide a much-needed boost to further innovation and integration of experimental and computational technologies empowered by booming AI field.
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Affiliation(s)
- Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
| | - Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
| | - Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75275, USA; (S.X.); (P.T.)
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75275, USA; (S.X.); (P.T.)
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8
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Xiao S, Verkhivker GM, Tao P. Machine learning and protein allostery. Trends Biochem Sci 2023; 48:375-390. [PMID: 36564251 PMCID: PMC10023316 DOI: 10.1016/j.tibs.2022.12.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 11/16/2022] [Accepted: 12/02/2022] [Indexed: 12/23/2022]
Abstract
The fundamental biological importance and complexity of allosterically regulated proteins stem from their central role in signal transduction and cellular processes. Recently, machine-learning approaches have been developed and actively deployed to facilitate theoretical and experimental studies of protein dynamics and allosteric mechanisms. In this review, we survey recent developments in applications of machine-learning methods for studies of allosteric mechanisms, prediction of allosteric effects and allostery-related physicochemical properties, and allosteric protein engineering. We also review the applications of machine-learning strategies for characterization of allosteric mechanisms and drug design targeting SARS-CoV-2. Continuous development and task-specific adaptation of machine-learning methods for protein allosteric mechanisms will have an increasingly important role in bridging a wide spectrum of data-intensive experimental and theoretical technologies.
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Affiliation(s)
- Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75205, USA.
| | - Gennady M Verkhivker
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75205, USA.
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9
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Dulko-Smith B, Ojeda-May P, Ådén J, Wolf-Watz M, Nam K. Mechanistic Basis for a Connection between the Catalytic Step and Slow Opening Dynamics of Adenylate Kinase. J Chem Inf Model 2023; 63:1556-1569. [PMID: 36802243 DOI: 10.1021/acs.jcim.2c01629] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
Escherichia coli adenylate kinase (AdK) is a small, monomeric enzyme that synchronizes the catalytic step with the enzyme's conformational dynamics to optimize a phosphoryl transfer reaction and the subsequent release of the product. Guided by experimental measurements of low catalytic activity in seven single-point mutation AdK variants (K13Q, R36A, R88A, R123A, R156K, R167A, and D158A), we utilized classical mechanical simulations to probe mutant dynamics linked to product release, and quantum mechanical and molecular mechanical calculations to compute a free energy barrier for the catalytic event. The goal was to establish a mechanistic connection between the two activities. Our calculations of the free energy barriers in AdK variants were in line with those from experiments, and conformational dynamics consistently demonstrated an enhanced tendency toward enzyme opening. This indicates that the catalytic residues in the wild-type AdK serve a dual role in this enzyme's function─one to lower the energy barrier for the phosphoryl transfer reaction and another to delay enzyme opening, maintaining it in a catalytically active, closed conformation for long enough to enable the subsequent chemical step. Our study also discovers that while each catalytic residue individually contributes to facilitating the catalysis, R36, R123, R156, R167, and D158 are organized in a tightly coordinated interaction network and collectively modulate AdK's conformational transitions. Unlike the existing notion of product release being rate-limiting, our results suggest a mechanistic interconnection between the chemical step and the enzyme's conformational dynamics acting as the bottleneck of the catalytic process. Our results also suggest that the enzyme's active site has evolved to optimize the chemical reaction step while slowing down the overall opening dynamics of the enzyme.
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Affiliation(s)
- Beata Dulko-Smith
- Department of Chemistry and Biochemistry, University of Texas at Arlington, Arlington, Texas 76019, United States
| | - Pedro Ojeda-May
- High Performance Computing Centre North (HPC2N), Umeå University, Umeå SE-90187, Sweden
| | - Jörgen Ådén
- Department of Chemistry, Umeå University, Umeå SE-90187, Sweden
| | | | - Kwangho Nam
- Department of Chemistry and Biochemistry, University of Texas at Arlington, Arlington, Texas 76019, United States
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10
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Fiorentini R, Tarenzi T, Potestio R. Fast, Accurate, and System-Specific Variable-Resolution Modeling of Proteins. J Chem Inf Model 2023; 63:1260-1275. [PMID: 36735551 PMCID: PMC9976289 DOI: 10.1021/acs.jcim.2c01311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Indexed: 02/04/2023]
Abstract
In recent years, a few multiple-resolution modeling strategies have been proposed, in which functionally relevant parts of a biomolecule are described with atomistic resolution, with the remainder of the system being concurrently treated using a coarse-grained model. In most cases, the parametrization of the latter requires lengthy reference all-atom simulations and/or the usage of off-shelf coarse-grained force fields, whose interactions have to be refined to fit the specific system under examination. Here, we overcome these limitations through a novel multiresolution modeling scheme for proteins, dubbed coarse-grained anisotropic network model for variable resolution simulations, or CANVAS. This scheme enables a user-defined modulation of the resolution level throughout the system structure; a fast parametrization of the potential without the necessity of reference simulations; and the straightforward usage of the model on the most commonly used molecular dynamics platforms. The method is presented and validated with two case studies, the enzyme adenylate kinase and the therapeutic antibody pembrolizumab, by comparing the results obtained with the CANVAS model against fully atomistic simulations. The modeling software, implemented in Python, is made freely available for the community on a collaborative github repository.
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Affiliation(s)
- Raffaele Fiorentini
- Department
of Physics, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, via Sommarive 14, I-38123 Trento, Italy
| | - Thomas Tarenzi
- Department
of Physics, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, via Sommarive 14, I-38123 Trento, Italy
| | - Raffaello Potestio
- Department
of Physics, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, via Sommarive 14, I-38123 Trento, Italy
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11
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Jaroensuk J, Chuaboon L, Chaiyen P. Biochemical reactions for in vitro ATP production and their applications. MOLECULAR CATALYSIS 2023. [DOI: 10.1016/j.mcat.2023.112937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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12
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Ali AAAI, Gulzar A, Wolf S, Stock G. Nonequilibrium Modeling of the Elementary Step in PDZ3 Allosteric Communication. J Phys Chem Lett 2022; 13:9862-9868. [PMID: 36251493 DOI: 10.1021/acs.jpclett.2c02821] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
While allostery is of paramount importance for protein signaling and regulation, the underlying dynamical process of allosteric communication is not well understood. The PDZ3 domain represents a prime example of an allosteric single-domain protein, as it features a well-established long-range coupling between the C-terminal α3-helix and ligand binding. In an intriguing experiment, Hamm and co-workers employed photoswitching of the α3-helix to initiate a conformational change of PDZ3 that propagates from the C-terminus to the bound ligand within 200 ns. Performing extensive nonequilibrium molecular dynamics simulations, the modeling of the experiment reproduces the measured time scales and reveals a detailed picture of the allosteric communication in PDZ3. In particular, a correlation analysis identifies a network of contacts connecting the α3-helix and the core of the protein, which move in a concerted manner. Representing a one-step process and involving direct α3-ligand contacts, this cooperative transition is considered as the elementary step in the propagation of conformational change.
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Affiliation(s)
- Ahmed A A I Ali
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, 79104Freiburg, Germany
| | - Adnan Gulzar
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, 79104Freiburg, Germany
| | - Steffen Wolf
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, 79104Freiburg, Germany
| | - Gerhard Stock
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, 79104Freiburg, Germany
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13
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Lu J, Scheerer D, Haran G, Li W, Wang W. Role of Repeated Conformational Transitions in Substrate Binding of Adenylate Kinase. J Phys Chem B 2022; 126:8188-8201. [PMID: 36222098 PMCID: PMC9589722 DOI: 10.1021/acs.jpcb.2c05497] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The catalytic cycle of the enzyme adenylate kinase involves large conformational motions between open and closed states. A previous single-molecule experiment showed that substrate binding tends to accelerate both the opening and the closing rates and that a single turnover event often involves multiple rounds of conformational switching. In this work, we showed that the repeated conformational transitions of adenylate kinase are essential for the relaxation of incorrectly bound substrates into the catalytically competent conformation by combining all-atom and coarse-grained molecular simulations. In addition, free energy calculations based on all-atom and coarse-grained models demonstrated that the enzyme with incorrectly bound substrates has much a lower free energy barrier for domain opening compared to that with the correct substrate conformation, which may explain the the acceleration of the domain opening rate by substrate binding. The results of this work provide mechanistic understanding to previous experimental observations and shed light onto the interplay between conformational dynamics and enzyme catalysis.
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Affiliation(s)
- Jiajun Lu
- Department
of Physics, National Laboratory of Solid State Microstructure, Nanjing University, Nanjing210093, China,Wenzhou
Key Laboratory of Biophysics, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang325000, China
| | - David Scheerer
- Department
of Chemical and Biological Physics, Weizmann
Institute of Science, Rehovot761001, Israel
| | - Gilad Haran
- Department
of Chemical and Biological Physics, Weizmann
Institute of Science, Rehovot761001, Israel,
| | - Wenfei Li
- Department
of Physics, National Laboratory of Solid State Microstructure, Nanjing University, Nanjing210093, China,Wenzhou
Key Laboratory of Biophysics, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang325000, China,
| | - Wei Wang
- Department
of Physics, National Laboratory of Solid State Microstructure, Nanjing University, Nanjing210093, China,
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14
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Orädd F, Ravishankar H, Goodman J, Rogne P, Backman L, Duelli A, Nors Pedersen M, Levantino M, Wulff M, Wolf-Watz M, Andersson M. Tracking the ATP-binding response in adenylate kinase in real time. SCIENCE ADVANCES 2021; 7:eabi5514. [PMID: 34788091 PMCID: PMC8597995 DOI: 10.1126/sciadv.abi5514] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 09/27/2021] [Indexed: 05/25/2023]
Abstract
The biological function of proteins is critically dependent on dynamics inherent to the native structure. Such structural dynamics obey a predefined order and temporal timing to execute the specific reaction. Determination of the cooperativity of key structural rearrangements requires monitoring protein reactions in real time. In this work, we used time-resolved x-ray solution scattering (TR-XSS) to visualize structural changes in the Escherichia coli adenylate kinase (AdK) enzyme upon laser-induced activation of a protected ATP substrate. A 4.3-ms transient intermediate showed partial closing of both the ATP- and AMP-binding domains, which indicates a cooperative closing mechanism. The ATP-binding domain also showed local unfolding and breaking of an Arg131-Asp146 salt bridge. Nuclear magnetic resonance spectroscopy data identified similar unfolding in an Arg131Ala AdK mutant, which refolded in a closed, substrate-binding conformation. The observed structural dynamics agree with a “cracking mechanism” proposed to underlie global structural transformation, such as allostery, in proteins.
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Affiliation(s)
- Fredrik Orädd
- Department of Chemistry, Umeå University, Linnaeus Väg 10, 901 87 Umeå, Sweden
| | - Harsha Ravishankar
- Department of Chemistry, Umeå University, Linnaeus Väg 10, 901 87 Umeå, Sweden
| | - Jack Goodman
- Department of Chemistry, Umeå University, Linnaeus Väg 10, 901 87 Umeå, Sweden
| | - Per Rogne
- Department of Chemistry, Umeå University, Linnaeus Väg 10, 901 87 Umeå, Sweden
| | - Lars Backman
- Department of Chemistry, Umeå University, Linnaeus Väg 10, 901 87 Umeå, Sweden
| | - Annette Duelli
- Department of Biomedical Sciences, University of Copenhagen, Blegdamsvej 3, 2200 Copenhagen, Denmark
| | - Martin Nors Pedersen
- ESRF—The European Synchrotron, 71 Avenue des Martyrs, CS40220, 38043 Grenoble, Cedex 9, France
| | - Matteo Levantino
- ESRF—The European Synchrotron, 71 Avenue des Martyrs, CS40220, 38043 Grenoble, Cedex 9, France
| | - Michael Wulff
- ESRF—The European Synchrotron, 71 Avenue des Martyrs, CS40220, 38043 Grenoble, Cedex 9, France
| | - Magnus Wolf-Watz
- Department of Chemistry, Umeå University, Linnaeus Väg 10, 901 87 Umeå, Sweden
| | - Magnus Andersson
- Department of Chemistry, Umeå University, Linnaeus Väg 10, 901 87 Umeå, Sweden
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15
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Ojeda-May P, Mushtaq AU, Rogne P, Verma A, Ovchinnikov V, Grundström C, Dulko-Smith B, Sauer UH, Wolf-Watz M, Nam K. Dynamic Connection between Enzymatic Catalysis and Collective Protein Motions. Biochemistry 2021; 60:2246-2258. [PMID: 34250801 PMCID: PMC8297476 DOI: 10.1021/acs.biochem.1c00221] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
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Enzymes employ a wide range of protein motions to achieve efficient catalysis of
chemical reactions. While the role of collective protein motions in substrate binding,
product release, and regulation of enzymatic activity is generally understood, their
roles in catalytic steps per se remain uncertain. Here, molecular dynamics simulations,
enzyme kinetics, X-ray crystallography, and nuclear magnetic resonance spectroscopy are
combined to elucidate the catalytic mechanism of adenylate kinase and to delineate the
roles of catalytic residues in catalysis and the conformational change in the enzyme.
This study reveals that the motions in the active site, which occur on a time scale of
picoseconds to nanoseconds, link the catalytic reaction to the slow conformational
dynamics of the enzyme by modulating the free energy landscapes of subdomain motions. In
particular, substantial conformational rearrangement occurs in the active site following
the catalytic reaction. This rearrangement not only affects the reaction barrier but
also promotes a more open conformation of the enzyme after the reaction, which then
results in an accelerated opening of the enzyme compared to that of the reactant state.
The results illustrate a linkage between enzymatic catalysis and collective protein
motions, whereby the disparate time scales between the two processes are bridged by a
cascade of intermediate-scale motion of catalytic residues modulating the free energy
landscapes of the catalytic and conformational change processes.
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Affiliation(s)
- Pedro Ojeda-May
- Department of Chemistry, Umeå University, Umeå SE-90187, Sweden.,High Performance Computing Centre North (HPC2N), Umeå University, Umeå SE-90187, Sweden
| | | | - Per Rogne
- Department of Chemistry, Umeå University, Umeå SE-90187, Sweden
| | - Apoorv Verma
- Department of Chemistry, Umeå University, Umeå SE-90187, Sweden
| | - Victor Ovchinnikov
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | | | - Beata Dulko-Smith
- Department of Chemistry and Biochemistry, University of Texas at Arlington, Arlington, Texas 76019, United States
| | - Uwe H Sauer
- Department of Chemistry, Umeå University, Umeå SE-90187, Sweden
| | | | - Kwangho Nam
- Department of Chemistry and Biochemistry, University of Texas at Arlington, Arlington, Texas 76019, United States
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16
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Shinobu A, Kobayashi C, Matsunaga Y, Sugita Y. Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins. J Chem Inf Model 2021; 61:2427-2443. [PMID: 33956432 DOI: 10.1021/acs.jcim.1c00286] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Large-scale conformational transitions in multi-domain proteins are often essential for their functions. To investigate the transitions, it is necessary to explore multiple potential pathways, which involve different intermediate structures. Here, we present a multi-basin (MB) coarse-grained (CG) structure-based Go̅ model for describing transitions in proteins with more than two moving domains. This model is an extension of our dual-basin Go̅ model in which system-dependent parameters are determined systematically using the multistate Bennett acceptance ratio method. In the MB Go̅ model for multi-domain proteins, we assume that intermediate structures may have partial inter-domain native contacts. This approach allows us to search multiple transition pathways that involve distinct intermediate structures using the CG molecular dynamics (MD) simulations. We apply this scheme to an enzyme, adenylate kinase (AdK), which has three major domains and can move along two different pathways. Using the optimized mixing parameters for each pathway, AdK shows frequent transitions between the Open, Closed, and the intermediate basins and samples a wide variety of conformations within each basin. The explored multiple transition pathways could be compared with experimental data and examined in more detail by atomistic MD simulations.
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Affiliation(s)
- Ai Shinobu
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
| | - Chigusa Kobayashi
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yasuhiro Matsunaga
- Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan
| | - Yuji Sugita
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan.,Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan.,Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
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17
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Girodat D, Pati AK, Terry DS, Blanchard SC, Sanbonmatsu KY. Quantitative comparison between sub-millisecond time resolution single-molecule FRET measurements and 10-second molecular simulations of a biosensor protein. PLoS Comput Biol 2020; 16:e1008293. [PMID: 33151943 PMCID: PMC7643941 DOI: 10.1371/journal.pcbi.1008293] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 08/27/2020] [Indexed: 12/15/2022] Open
Abstract
Molecular Dynamics (MD) simulations seek to provide atomic-level insights into conformationally dynamic biological systems at experimentally relevant time resolutions, such as those afforded by single-molecule fluorescence measurements. However, limitations in the time scales of MD simulations and the time resolution of single-molecule measurements have challenged efforts to obtain overlapping temporal regimes required for close quantitative comparisons. Achieving such overlap has the potential to provide novel theories, hypotheses, and interpretations that can inform idealized experimental designs that maximize the detection of the desired reaction coordinate. Here, we report MD simulations at time scales overlapping with in vitro single-molecule Förster (fluorescence) resonance energy transfer (smFRET) measurements of the amino acid binding protein LIV-BPSS at sub-millisecond resolution. Computationally efficient all-atom structure-based simulations, calibrated against explicit solvent simulations, were employed for sampling multiple cycles of LIV-BPSS clamshell-like conformational changes on the time scale of seconds, examining the relationship between these events and those observed by smFRET. The MD simulations agree with the smFRET measurements and provide valuable information on local dynamics of fluorophores at their sites of attachment on LIV-BPSS and the correlations between fluorophore motions and large-scale conformational changes between LIV-BPSS domains. We further utilize the MD simulations to inform the interpretation of smFRET data, including Förster radius (R0) and fluorophore orientation factor (κ2) determinations. The approach we describe can be readily extended to distinct biochemical systems, allowing for the interpretation of any FRET system conjugated to protein or ribonucleoprotein complexes, including those with more conformational processes, as well as those implementing multi-color smFRET. Förster (fluorescence) resonance energy transfer (FRET) has been used extensively by biophysicists as a molecular-scale ruler that yields fundamental structural and kinetic insights into transient processes including complex formation and conformational rearrangements required for biological function. FRET techniques require the identification of informative fluorophore labeling sites, spaced at defined distances to inform on a reaction coordinate of interest and consideration of noise sources that have the potential to obscure quantitative interpretations. Here, we describe an approach to leverage advancements in computationally efficient all-atom structure-based molecular dynamics simulations in which structural dynamics observed via FRET can be interpreted in full atomistic detail on commensurate time scales. We demonstrate the potential of this approach using a model FRET system, the amino acid binding protein LIV-BPSS conjugated to self-healing organic fluorophores. LIV-BPSS exhibits large scale, sub-millisecond clamshell-like conformational changes between open and closed conformations associated with ligand unbinding and binding, respectively. Our findings inform on the molecular basis of the dynamics observed by smFRET and on strategies to optimize fluorophore labeling sites, the manner of fluorophore attachment, and fluorophore composition.
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Affiliation(s)
- Dylan Girodat
- Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Avik K Pati
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee, United States of America
| | - Daniel S Terry
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee, United States of America
| | - Scott C Blanchard
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee, United States of America
| | - Karissa Y Sanbonmatsu
- Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.,New Mexico Consortium, Los Alamos, New Mexico, United States of America
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18
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Zhang Y, Cao Z, Zhang JZ, Xia F. Double-Well Ultra-Coarse-Grained Model to Describe Protein Conformational Transitions. J Chem Theory Comput 2020; 16:6678-6689. [PMID: 32926616 DOI: 10.1021/acs.jctc.0c00551] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The double-well model is usually used to describe the conformational transition between two states of a protein. Since conformational changes usually occur within a relatively large time scale, coarse-grained models are often used to accelerate the dynamic process due to their inexpensive computational cost. In this work, we develop a double-well ultra-coarse-grained (DW-UCG) model to describe the conformational transitions of the adenylate kinase, glutamine-binding protein, and lactoferrin. The coarse-grained simulation results show that the DW-UCG model of adenylate kinase captures the crucial intermediate states in the LID-closing and NMP-closing pathways, reflecting the key secondary structural changes in the conformational transition. A comparison of the different DW-UCG models of adenylate kinase indicates that an appropriate choice of bead resolution could generate the free energy landscape that is comparable to that from the residue-based model. The coarse-grained simulations for the glutamine-binding protein and lactoferrin also demonstrate that the DW-UCG model is valid in reproducing the correct two-state behavior for their functional study, which indicates the potential application of the DW-UCG model in investigating the mechanism of conformational changes of large proteins.
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Affiliation(s)
- Yuwei Zhang
- State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemistry Engineering, Xiamen University, Xiamen 361005, China.,School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
| | - Zexing Cao
- State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemistry Engineering, Xiamen University, Xiamen 361005, China
| | - John Zenghui Zhang
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.,Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - Fei Xia
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.,Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
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19
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Yuan Y, Zhu Q, Song R, Ma J, Dong H. A Two-Ended Data-Driven Accelerated Sampling Method for Exploring the Transition Pathways between Two Known States of Protein. J Chem Theory Comput 2020; 16:4631-4640. [PMID: 32320614 DOI: 10.1021/acs.jctc.9b01184] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Conformational transitions of protein between different states are often associated with their biological functions. These dynamic processes, however, are usually not easy to be well characterized by experimental measurements, mainly because of inadequate temporal and spatial resolution. Meantime, sampling of configuration space with molecular dynamics (MD) simulations is still a challenge. Here we proposed a robust two-ended data-driven accelerated (teDA2) conformational sampling method, which drives the structural change in an adaptively updated feature space without introducing a bias potential. teDA2 was applied to explore adenylate kinase (ADK), a model with well characterized "open" and "closed" states. A single conformational transition event of ADK could be achieved within only a few or tens of nanoseconds sampled with teDA2. By analyzing hundreds of transition events, we reproduced different mechanisms and the associated pathways for domain motion of ADK reported in the literature. The multiroute characteristic of ADK was confirmed by the fact that some metastable states identified with teDA2 resemble available crystal structures determined at different conditions. This feature was further validated with Markov state modeling with independent MD simulations. Therefore, our work provides strong evidence for the conformational plasticity of protein, which is mainly due to the inherent degree of flexibility. As a reliable and efficient enhanced sampling protocol, teDA2 could be used to study the dynamics between functional states of various biomolecular machines.
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Affiliation(s)
- Yigao Yuan
- Kuang Yaming Honors School, Nanjing University, 210023 Nanjing, China
| | - Qiang Zhu
- Kuang Yaming Honors School, Nanjing University, 210023 Nanjing, China.,Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, 210023 Nanjing China
| | - Ruiheng Song
- Kuang Yaming Honors School, Nanjing University, 210023 Nanjing, China
| | - Jing Ma
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, 210023 Nanjing China
| | - Hao Dong
- Kuang Yaming Honors School, Nanjing University, 210023 Nanjing, China.,Institute for Brain Sciences, Nanjing University, Nanjing 210023, China
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20
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Li D, Ji B. Protein conformational transitions coupling with ligand interactions: Simulations from molecules to medicine. MEDICINE IN NOVEL TECHNOLOGY AND DEVICES 2019. [DOI: 10.1016/j.medntd.2019.100026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
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21
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Thirumalai D, Hyeon C, Zhuravlev PI, Lorimer GH. Symmetry, Rigidity, and Allosteric Signaling: From Monomeric Proteins to Molecular Machines. Chem Rev 2019; 119:6788-6821. [DOI: 10.1021/acs.chemrev.8b00760] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- D. Thirumalai
- Department of Chemistry, The University of Texas, Austin, Texas 78712, United States
| | - Changbong Hyeon
- Korea Institute for Advanced Study, Seoul 02455, Republic of Korea
| | - Pavel I. Zhuravlev
- Biophysics Program, Institute for Physical Science and Technology and Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland 20742, United States
| | - George H. Lorimer
- Biophysics Program, Institute for Physical Science and Technology and Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland 20742, United States
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22
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Roston D, Lu X, Fang D, Demapan D, Cui Q. Analysis of Phosphoryl-Transfer Enzymes with QM/MM Free Energy Simulations. Methods Enzymol 2018; 607:53-90. [PMID: 30149869 DOI: 10.1016/bs.mie.2018.05.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
We discuss the application of quantum mechanics/molecular mechanics (QM/MM) free energy simulations to the analysis of phosphoryl transfers catalyzed by two enzymes: alkaline phosphatase and myosin. We focus on the nature of the transition state and the issue of mechanochemical coupling, respectively, in the two enzymes. The results illustrate unique insights that emerged from the QM/MM simulations, especially concerning the interpretation of experimental data regarding the nature of enzymatic transition states and coupling between global structural transition and catalysis in the active site. We also highlight a number of technical issues worthy of attention when applying QM/MM free energy simulations, and comment on a number of technical and mechanistic issues that require further studies.
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Affiliation(s)
- Daniel Roston
- Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin, Madison, Madison, WI, United States
| | - Xiya Lu
- Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin, Madison, Madison, WI, United States
| | - Dong Fang
- Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin, Madison, Madison, WI, United States
| | - Darren Demapan
- Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin, Madison, Madison, WI, United States
| | - Qiang Cui
- Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin, Madison, Madison, WI, United States.
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