1
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Wu S, Li M, Wang L, Yang L, Cui J, Li F, Wang Q, Shi Y, Lv M. Structural basis for TNIP1 binding to FIP200 during mitophagy. J Biol Chem 2024; 300:107605. [PMID: 39059492 PMCID: PMC11367644 DOI: 10.1016/j.jbc.2024.107605] [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: 04/01/2024] [Revised: 06/07/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024] Open
Abstract
TNIP1 has been increasingly recognized as a security check to finely adjust the rate of mitophagy by disrupting the recycling of the Unc-51-like kinase complex during autophagosome formation. Through tank-binding kinase 1-mediated phosphorylation of the TNIP1 FIP200 interacting region (FIR) motif, the binding affinity of TNIP1 for FIP200, a component of the Unc-51-like kinase complex, is enhanced, allowing TNIP1 to outcompete autophagy receptors. Consequently, FIP200 is released from the autophagosome, facilitating further autophagosome expansion. However, the molecular basis by which FIP200 utilizes its claw domain to distinguish the phosphorylation status of residues in the TNIP1 FIR motif for recognition is not well understood. Here, we elucidated multiple crystal structures of the complex formed by the FIP200 claw domain and various phosphorylated TNIP1 FIR peptides. Structural and isothermal titration calorimetry analyses identified the crucial residues in the FIP200 claw domain responsible for the specific recognition of phosphorylated TNIP1 FIR peptides. Additionally, utilizing structural comparison and molecular dynamics simulation data, we demonstrated that the C-terminal tail of TNIP1 peptide affected its binding to the FIP200 claw domain. Moreover, the phosphorylation of TNIP1 Ser123 enabled the peptide to effectively compete with the peptide p-CCPG1 (the FIR motif of the autophagy receptor CCPG1) for binding with the FIP200 claw domain. Overall, our work provides a comprehensive understanding of the specific recognition of phosphorylated TNIP1 by the FIP200 claw domain, marking an initial step toward fully understanding the molecular mechanism underlying the TNIP1-dependent inhibition of mitophagy.
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Affiliation(s)
- Shengmei Wu
- Hefei National Research Center for Cross Disciplinary Science, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China; Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, China; Division of Life Sciences and Medicine, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science and Technology of China, Hefei, Anhui, China
| | - Mingwei Li
- Department of Physics, University of Science and Technology of China, Hefei, Anhui, China
| | - Lei Wang
- Hefei National Research Center for Cross Disciplinary Science, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China; Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, China; Division of Life Sciences and Medicine, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science and Technology of China, Hefei, Anhui, China
| | - Lingna Yang
- Hefei National Research Center for Cross Disciplinary Science, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China; Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, China; Division of Life Sciences and Medicine, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science and Technology of China, Hefei, Anhui, China
| | - Jing Cui
- Hefei National Research Center for Cross Disciplinary Science, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China; Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, China; Division of Life Sciences and Medicine, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science and Technology of China, Hefei, Anhui, China
| | - Fudong Li
- Hefei National Research Center for Cross Disciplinary Science, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China; Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, China; Division of Life Sciences and Medicine, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science and Technology of China, Hefei, Anhui, China
| | - Qian Wang
- Department of Physics, University of Science and Technology of China, Hefei, Anhui, China.
| | - Yunyu Shi
- Hefei National Research Center for Cross Disciplinary Science, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China; Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, China; Division of Life Sciences and Medicine, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science and Technology of China, Hefei, Anhui, China.
| | - Mengqi Lv
- Hefei National Research Center for Cross Disciplinary Science, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China; Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, China; Division of Life Sciences and Medicine, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science and Technology of China, Hefei, Anhui, China; Department of Hepatobiliary Surgery, Innovative Institute of Tumor Immunity and Medicine (ITIM), Anhui Province Key Laboratory of Tumor Immune Microenvironment and Immunotherapy, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
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2
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Wang J, Miao Y. Ligand Gaussian Accelerated Molecular Dynamics 3 (LiGaMD3): Improved Calculations of Binding Thermodynamics and Kinetics of Both Small Molecules and Flexible Peptides. J Chem Theory Comput 2024; 20:5829-5841. [PMID: 39002136 DOI: 10.1021/acs.jctc.4c00502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/15/2024]
Abstract
Binding thermodynamics and kinetics play critical roles in drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics of small molecules and flexible peptides using conventional molecular dynamics (cMD), due to limited simulation time scales. Based on our previously developed ligand Gaussian accelerated molecular dynamics (LiGaMD) method, we present a new approach, termed "LiGaMD3″, in which we introduce triple boosts into three individual energy terms that play important roles in small-molecule/peptide dissociation, rebinding, and system conformational changes to improve the sampling efficiency of small-molecule/peptide interactions with target proteins. To validate the performance of LiGaMD3, MDM2 bound by a small molecule (Nutlin 3) and two highly flexible peptides (PMI and P53) were chosen as the model systems. LiGaMD3 could efficiently capture repetitive small-molecule/peptide dissociation and binding events within 2 μs simulations. The predicted binding kinetic constant rates and free energies from LiGaMD3 were in agreement with the available experimental values and previous simulation results. Therefore, LiGaMD3 provides a more general and efficient approach to capture dissociation and binding of both small-molecule ligands and flexible peptides, allowing for accurate prediction of their binding thermodynamics and kinetics.
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Affiliation(s)
- Jinan Wang
- Computational Medicine Program and Department of Pharmacology, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Yinglong Miao
- Computational Medicine Program and Department of Pharmacology, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States
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3
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Jung J, Yagi K, Tan C, Oshima H, Mori T, Yu I, Matsunaga Y, Kobayashi C, Ito S, Ugarte La Torre D, Sugita Y. GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models. J Phys Chem B 2024; 128:6028-6048. [PMID: 38876465 PMCID: PMC11215777 DOI: 10.1021/acs.jpcb.4c02096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 05/15/2024] [Accepted: 05/21/2024] [Indexed: 06/16/2024]
Abstract
GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.
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Affiliation(s)
- Jaewoon Jung
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Kiyoshi Yagi
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Cheng Tan
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Hiraku Oshima
- Laboratory
for Biomolecular Function Simulation, RIKEN
Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
- Graduate
School of Life Science, University of Hyogo, Harima Science Park City, Hyogo 678-1297, Japan
| | - Takaharu Mori
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department
of Chemistry, Tokyo University of Science, Shinjuku-ku, Tokyo 162-8601, Japan
| | - Isseki Yu
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department
of Bioinformatics, Maebashi Institute of
Technology, Maebashi, Gunma 371-0816, Japan
| | - Yasuhiro Matsunaga
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
- Graduate
School of Science and Engineering, Saitama
University, Saitama 338-8570, Japan
| | - Chigusa Kobayashi
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Shingo Ito
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Diego Ugarte La Torre
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
- Laboratory
for Biomolecular Function Simulation, RIKEN
Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
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4
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Wang J, Miao Y. Ligand Gaussian accelerated Molecular Dynamics 3 (LiGaMD3): Improved Calculations of Binding Thermodynamics and Kinetics of Both Small Molecules and Flexible Peptides. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.06.592668. [PMID: 38766067 PMCID: PMC11100592 DOI: 10.1101/2024.05.06.592668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Binding thermodynamics and kinetics play critical roles in drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics of small molecules and flexible peptides using conventional Molecular Dynamics (cMD), due to limited simulation timescales. Based on our previously developed Ligand Gaussian accelerated Molecular Dynamics (LiGaMD) method, we present a new approach, termed "LiGaMD3", in which we introduce triple boosts into three individual energy terms that play important roles in small-molecule/peptide dissociation, rebinding and system conformational changes to improve the sampling efficiency of small-molecule/peptide interactions with target proteins. To validate the performance of LiGaMD3, MDM2 bound by a small molecule (Nutlin 3) and two highly flexible peptides (PMI and P53) were chosen as model systems. LiGaMD3 could efficiently capture repetitive small-molecule/peptide dissociation and binding events within 2 microsecond simulations. The predicted binding kinetic constant rates and free energies from LiGaMD3 agreed with available experimental values and previous simulation results. Therefore, LiGaMD3 provides a more general and efficient approach to capture dissociation and binding of both small-molecule ligand and flexible peptides, allowing for accurate prediction of their binding thermodynamics and kinetics.
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Affiliation(s)
- Jinan Wang
- Computational Medicine Program and Department of Pharmacology, University of North Carolina – Chapel Hill, Chapel Hill, North Carolina, USA 27599
| | - Yinglong Miao
- Computational Medicine Program and Department of Pharmacology, University of North Carolina – Chapel Hill, Chapel Hill, North Carolina, USA 27599
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5
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Chyży P, Kulik M, Shinobu A, Re S, Sugita Y, Trylska J. Molecular dynamics in multidimensional space explains how mutations affect the association path of neomycin to a riboswitch. Proc Natl Acad Sci U S A 2024; 121:e2317197121. [PMID: 38579011 PMCID: PMC11009640 DOI: 10.1073/pnas.2317197121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 02/15/2024] [Indexed: 04/07/2024] Open
Abstract
Riboswitches are messenger RNA (mRNA) fragments binding specific small molecules to regulate gene expression. A synthetic N1 riboswitch, inserted into yeast mRNA controls the translation of a reporter gene in response to neomycin. However, its regulatory activity is sensitive to single-point RNA mutations, even those distant from the neomycin binding site. While the association paths of neomycin to N1 and its variants remain unknown, recent fluorescence kinetic experiments indicate a two-step process driven by conformational selection. This raises the question of which step is affected by mutations. To address this, we performed all-atom two-dimensional replica-exchange molecular dynamics simulations for N1 and U14C, U14C[Formula: see text], U15A, and A17G mutants, ensuring extensive conformational sampling of both RNA and neomycin. The obtained neomycin association and binding paths, along with multidimensional free-energy profiles, revealed a two-step binding mechanism, consisting of conformational selection and induced fit. Neomycin binds to a preformed N1 conformation upon identifying a stable upper stem and U-turn motif in the riboswitch hairpin. However, the positioning of neomycin in the binding site occurs at different RNA-neomycin distances for each mutant, which may explain their different regulatory activities. The subsequent induced fit arises from the interactions of the neomycin's N3 amino group with RNA, causing the G9 backbone to rearrange. In the A17G mutant, the critical C6-A17/G17 stacking forms at a closer RNA-neomycin distance compared to N1. These findings together with estimated binding free energies coincide with experiments and elucidate why the A17G mutation decreases and U15A enhances N1 activity in response to neomycin.
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Affiliation(s)
- Piotr Chyży
- Centre of New Technologies, University of Warsaw, 02-097Warsaw, Poland
| | - Marta Kulik
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, 02-093Warsaw, Poland
| | - Ai Shinobu
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, 650-0047Kobe, Japan
| | - Suyong Re
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, 650-0047Kobe, Japan
- Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health, and Nutrition, 567-0085Ibaraki, Japan
| | - Yuji Sugita
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, 650-0047Kobe, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 351-0198Wako, Japan
- RIKEN Center for Computational Science, 650-0047Kobe, Japan
| | - Joanna Trylska
- Centre of New Technologies, University of Warsaw, 02-097Warsaw, Poland
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6
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Trevitt CR, Yashwanth Kumar DR, Fowler NJ, Williamson MP. Interactions between the protein barnase and co-solutes studied by NMR. Commun Chem 2024; 7:44. [PMID: 38418894 PMCID: PMC10902301 DOI: 10.1038/s42004-024-01127-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 02/09/2024] [Indexed: 03/02/2024] Open
Abstract
Protein solubility and stability depend on the co-solutes present. There is little theoretical basis for selection of suitable co-solutes. Some guidance is provided by the Hofmeister series, an empirical ordering of anions according to their effect on solubility and stability; and by osmolytes, which are small organic molecules produced by cells to allow them to function in stressful environments. Here, NMR titrations of the protein barnase with Hofmeister anions and osmolytes are used to measure and locate binding, and thus to separate binding and bulk solvent effects. We describe a rationalisation of Hofmeister (and inverse Hofmeister) effects, which is similar to the traditional chaotrope/kosmotrope idea but based on solvent fluctuation rather than water withdrawal, and characterise how co-solutes affect protein stability and solubility, based on solvent fluctuations. This provides a coherent explanation for solute effects, and points towards a more rational basis for choice of excipients.
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Affiliation(s)
- Clare R Trevitt
- School of Biosciences, University of Sheffield, Sheffield, S10 2TN, UK
- Certara UK Ltd, Level 2-Acero, 1 Concourse Way, Sheffield, S1 3BJ, UK
| | | | - Nicholas J Fowler
- School of Biosciences, University of Sheffield, Sheffield, S10 2TN, UK
| | - Mike P Williamson
- School of Biosciences, University of Sheffield, Sheffield, S10 2TN, UK.
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7
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Tripathi S, Nair NN. Temperature Accelerated Sliced Sampling to Probe Ligand Dissociation from Protein. J Chem Inf Model 2023; 63:5182-5191. [PMID: 37540828 DOI: 10.1021/acs.jcim.3c00376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2023]
Abstract
Modeling ligand unbinding in proteins to estimate the free energy of binding and probing the mechanism presents several challenges. They primarily pertain to the entropic bottlenecks resulting from protein and solvent conformations. While exploring the unbinding processes using enhanced sampling techniques, very long simulations are required to sample all of the conformational states as the system gets trapped in local free energy minima along transverse coordinates. Here, we demonstrate that temperature accelerated sliced sampling (TASS) is an ideal approach to overcome some of the difficulties faced by conventional sampling methods in studying ligand unbinding. Using TASS, we study the unbinding of avibactam inhibitor molecules from the Class C β-lactamase (CBL) active site. Extracting CBL-avibactam unbinding free energetics, unbinding pathways, and identifying critical interactions from the TASS simulations are demonstrated.
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Affiliation(s)
- Shubhandra Tripathi
- Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur 208016, India
| | - Nisanth N Nair
- Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur 208016, India
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8
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Jung J, Kobayashi C, Sugita Y. Acceleration of generalized replica exchange with solute tempering simulations of large biological systems on massively parallel supercomputer. J Comput Chem 2023. [PMID: 37141320 DOI: 10.1002/jcc.27124] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 04/10/2023] [Accepted: 04/14/2023] [Indexed: 05/06/2023]
Abstract
Generalized replica exchange with solute tempering (gREST) is one of the enhanced sampling algorithms for proteins or other systems with rugged energy landscapes. Unlike the replica-exchange molecular dynamics (REMD) method, solvent temperatures are the same in all replicas, while solute temperatures are different and are exchanged frequently between replicas for exploring various solute structures. Here, we apply the gREST scheme to large biological systems containing over one million atoms using a large number of processors in a supercomputer. First, communication time on a multi-dimensional torus network is reduced by matching each replica to MPI processors optimally. This is applicable not only to gREST but also to other multi-copy algorithms. Second, energy evaluations, which are necessary for the multistate bennet acceptance ratio (MBAR) method for free energy estimations, are performed on-the-fly during the gREST simulations. Using these two advanced schemes, we observed 57.72 ns/day performance in 128-replica gREST calculations with 1.5 million atoms system using 16,384 nodes in Fugaku. These schemes implemented in the latest version of GENESIS software could open new possibilities to answer unresolved questions on large biomolecular complex systems with slow conformational dynamics.
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Affiliation(s)
- Jaewoon Jung
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Saitama, Japan
| | - Chigusa Kobayashi
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Japan
| | - Yuji Sugita
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Saitama, Japan
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
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9
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Ahalawat N, Sahil M, Mondal J. Resolving Protein Conformational Plasticity and Substrate Binding via Machine Learning. J Chem Theory Comput 2023; 19:2644-2657. [PMID: 37068044 DOI: 10.1021/acs.jctc.2c00932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
A long-standing target in elucidating the biomolecular recognition process is the identification of binding-competent conformations of the receptor protein. However, protein conformational plasticity and the stochastic nature of the recognition processes often preclude the assignment of a specific protein conformation to an individual ligand-bound pose. Here, we demonstrate that a computational framework coined as RF-TICA-MD, which integrates an ensemble decision-tree-based Random Forest (RF) machine learning (ML) technique with an unsupervised dimension reduction approach time-structured independent component analysis (TICA), provides an efficient and unambiguous solution toward resolving protein conformational plasticity and the substrate binding process. In particular, we consider multimicrosecond-long molecular dynamics (MD) simulation trajectories of a ligand recognition process in solvent-inaccessible cavities of archetypal proteins T4 lysozyme and cytochrome P450cam. We show that in a scenario in which clear correspondence between protein conformation and binding-competent macrostates could not be obtained via an unsupervised dimension reduction approach, an a priori decision-tree-based supervised classification of the simulated recognition trajectories via RF would help characterize key amino acid residue pairs of the protein that are deemed sensitive for ligand binding. A subsequent unsupervised dimensional reduction of the selected residue pairs via TICA would then delineate a conformational landscape of protein which is able to demarcate ligand-bound poses from unbound ones. The proposed RF-TICA-MD approach is shown to be data agnostic and found to be robust when using other ML-based classification methods such as XGBoost. As a promising spinoff of the protocol, the framework is found to be capable of identifying distal protein locations which would be allosterically important for ligand binding and would characterize their roles in recognition pathways. A Python implementation of a proposed ML workflow is available in GitHub https://github.com/navjeet0211/rf-tica-md.
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Affiliation(s)
- Navjeet Ahalawat
- Department of Bioinformatics and Computational Biology, College of Biotechnology, CCS Haryana Agricultural University, Hisar 125 004, Haryana, India
| | - Mohammad Sahil
- Center for Interdisciplinary Sciences, Tata Institute of Fundamental Research, Hyderabad 500046, India
| | - Jagannath Mondal
- Center for Interdisciplinary Sciences, Tata Institute of Fundamental Research, Hyderabad 500046, India
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10
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Ligand Gaussian Accelerated Molecular Dynamics 2 (LiGaMD2): Improved Calculations of Ligand Binding Thermodynamics and Kinetics with Closed Protein Pocket. J Chem Theory Comput 2023; 19:733-745. [PMID: 36706316 DOI: 10.1021/acs.jctc.2c01194] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Ligand binding thermodynamics and kinetics are critical parameters for drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics from molecular simulations due to limited simulation timescales. Protein dynamics, especially in the ligand binding pocket, often plays an important role in ligand binding. Based on our previously developed Ligand Gaussian accelerated molecular dynamics (LiGaMD), here we present LiGaMD2 in which a selective boost potential was applied to both the ligand and protein residues in the binding pocket to improve sampling of ligand binding and dissociation. To validate the performance of LiGaMD2, the T4 lysozyme (T4L) mutants with open and closed pockets bound by different ligands were chosen as model systems. LiGaMD2 could efficiently capture repetitive ligand dissociation and binding within microsecond simulations of all T4L systems. The obtained ligand binding kinetic rates and free energies agreed well with available experimental values and previous modeling results. Therefore, LiGaMD2 provides an improved approach to sample opening of closed protein pockets for ligand dissociation and binding, thereby allowing for efficient calculations of ligand binding thermodynamics and kinetics.
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11
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Niitsu A, Sugita Y. Towards de novo design of transmembrane α-helical assemblies using structural modelling and molecular dynamics simulation. Phys Chem Chem Phys 2023; 25:3595-3606. [PMID: 36647771 DOI: 10.1039/d2cp03972a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Computational de novo protein design involves iterative processes consisting of amino acid sequence design, structural modelling and scoring, and design validation by synthesis and experimental characterisation. Recent advances in protein structure prediction and modelling methods have enabled the highly efficient and accurate design of water-soluble proteins. However, the design of membrane proteins remains a major challenge. To advance membrane protein design, considering the higher complexity of membrane protein folding, stability, and dynamic interactions between water, ions, lipids, and proteins is an important task. For introducing explicit solvents and membranes to these design methods, all-atom molecular dynamics (MD) simulations of designed proteins provide useful information that cannot be obtained experimentally. In this review, we first describe two major approaches to designing transmembrane α-helical assemblies, consensus and de novo design. We further illustrate recent MD studies of membrane protein folding related to protein design, as well as advanced treatments in molecular models and conformational sampling techniques in the simulations. Finally, we discuss the possibility to introduce MD simulations after the existing static modelling and screening of design decoys as an additional step for refinement of the design, which considers membrane protein folding dynamics and interactions with explicit membranes.
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Affiliation(s)
- Ai Niitsu
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan. .,Computational Biophysics Research Team, RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, 6-7-1 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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12
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Sohraby F, Nunes-Alves A. Advances in computational methods for ligand binding kinetics. Trends Biochem Sci 2022; 48:437-449. [PMID: 36566088 DOI: 10.1016/j.tibs.2022.11.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 11/16/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022]
Abstract
Binding kinetic parameters can be correlated with drug efficacy, which in recent years led to the development of various computational methods for predicting binding kinetic rates and gaining insight into protein-drug binding paths and mechanisms. In this review, we introduce and compare computational methods recently developed and applied to two systems, trypsin-benzamidine and kinase-inhibitor complexes. Methods involving enhanced sampling in molecular dynamics simulations or machine learning can be used not only to predict kinetic rates, but also to reveal factors modulating the duration of residence times, selectivity, and drug resistance to mutations. Methods which require less computational time to make predictions are highlighted, and suggestions to reduce the error of computed kinetic rates are presented.
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Affiliation(s)
- Farzin Sohraby
- Institute of Chemistry, Technische Universität Berlin, 10623 Berlin, Germany
| | - Ariane Nunes-Alves
- Institute of Chemistry, Technische Universität Berlin, 10623 Berlin, Germany.
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13
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Ruzmetov T, Montes R, Sun J, Chen SH, Tang Z, Chang CEA. Binding Kinetics Toolkit for Analyzing Transient Molecular Conformations and Computing Free Energy Landscapes. J Phys Chem A 2022; 126:8761-8770. [DOI: 10.1021/acs.jpca.2c05499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Talant Ruzmetov
- Department of Chemistry, University of California at Riverside, Riverside, California92521, United States
| | - Ruben Montes
- Department of Chemistry, University of California at Riverside, Riverside, California92521, United States
| | - Jianan Sun
- Department of Chemistry, University of California at Riverside, Riverside, California92521, United States
| | - Si-Han Chen
- Department of Chemistry, University of California at Riverside, Riverside, California92521, United States
| | - Zhiye Tang
- Department of Chemistry, University of California at Riverside, Riverside, California92521, United States
| | - Chia-en A. Chang
- Department of Chemistry, University of California at Riverside, Riverside, California92521, United States
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14
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Matsubara D, Kasahara K, Dokainish HM, Oshima H, Sugita Y. Modified Protein-Water Interactions in CHARMM36m for Thermodynamics and Kinetics of Proteins in Dilute and Crowded Solutions. Molecules 2022; 27:molecules27175726. [PMID: 36080494 PMCID: PMC9457699 DOI: 10.3390/molecules27175726] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/30/2022] [Accepted: 08/30/2022] [Indexed: 11/16/2022] Open
Abstract
Proper balance between protein-protein and protein-water interactions is vital for atomistic molecular dynamics (MD) simulations of globular proteins as well as intrinsically disordered proteins (IDPs). The overestimation of protein-protein interactions tends to make IDPs more compact than those in experiments. Likewise, multiple proteins in crowded solutions are aggregated with each other too strongly. To optimize the balance, Lennard-Jones (LJ) interactions between protein and water are often increased about 10% (with a scaling parameter, λ = 1.1) from the existing force fields. Here, we explore the optimal scaling parameter of protein-water LJ interactions for CHARMM36m in conjunction with the modified TIP3P water model, by performing enhanced sampling MD simulations of several peptides in dilute solutions and conventional MD simulations of globular proteins in dilute and crowded solutions. In our simulations, 10% increase of protein-water LJ interaction for the CHARMM36m cannot maintain stability of a small helical peptide, (AAQAA)3 in a dilute solution and only a small modification of protein-water LJ interaction up to the 3% increase (λ = 1.03) is allowed. The modified protein-water interactions are applicable to other peptides and globular proteins in dilute solutions without changing thermodynamic properties from the original CHARMM36m. However, it has a great impact on the diffusive properties of proteins in crowded solutions, avoiding the formation of too sticky protein-protein interactions.
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Affiliation(s)
- Daiki Matsubara
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Hyogo, Japan
| | - Kento Kasahara
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Hyogo, Japan
- Division of Chemical Engineering, Graduate School of Engineering Science, Osaka University, Toyonaka 560-8531, Osaka, Japan
| | - Hisham M. Dokainish
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako 351-0198, Saitama, Japan
| | - Hiraku Oshima
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Hyogo, Japan
| | - Yuji Sugita
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Hyogo, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako 351-0198, Saitama, Japan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe 650-0047, Hyogo, Japan
- Correspondence: ; Tel.: +81-48-462-1407
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15
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Shinobu A, Re S, Sugita Y. Practical Protocols for Efficient Sampling of Kinase-Inhibitor Binding Pathways Using Two-Dimensional Replica-Exchange Molecular Dynamics. Front Mol Biosci 2022; 9:878830. [PMID: 35573746 PMCID: PMC9099257 DOI: 10.3389/fmolb.2022.878830] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
Molecular dynamics (MD) simulations are increasingly used to study various biological processes such as protein folding, conformational changes, and ligand binding. These processes generally involve slow dynamics that occur on the millisecond or longer timescale, which are difficult to simulate by conventional atomistic MD. Recently, we applied a two-dimensional (2D) replica-exchange MD (REMD) method, which combines the generalized replica exchange with solute tempering (gREST) with the replica-exchange umbrella sampling (REUS) in kinase-inhibitor binding simulations, and successfully observed multiple ligand binding/unbinding events. To efficiently apply the gREST/REUS method to other kinase-inhibitor systems, we establish modified, practical protocols with non-trivial simulation parameter tuning. The current gREST/REUS simulation protocols are tested for three kinase-inhibitor systems: c-Src kinase with PP1, c-Src kinase with Dasatinib, and c-Abl kinase with Imatinib. We optimized the definition of kinase-ligand distance as a collective variable (CV), the solute temperatures in gREST, and replica distributions and umbrella forces in the REUS simulations. Also, the initial structures of each replica in the 2D replica space were prepared carefully by pulling each ligand from and toward the protein binding sites for keeping stable kinase conformations. These optimizations were carried out individually in multiple short MD simulations. The current gREST/REUS simulation protocol ensures good random walks in 2D replica spaces, which are required for enhanced sampling of inhibitor dynamics around a target kinase.
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Affiliation(s)
- Ai Shinobu
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Suyong Re
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
- Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health, and Nutrition, Ibaraki, Japan
| | - Yuji Sugita
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Saitama, Japan
- RIKEN Center for Computational Science, Kobe, Japan
- *Correspondence: Yuji Sugita,
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16
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Pantsar T, Kaiser PD, Kudolo M, Forster M, Rothbauer U, Laufer SA. Decisive role of water and protein dynamics in residence time of p38α MAP kinase inhibitors. Nat Commun 2022; 13:569. [PMID: 35091547 PMCID: PMC8799644 DOI: 10.1038/s41467-022-28164-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 01/06/2022] [Indexed: 12/31/2022] Open
Abstract
Target residence time plays a crucial role in the pharmacological activity of small molecule inhibitors. Little is known, however, about the underlying causes of inhibitor residence time at the molecular level, which complicates drug optimization processes. Here, we employ all-atom molecular dynamics simulations (~400 μs in total) to gain insight into the binding modes of two structurally similar p38α MAPK inhibitors (type I and type I½) with short and long residence times that otherwise show nearly identical inhibitory activities in the low nanomolar IC50 range. Our results highlight the importance of protein conformational stability and solvent exposure, buried surface area of the ligand and binding site resolvation energy for residence time. These findings are further confirmed by simulations with a structurally diverse short residence time inhibitor SB203580. In summary, our data provide guidance in compound design when aiming for inhibitors with improved target residence time. The molecular determinants of the residence time of a small molecule inhibitor at its target protein are not well understood. Here, Pantsar et al. show that the target protein’s conformational stability and solvent exposure are key factors governing the target residence time of kinase inhibitors.
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Affiliation(s)
- Tatu Pantsar
- Department of Pharmaceutical and Medicinal Chemistry, Institute of Pharmaceutical Sciences, Eberhard Karls Universität Tübingen, Auf der Morgenstelle 8, 72076, Tuebingen, Germany.,School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Yliopistonranta 1, 70210, Kuopio, Finland
| | - Philipp D Kaiser
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstrasse 55, 72770, Reutlingen, Germany
| | - Mark Kudolo
- Department of Pharmaceutical and Medicinal Chemistry, Institute of Pharmaceutical Sciences, Eberhard Karls Universität Tübingen, Auf der Morgenstelle 8, 72076, Tuebingen, Germany
| | - Michael Forster
- Department of Pharmaceutical and Medicinal Chemistry, Institute of Pharmaceutical Sciences, Eberhard Karls Universität Tübingen, Auf der Morgenstelle 8, 72076, Tuebingen, Germany
| | - Ulrich Rothbauer
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstrasse 55, 72770, Reutlingen, Germany.,Pharmaceutical Biotechnology, Eberhard Karls University Tuebingen, Markwiesenstrasse 55, 72770, Reutlingen, Germany.,Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, 72076, Tuebingen, Germany
| | - Stefan A Laufer
- Department of Pharmaceutical and Medicinal Chemistry, Institute of Pharmaceutical Sciences, Eberhard Karls Universität Tübingen, Auf der Morgenstelle 8, 72076, Tuebingen, Germany. .,Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, 72076, Tuebingen, Germany. .,Tuebingen Center for Academic Drug Discovery & Development (TüCAD2), 72076, Tuebingen, Germany.
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17
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Challenges and frontiers of computational modelling of biomolecular recognition. QRB DISCOVERY 2022. [DOI: 10.1017/qrd.2022.11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Abstract
Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have presented challenges for computational modelling. Here, we review the challenges and computational approaches developed to characterise biomolecular binding, including molecular docking, molecular dynamics simulations (especially enhanced sampling) and machine learning. Further improvements are still needed in order to accurately and efficiently characterise binding structures, mechanisms, thermodynamics and kinetics of biomolecules in the future.
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18
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Peng J, Svetec N, Zhao L. Intermolecular interactions drive protein adaptive and co-adaptive evolution at both species and population levels. Mol Biol Evol 2021; 39:6456312. [PMID: 34878126 PMCID: PMC8789070 DOI: 10.1093/molbev/msab350] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Proteins are the building blocks for almost all the functions in cells. Understanding the molecular evolution of proteins and the forces that shape protein evolution is essential in understanding the basis of function and evolution. Previous studies have shown that adaptation frequently occurs at the protein surface, such as in genes involved in host–pathogen interactions. However, it remains unclear whether adaptive sites are distributed randomly or at regions associated with particular structural or functional characteristics across the genome, since many proteins lack structural or functional annotations. Here, we seek to tackle this question by combining large-scale bioinformatic prediction, structural analysis, phylogenetic inference, and population genomic analysis of Drosophila protein-coding genes. We found that protein sequence adaptation is more relevant to function-related rather than structure-related properties. Interestingly, intermolecular interactions contribute significantly to protein adaptation. We further showed that intermolecular interactions, such as physical interactions, may play a role in the coadaptation of fast-adaptive proteins. We found that strongly differentiated amino acids across geographic regions in protein-coding genes are mostly adaptive, which may contribute to the long-term adaptive evolution. This strongly indicates that a number of adaptive sites tend to be repeatedly mutated and selected throughout evolution in the past, present, and maybe future. Our results highlight the important roles of intermolecular interactions and coadaptation in the adaptive evolution of proteins both at the species and population levels.
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Affiliation(s)
- Junhui Peng
- Laboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY, 10065, USA
| | - Nicolas Svetec
- Laboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY, 10065, USA
| | - Li Zhao
- Laboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY, 10065, USA
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19
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Fujiyama K, Kato N, Re S, Kinugasa K, Watanabe K, Takita R, Nogawa T, Hino T, Osada H, Sugita Y, Takahashi S, Nagano S. Molecular Basis for Two Stereoselective Diels–Alderases that Produce Decalin Skeletons**. Angew Chem Int Ed Engl 2021. [DOI: 10.1002/ange.202106186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Keisuke Fujiyama
- Department of Chemistry and Biotechnology Graduate School of Engineering Tottori University 4-101 Koyama-cho Minami Tottori 680-8552 Japan
- Current address: Dormancy and Adaptation Research Unit RIKEN Center for Sustainable Resource Science 1-7-22 Suehiro, Tsurumi Yokohama Kanagawa 230-0045 Japan
| | - Naoki Kato
- Natural Product Biosynthesis Research Unit RIKEN Center for Sustainable Research Science 2-1 Hirosawa Wako Saitama 351-0198 Japan
- Faculty of Agriculture Setsunan University 45-1 Nagaotoge-cho, Hirakata Osaka 573-0101 Japan
| | - Suyong Re
- Laboratory for Biomolecular Function Simulation RIKEN Center for Biosystems Dynamics Research 2-2-3 Minatojima-minami-machi, Chuo-ku Kobe Hyogo 650-0047 Japan
- Artificial Intelligence Center for Health and Biomedical Research National Institutes of Biomedical Innovation, Health, and Nutrition 7-6-8, Saito-Asagi, Ibaraki Osaka 567-0085 Japan
| | - Kiyomi Kinugasa
- Natural Product Biosynthesis Research Unit RIKEN Center for Sustainable Research Science 2-1 Hirosawa Wako Saitama 351-0198 Japan
| | - Kohei Watanabe
- Graduate School of Pharmaceutical Sciences The University of Tokyo 7-3-1 Hongo, Bunkyo-ku Tokyo 113-0033 Japan
| | - Ryo Takita
- Graduate School of Pharmaceutical Sciences The University of Tokyo 7-3-1 Hongo, Bunkyo-ku Tokyo 113-0033 Japan
| | - Toshihiko Nogawa
- Chemical Biology Research Group RIKEN Center for Sustainable Research Science 2-1 Hirosawa Wako Saitama 351-0198 Japan
| | - Tomoya Hino
- Department of Chemistry and Biotechnology Graduate School of Engineering Tottori University 4-101 Koyama-cho Minami Tottori 680-8552 Japan
- Center for Research on Green Sustainable Chemistry Tottori University 4-101 Koyama-cho Minami Tottori 680-8552 Japan
| | - Hiroyuki Osada
- Chemical Biology Research Group RIKEN Center for Sustainable Research Science 2-1 Hirosawa Wako Saitama 351-0198 Japan
| | - Yuji Sugita
- Laboratory for Biomolecular Function Simulation RIKEN Center for Biosystems Dynamics Research 2-2-3 Minatojima-minami-machi, Chuo-ku Kobe Hyogo 650-0047 Japan
- Theoretical Molecular Science Laboratory RIKEN Cluster for Pioneering Research 2-1 Hirosawa Wako Saitama 351-0198 Japan
- Computational Biophysics Research Team RIKEN Center for Computational Science 7-1-26 Minatojima-minami-machi Chuo-ku Kobe, Hyogo 650-0047 Japan
| | - Shunji Takahashi
- Natural Product Biosynthesis Research Unit RIKEN Center for Sustainable Research Science 2-1 Hirosawa Wako Saitama 351-0198 Japan
| | - Shingo Nagano
- Department of Chemistry and Biotechnology Graduate School of Engineering Tottori University 4-101 Koyama-cho Minami Tottori 680-8552 Japan
- Center for Research on Green Sustainable Chemistry Tottori University 4-101 Koyama-cho Minami Tottori 680-8552 Japan
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20
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Fujiyama K, Kato N, Re S, Kinugasa K, Watanabe K, Takita R, Nogawa T, Hino T, Osada H, Sugita Y, Takahashi S, Nagano S. Molecular Basis for Two Stereoselective Diels-Alderases that Produce Decalin Skeletons*. Angew Chem Int Ed Engl 2021; 60:22401-22410. [PMID: 34121297 PMCID: PMC8518865 DOI: 10.1002/anie.202106186] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Indexed: 12/02/2022]
Abstract
Enzymes catalyzing [4+2] cycloaddition have attracted increasing attention because of their key roles in natural product biosynthesis. Here, we solved the X-ray crystal structures of a pair of decalin synthases, Fsa2 and Phm7, that catalyze intramolecular [4+2] cycloadditions to form enantiomeric decalin scaffolds during biosynthesis of the HIV-1 integrase inhibitor equisetin and its stereochemical opposite, phomasetin. Computational modeling, using molecular dynamics simulations as well as quantum chemical calculations, demonstrates that the reactions proceed through synergetic conformational constraints assuring transition state-like substrates folds and their stabilization by specific protein-substrate interactions. Site-directed mutagenesis experiments verified the binding models. Intriguingly, the flexibility of bound substrates is largely different in two enzymes, suggesting the distinctive mechanism of dynamics regulation behind these stereoselective reactions. The proposed reaction mechanism herein deepens the basic understanding how these enzymes work but also provides a guiding principle to create artificial enzymes.
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Affiliation(s)
- Keisuke Fujiyama
- Department of Chemistry and BiotechnologyGraduate School of EngineeringTottori University4-101 Koyama-choMinamiTottori680-8552Japan
- Current address: Dormancy and Adaptation Research UnitRIKEN Center for Sustainable Resource Science1-7-22 Suehiro, TsurumiYokohamaKanagawa230-0045Japan
| | - Naoki Kato
- Natural Product Biosynthesis Research UnitRIKEN Center for Sustainable Research Science2-1 HirosawaWakoSaitama351-0198Japan
- Faculty of AgricultureSetsunan University45-1 Nagaotoge-cho, HirakataOsaka573-0101Japan
| | - Suyong Re
- Laboratory for Biomolecular Function SimulationRIKEN Center for Biosystems Dynamics Research2-2-3 Minatojima-minami-machi, Chuo-kuKobeHyogo650-0047Japan
- Artificial Intelligence Center for Health and Biomedical ResearchNational Institutes of Biomedical Innovation, Health, and Nutrition7-6-8, Saito-Asagi, IbarakiOsaka567-0085Japan
| | - Kiyomi Kinugasa
- Natural Product Biosynthesis Research UnitRIKEN Center for Sustainable Research Science2-1 HirosawaWakoSaitama351-0198Japan
| | - Kohei Watanabe
- Graduate School of Pharmaceutical SciencesThe University of Tokyo7-3-1 Hongo, Bunkyo-kuTokyo113-0033Japan
| | - Ryo Takita
- Graduate School of Pharmaceutical SciencesThe University of Tokyo7-3-1 Hongo, Bunkyo-kuTokyo113-0033Japan
| | - Toshihiko Nogawa
- Chemical Biology Research GroupRIKEN Center for Sustainable Research Science2-1 HirosawaWakoSaitama351-0198Japan
| | - Tomoya Hino
- Department of Chemistry and BiotechnologyGraduate School of EngineeringTottori University4-101 Koyama-choMinamiTottori680-8552Japan
- Center for Research on Green Sustainable ChemistryTottori University4-101 Koyama-choMinamiTottori680-8552Japan
| | - Hiroyuki Osada
- Chemical Biology Research GroupRIKEN Center for Sustainable Research Science2-1 HirosawaWakoSaitama351-0198Japan
| | - Yuji Sugita
- Laboratory for Biomolecular Function SimulationRIKEN Center for Biosystems Dynamics Research2-2-3 Minatojima-minami-machi, Chuo-kuKobeHyogo650-0047Japan
- Theoretical Molecular Science LaboratoryRIKEN Cluster for Pioneering Research2-1 HirosawaWakoSaitama351-0198Japan
- Computational Biophysics Research TeamRIKEN Center for Computational Science7-1-26 Minatojima-minami-machiChuo-kuKobe, Hyogo650-0047Japan
| | - Shunji Takahashi
- Natural Product Biosynthesis Research UnitRIKEN Center for Sustainable Research Science2-1 HirosawaWakoSaitama351-0198Japan
| | - Shingo Nagano
- Department of Chemistry and BiotechnologyGraduate School of EngineeringTottori University4-101 Koyama-choMinamiTottori680-8552Japan
- Center for Research on Green Sustainable ChemistryTottori University4-101 Koyama-choMinamiTottori680-8552Japan
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21
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Jung J, Kasahara K, Kobayashi C, Oshima H, Mori T, Sugita Y. Optimized Hydrogen Mass Repartitioning Scheme Combined with Accurate Temperature/Pressure Evaluations for Thermodynamic and Kinetic Properties of Biological Systems. J Chem Theory Comput 2021; 17:5312-5321. [PMID: 34278793 DOI: 10.1021/acs.jctc.1c00185] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
In recent years, molecular dynamics (MD) simulations with larger time steps have been performed with the hydrogen-mass-repartitioning (HMR) scheme, where the mass of each hydrogen atom is increased to reduce high-frequency motion while the mass of a non-hydrogen atom bonded to a hydrogen atom is decreased to keep the total molecular mass unchanged. Here, we optimize the scaling factors in HMR and combine them with previously developed accurate temperature/pressure evaluations. The heterogeneous HMR scaling factors are useful to avoid the structural instability of amino acid residues having a five- or six-membered ring in MD simulations with larger time steps. It also reproduces kinetic properties, namely translational and rotational diffusions, if the HMR scaling factors are applied to only solute molecules. The integration scheme is tested for biological systems that include soluble/membrane proteins and lipid bilayers for about 200 μs MD simulations in total and give consistent results in MD simulations with both a small time step of 2.0 fs and a large, multiple time step integration with time steps of 3.5 fs (for fast motions) and 7.0 fs (for slower motions). We also confirm that the multiple time step integration scheme used in this study provides more accurate energy conservations than the RESPA/C1 and is comparable to the RESPA/C2 in NAMD. In summary, the current integration scheme combining the optimized HMR with accurate temperature/pressure evaluations can provide stable and reliable MD trajectories with a larger time step, which are computationally more than 2-fold efficient compared to the conventional methods.
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Affiliation(s)
- Jaewoon Jung
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.,Computational Biophysics Research Team, RIKEN Center for Computational Science, 7-1-26 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Kento Kasahara
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, 6-7-1 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Chigusa Kobayashi
- Computational Biophysics Research Team, RIKEN Center for Computational Science, 7-1-26 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Hiraku Oshima
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, 6-7-1 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.,Computational Biophysics Research Team, RIKEN Center for Computational Science, 7-1-26 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, 6-7-1 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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22
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Reduced efficacy of a Src kinase inhibitor in crowded protein solution. Nat Commun 2021; 12:4099. [PMID: 34215742 PMCID: PMC8253829 DOI: 10.1038/s41467-021-24349-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 06/14/2021] [Indexed: 12/22/2022] Open
Abstract
The inside of a cell is highly crowded with proteins and other biomolecules. How proteins express their specific functions together with many off-target proteins in crowded cellular environments is largely unknown. Here, we investigate an inhibitor binding with c-Src kinase using atomistic molecular dynamics (MD) simulations in dilute as well as crowded protein solution. The populations of the inhibitor, 4-amino-5-(4-methylphenyl)-7-(t-butyl)pyrazolo[3,4-d]pyrimidine (PP1), in bulk solution and on the surface of c-Src kinase are reduced as the concentration of crowder bovine serum albumins (BSAs) increases. This observation is consistent with the reduced PP1 inhibitor efficacy in experimental c-Src kinase assays in addition with BSAs. The crowded environment changes the major binding pathway of PP1 toward c-Src kinase compared to that in dilute solution. This change is explained based on the population shift mechanism of local conformations near the inhibitor binding site in c-Src kinase.
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23
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Ekimoto T, Kudo T, Yamane T, Ikeguchi M. Mechanism of Vitamin D Receptor Ligand-Binding Domain Regulation Studied by gREST Simulations. J Chem Inf Model 2021; 61:3625-3637. [PMID: 34189910 DOI: 10.1021/acs.jcim.1c00534] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The vitamin D receptor ligand-binding domain (VDR-LBD) undergoes conformational changes upon ligand binding. In this nuclear receptor family, agonistic or antagonistic activities are controlled by the conformation of the helix (H)12. However, all crystal structures of VDR-LBD reported to date correspond to the active H12 conformation, regardless of agonist/antagonist binding. To understand the mechanism of VDR-LBD regulation structurally, conformational samplings of agonist- and antagonist-bound rat VDR-LBD were performed using the generalized replica exchange with solute tempering (gREST) method. The gREST simulations demonstrated different structural responses of rat VDR-LBD to agonist or antagonist binding, whereas in conventional molecular dynamics simulations, the conformation was the same as that of the crystal structures, regardless of agonist/antagonist binding. In the gREST simulations, a spontaneous conformational change of H12 was observed only for the antagonist complex. The different responses to agonist/antagonist binding were attributed to hydrophobic core formation at the ligand-binding pocket and cooperative rearrangements of H11. The gREST method can be applied to the examination of structure-activity relationships for multiple VDR-LBD ligands.
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Affiliation(s)
- Toru Ekimoto
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Takafumi Kudo
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Tsutomu Yamane
- Center for Computational Science, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Mitsunori Ikeguchi
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.,Center for Computational Science, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
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24
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Ren W, Dokainish HM, Shinobu A, Oshima H, Sugita Y. Unraveling the Coupling between Conformational Changes and Ligand Binding in Ribose Binding Protein Using Multiscale Molecular Dynamics and Free-Energy Calculations. J Phys Chem B 2021; 125:2898-2909. [PMID: 33728914 PMCID: PMC10954230 DOI: 10.1021/acs.jpcb.0c11600] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Conformational changes of proteins upon ligand binding are usually explained in terms of several mechanisms including the induced fit, conformational selection, or their mixtures. Due to the slow time scales, conventional molecular dynamics (cMD) simulations based on the atomistic models cannot easily simulate the open-to-closed conformational transition in proteins. In our previous study, we have developed an enhanced sampling scheme (generalized replica exchange with solute tempering selected surface charged residues: gREST_SSCR) for multidomain proteins and applied it to ligand-mediated conformational changes in the G134R mutant of ribose-binding protein (RBPG134R) in solution. The free-energy landscape (FEL) of RBPG134R in the presence of a ribose at the binding site included the open and closed states and two intermediates, open-like and closed-like forms. Only the open and open-like forms existed in the FEL without a ribose. In the current study, the coupling between the conformational changes and ligand binding is further investigated using coarse-grained MD, multiple atomistic cMD, and free-energy calculations. The ribose is easily dissociated from the binding site of wild-type RBP and RBPG134R in the cMD simulations starting from the open and open-like forms. In contrast, it is stable at the binding site in the simulations from the closed and closed-like forms. The free-energy calculations provide the binding affinities of different structures, supporting the results of cMD simulations. Importantly, cMD simulations from the closed-like structures reveal transitions toward the closed one in the presence of a bound ribose. On the basis of the computational results, we propose a molecular mechanism in which conformational selection and induced fit happen in the first and second halves of the open-to-closed transition in RBP, respectively.
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Affiliation(s)
- Weitong Ren
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Hisham M. Dokainish
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Ai Shinobu
- Laboratory
for Biomolecular Function Simulation, RIKEN
Center for Biosystems Dynamics Research, Integrated Innovation Building 7F, 6-7-1 minatojima-minamimachi,
Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Hiraku Oshima
- Laboratory
for Biomolecular Function Simulation, RIKEN
Center for Biosystems Dynamics Research, Integrated Innovation Building 7F, 6-7-1 minatojima-minamimachi,
Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Integrated Innovation Building 7F, 6-7-1 minatojima-minamimachi,
Chuo-ku, Kobe, Hyogo 650-0047, Japan
- Laboratory
for Biomolecular Function Simulation, RIKEN
Center for Biosystems Dynamics Research, Integrated Innovation Building 7F, 6-7-1 minatojima-minamimachi,
Chuo-ku, Kobe, Hyogo 650-0047, Japan
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25
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Red-Edge Excitation Shift Spectroscopy (REES): Application to Hidden Bound States of Ligands in Protein-Ligand Complexes. Int J Mol Sci 2021; 22:ijms22052582. [PMID: 33806656 PMCID: PMC7961384 DOI: 10.3390/ijms22052582] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 02/24/2021] [Accepted: 02/26/2021] [Indexed: 01/13/2023] Open
Abstract
Ligand-protein binding is responsible for the vast majority of bio-molecular functions. Most experimental techniques examine the most populated ligand-bound state. The determination of less populated, intermediate, and transient bound states is experimentally challenging. However, hidden bound states are also important because these can strongly influence ligand binding and unbinding processes. Here, we explored the use of a classical optical spectroscopic technique, red-edge excitation shift spectroscopy (REES) to determine the number, population, and energetics associated with ligand-bound states in protein–ligand complexes. We describe a statistical mechanical model of a two-level fluorescent ligand located amongst a finite number of discrete protein microstates. We relate the progressive emission red shift with red-edge excitation to thermodynamic parameters underlying the protein–ligand free energy landscape and to photo-physical parameters relating to the fluorescent ligand. We applied the theoretical model to published red-edge excitation shift data from small molecule inhibitor–kinase complexes. The derived thermodynamic parameters allowed dissection of the energetic contribution of intermediate bound states to inhibitor–kinase interactions.
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26
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Abdelsattar AS, Mansour Y, Aboul-Ela F. The Perturbed Free-Energy Landscape: Linking Ligand Binding to Biomolecular Folding. Chembiochem 2021; 22:1499-1516. [PMID: 33351206 DOI: 10.1002/cbic.202000695] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/19/2020] [Indexed: 12/24/2022]
Abstract
The effects of ligand binding on biomolecular conformation are crucial in drug design, enzyme mechanisms, the regulation of gene expression, and other biological processes. Descriptive models such as "lock and key", "induced fit", and "conformation selection" are common ways to interpret such interactions. Another historical model, linked equilibria, proposes that the free-energy landscape (FEL) is perturbed by the addition of ligand binding energy for the bound population of biomolecules. This principle leads to a unified, quantitative theory of ligand-induced conformation change, building upon the FEL concept. We call the map of binding free energy over biomolecular conformational space the "binding affinity landscape" (BAL). The perturbed FEL predicts/explains ligand-induced conformational changes conforming to all common descriptive models. We review recent experimental and computational studies that exemplify the perturbed FEL, with emphasis on RNA. This way of understanding ligand-induced conformation dynamics motivates new experimental and theoretical approaches to ligand design, structural biology and systems biology.
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Affiliation(s)
- Abdallah S Abdelsattar
- Center for X-Ray Determination of the Structure of Matter, Zewail City of Science and Technology, Ahmed Zewail Road, October Gardens, 12578, Giza, Egypt
| | - Youssef Mansour
- Center for X-Ray Determination of the Structure of Matter, Zewail City of Science and Technology, Ahmed Zewail Road, October Gardens, 12578, Giza, Egypt
| | - Fareed Aboul-Ela
- Center for X-Ray Determination of the Structure of Matter, Zewail City of Science and Technology, Ahmed Zewail Road, October Gardens, 12578, Giza, Egypt
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27
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Abstract
Every protein has a story-how it folds, what it binds, its biological actions, and how it misbehaves in aging or disease. Stories are often inferred from a protein's shape (i.e., its structure). But increasingly, stories are told using computational molecular physics (CMP). CMP is rooted in the principled physics of driving forces and reveals granular detail of conformational populations in space and time. Recent advances are accessing longer time scales, larger actions, and blind testing, enabling more of biology's stories to be told in the language of atomistic physics.
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Affiliation(s)
- Emiliano Brini
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Carlos Simmerling
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA.,Department of Chemistry, Stony Brook University, Stony Brook, NY 11794, USA
| | - Ken Dill
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA. .,Department of Chemistry, Stony Brook University, Stony Brook, NY 11794, USA.,Department of Physics and Astronomy, Stony Brook University, Stony Brook, New NY 11794, USA
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28
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Spitaleri A, Zia SR, Di Micco P, Al-Lazikani B, Soler MA, Rocchia W. Tuning Local Hydration Enables a Deeper Understanding of Protein-Ligand Binding: The PP1-Src Kinase Case. J Phys Chem Lett 2021; 12:49-58. [PMID: 33300337 PMCID: PMC7812613 DOI: 10.1021/acs.jpclett.0c03075] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 12/03/2020] [Indexed: 05/13/2023]
Abstract
Water plays a key role in biomolecular recognition and binding. Despite the development of several computational and experimental approaches, it is still challenging to comprehensively characterize water-mediated effects on the binding process. Here, we investigate how water affects the binding of Src kinase to one of its inhibitors, PP1. Src kinase is a target for treating several diseases, including cancer. We use biased molecular dynamics simulations, where the hydration of predetermined regions is tuned at will. This computational technique efficiently accelerates the SRC-PP1 binding simulation and allows us to identify several key and yet unexplored aspects of the solvent's role. This study provides a further perspective on the binding phenomenon, which may advance the current drug design approaches for the development of new kinase inhibitors.
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Affiliation(s)
- Andrea Spitaleri
- CONCEPT
Lab, Istituto Italiano di Tecnologia, via Morego 30, Genoa I-16163, Italy
- Center
for Omics Sciences, Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Syeda R. Zia
- CONCEPT
Lab, Istituto Italiano di Tecnologia, via Morego 30, Genoa I-16163, Italy
- Dr.
Panjwani Center for Molecular Medicine and Drug Research, International
Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan
| | - Patrizio Di Micco
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Bissan Al-Lazikani
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Miguel A. Soler
- CONCEPT
Lab, Istituto Italiano di Tecnologia, via Morego 30, Genoa I-16163, Italy
| | - Walter Rocchia
- CONCEPT
Lab, Istituto Italiano di Tecnologia, via Morego 30, Genoa I-16163, Italy
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29
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Abstract
Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.
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30
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Dokainish HM, Sugita Y. Exploring Large Domain Motions in Proteins Using Atomistic Molecular Dynamics with Enhanced Conformational Sampling. Int J Mol Sci 2020; 22:ijms22010270. [PMID: 33383937 PMCID: PMC7796230 DOI: 10.3390/ijms22010270] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 12/23/2020] [Accepted: 12/25/2020] [Indexed: 11/26/2022] Open
Abstract
Conformational transitions in multidomain proteins are essential for biological functions. The Apo conformations are typically open and flexible, while the Holo states form more compact conformations stabilized by protein-ligand interactions. Unfortunately, the atomically detailed mechanisms for such open-closed conformational changes are difficult to be accessed experimentally as well as computationally. To simulate the transitions using atomistic molecular dynamics (MD) simulations, efficient conformational sampling algorithms are required. In this work, we propose a new approach based on generalized replica-exchange with solute tempering (gREST) for exploring the open-closed conformational changes in multidomain proteins. Wherein, selected surface charged residues in a target protein are defined as the solute region in gREST simulation and the solute temperatures are different in replicas and exchanged between them to enhance the domain motions. This approach is called gREST selected surface charged residues (gREST_SSCR) and is applied to the Apo and Holo states of ribose binding protein (RBP) in solution. The conformational spaces sampled with gREST_SSCR are much wider than those with the conventional MD, sampling open-closed conformational changes while maintaining RBP domains’ stability. The free-energy landscapes of RBP in the Apo and Holo states are drawn along with twist and hinge angles of the two moving domains. The inter-domain salt-bridges that are not observed in the experimental structures are also important in the intermediate states during the conformational changes.
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Affiliation(s)
- Hisham M. Dokainish
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan;
| | - Yuji Sugita
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan;
- RIKEN Center for Computational Science, Integrated Innovation Building 7F, 6-7-1 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
- RIKEN Center for Biosystems Dynamics Research, Integrated Innovation Building 7F, 6-7-1 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
- Correspondence: ; Tel.: +81-48-462-1407
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31
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Kim S, Oshima H, Zhang H, Kern NR, Re S, Lee J, Roux B, Sugita Y, Jiang W, Im W. CHARMM-GUI Free Energy Calculator for Absolute and Relative Ligand Solvation and Binding Free Energy Simulations. J Chem Theory Comput 2020; 16:7207-7218. [PMID: 33112150 DOI: 10.1021/acs.jctc.0c00884] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Alchemical free energy simulations have long been utilized to predict free energy changes for binding affinity and solubility of small molecules. However, while the theoretical foundation of these methods is well established, seamlessly handling many of the practical aspects regarding the preparation of the different thermodynamic end states of complex molecular systems and the numerous processing scripts often remains a burden for successful applications. In this work, we present CHARMM-GUI Free Energy Calculator (http://www.charmm-gui.org/input/fec) that provides various alchemical free energy perturbation molecular dynamics (FEP/MD) systems with input and post-processing scripts for NAMD and GENESIS. Four submodules are available: Absolute Ligand Binder (for absolute ligand binding FEP/MD), Relative Ligand Binder (for relative ligand binding FEP/MD), Absolute Ligand Solvator (for absolute ligand solvation FEP/MD), and Relative Ligand Solvator (for relative ligand solvation FEP/MD). Each module is designed to build multiple systems of a set of selected ligands at once for high-throughput FEP/MD simulations. The capability of Free Energy Calculator is illustrated by absolute and relative solvation FEP/MD of a set of ligands and absolute and relative binding FEP/MD of a set of ligands for T4-lysozyme in solution and the adenosine A2A receptor in a membrane. The calculated free energy values are overall consistent with the experimental and published free energy results (within ∼1 kcal/mol). We hope that Free Energy Calculator is useful to carry out high-throughput FEP/MD simulations in the field of biomolecular sciences and drug discovery.
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Affiliation(s)
- Seonghoon Kim
- Department of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, United States.,School of Computational Sciences, Korea Institute for Advanced Study, Seoul 02455, Republic of Korea
| | - Hiraku Oshima
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Japan
| | - Han Zhang
- Department of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, United States
| | - Nathan R Kern
- Department of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, United States
| | - Suyong Re
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Japan
| | - Jumin Lee
- Department of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, United States
| | - Benoît Roux
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, Illinois 60637, United States
| | - Yuji Sugita
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Japan.,Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe 650-0047, Japan.,Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako 351-0198, Japan
| | - Wei Jiang
- Leadership Computing Facility, Argonne National Laboratory, Argonne, Illinois 60439, United States
| | - Wonpil Im
- Department of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, United States
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32
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Krah A, Huber RG, McMillan DGG, Bond PJ. The Molecular Basis for Purine Binding Selectivity in the Bacterial ATP Synthase ϵ Subunit. Chembiochem 2020; 21:3249-3254. [PMID: 32608105 DOI: 10.1002/cbic.202000291] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 06/30/2020] [Indexed: 12/21/2022]
Abstract
The ϵ subunit of ATP synthases has been proposed to regulate ATP hydrolysis in bacteria. Prevailing evidence supports the notion that when the ATP concentration falls below a certain threshold, the ϵ subunit changes its conformation from a non-inhibitory down-state to an extended up-state that then inhibits enzymatic ATP hydrolysis by binding to the catalytic domain. It has been demonstrated that the ϵ subunit from Bacillus PS3 is selective for ATP over other nucleotides, including GTP. In this study, the purine triphosphate selectivity is rationalized by using results from MD simulations and free energy calculations for the R103A/R115A mutant of the ϵ subunit from Bacillus PS3, which binds ATP more strongly than the wild-type protein. Our results are in good agreement with experimental data, and the elucidated molecular basis for selectivity could help to guide the design of novel GTP sensors.
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Affiliation(s)
- Alexander Krah
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Str. #07-01 Matrix, Singapore, 138671, Singapore.,Korea Institute for Advanced Study, School of Computational Sciences, 85 Hoegiro, Dongdaemun-gu, Seoul, 02455, Republic of Korea
| | - Roland G Huber
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Str. #07-01 Matrix, Singapore, 138671, Singapore
| | - Duncan G G McMillan
- Delft University of Technology, Department of Biotechnology, Van der Maasweg 9, Delft, 2629HZ, The Netherlands
| | - Peter J Bond
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis Str. #07-01 Matrix, Singapore, 138671, Singapore.,National University of Singapore, Department of Biological Sciences, 14 Science Drive 4, Singapore, 117543, Singapore
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33
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Oshima H, Re S, Sugita Y. Prediction of Protein–Ligand Binding Pose and Affinity Using the gREST+FEP Method. J Chem Inf Model 2020; 60:5382-5394. [DOI: 10.1021/acs.jcim.0c00338] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Hiraku Oshima
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Integrated Innovation Building 7F, 6-7-1 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Suyong Re
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Integrated Innovation Building 7F, 6-7-1 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Integrated Innovation Building 7F, 6-7-1 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Integrated Innovation Building 7F, 6-7-1 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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34
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Sugita M, Hamano M, Kasahara K, Kikuchi T, Hirata F. New Protocol for Predicting the Ligand-Binding Site and Mode Based on the 3D-RISM/KH Theory. J Chem Theory Comput 2020; 16:2864-2876. [PMID: 32176492 DOI: 10.1021/acs.jctc.9b01069] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
An efficient algorithm to find the binding position and mode of small ligands bound at an active site of protein is proposed based on the spatial distribution function (SDF) obtained from the three-dimensional reference interaction site model (3D-RISM) theory with the Kovalenko-Hirata (KH) closure relation. The ligand examined includes hydrophobic, acidic, and basic molecules and zwitterions. Eighteen different types of proteins, which serve as targets for those ligands, are selected to examine the robustness of the algorithm. An imaginary atom, referred to as an "anchor site", is defined at the center of geometry of a ligand molecule that serves as a center for searching the binding position and mode of the ligand molecule in the translational and rotational spaces. The probable binding sites (PBSs) are identified based on the SDFs of the ligand molecules around the protein, and the PBS is ranked according to the peak height of SDF. The deviations from the mean height of the peak values of SDFs for 50 PBSs are analyzed based on the z-score, which is a measure of prominence of the site. The PBS found at the closest distance from the anchor site of the crystal structure is referred to as the "nearest site". The orientation of the ligand molecule at each PBS is explored by changing the Euler angles, and the most probable binding mode is determined based on the superposition approximation. The binding position of ligand molecules is successfully predicted as one of the distinct peaks in SDF of the anchor site, with a few exceptions. The binding mode of the ligand molecule predicted based on the superposition approximation is consistent with the X-ray crystal structure in nine systems, a half of the systems investigated. The significance of the results is discussed in detail. An application of the new protocol to fragment-based drug discovery is suggested.
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Affiliation(s)
- Masatake Sugita
- Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1, Noji-higashi, Kusatsu, Shiga 525-8577, Japan.,Department of Computer Science, School of Computing, Tokyo Institute of Technology, W8-76, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550, Japan
| | - Masataka Hamano
- Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1, Noji-higashi, Kusatsu, Shiga 525-8577, Japan
| | - Kota Kasahara
- Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1, Noji-higashi, Kusatsu, Shiga 525-8577, Japan
| | - Takeshi Kikuchi
- Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1, Noji-higashi, Kusatsu, Shiga 525-8577, Japan
| | - Fumio Hirata
- Toyota Physical and Chemical Research Institute, 41-1, Yokomichi, Nagakute, Aichi 480-1192, Japan
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35
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Timr S, Madern D, Sterpone F. Protein thermal stability. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2020; 170:239-272. [PMID: 32145947 DOI: 10.1016/bs.pmbts.2019.12.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Proteins, in general, fold to a well-organized three-dimensional structure in order to function. The stability of this functional shape can be perturbed by external environmental conditions, such as temperature. Understanding the molecular factors underlying the resistance of proteins to the thermal stress has important consequences. First of all, it can aid the design of thermostable enzymes able to perform efficient catalysis in the high-temperature regime. Second, it is an essential brick of knowledge required to decipher the evolutionary pathways of life adaptation on Earth. Thanks to the development of atomistic simulations and ad hoc enhanced sampling techniques, it is now possible to investigate this problem in silico, and therefore provide support to experiments. After having described the methodological aspects, the chapter proposes an extended discussion on two problems. First, we focus on thermophilic proteins, a perfect model to address the issue of thermal stability and molecular evolution. Second, we discuss the issue of how protein thermal stability is affected by crowded in vivo-like conditions.
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Affiliation(s)
- Stepan Timr
- CNRS, Université de Paris, UPR 9080, Laboratoire de Biochimie Théorique, Paris, France; Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | | | - Fabio Sterpone
- CNRS, Université de Paris, UPR 9080, Laboratoire de Biochimie Théorique, Paris, France; Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, Paris, France.
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36
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Oshima H, Re S, Sugita Y. Replica-Exchange Umbrella Sampling Combined with Gaussian Accelerated Molecular Dynamics for Free-Energy Calculation of Biomolecules. J Chem Theory Comput 2019; 15:5199-5208. [PMID: 31539245 DOI: 10.1021/acs.jctc.9b00761] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
We have developed an enhanced conformational sampling method combining replica-exchange umbrella sampling (REUS) with Gaussian accelerated molecular dynamics (GaMD). REUS enhances the sampling along predefined reaction coordinates, while GaMD accelerates the conformational dynamics by adding a boost potential to the system energy. The method, which we call GaREUS (Gaussian accelerated replica-exchange umbrella sampling), enhances the sampling more efficiently than REUS or GaMD, while the computational resource for GaREUS is the same as that required for REUS. The two-step reweighting procedure using the multistate Bennett acceptance ratio method and the cumulant expansion for the exponential average is applied to the simulation trajectories for obtaining the unbiased free-energy landscapes. We apply GaREUS to the calculations of free-energy landscapes for three different cases: conformational equilibria of N-glycan, folding of chignolin, and conformational change of adenyl kinase. We show that GaREUS speeds up the convergences of free-energy calculations using the same amount of computational resources as REUS. The free-energy landscapes reweighted from the trajectories of GaREUS agree with previously reported ones. GaREUS is applicable to free-energy calculations of various biomolecular dynamics and functions with reasonable computational costs.
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Affiliation(s)
- Hiraku Oshima
- Laboratory for Biomolecular Function Simulation , RIKEN Center for Biosystems Dynamics Research , Integrated Innovation Building N702, 6-7-1 Minatojima-minamimachi, Chuo-ku , Kobe , Hyogo 650-0047 , Japan
| | - Suyong Re
- Laboratory for Biomolecular Function Simulation , RIKEN Center for Biosystems Dynamics Research , Integrated Innovation Building N702, 6-7-1 Minatojima-minamimachi, Chuo-ku , Kobe , Hyogo 650-0047 , Japan
| | - Yuji Sugita
- Laboratory for Biomolecular Function Simulation , RIKEN Center for Biosystems Dynamics Research , Integrated Innovation Building N702, 6-7-1 Minatojima-minamimachi, Chuo-ku , Kobe , Hyogo 650-0047 , Japan.,Theoretical Molecular Science Laboratory , RIKEN Cluster for Pioneering Research , 2-1 Hirosawa, Wako-shi , Saitama 351-0198 , Japan.,Computational Biophysics Research Team , RIKEN Center for Computational Science , Integrated Innovation Building N702, 6-7-1 Minatojima-minamimachi, Chuo-ku , Kobe , Hyogo 650-0047 , Japan
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