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Tu G, Gong Y, Yao X, Liu Q, Xue W, Zhang R. Pathways and mechanism of MRTX1133 binding to KRAS G12D elucidated by molecular dynamics simulations and Markov state models. Int J Biol Macromol 2024; 274:133374. [PMID: 38925182 DOI: 10.1016/j.ijbiomac.2024.133374] [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: 04/12/2024] [Revised: 06/19/2024] [Accepted: 06/21/2024] [Indexed: 06/28/2024]
Abstract
KRAS G12D is the most common oncogenic mutation identified in several types of cancer. Therefore, design of inhibitors targeting KRAS G12D represents a promising strategy for anticancer therapy. MRTX1133 is a highly potent inhibitor (approximate experiment Kd ≈ 0.0002 nM) of KRAS G12D and is currently in Phase 1/2 study, however, pathways of the compound binding to KRAS G12D has remained unknown, and the mechanism underlying the complicated dynamic process are challenging to capture experimentally, which hinder the structure-based anti-cancer drug design. Here, using MRTX1133 as a probe, unbiased molecular dynamics (MD) was used to simulate the process of MRTX1133 spontaneously binding to KRAS G12D. In six of 42 independent MD simulation (a total of 99 μs), MRTX1133 was observed to successfully associate with KRAS G12D. The kinetically metastable states refer to the potential pathways of MRTX1133 binding to KRAS G12D were revealed by Markov state models (MSM) analysis. Additionally, 8 key residues that are essential for MRTX1133 recognition and tight binding at the preferred low energy states were identified by MM/GBSA analysis. In sum, this study provides a new perspective on understanding the pathways and mechanism of MRTX1133 binding to KRAS G12D.
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Affiliation(s)
- Gao Tu
- Department of Pharmacy, The Second Affiliated Hospital, Army Medical University, 183 Xinqiao Road, Chongqing 400037, China; Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, 999078, Macau
| | - Yaguo Gong
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, 999078, Macau
| | - Xiaojun Yao
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, 999078, Macau.
| | - Qing Liu
- Suzhou Institute for Advance Research, University of Science and Technology of China, Suzhou, China
| | - Weiwei Xue
- School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China.
| | - Rong Zhang
- Department of Pharmacy, The Second Affiliated Hospital, Army Medical University, 183 Xinqiao Road, Chongqing 400037, China.
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Gao B, Wang Z, Dai K, Wang Y, Li L, Li G, Niu X, Li X, Yu Z, Wang Z, Chen G. Acetylation of mtHSP70 at Lys595/653 affecting its interaction between GrpEL1 regulates glioblastoma progression via UPRmt. Free Radic Biol Med 2024; 213:394-408. [PMID: 38281626 DOI: 10.1016/j.freeradbiomed.2024.01.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 01/01/2024] [Accepted: 01/21/2024] [Indexed: 01/30/2024]
Abstract
BACKGROUND The mitochondrial unfolded protein response (UPRmt) is a vital biological process that regulates mitochondrial protein homeostasis and enables glioblastoma cells to cope with mitochondrial oxidative stress in the tumor microenvironment. We previously reported that the binding of mitochondrial stress-70 protein (mtHSP70) to GrpE protein homolog 1 (GrpEL1) is involved in the regulation of the UPRmt. However, the mechanisms regulating their binding remain unclear. Herein, we examined the UPRmt in glioblastoma and explored whether modulating the interaction between mtHSP70 and GrpEL1 affects the UPRmt. METHODS Western blot analysis, aggresome staining, and transmission electron microscopy were used to detect the activation of the UPRmt and protein aggregates within mitochondria. Molecular dynamics simulations were performed to investigate the impact of different mutations in mtHSP70 on its binding to GrpEL1. Endogenous site-specific mutations were introduced into mtHSP70 in glioblastoma cells using CRISPR/Cas9. In vitro and in vivo experiments were conducted to assess mitochondrial function and glioblastoma progression. RESULTS The UPRmt was activated in glioblastoma cells in response to oxidative stress. mtHSP70 regulated mitochondrial protein homeostasis by facilitating UPRmt-progress protein import into the mitochondria. Acetylation of mtHSP70 at Lys595/653 enhanced its binding to GrpEL1. Missense mutations at Lys595/653 increased mitochondrial protein aggregates and inhibited glioblastoma progression in vitro and in vivo. CONCLUSIONS We identified an innovative mechanism in glioblastoma progression by which acetylation of mtHSP70 at Lys595/653 influences its interaction with GrpEL1 to regulate the UPRmt. Mutations at Lys595/653 in mtHSP70 could potentially serve as therapeutic targets and prognostic indicators of glioblastoma.
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Affiliation(s)
- Bixi Gao
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China
| | - Zongqi Wang
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China
| | - Kun Dai
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China
| | - Yunjiang Wang
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China; Department of Neurosurgery, Yancheng Third People's Hospital, Yancheng, 224000, China
| | - Longyuan Li
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China
| | - Guangzhao Li
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China; Department of Neurosurgery, Hefei First People's Hospital, Hefei, 230031, China
| | - Xiaowang Niu
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China; Department of Neurosurgery, The Affiliated Suqian Hospital of Xuzhou Medical University, Suqian, 223800, China
| | - Xiang Li
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China; Department of Neurosurgery, Xinghua People's Hospital, Xinghua, 225700, China
| | - Zhengquan Yu
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China
| | - Zhong Wang
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China.
| | - Gang Chen
- Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, 215006, China; Institute of Stroke Research, Soochow University, Suzhou, 215006, China
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Wang H, Zhu X, Zhao Y, Zang Y, Zhang J, Kang Y, Yang Z, Lin P, Zhang L, Zhang S. Markov State Models Underlying the N-Terminal Premodel of TOPK/PBK. J Phys Chem B 2022; 126:10662-10671. [PMID: 36512332 DOI: 10.1021/acs.jpcb.2c06559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Lymphokine-activated killer T-cell-originated protein kinase (TOPK) is a potential target for cancer therapy. To explore the micromechanism, we proposed the N-terminal premodel (NTPM) of the TOPK monomer via homology modeling and molecular dynamic simulations and analyzed the conformational dynamics by Markov state model analysis. The electronegative insert (ENI) motif of the NTPM can be opened with a small probability under wild type, regulated by the so-called "N-C" interaction zone consisting of the N-terminal head, the coil between β3-strand and αC-helix, and the ENI motif. Glutamate substitution at threonine residue 9 or tyrosine residue 74 promotes the closed-open transition, revealing the details of phosphorylation. Allosteric effects induce functionally relevant structural changes, such as increased structural flexibility and active sites, which are thought to be necessary for further activation or binding. These findings provide rational structural templates for designing state-dependent inhibitors and give insight into the molecular regulatory mechanisms of TOPK monomers.
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Affiliation(s)
- He Wang
- MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an710049, China
| | - Xun Zhu
- MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an710049, China
| | - Yizhen Zhao
- MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an710049, China
| | - Yongjian Zang
- MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an710049, China
| | - Jianwen Zhang
- MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an710049, China
| | - Ying Kang
- MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an710049, China
| | - Zhiwei Yang
- MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an710049, China
| | - Peng Lin
- National Translational Science Center for Molecular Medicine & Department of Cell Biology, Fourth Military Medical University, Xi'an710032, China
| | - Lei Zhang
- MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an710049, China
| | - Shengli Zhang
- MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an710049, China
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Pomarici ND, Fernández-Quintero ML, Quoika PK, Waibl F, Bujotzek A, Georges G, Liedl KR. Bispecific antibodies-effects of point mutations on CH3-CH3 interface stability. Protein Eng Des Sel 2022; 35:6873150. [PMID: 36468666 PMCID: PMC9741699 DOI: 10.1093/protein/gzac012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 10/19/2022] [Accepted: 10/19/2022] [Indexed: 12/12/2022] Open
Abstract
A new format of therapeutic proteins is bispecific antibodies, in which two different heavy chains heterodimerize to obtain two different binding sites. Therefore, it is crucial to understand and optimize the third constant domain (CH3-CH3) interface to favor heterodimerization over homodimerization, and to preserve the physicochemical properties, as thermal stability. Here, we use molecular dynamics simulations to investigate the dissociation process of 19 CH3-CH3 crystal structures that differ from each other in few point mutations. We describe the dissociation of the dimeric interface as a two-steps mechanism. As confirmed by a Markov state model, apart from the bound and the dissociated state, we observe an additional intermediate state, which corresponds to an encounter complex. The analysis of the interdomain contacts reveals key residues that stabilize the interface. We expect that our results will improve the understanding of the CH3-CH3 interface interactions and thus advance the developability and design of new antibodies formats.
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Affiliation(s)
- Nancy D Pomarici
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, A-6020 Innsbruck, Austria
| | - Monica L Fernández-Quintero
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, A-6020 Innsbruck, Austria
| | - Patrick K Quoika
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, A-6020 Innsbruck, Austria,Center for Protein Assemblies (CPA), Department of Physics, Chair of Theoretical Biophysics, Technical University of Munich, Ernst-Otto-Fischer-Str. 8, 85748, Garching, Germany
| | - Franz Waibl
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, A-6020 Innsbruck, Austria
| | - Alexander Bujotzek
- Roche Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Penzberg, Nonnenwald 2, Penzberg, 82377, Germany
| | - Guy Georges
- Roche Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Penzberg, Nonnenwald 2, Penzberg, 82377, Germany
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5
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Deciphering the Effect of Lysine Acetylation on the Misfolding and Aggregation of Human Tau Fragment 171IPAKTPPAPK 180 Using Molecular Dynamic Simulation and the Markov State Model. Int J Mol Sci 2022; 23:ijms23052399. [PMID: 35269542 PMCID: PMC8910285 DOI: 10.3390/ijms23052399] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 01/25/2022] [Accepted: 01/26/2022] [Indexed: 02/04/2023] Open
Abstract
The formation of neurofibrillary tangles (NFT) with β-sheet-rich structure caused by abnormal aggregation of misfolded microtubule-associated protein Tau is a hallmark of tauopathies, including Alzheimer’s Disease. It has been reported that acetylation, especially K174 located in the proline-rich region, can largely promote Tau aggregation. So far, the mechanism of the abnormal acetylation of Tau that affects its misfolding and aggregation is still unclear. Therefore, revealing the effect of acetylation on Tau aggregation could help elucidate the pathogenic mechanism of tauopathies. In this study, molecular dynamics simulation combined with multiple computational analytical methods were performed to reveal the effect of K174 acetylation on the spontaneous aggregation of Tau peptide 171IPAKTPPAPK180, and the dimerization mechanism as an early stage of the spontaneous aggregation was further specifically analyzed by Markov state model (MSM) analysis. The results showed that both the actual acetylation and the mutation mimicking the acetylated state at K174 induced the aggregation of the studied Tau fragment; however, the effect of actual acetylation on the aggregation was more pronounced. In addition, acetylated K174 plays a major contributing role in forming and stabilizing the antiparallel β-sheet dimer by forming several hydrogen bonds and side chain van der Waals interactions with residues I171, P172, A173 and T175 of the corresponding chain. In brief, this study uncovered the underlying mechanism of Tau peptide aggregation in response to the lysine K174 acetylation, which can deepen our understanding on the pathogenesis of tauopathies.
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6
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Jing Y, Cheng Y, Li F, Li Y, Liu F, Zhang J. Linkage of nanosecond protein motion with enzymatic methyl transfer by nicotinamide N-methyltransferase. Turk J Biol 2021; 45:333-341. [PMID: 34377057 PMCID: PMC8313939 DOI: 10.3906/biy-2101-54] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 05/19/2021] [Indexed: 11/17/2022] Open
Abstract
Nicotinamide N-methyltransferase (NNMT), a key cytoplasmic protein in the human body, is accountable to catalyze the nicotinamide (NCA) N1-methylation through S-adenosyl-L-methionine (SAM) as a methyl donor, which has been linked to many diseases. Although extensive studies have concerned about the biological aspect, the detailed mechanism study of the enzyme function, especially in the part of protein dynamics is lacking. Here, wild-type nicotinamide N-methyltransferase together with the mutation at position 20 with Y20F, Y20G, and free tryptophan were carried out to explore the connection between protein dynamics and catalysis using time-resolved fluorescence lifetimes. The results show that wild-type nicotinamide N-methyltransferase prefers to adapt a less flexible protein conformation to achieve enzyme catalysis.
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Affiliation(s)
- Yahui Jing
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin China
| | - Yiting Cheng
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin China
| | - Fangya Li
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin China
| | - Yuping Li
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin China.,Binzhou Institute for Food and Drug Control, Binzhou, Shandong China
| | - Fan Liu
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin China
| | - Jianyu Zhang
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin China
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7
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Liu H, Zhong H, Liu X, Zhou S, Tan S, Liu H, Yao X. Disclosing the Mechanism of Spontaneous Aggregation and Template-Induced Misfolding of the Key Hexapeptide (PHF6) of Tau Protein Based on Molecular Dynamics Simulation. ACS Chem Neurosci 2019; 10:4810-4823. [PMID: 31661961 DOI: 10.1021/acschemneuro.9b00488] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The microtubule-associated protein tau is critical for the development and maintenance of the nervous system. Tau dysfunction is associated with a variety of neurodegenerative diseases called tauopathies, which are characterized by neurofibrillary tangles formed by abnormally aggregated tau protein. Studying the aggregation mechanism of tau protein is of great significance for elucidating the etiology of tauopathies. The hexapeptide 306VQIVYK311 (PHF6) of R3 has been shown to play a vital role in promoting tau aggregation. In this study, long-term all-atom molecular dynamics simulations in explicit solvent were performed to investigate the mechanisms of spontaneous aggregation and template-induced misfolding of PHF6, and the dimerization at the early stage of nucleation was further specifically analyzed by the Markov state model (MSM). Our results show that PHF6 can spontaneously aggregate to form multimers enriched with β-sheet structure and the β-sheets in multimers prefer to exist in a parallel way. It is observed that PHF6 monomer can be induced to form a β-sheet structure on either side of the template but in a different way. In detail, the β-sheet structure is easier to form on the left side but does not extend well, but on the right side, the monomer can form the extended β-sheet structure. Furthermore, MSM analysis shows that the formation of dimer mainly occurs in three steps. First, the separated monomers collide with each other at random orientations, and then a dimer with short β-sheet structure at the N-terminal forms; finally, β-sheets elongate to form an extended parallel β-sheet dimer. During these processes, multiple intermediate states are identified and multiple paths can form a parallel β-sheet dimer from the disordered coil structure. Moreover, the residues I308, V309, and Y310 play an essential role in the dimerization. In a word, our results uncover the aggregation and misfolding mechanism of PHF6 from the atomic level, which can provide useful theoretical guidance for rational design of effective therapeutic drugs against tauopathies.
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Affiliation(s)
| | | | | | - Shuangyan Zhou
- Chongqing Key Laboratory on Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | | | | | - Xiaojun Yao
- State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau 999078, China
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8
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Bernetti M, Masetti M, Recanatini M, Amaro RE, Cavalli A. An Integrated Markov State Model and Path Metadynamics Approach To Characterize Drug Binding Processes. J Chem Theory Comput 2019; 15:5689-5702. [DOI: 10.1021/acs.jctc.9b00450] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- Mattia Bernetti
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum, Università di Bologna, Via Belmeloro 6, I-40126 Bologna, Italy
| | - Matteo Masetti
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum, Università di Bologna, Via Belmeloro 6, I-40126 Bologna, Italy
| | - Maurizio Recanatini
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum, Università di Bologna, Via Belmeloro 6, I-40126 Bologna, Italy
| | - Rommie E. Amaro
- Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093-0340, United States
| | - Andrea Cavalli
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum, Università di Bologna, Via Belmeloro 6, I-40126 Bologna, Italy
- Computational & Chemical Biology, Istituto Italiano di Tecnologia, Via Morego 30, I-16163 Genova, Italy
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9
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Zhang H, Gong Q, Zhang H, Chen C. Combining the biased and unbiased sampling strategy into one convenient free energy calculation method. J Comput Chem 2019; 40:1806-1815. [PMID: 30942500 DOI: 10.1002/jcc.25834] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 03/15/2019] [Accepted: 03/17/2019] [Indexed: 12/14/2022]
Abstract
Constructing a free energy landscape for a large molecule is difficult. One has to use either a high temperature or a strong driving force to enhance the sampling on the free energy barriers. In this work, we propose a mixed method that combines these two kinds of acceleration strategies into one simulation. First, it applies an adaptive biasing potential to some replicas of the molecule. These replicas are particularly accelerated in a collective variable space. Second, it places some unbiased and exchangeable replicas at various temperature levels. These replicas generate unbiased sampling data in the canonical ensemble. To improve the sampling efficiency, biased replicas transfer their state variables to the unbiased replicas after equilibrium by Monte Carlo trial moves. In comparison to previous integrated methods, it is more convenient for users. It does not need an initial reference biasing potential to guide the sampling of the molecule. And it is also unnecessary to insert many replicas for the requirement of passing the free energy barriers. The free energy calculation is accomplished in a single stage. It samples the data as fast as a biased simulation and it processes the data as simple as an unbiased simulation. The method provides a minimalist approach to the construction of the free energy landscape. © 2019 Wiley Periodicals, Inc.
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Affiliation(s)
- Haomiao Zhang
- Biomolecular Physics and Modeling Group, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Qiankun Gong
- Biomolecular Physics and Modeling Group, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Haozhe Zhang
- Biomolecular Physics and Modeling Group, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Changjun Chen
- Biomolecular Physics and Modeling Group, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
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10
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Ahalawat N, Mondal J. Mapping the Substrate Recognition Pathway in Cytochrome P450. J Am Chem Soc 2018; 140:17743-17752. [PMID: 30479124 DOI: 10.1021/jacs.8b10840] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Cytochrome P450s are ubiquitous metalloenzymes involved in the metabolism and detoxification of foreign components via catalysis of the hydroxylation reactions of a vast array of organic substrates. However, the mechanism underlying the pharmaceutically critical process of substrate access to the catalytic center of cytochrome P450 is a long-standing puzzle, further complicated by the crystallographic evidence of a closed catalytic center in both substrate-free and substrate-bound cytochrome P450. Here, we address a crucial question whether the conformational heterogeneity prevalent in cytochrome P450 translates to heterogeneous pathways for substrate access to the catalytic center of these metalloenzymes. By atomistically capturing the full process of spontaneous substrate association from bulk solvent to the occluded catalytic center of an archetypal system P450cam in multi-microsecond-long continuous unbiased molecular dynamics simulations, we here demonstrate that the substrate recognition in P450cam always occurs through a single well-defined dominant pathway. The simulated final bound pose resulting from these unguided simulations is in striking resemblance with the crystallographic bound pose. Each individual binding trajectory reveals that the substrate, initially placed at random locations in bulk solvent, spontaneously lands on a single key channel on the protein-surface of P450cam and resides there for an uncharacteristically long period, before correctly identifying the occluded target-binding cavity. Surprisingly, the passage of substrate to the closed catalytic center is not accompanied by any large-scale opening in protein. Rather, the unbiased simulated trajectories (∼57 μs) and underlying Markov state model, in combination with free-energy analysis, unequivocally show that the substrate recognition process in P450cam needs a substrate-induced side-chain displacement coupled with a complex array of dynamical interconversions of multiple metastable substrate conformations. Further, the work reconciles multiple precedent experimental and theoretical observations on P450cam and establishes a comprehensive view of substrate-recognition in cytochrome P450 that only occurs via substrate-induced structural rearrangements.
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Affiliation(s)
- Navjeet Ahalawat
- Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences , Hyderabad 500107 , India
| | - Jagannath Mondal
- Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences , Hyderabad 500107 , India
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11
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Wang W, Liang T, Sheong FK, Fan X, Huang X. An efficient Bayesian kinetic lumping algorithm to identify metastable conformational states via Gibbs sampling. J Chem Phys 2018; 149:072337. [PMID: 30134698 DOI: 10.1063/1.5027001] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
Markov State Model (MSM) has become a popular approach to study the conformational dynamics of complex biological systems in recent years. Built upon a large number of short molecular dynamics simulation trajectories, MSM is able to predict the long time scale dynamics of complex systems. However, to achieve Markovianity, an MSM often contains hundreds or thousands of states (microstates), hindering human interpretation of the underlying system mechanism. One way to reduce the number of states is to lump kinetically similar states together and thus coarse-grain the microstates into macrostates. In this work, we introduce a probabilistic lumping algorithm, the Gibbs lumping algorithm, to assign a probability to any given kinetic lumping using the Bayesian inference. In our algorithm, the transitions among kinetically distinct macrostates are modeled by Poisson processes, which will well reflect the separation of time scales in the underlying free energy landscape of biomolecules. Furthermore, to facilitate the search for the optimal kinetic lumping (i.e., the lumped model with the highest probability), a Gibbs sampling algorithm is introduced. To demonstrate the power of our new method, we apply it to three systems: a 2D potential, alanine dipeptide, and a WW protein domain. In comparison with six other popular lumping algorithms, we show that our method can persistently produce the lumped macrostate model with the highest probability as well as the largest metastability. We anticipate that our Gibbs lumping algorithm holds great promise to be widely applied to investigate conformational changes in biological macromolecules.
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Affiliation(s)
- Wei Wang
- HKUST-Shenzhen Research Institute, Hi-Tech Park, Nanshan, Shenzhen 518057, China
| | - Tong Liang
- Department of Statistics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong
| | - Fu Kit Sheong
- Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Xiaodan Fan
- Department of Statistics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong
| | - Xuhui Huang
- HKUST-Shenzhen Research Institute, Hi-Tech Park, Nanshan, Shenzhen 518057, China
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Krüger A, Zimbres FM, Kronenberger T, Wrenger C. Molecular Modeling Applied to Nucleic Acid-Based Molecule Development. Biomolecules 2018; 8:E83. [PMID: 30150587 PMCID: PMC6163985 DOI: 10.3390/biom8030083] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 08/12/2018] [Accepted: 08/16/2018] [Indexed: 12/15/2022] Open
Abstract
Molecular modeling by means of docking and molecular dynamics (MD) has become an integral part of early drug discovery projects, enabling the screening and enrichment of large libraries of small molecules. In the past decades, special emphasis was drawn to nucleic acid (NA)-based molecules in the fields of therapy, diagnosis, and drug delivery. Research has increased dramatically with the advent of the SELEX (systematic evolution of ligands by exponential enrichment) technique, which results in single-stranded DNA or RNA sequences that bind with high affinity and specificity to their targets. Herein, we discuss the role and contribution of docking and MD to the development and optimization of new nucleic acid-based molecules. This review focuses on the different approaches currently available for molecular modeling applied to NA interaction with proteins. We discuss topics ranging from structure prediction to docking and MD, highlighting their main advantages and limitations and the influence of flexibility on their calculations.
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Affiliation(s)
- Arne Krüger
- Unit for Drug Discovery, Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP 05508-000, Brazil.
| | - Flávia M Zimbres
- Department of Biochemistry and Molecular Biology and Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA.
| | - Thales Kronenberger
- Department of Internal Medicine VIII, University Hospital of Tübingen, 72076 Tübingen, Germany.
| | - Carsten Wrenger
- Unit for Drug Discovery, Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP 05508-000, Brazil.
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13
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Perricone U, Gulotta MR, Lombino J, Parrino B, Cascioferro S, Diana P, Cirrincione G, Padova A. An overview of recent molecular dynamics applications as medicinal chemistry tools for the undruggable site challenge. MEDCHEMCOMM 2018; 9:920-936. [PMID: 30108981 PMCID: PMC6072422 DOI: 10.1039/c8md00166a] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Accepted: 04/19/2018] [Indexed: 12/14/2022]
Abstract
Molecular dynamics (MD) has become increasingly popular due to the development of hardware and software solutions and the improvement in algorithms, which allowed researchers to scale up calculations in order to speed them up. MD simulations are usually used to address protein folding issues or protein-ligand complex stability through energy profile analysis over time. In recent years, the development of new tools able to deeply explore a potential energy surface (PES) has allowed researchers to focus on the dynamic nature of the binding recognition process and binding-induced protein conformational changes. Moreover, modern approaches have been demonstrated to be effective and reliable in calculating some kinetic and thermodynamic parameters behind the host-guest recognition process. Starting from all of these considerations, several efforts have been made in order to integrate MD within the virtual screening process in drug discovery. Knowledge retrieved from MD can, in fact, be exploited as a starting point to build pharmacophores or docking constraints in the early stage of the screening campaign as well as to define key features, in order to unravel hidden binding modes and help the optimisation of the molecular structure of a lead compound. Based on these outcomes, researchers are nowadays using MD as an invaluable tool to discover and target previously considered undruggable binding sites, including protein-protein interactions and allosteric sites on a protein surface. As a matter of fact, the use of MD has been recognised as vital to the discovery of selective protein-protein interaction modulators. The use of a dynamic overview on how the host-guest recognition occurs and of the relative conformational modifications induced allows researchers to optimise small molecules and small peptides capable of tightly interacting within the cleft between two proteins. In this review, we aim to present the most recent applications of MD as an integrated tool to be used in the rational design of small molecules or small peptides able to modulate undruggable targets, such as allosteric sites and protein-protein interactions.
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Affiliation(s)
- Ugo Perricone
- Computational and Medicinal Chemistry Group , Fondazione Ri.MED , Via Bandiera 11 , 90133 Palermo , Italy .
| | - Maria Rita Gulotta
- Computational and Medicinal Chemistry Group , Fondazione Ri.MED , Via Bandiera 11 , 90133 Palermo , Italy .
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Jessica Lombino
- Computational and Medicinal Chemistry Group , Fondazione Ri.MED , Via Bandiera 11 , 90133 Palermo , Italy .
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Barbara Parrino
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Stella Cascioferro
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Patrizia Diana
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Girolamo Cirrincione
- Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF) , Università degli Studi di Palermo , Via Archirafi 32 , 90123 Palermo , Italy
| | - Alessandro Padova
- Computational and Medicinal Chemistry Group , Fondazione Ri.MED , Via Bandiera 11 , 90133 Palermo , Italy .
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14
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Mondal J, Ahalawat N, Pandit S, Kay LE, Vallurupalli P. Atomic resolution mechanism of ligand binding to a solvent inaccessible cavity in T4 lysozyme. PLoS Comput Biol 2018; 14:e1006180. [PMID: 29775455 PMCID: PMC5979041 DOI: 10.1371/journal.pcbi.1006180] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Revised: 05/31/2018] [Accepted: 05/06/2018] [Indexed: 12/22/2022] Open
Abstract
Ligand binding sites in proteins are often localized to deeply buried cavities, inaccessible to bulk solvent. Yet, in many cases binding of cognate ligands occurs rapidly. An intriguing system is presented by the L99A cavity mutant of T4 Lysozyme (T4L L99A) that rapidly binds benzene (~106 M-1s-1). Although the protein has long served as a model system for protein thermodynamics and crystal structures of both free and benzene-bound T4L L99A are available, the kinetic pathways by which benzene reaches its solvent-inaccessible binding cavity remain elusive. The current work, using extensive molecular dynamics simulation, achieves this by capturing the complete process of spontaneous recognition of benzene by T4L L99A at atomistic resolution. A series of multi-microsecond unbiased molecular dynamics simulation trajectories unequivocally reveal how benzene, starting in bulk solvent, diffuses to the protein and spontaneously reaches the solvent inaccessible cavity of T4L L99A. The simulated and high-resolution X-ray derived bound structures are in excellent agreement. A robust four-state Markov model, developed using cumulative 60 μs trajectories, identifies and quantifies multiple ligand binding pathways with low activation barriers. Interestingly, none of these identified binding pathways required large conformational changes for ligand access to the buried cavity. Rather, these involve transient but crucial opening of a channel to the cavity via subtle displacements in the positions of key helices (helix4/helix6, helix7/helix9) leading to rapid binding. Free energy simulations further elucidate that these channel-opening events would have been unfavorable in wild type T4L. Taken together and via integrating with results from experiments, these simulations provide unprecedented mechanistic insights into the complete ligand recognition process in a buried cavity. By illustrating the power of subtle helix movements in opening up multiple pathways for ligand access, this work offers an alternate view of ligand recognition in a solvent-inaccessible cavity, contrary to the common perception of a single dominant pathway for ligand binding.
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Affiliation(s)
| | | | | | - Lewis E. Kay
- Departments of Molecular Genetics, Biochemistry and Chemistry, University of Toronto, Toronto, Ontario, Canada
- Hospital for Sick Children Program in Molecular Medicine, Toronto, Ontario, Canada
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15
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Unarta IC, Zhu L, Tse CKM, Cheung PPH, Yu J, Huang X. Molecular mechanisms of RNA polymerase II transcription elongation elucidated by kinetic network models. Curr Opin Struct Biol 2018; 49:54-62. [PMID: 29414512 DOI: 10.1016/j.sbi.2018.01.002] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 12/22/2017] [Accepted: 01/02/2018] [Indexed: 12/30/2022]
Abstract
Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error.
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Affiliation(s)
- Ilona Christy Unarta
- Bioengineering Graduate Program, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & Reconstruction, Hong Kong
| | - Lizhe Zhu
- Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & Reconstruction, Hong Kong; Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Carmen Ka Man Tse
- Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & Reconstruction, Hong Kong; Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Peter Pak-Hang Cheung
- Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & Reconstruction, Hong Kong
| | - Jin Yu
- Beijing Computational Science Research Center, Beijing 100084, China
| | - Xuhui Huang
- Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & Reconstruction, Hong Kong; Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; HKUST-Shenzhen Research Institute, Hi-Tech Park, Nanshan, Shenzhen 518057, China.
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16
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Miranda WE, Ngo VA, Perissinotti LL, Noskov SY. Computational membrane biophysics: From ion channel interactions with drugs to cellular function. BIOCHIMICA ET BIOPHYSICA ACTA. PROTEINS AND PROTEOMICS 2017; 1865:1643-1653. [PMID: 28847523 PMCID: PMC5764198 DOI: 10.1016/j.bbapap.2017.08.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2017] [Revised: 08/16/2017] [Accepted: 08/16/2017] [Indexed: 12/16/2022]
Abstract
The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.
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Affiliation(s)
- Williams E Miranda
- Centre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Van A Ngo
- Centre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Laura L Perissinotti
- Centre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Sergei Yu Noskov
- Centre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada.
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17
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Wang W, Cao S, Zhu L, Huang X. Constructing Markov State Models to elucidate the functional conformational changes of complex biomolecules. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2017. [DOI: 10.1002/wcms.1343] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Wei Wang
- Department of ChemistryThe Hong Kong University of Science and Technology Kowloon Hong Kong
- Center of Systems Biology and Human HealthThe Hong Kong University of Science and Technology Kowloon Hong Kong
| | - Siqin Cao
- Department of ChemistryThe Hong Kong University of Science and Technology Kowloon Hong Kong
| | - Lizhe Zhu
- Department of ChemistryThe Hong Kong University of Science and Technology Kowloon Hong Kong
- Center of Systems Biology and Human HealthThe Hong Kong University of Science and Technology Kowloon Hong Kong
| | - Xuhui Huang
- Department of ChemistryThe Hong Kong University of Science and Technology Kowloon Hong Kong
- Center of Systems Biology and Human HealthThe Hong Kong University of Science and Technology Kowloon Hong Kong
- Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & ReconstructionThe Hong Kong University of Science and Technology Kowloon Hong Kong
- HKUST‐Shenzhen Research Institute Shenzhen China
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18
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Hu H, Luo C, Zheng YG. Transient Kinetics Define a Complete Kinetic Model for Protein Arginine Methyltransferase 1. J Biol Chem 2016; 291:26722-26738. [PMID: 27834681 DOI: 10.1074/jbc.m116.757625] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 11/10/2016] [Indexed: 12/31/2022] Open
Abstract
Protein arginine methyltransferases (PRMTs) are the enzymes responsible for posttranslational methylation of protein arginine residues in eukaryotic cells, particularly within the histone tails. A detailed mechanistic model of PRMT-catalyzed methylation is currently lacking, but it is essential for understanding the functions of PRMTs in various cellular pathways and for efficient design of PRMT inhibitors as potential treatments for a range of human diseases. In this work, we used stopped-flow fluorescence in combination with global kinetic simulation to dissect the transient kinetics of PRMT1, the predominant type I arginine methyltransferase. Several important mechanistic insights were revealed. The cofactor and the peptide substrate bound to PRMT1 in a random manner and then followed a kinetically preferred pathway to generate the catalytic enzyme-cofactor-substrate ternary complex. Product release proceeded in an ordered fashion, with peptide dissociation followed by release of the byproduct S-adenosylhomocysteine. Importantly, the dissociation rate of the monomethylated intermediate from the ternary complex was much faster than the methyl transfer. Such a result provided direct evidence for distributive arginine dimethylation, which means the monomethylated substrate has to be released to solution and rebind with PRMT1 before it undergoes further methylation. In addition, cofactor binding involved a conformational transition, likely an open-to-closed conversion of the active site pocket. Further, the histone H4 peptide bound to the two active sites of the PRMT1 homodimer with differential affinities, suggesting a negative cooperativity mechanism of substrate binding. These findings provide a new mechanistic understanding of how PRMTs interact with their substrates and transfer methyl groups.
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Affiliation(s)
- Hao Hu
- From the Department of Pharmaceutical and Biomedical Sciences, University of Georgia, Athens, Georgia 30602 and
| | - Cheng Luo
- the State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Y George Zheng
- From the Department of Pharmaceutical and Biomedical Sciences, University of Georgia, Athens, Georgia 30602 and
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19
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Maximova T, Moffatt R, Ma B, Nussinov R, Shehu A. Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics. PLoS Comput Biol 2016; 12:e1004619. [PMID: 27124275 PMCID: PMC4849799 DOI: 10.1371/journal.pcbi.1004619] [Citation(s) in RCA: 132] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.
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Affiliation(s)
- Tatiana Maximova
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
| | - Ryan Moffatt
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
| | - Buyong Ma
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America
| | - Ruth Nussinov
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America
- Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Amarda Shehu
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
- Department of Biongineering, George Mason University, Fairfax, Virginia, United States of America
- School of Systems Biology, George Mason University, Manassas, Virginia, United States of America
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20
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Affiliation(s)
- Andre A. S. T. Ribeiro
- Department of Chemical Engineering, Columbia University, New York, New York 10027, United States
| | - Vanessa Ortiz
- Department of Chemical Engineering, Columbia University, New York, New York 10027, United States
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21
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Zhang L, Jiang H, Sheong F, Pardo-Avila F, Cheung PH, Huang X. Constructing Kinetic Network Models to Elucidate Mechanisms of Functional Conformational Changes of Enzymes and Their Recognition with Ligands. Methods Enzymol 2016; 578:343-71. [DOI: 10.1016/bs.mie.2016.05.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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22
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Da LT, E C, Duan B, Zhang C, Zhou X, Yu J. A Jump-from-Cavity Pyrophosphate Ion Release Assisted by a Key Lysine Residue in T7 RNA Polymerase Transcription Elongation. PLoS Comput Biol 2015; 11:e1004624. [PMID: 26599007 PMCID: PMC4658072 DOI: 10.1371/journal.pcbi.1004624] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2015] [Accepted: 10/26/2015] [Indexed: 11/18/2022] Open
Abstract
Pyrophosphate ion (PPi) release during transcription elongation is a signature step in each nucleotide addition cycle. The kinetics and energetics of the process as well as how it proceeds with substantial conformational changes of the polymerase complex determine the mechano-chemical coupling mechanism of the transcription elongation. Here we investigated detailed dynamics of the PPi release process in a single-subunit RNA polymerase (RNAP) from bacteriophage T7, implementing all-atom molecular dynamics (MD) simulations. We obtained a jump-from-cavity kinetic model of the PPi release utilizing extensive nanosecond MD simulations. We found that the PPi release in T7 RNAP is initiated by the PPi dissociation from two catalytic aspartic acids, followed by a comparatively slow jump-from-cavity activation process. Combining with a number of microsecond long MD simulations, we also found that the activation process is hindered by charged residue associations as well as by local steric and hydrogen bond interactions. On the other hand, the activation is greatly assisted by a highly flexible lysine residue Lys472 that swings its side chain to pull PPi out. The mechanism can apply in general to single subunit RNA and DNA polymerases with similar molecular structures and conserved key residues. Remarkably, the flexible lysine or arginine residue appears to be a universal module that assists the PPi release even in multi-subunit RNAPs with charge facilitated hopping mechanisms. We also noticed that the PPi release is not tightly coupled to opening motions of an O-helix on the fingers domain of T7 RNAP according to the microsecond MD simulations. Our study thus supports the Brownian ratchet scenario of the mechano-chemical coupling in the transcription elongation of the single-subunit polymerase.
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Affiliation(s)
- Lin-Tai Da
- Department of Physics and Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida, United States of America
| | - Chao E
- Beijing Computational Science Research Center, Beijing, China
| | - Baogen Duan
- Beijing Computational Science Research Center, Beijing, China
| | - Chuanbiao Zhang
- School of Physics, University of the Chinese Academy of Sciences, Beijing, China
| | - Xin Zhou
- School of Physics, University of the Chinese Academy of Sciences, Beijing, China
| | - Jin Yu
- Beijing Computational Science Research Center, Beijing, China
- * E-mail:
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23
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Hospital A, Goñi JR, Orozco M, Gelpí JL. Molecular dynamics simulations: advances and applications. Adv Appl Bioinform Chem 2015; 8:37-47. [PMID: 26604800 PMCID: PMC4655909 DOI: 10.2147/aabc.s70333] [Citation(s) in RCA: 240] [Impact Index Per Article: 26.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Molecular dynamics simulations have evolved into a mature technique that can be used effectively to understand macromolecular structure-to-function relationships. Present simulation times are close to biologically relevant ones. Information gathered about the dynamic properties of macromolecules is rich enough to shift the usual paradigm of structural bioinformatics from studying single structures to analyze conformational ensembles. Here, we describe the foundations of molecular dynamics and the improvements made in the direction of getting such ensemble. Specific application of the technique to three main issues (allosteric regulation, docking, and structure refinement) is discussed.
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Affiliation(s)
- Adam Hospital
- Institute for Research in Biomedicine, The Barcelona Institute of Science and Technology, University of Barcelona, Barcelona, Spain
| | - Josep Ramon Goñi
- Joint BSC-IRB Research Program in Computational Biology, University of Barcelona, Barcelona, Spain ; Barcelona Supercomputing Center, University of Barcelona, Barcelona, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine, The Barcelona Institute of Science and Technology, University of Barcelona, Barcelona, Spain ; Joint BSC-IRB Research Program in Computational Biology, University of Barcelona, Barcelona, Spain ; Barcelona Supercomputing Center, University of Barcelona, Barcelona, Spain ; Department of Biochemistry and Molecular Biology, University of Barcelona, Barcelona, Spain
| | - Josep L Gelpí
- Joint BSC-IRB Research Program in Computational Biology, University of Barcelona, Barcelona, Spain ; Barcelona Supercomputing Center, University of Barcelona, Barcelona, Spain ; Department of Biochemistry and Molecular Biology, University of Barcelona, Barcelona, Spain
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