1
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Lazou M, Kozakov D, Joseph-McCarthy D, Vajda S. Which cryptic sites are feasible drug targets? Drug Discov Today 2024; 29:104197. [PMID: 39368697 DOI: 10.1016/j.drudis.2024.104197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Revised: 09/18/2024] [Accepted: 09/30/2024] [Indexed: 10/07/2024]
Abstract
Cryptic sites can expand the space of druggable proteins, but the potential usefulness of such sites needs to be investigated before any major effort. Given that the binding pockets are not formed, the druggability of such sites is not well understood. The analysis of proteins and their ligands shows that cryptic sites that are formed primarily by the motion of side chains moving out of the pocket to enable ligand binding generally do not bind drug-sized molecules with sufficient potency. By contrast, sites that are formed by loop or hinge motion are potentially valuable drug targets. Arguments are provided to explain the underlying causes in terms of classical enzyme inhibition theory and the kinetics of side chain motion and ligand binding.
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Affiliation(s)
- Maria Lazou
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, USA; Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Diane Joseph-McCarthy
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Department of Chemistry, Boston University, Boston, MA 02215, USA
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Department of Chemistry, Boston University, Boston, MA 02215, USA.
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2
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Kaushik S, Hung TI, Chang CA. Molecular mechanics studies of factors affecting overall rate in cascade reactions: Multi-enzyme colocalization and environment. Protein Sci 2024; 33:e5175. [PMID: 39276014 PMCID: PMC11401055 DOI: 10.1002/pro.5175] [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: 02/01/2024] [Revised: 08/27/2024] [Accepted: 08/29/2024] [Indexed: 09/16/2024]
Abstract
Millions of years of evolution have optimized many biosynthetic pathways by use of multi-step catalysis. In addition, multi-step metabolic pathways are commonly found in and on membrane-bound organelles in eukaryotic biochemistry. The fundamental mechanisms that facilitate these reaction processes provide strategies to bioengineer metabolic pathways in synthetic chemistry. Using Brownian dynamics simulations, here we modeled intermediate substrate transportation of colocalized yeast-ester biosynthesis enzymes on the membrane. The substrate acetate ion traveled from the pocket of aldehyde dehydrogenase to its target enzyme acetyl-CoA synthetase, then the substrate acetyl CoA diffused from Acs1 to the active site of the next enzyme, alcohol-O-acetyltransferase. Arranging two enzymes with the smallest inter-enzyme distance of 60 Å had the fastest average substrate association time as compared with anchoring enzymes with larger inter-enzyme distances. When the off-target side reactions were turned on, most substrates were lost, which suggests that native localization is necessary for efficient final product synthesis. We also evaluated the effects of intermolecular interactions, local substrate concentrations, and membrane environment to bring mechanistic insights into the colocalization pathways. The computation work demonstrates that creating spatially organized multi-enzymes on membranes can be an effective strategy to increase final product synthesis in bioengineering systems.
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Affiliation(s)
- Shivansh Kaushik
- Department of ChemistryUniversity of California RiversideRiversideCaliforniaUSA
| | - Ta I Hung
- Department of ChemistryUniversity of California RiversideRiversideCaliforniaUSA
| | - Chia‐en A. Chang
- Department of ChemistryUniversity of California RiversideRiversideCaliforniaUSA
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3
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Hazarika S, Yu T, Biswas A, Dube N, Villalona P, Okafor CD. Nuclear Receptor Interdomain Communication is Mediated by the Hinge with Ligand Specificity. J Mol Biol 2024; 436:168805. [PMID: 39332668 DOI: 10.1016/j.jmb.2024.168805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 09/20/2024] [Accepted: 09/23/2024] [Indexed: 09/29/2024]
Abstract
Nuclear receptors are ligand-induced transcription factors that bind directly to target genes and regulate their expression. Ligand binding initiates conformational changes that propagate to other domains, allosterically regulating their activity. The nature of this interdomain communication in nuclear receptors is poorly understood, largely owing to the difficulty of experimentally characterizing full-length structures. We have applied computational modeling approaches to describe and study the structure of the full-length farnesoid X receptor (FXR), approximated by the DNA binding domain (DBD) and ligand binding domain (LBD) connected by the flexible hinge region. Using extended molecular dynamics simulations (>10 microseconds) and enhanced sampling simulations, we provide evidence that ligands selectively induce domain rearrangement, leading to interdomain contact. We use protein-protein interaction assays to provide experimental evidence of these interactions, identifying a critical role of the hinge in mediating interdomain contact. Our results illuminate previously unknown aspects of interdomain communication in FXR and provide a framework to enable characterization of other full-length nuclear receptors.
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Affiliation(s)
- Saurov Hazarika
- Department of Chemistry, Pennsylvania State University, University Park, PA 16802, USA
| | - Tracy Yu
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Arumay Biswas
- Department of Chemistry, Pennsylvania State University, University Park, PA 16802, USA
| | - Namita Dube
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Priscilla Villalona
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - C Denise Okafor
- Department of Chemistry, Pennsylvania State University, University Park, PA 16802, USA; Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA.
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4
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Shi D, Zhu X, Zhang H, Yan J, Bai C. Catalytic mechanism study of ATP-citrate lyase during citryl-CoA synthesis process. iScience 2024; 27:110605. [PMID: 39220258 PMCID: PMC11365397 DOI: 10.1016/j.isci.2024.110605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 06/03/2024] [Accepted: 07/25/2024] [Indexed: 09/04/2024] Open
Abstract
ATP-citrate lyase (ACLY) is a critical metabolic enzyme and promising target for drug development. The structure determinations of ACLY have revealed its homotetramer states with various subunit symmetries, but catalytic mechanism of ACLY tetramer and the importance of subunit symmetry have not been clarified. Here, we constructed the free energy landscape of ACLY tetramer with arbitrary subunit symmetries and investigated energetic and conformational coupling of subunits during citryl-CoA synthesis process. The optimal conformational pathway indicates that ACLY tetramer encounters three critical conformational barriers and undergoes a loss of rigid-D2 symmetry to gain an energetic advantage. Energetic coupling of conformational changes and biochemical reactions suggests that these biological events are not independent but rather coupled with each other, showing a comparable energy barrier to the experimental data for the rate-limiting step. These findings could contribute to further research on catalytic mechanism, functional modulation, and inhibitor design of ACLY.
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Affiliation(s)
- Danfeng Shi
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen 518172, Guangdong, People's Republic of China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China
- Xuzhou College of Industrial Technology, Xuzhou 221140, China
| | - Xiaohong Zhu
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen 518172, Guangdong, People's Republic of China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China
| | - Honghui Zhang
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen 518172, Guangdong, People's Republic of China
| | - Junfang Yan
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen 518172, Guangdong, People's Republic of China
| | - Chen Bai
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen 518172, Guangdong, People's Republic of China
- Chenzhu Biotechnology Co., Ltd, Hangzhou 310005, China
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5
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Riccabona JR, Spoendlin FC, Fischer ALM, Loeffler JR, Quoika PK, Jenkins TP, Ferguson JA, Smorodina E, Laustsen AH, Greiff V, Forli S, Ward AB, Deane CM, Fernández-Quintero ML. Assessing AF2's ability to predict structural ensembles of proteins. Structure 2024:S0969-2126(24)00370-8. [PMID: 39332396 DOI: 10.1016/j.str.2024.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 08/07/2024] [Accepted: 09/02/2024] [Indexed: 09/29/2024]
Abstract
Recent breakthroughs in protein structure prediction have enhanced the precision and speed at which protein configurations can be determined. Additionally, molecular dynamics (MD) simulations serve as a crucial tool for capturing the conformational space of proteins, providing valuable insights into their structural fluctuations. However, the scope of MD simulations is often limited by the accessible timescales and the computational resources available, posing challenges to comprehensively exploring protein behaviors. Recently emerging approaches have focused on expanding the capability of AlphaFold2 (AF2) to predict conformational substates of protein. Here, we benchmark the performance of various workflows that have adapted AF2 for ensemble prediction and compare the obtained structures with ensembles obtained from MD simulations and NMR. We provide an overview of the levels of performance and accessible timescales that can currently be achieved with machine learning (ML) based ensemble generation. Significant minima of the free energy surfaces remain undetected.
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Affiliation(s)
- Jakob R Riccabona
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innsbruck, Austria
| | - Fabian C Spoendlin
- Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford OX1 3LB, UK
| | - Anna-Lena M Fischer
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innsbruck, Austria
| | - Johannes R Loeffler
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Patrick K Quoika
- Center for Functional Protein Assemblies, Technical University of Munich, Ernst-Otto-Fischer-Str. 8, 85748 Garching, Germany
| | - Timothy P Jenkins
- Department of Biotechnology and Biomedicine, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark
| | - James A Ferguson
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Eva Smorodina
- Department of Immunology, University of Oslo, Oslo, Norway
| | - Andreas H Laustsen
- Department of Biotechnology and Biomedicine, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark
| | - Victor Greiff
- Department of Immunology, University of Oslo, Oslo, Norway
| | - Stefano Forli
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Andrew B Ward
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA.
| | - Charlotte M Deane
- Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford OX1 3LB, UK.
| | - Monica L Fernández-Quintero
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innsbruck, Austria; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA; Department of Biotechnology and Biomedicine, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark.
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6
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Babbitt GA, Rajendran M, Lynch ML, Asare-Bediako R, Mouli LT, Ryan CJ, Srivastava H, Rynkiewicz P, Phadke K, Reed ML, Moore N, Ferran MC, Fokoue EP. ATOMDANCE: Kernel-based denoising and choreographic analysis for protein dynamic comparison. Biophys J 2024; 123:2705-2715. [PMID: 38515299 PMCID: PMC11393699 DOI: 10.1016/j.bpj.2024.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/16/2023] [Accepted: 03/19/2024] [Indexed: 03/23/2024] Open
Abstract
Comparative methods in molecular evolution and structural biology rely heavily upon the site-wise analysis of DNA sequence and protein structure, both static forms of information. However, it is widely accepted that protein function results from nanoscale nonrandom machine-like motions induced by evolutionarily conserved molecular interactions. Comparisons of molecular dynamics (MD) simulations conducted between homologous sites representative of different functional or mutational states can potentially identify local effects on binding interaction and protein evolution. In addition, comparisons of different (i.e., nonhomologous) sites within MD simulations could be employed to identify functional shifts in local time-coordinated dynamics indicative of logic gating within proteins. However, comparative MD analysis is challenged by the large fraction of protein motion caused by random thermal noise in the surrounding solvent. Therefore, properly denoised MD comparisons could reveal functional sites involving these machine-like dynamics with good accuracy. Here, we introduce ATOMDANCE, a user-interfaced suite of comparative machine learning-based denoising tools designed for identifying functional sites and the patterns of coordinated motion they can create within MD simulations. ATOMDANCE-maxDemon4.0 employs Gaussian kernel functions to compute site-wise maximum mean discrepancy between learned features of motion, thereby assessing denoised differences in the nonrandom motions between functional or evolutionary states (e.g., ligand bound versus unbound, wild-type versus mutant). ATOMDANCE-maxDemon4.0 also employs maximum mean discrepancy to analyze potential random amino acid replacements allowing for a site-wise test of neutral versus nonneutral evolution on the divergence of dynamic function in protein homologs. Finally, ATOMDANCE-Choreograph2.0 employs mixed-model analysis of variance and graph network to detect regions where time-synchronized shifts in dynamics occur. Here, we demonstrate ATOMDANCE's utility for identifying key sites involved in dynamic responses during functional binding interactions involving DNA, small-molecule drugs, and virus-host recognition, as well as understanding shifts in global and local site coordination occurring during allosteric activation of a pathogenic protease.
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Affiliation(s)
- Gregory A Babbitt
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, New York.
| | - Madhusudan Rajendran
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, New York
| | - Miranda L Lynch
- Hauptmann Woodward Medical Research Institute, Buffalo, New York
| | - Richmond Asare-Bediako
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, New York
| | - Leora T Mouli
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, New York
| | - Cameron J Ryan
- McQuaid Jesuit High School Computer Club, Rochester, New York
| | | | - Patrick Rynkiewicz
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, New York
| | - Kavya Phadke
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, New York
| | - Makayla L Reed
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, New York
| | - Nadia Moore
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, New York
| | - Maureen C Ferran
- Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, New York
| | - Ernest P Fokoue
- School of Mathematical Sciences, Rochester Institute of Technology, Rochester, New York.
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7
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van Gunsteren WF, Oostenbrink C. Methods for Classical-Mechanical Molecular Simulation in Chemistry: Achievements, Limitations, Perspectives. J Chem Inf Model 2024; 64:6281-6304. [PMID: 39136351 DOI: 10.1021/acs.jcim.4c00823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
More than a half century ago it became feasible to simulate, using classical-mechanical equations of motion, the dynamics of molecular systems on a computer. Since then classical-physical molecular simulation has become an integral part of chemical research. It is widely applied in a variety of branches of chemistry and has significantly contributed to the development of chemical knowledge. It offers understanding and interpretation of experimental results, semiquantitative predictions for measurable and nonmeasurable properties of substances, and allows the calculation of properties of molecular systems under conditions that are experimentally inaccessible. Yet, molecular simulation is built on a number of assumptions, approximations, and simplifications which limit its range of applicability and its accuracy. These concern the potential-energy function used, adequate sampling of the vast statistical-mechanical configurational space of a molecular system and the methods used to compute particular properties of chemical systems from statistical-mechanical ensembles. During the past half century various methodological ideas to improve the efficiency and accuracy of classical-physical molecular simulation have been proposed, investigated, evaluated, implemented in general simulation software or were abandoned. The latter because of fundamental flaws or, while being physically sound, computational inefficiency. Some of these methodological ideas are briefly reviewed and the most effective methods are highlighted. Limitations of classical-physical simulation are discussed and perspectives are sketched.
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Affiliation(s)
- Wilfred F van Gunsteren
- Institute for Molecular Physical Science, Swiss Federal Institute of Technology, ETH, CH-8093 Zurich, Switzerland
| | - Chris Oostenbrink
- Institute of Molecular Modelling and Simulation, BOKU University, 1190 Vienna, Austria
- Christian Doppler Laboratory for Molecular Informatics in the Biosciences, BOKU University, Muthgasse 18, 1190 Vienna, Austria
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8
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Mandal N, Surpeta B, Brezovsky J. Reinforcing Tunnel Network Exploration in Proteins Using Gaussian Accelerated Molecular Dynamics. J Chem Inf Model 2024; 64:6623-6635. [PMID: 39143923 DOI: 10.1021/acs.jcim.4c00966] [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: 08/16/2024]
Abstract
Tunnels are structural conduits in biomolecules responsible for transporting chemical compounds and solvent molecules from the active site. They have been shown to be present in a wide variety of enzymes across all functional and structural classes. However, the study of such pathways is experimentally challenging, because they are typically transient. Computational methods, such as molecular dynamics (MD) simulations, have been successfully proposed to explore tunnels. Conventional MD (cMD) provides structural details to characterize tunnels but suffers from sampling limitations to capture rare tunnel openings on longer time scales. Therefore, in this study, we explored the potential of Gaussian accelerated MD (GaMD) simulations to improve the exploration of complex tunnel networks in enzymes. We used the haloalkane dehalogenase LinB and its two variants with engineered transport pathways, which are not only well-known for their application potential but have also been extensively studied experimentally and computationally regarding their tunnel networks and their importance in multistep catalytic reactions. Our study demonstrates that GaMD efficiently improves tunnel sampling and allows the identification of all known tunnels for LinB and its two mutants. Furthermore, the improved sampling provided insight into a previously unknown transient side tunnel (ST). The extensive conformational landscape explored by GaMD simulations allowed us to investigate in detail the mechanism of ST opening. We determined variant-specific dynamic properties of ST opening, which were previously inaccessible due to limited sampling of cMD. Our comprehensive analysis supports multiple indicators of the functional relevance of the ST, emphasizing its potential significance beyond structural considerations. In conclusion, our research proves that the GaMD method can overcome the sampling limitations of cMD for the effective study of tunnels in enzymes, providing further means for identifying rare tunnels in enzymes with the potential for drug development, precision medicine, and rational protein engineering.
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Affiliation(s)
- Nishita Mandal
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, Poznan 61-614, Poland
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, Warsaw 02-109, Poland
| | - Bartlomiej Surpeta
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, Poznan 61-614, Poland
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, Warsaw 02-109, Poland
| | - Jan Brezovsky
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, Poznan 61-614, Poland
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, Warsaw 02-109, Poland
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9
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Williams CD, Kalayan J, Burton NA, Bryce RA. Stable and accurate atomistic simulations of flexible molecules using conformationally generalisable machine learned potentials. Chem Sci 2024; 15:12780-12795. [PMID: 39148799 PMCID: PMC11323334 DOI: 10.1039/d4sc01109k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 07/07/2024] [Indexed: 08/17/2024] Open
Abstract
Computational simulation methods based on machine learned potentials (MLPs) promise to revolutionise shape prediction of flexible molecules in solution, but their widespread adoption has been limited by the way in which training data is generated. Here, we present an approach which allows the key conformational degrees of freedom to be properly represented in reference molecular datasets. MLPs trained on these datasets using a global descriptor scheme are generalisable in conformational space, providing quantum chemical accuracy for all conformers. These MLPs are capable of propagating long, stable molecular dynamics trajectories, an attribute that has remained a challenge. We deploy the MLPs in obtaining converged conformational free energy surfaces for flexible molecules via well-tempered metadynamics simulations; this approach provides a hitherto inaccessible route to accurately computing the structural, dynamical and thermodynamical properties of a wide variety of flexible molecular systems. It is further demonstrated that MLPs must be trained on reference datasets with complete coverage of conformational space, including in barrier regions, to achieve stable molecular dynamics trajectories.
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Affiliation(s)
- Christopher D Williams
- Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester Oxford Road Manchester M13 9PL UK
| | - Jas Kalayan
- Science and Technologies Facilities Council (STFC), Daresbury Laboratory Keckwick Lane, Daresbury Warrington WA4 4AD UK
| | - Neil A Burton
- Department of Chemistry, School of Natural Sciences, Faculty of Science and Engineering, The University of Manchester Oxford Road Manchester M13 9PL UK
| | - Richard A Bryce
- Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester Oxford Road Manchester M13 9PL UK
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10
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AlRawashdeh S, Mosa FES, Barakat KH. Computational insights into the mechanisms underlying structural destabilization and recovery in trafficking-deficient hERG mutants. Front Mol Biosci 2024; 11:1341727. [PMID: 39193219 PMCID: PMC11347279 DOI: 10.3389/fmolb.2024.1341727] [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: 11/20/2023] [Accepted: 07/31/2024] [Indexed: 08/29/2024] Open
Abstract
Cardiovascular diseases are a major global health concern, responsible for a significant number of deaths each year, often linked to cardiac arrhythmias resulting from dysfunction in ion channels. Hereditary Long QT Syndrome (LQTS) is a condition characterized by a prolonged QT interval on ECG, increasing the risk of sudden cardiac death. The most common type of LQTS, LQT2, is caused by mutations in the hERG gene, affecting a potassium ion channel. The majority of these mutations disrupt the channel's trafficking to the cell membrane, leading to intracellular retention. Specific high-affinity hERG blockers (e.g., E-4031) can rescue this mutant phenotype, but the exact mechanism is unknown. This study used accelerated molecular dynamics simulations to investigate how these mutations affect the hERG channel's structure, folding, endoplasmic reticulum (ER) retention, and trafficking. We reveal that these mutations induce structural changes in the channel, narrowing its central pore and altering the conformation of the intracellular domains. These changes expose internalization signals that contribute to ER retention and degradation of the mutant hERG channels. Moreover, the study found that the trafficking rescue drug E-4031 can inhibit these structural changes, potentially rescuing the mutant channels. This research offers valuable insights into the structural issues responsible for the degradation of rescuable transmembrane trafficking mutants. Understanding the defective trafficking structure of the hERG channel could help identify binding sites for small molecules capable of restoring proper folding and facilitating channel trafficking. This knowledge has the potential to lead to mechanism-based therapies that address the condition at the cellular level, which may prove more effective than treating clinical symptoms, ultimately offering hope for individuals with hereditary Long QT Syndrome.
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Affiliation(s)
| | | | - Khaled H. Barakat
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada
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11
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Zhou J, Huang M. Navigating the landscape of enzyme design: from molecular simulations to machine learning. Chem Soc Rev 2024; 53:8202-8239. [PMID: 38990263 DOI: 10.1039/d4cs00196f] [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: 07/12/2024]
Abstract
Global environmental issues and sustainable development call for new technologies for fine chemical synthesis and waste valorization. Biocatalysis has attracted great attention as the alternative to the traditional organic synthesis. However, it is challenging to navigate the vast sequence space to identify those proteins with admirable biocatalytic functions. The recent development of deep-learning based structure prediction methods such as AlphaFold2 reinforced by different computational simulations or multiscale calculations has largely expanded the 3D structure databases and enabled structure-based design. While structure-based approaches shed light on site-specific enzyme engineering, they are not suitable for large-scale screening of potential biocatalysts. Effective utilization of big data using machine learning techniques opens up a new era for accelerated predictions. Here, we review the approaches and applications of structure-based and machine-learning guided enzyme design. We also provide our view on the challenges and perspectives on effectively employing enzyme design approaches integrating traditional molecular simulations and machine learning, and the importance of database construction and algorithm development in attaining predictive ML models to explore the sequence fitness landscape for the design of admirable biocatalysts.
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Affiliation(s)
- Jiahui Zhou
- School of Chemistry and Chemical Engineering, Queen's University, David Keir Building, Stranmillis Road, Belfast BT9 5AG, Northern Ireland, UK.
| | - Meilan Huang
- School of Chemistry and Chemical Engineering, Queen's University, David Keir Building, Stranmillis Road, Belfast BT9 5AG, Northern Ireland, UK.
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12
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Saporiti S, Bianchi D, Ben Mariem O, Rossi M, Guerrini U, Eberini I, Centola F. In silico evaluation of the role of Fab glycosylation in cetuximab antibody dynamics. Front Immunol 2024; 15:1429600. [PMID: 39185413 PMCID: PMC11342397 DOI: 10.3389/fimmu.2024.1429600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 07/23/2024] [Indexed: 08/27/2024] Open
Abstract
Introduction N-glycosylation is a post-translational modification that is highly important for the development of monoclonal antibodies (mAbs), as it regulates their biological activity, particularly in terms of immune effector functions. While typically added at the Fc level, approximately 15-25% of circulating antibodies exhibit glycosylation in the Fab domains as well. To the best of our knowledge, cetuximab (Erbitux®) is the only therapeutic antibody presenting Fab glycosylation approved world-wide targeting the epidermal growth factor receptor for the treatment of metastatic-colorectal and head and neck cancers. Additionally, it can trigger antibody-dependent cell cytotoxicity (ADCC), a response that typically is influenced by N-glycosylation at Fc level. However, the role of Fab glycosylation in cetuximab remains poorly understood. Hence, this study aims to investigate the structural role of Fab glycosylation on the conformational behavior of cetuximab. Methods The study was performed in silico via accelerated molecular dynamics simulations. The commercial cetuximab was compared to its form without Fab glycosylation and structural descriptors were evaluated to establish conformational differences. Results The results clearly show a correlation between the Fab glycosylation and structural descriptors that may modulate the conformational freedom of the antibody, potentially affecting Fc effector functions, and suggesting a negative role of Fab glycosylation on the interaction with FcγRIIIa. Conclusion Fab glycosylation of cetuximab is the most critical challenge for biosimilar development, but the differences highlighted in this work with respect to its aglycosylated form can improve the knowledge and represent also a great opportunity to develop novel strategies of biotherapeutics.
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Affiliation(s)
- Simona Saporiti
- Analytical Excellence and Program Management, Merck Serono S.p.A., Rome, Italy
| | - Davide Bianchi
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy
| | - Omar Ben Mariem
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy
| | - Mara Rossi
- Analytical Excellence and Program Management, Merck Serono S.p.A., Rome, Italy
| | - Uliano Guerrini
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy
| | - Ivano Eberini
- Dipartimento di Scienze Farmacologiche e Biomolecolari & Data Science Research Center (DSRC), Università degli Studi di Milano, Milan, Italy
| | - Fabio Centola
- Analytical Excellence and Program Management, Merck Serono S.p.A., Rome, Italy
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13
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Mitsuta Y, Asada T. Parameter Optimization Method in Multidimensional Umbrella Sampling. J Chem Theory Comput 2024. [PMID: 39101750 DOI: 10.1021/acs.jctc.4c00282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2024]
Abstract
Umbrella sampling (US) is an effective method for calculating free-energy landscapes (FELs). However, the complexity of controlling the sampling positions complicates multidimensional FEL calculations. In this study, we proposed a method for controlling sampling by optimizing the US parameters. This method comprises the introduction of a target point and the optimization of the parameters to sample a window around this point. We approximated each window to normal distributions using an umbrella integration method and calculated the divergences between the window distributions and the state distributed at the target position by a variationally enhanced sampling method. Thus, the minimization of the divergence facilitated sampling around the target point, after which the parameters could be optimized on the fly while performing equilibration simulation. In practice, our method employs bias potentials with off-diagonal terms, ensuring a more efficient calculation of multidimensional FEL. Additionally, we developed an algorithm for determining the target point for automated FEL search; the algorithm samples in a specified direction while controlling the overlap of distributions. We performed three different FEL calculations as examples: (1) the calculation of the permeation of a water molecule through a lipid bilayer (one-dimensional FEL), (2) the calculation of the internal structural changes in alanine dipeptide in water (two-dimensional FEL), and (3) the calculation of the internal structural changes from a β-strand structure to an α-helix structure in alanine decapeptide (Ala10, 16-dimensional FEL). These results confirmed that our method could control the number of US windows and calculate the high-dimensional FELs that could not be evaluated by the conventional US method.
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Affiliation(s)
- Yuki Mitsuta
- Department of Chemistry, Osaka Metropolitan University, 3-3-138, Sugimoto, Sumiyoshi-ku, Osaka 558-8585, Japan
- RIMED, Osaka Metropolitan University, 3-3-138, Sugimoto, Sumiyoshi-ku, Osaka 558-8585, Japan
| | - Toshio Asada
- Department of Chemistry, Osaka Metropolitan University, 3-3-138, Sugimoto, Sumiyoshi-ku, Osaka 558-8585, Japan
- RIMED, Osaka Metropolitan University, 3-3-138, Sugimoto, Sumiyoshi-ku, Osaka 558-8585, Japan
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14
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Wang J, Koirala K, Do HN, Miao Y. PepBinding: A Workflow for Predicting Peptide Binding Structures by Combining Peptide Docking and Peptide Gaussian Accelerated Molecular Dynamics Simulations. J Phys Chem B 2024; 128:7332-7340. [PMID: 39041172 DOI: 10.1021/acs.jpcb.4c02047] [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: 07/24/2024]
Abstract
Predicting protein-peptide interactions is crucial for understanding peptide binding processes and designing peptide drugs. However, traditional computational modeling approaches face challenges in accurately predicting peptide-protein binding structures due to the slow dynamics and high flexibility of the peptides. Here, we introduce a new workflow termed "PepBinding" for predicting peptide binding structures, which combines peptide docking, all-atom enhanced sampling simulations using the Peptide Gaussian accelerated Molecular Dynamics (Pep-GaMD) method, and structural clustering. PepBinding has been demonstrated on seven distinct model peptides. In peptide docking using HPEPDOCK, the peptide backbone root-mean-square deviations (RMSDs) of their bound conformations relative to X-ray structures ranged from 3.8 to 16.0 Å, corresponding to the medium to inaccurate quality models according to the Critical Assessment of PRediction of Interactions (CAPRI) criteria. The Pep-GaMD simulations performed for only 200 ns significantly improved the docking models, resulting in five medium and two acceptable quality models. Therefore, PepBinding is an efficient workflow for predicting peptide binding structures and is publicly available at https://github.com/MiaoLab20/PepBinding.
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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
| | - Kushal Koirala
- Computational Medicine Program and Department of Pharmacology, University of North Carolina - Chapel Hill, Chapel Hill, North Carolina 27599, United States
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina - Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Hung N Do
- Computational Biology Program, Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, 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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15
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Hasse T, Huang YMM. Multiple Parameter Replica Exchange Gaussian Accelerated Molecular Dynamics for Enhanced Sampling and Free Energy Calculation of Biomolecular Systems. J Chem Theory Comput 2024. [PMID: 39085770 DOI: 10.1021/acs.jctc.4c00501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
This study introduces a novel method named multiple parameter replica exchange Gaussian accelerated molecular dynamics (MP-Rex-GaMD), building on the Gaussian accelerated molecular dynamics (GaMD) algorithm. GaMD enhances sampling and retrieves free energy information for biomolecular systems by adding a harmonic boost potential to smooth the potential energy surface without the need for predefined reaction coordinates. Our innovative approach advances the acceleration power and energetic reweighting accuracy of GaMD by incorporating a replica exchange algorithm that enables the exchange of multiple parameters, including the GaMD boost parameters of force constant and energy threshold, as well as temperature. Applying MP-Rex-GaMD to the three model systems of dialanine, chignolin, and HIV protease, we demonstrate its superior capability over conventional molecular dynamics and GaMD simulations in exploring protein conformations and effectively navigating various biomolecular states across energy barriers. MP-Rex-GaMD allows users to accurately map free energy landscapes through energetic reweighting, capturing the ensemble of biomolecular states from low-energy conformations to rare high-energy transitions within practical computational time scales.
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Affiliation(s)
- Timothy Hasse
- Department of Physics and Astronomy, Wayne State University, Detroit, Michigan 48201, United States
| | - Yu-Ming M Huang
- Department of Physics and Astronomy, Wayne State University, Detroit, Michigan 48201, United States
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16
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Mondal S, Sauer MA, Heyden M. Exploring Conformational Landscapes Along Anharmonic Low-Frequency Vibrations. J Phys Chem B 2024; 128:7112-7120. [PMID: 38986052 DOI: 10.1021/acs.jpcb.4c02743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024]
Abstract
We aim to automatize the identification of collective variables to simplify and speed up enhanced sampling simulations of conformational dynamics in biomolecules. We focus on anharmonic low-frequency vibrations that exhibit fluctuations on time scales faster than conformational transitions but describe a path of least resistance toward structural change. A key challenge is that harmonic approximations are ill-suited to characterize these vibrations, which are observed at far-infrared frequencies and are easily excited by thermal collisions at room temperature. Here, we approached this problem with a frequency-selective anharmonic (FRESEAN) mode analysis that does not rely on harmonic approximations and successfully isolates anharmonic low-frequency vibrations from short molecular dynamics simulation trajectories. We applied FRESEAN mode analysis to simulations of alanine dipeptide, a common test system for enhanced sampling simulation protocols, and compared the performance of isolated low-frequency vibrations to conventional user-defined collective variables (here backbone dihedral angles) in enhanced sampling simulations. The comparison shows that enhanced sampling along anharmonic low-frequency vibrations not only reproduces known conformational dynamics but can even further improve the sampling of slow transitions compared to user-defined collective variables. Notably, free energy surfaces spanned by low-frequency anharmonic vibrational modes exhibit lower barriers associated with conformational transitions relative to representations in backbone dihedral space. We thus conclude that anharmonic low-frequency vibrations provide a promising path for highly effective and fully automated enhanced sampling simulations of conformational dynamics in biomolecules.
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Affiliation(s)
- Souvik Mondal
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States
| | - Michael A Sauer
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States
| | - Matthias Heyden
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States
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17
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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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18
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Joshi P, Pandey P, Rawat S, Chandra S. Repurposing of Drug Bank Compounds against Plasmodium falciparum Dihydroorotate Dehydrogenase as novel anti malarial drug candidates by Computational approaches. In Silico Pharmacol 2024; 12:60. [PMID: 38978708 PMCID: PMC11227489 DOI: 10.1007/s40203-024-00232-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 06/14/2024] [Indexed: 07/10/2024] Open
Abstract
This study aimed to repurpose Drug Bank Compounds against P. falciparum Dihydroorotate dehydrogenase (Pf-DHODH)a potential molecular target for antimalarial drug development due to its vital role in P. falciparum survival. Initially, the MATGEN server was used to screen drugs against Pf-DHODH (PDB ID 6GJG), followed by revalidating the results through docking by Autodock Vina through PyRx. Based on the docking results, three drugs namely, Talnifumate, Sulfaphenazole, and (3S)-N-[(2S)-1-[2-(1H-indol-3-yl)ethylamino]-1-oxopropan-2-yl]-1-(4-methoxyphenyl)-5-oxopyrrolidine-3-carboxamide-were subjected to molecular dynamics simulation for 100 ns. Molecular dynamics simulation results indicate that (3S)-N-[(2S)-1-[2-(1H-indol-3-yl)ethylamino]-1-oxopropan-2-yl]-1-(4-methoxyphenyl)-5-oxopyrrolidine-3-carboxamide- and Sulfaphenazole may target Pf-DHODH by forming a stable protein-ligand complex as they showed better free binding energy -130.58 kJ/mol, and -79.84 kJ/mol, respectively as compared to the free binding energy 116.255 kJ/mol of the reference compound; 3,6-dimethyl- ~ {N}-[4-(trifluoromethyl)phenyl]-[1,2]oxazolo[5,4-d]pyrimidin-4-amine. Although the studied compounds are drugs, still we applied Lipinski's rules and ADMET analysis that reconfirmed that these drugs have favorable drug-like properties. In conclusion, the results of the study show that Talniflumate and Sulfaphenazole may be potential antimalarial drug candidates.The derivatives of these drugs could be designed and tested to develop better drugs against Plasmodium species. Graphical Abstract
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Affiliation(s)
- Priyanka Joshi
- Computational Biology & Biotechnology Laboratory, Department of Botany, Soban Singh Jeena University, Almora, 263601 Uttarakhand India
| | - Pankaja Pandey
- Computational Biology & Biotechnology Laboratory, Department of Botany, Soban Singh Jeena University, Almora, 263601 Uttarakhand India
| | - Shilpi Rawat
- Computational Biology & Biotechnology Laboratory, Department of Botany, Soban Singh Jeena University, Almora, 263601 Uttarakhand India
| | - Subhash Chandra
- Computational Biology & Biotechnology Laboratory, Department of Botany, Soban Singh Jeena University, Almora, 263601 Uttarakhand India
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19
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Agarwal R, Pattarawat P, Duff MR, Wang HCR, Baudry J, Smith JC. Structure-Based Identification of Novel Histone Deacetylase 4 (HDAC4) Inhibitors. Pharmaceuticals (Basel) 2024; 17:867. [PMID: 39065718 PMCID: PMC11279411 DOI: 10.3390/ph17070867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Revised: 06/22/2024] [Accepted: 06/26/2024] [Indexed: 07/28/2024] Open
Abstract
Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the transcriptional corepressor component protein NCoR. These pockets were screened using an ensemble docking approach combined with consensus scoring to identify compounds with a different binding mechanism than the currently known HDAC modulators. Binding was compared in experimental assays between HDAC4 and HDAC3, which belong to a different family of HDACs. HDAC4 was significantly inhibited by compound 88402 but not HDAC3. Two other compounds (67436 and 134199) had IC50 values in the low micromolar range for both HDACs, which is comparable to the known inhibitor of HDAC4, SAHA (Vorinostat). However, both of these compounds were significantly weaker inhibitors of HDAC3 than SAHA and thus more selective, albeit to a limited extent. Five compounds exhibited activity on human breast carcinoma and/or urothelial carcinoma cell lines. The present result suggests potential mechanistic and chemical approaches for developing selective HDAC4 modulators.
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Affiliation(s)
- Rupesh Agarwal
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA;
| | - Pawat Pattarawat
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996, USA; (P.P.); (H.-C.R.W.)
| | - Michael R. Duff
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA;
| | - Hwa-Chain Robert Wang
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996, USA; (P.P.); (H.-C.R.W.)
| | - Jerome Baudry
- Department of Biological Sciences, The University of Alabama in Huntsville, Huntsville, AL 35899, USA;
| | - Jeremy C. Smith
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA;
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20
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D’Ursi P, Rondina A, Zani A, Uggeri M, Messali S, Caruso A, Caccuri F. Molecular Mechanisms Involved in the B Cell Growth and Clonogenic Activity of HIV-1 Matrix Protein p17 Variants. Viruses 2024; 16:1048. [PMID: 39066211 PMCID: PMC11281387 DOI: 10.3390/v16071048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 06/24/2024] [Accepted: 06/26/2024] [Indexed: 07/28/2024] Open
Abstract
The human immunodeficiency virus (HIV-1) matrix protein p17 (p17) is released from infected cells as a protein capable of deregulating the biological activity of different cells. P17 variants (vp17s), more frequently detected in the plasma of HIV-1+ patients with rather than without lymphoma and characterized by amino acids insertions in their C-terminal region, were found to trigger B cell growth and clonogenicity. Vp17s endowed with B-cell-growth-promoting activity are drastically destabilized, whereas, in a properly folded state, reference p17 (refp17) does not exert any biological activity on B cell growth and clonogenicity. However, misfolding of refp17 is necessary to expose a masked functional epitope, interacting with the protease-activated receptor 1 (PAR-1), endowed with B cell clonogenicity. Indeed, it is worth noting that changes in the secondary structure can strongly impact the function of a protein. Here, we performed computational studies to show that the gain of function of vp17s is linked to dramatic conformational changes due to structural modification in the secondary-structure elements and in the rearrangement of the hydrogen bond (H-bond) network. In particular, all clonogenic vp17s showed the disengagement of two critical residues, namely Trp16 and Tyr29, from their hydrophobic core. Biological data showed that the mutation of Trp16 and Tyr29 to Ala in the refp17 backbone, alone or in combination, resulted in a protein endowed with B cell clonogenic activity. These data show the pivotal role of the hydrophobic component in maintaining refp17 stability and identify a novel potential therapeutic target to counteract vp17-driven lymphomagenesis in HIV-1+ patients.
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Affiliation(s)
- Pasqualina D’Ursi
- Institute of Technologies in Biomedicine, National Research Council, 20090 Segrate, Italy
| | - Alessandro Rondina
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy (M.U.)
| | - Alberto Zani
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy (M.U.)
| | - Matteo Uggeri
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy (M.U.)
- Lifescience Innovation Good Healthcare Technology—LIGHT s.c.ar.l., 25123 Brescia, Italy
| | - Serena Messali
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy (M.U.)
| | - Arnaldo Caruso
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy (M.U.)
- Centre for Advanced Medical and Pharmaceutical Research, “George Emil Palade” University of Medicine, Pharmacy, Science and Technology, 540142 Targu Mures, Romania
| | - Francesca Caccuri
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy (M.U.)
- Centre for Advanced Medical and Pharmaceutical Research, “George Emil Palade” University of Medicine, Pharmacy, Science and Technology, 540142 Targu Mures, Romania
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21
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Chen JN, Dai B, Wu YD. Probability Density Reweighting of High-Temperature Molecular Dynamics. J Chem Theory Comput 2024; 20:4977-4985. [PMID: 38758038 DOI: 10.1021/acs.jctc.3c01423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2024]
Abstract
Molecular dynamics (MD) simulation is a popular method for elucidating the structures and functions of biomolecules. However, exploring the conformational space, especially for large systems with slow transitions, often requires enhanced sampling methods. Although conducting MD at high temperatures provides a straightforward approach, resulting conformational ensembles diverge significantly from those at low temperatures. To address this discrepancy, we propose a novel probability density-based reweighting (PDR) method. PDR exhibits robust performance across four distinct systems, including a miniprotein, a cyclic peptide, a protein loop, and a protein-peptide complex. It accurately restores the conformational distributions at high temperatures to those at low temperatures. Additionally, we apply PDR to reweight previously studied high-T MD simulations of 12 protein-peptide complexes, enabling a comprehensive investigation of the conformational space of protein-peptide complexes.
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Affiliation(s)
- Jia-Nan Chen
- Laboratory of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Botao Dai
- Laboratory of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Yun-Dong Wu
- Laboratory of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Shenzhen Bay Laboratory, Shenzhen 518132, China
- College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
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22
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Zhao L, Wang J, Yang W, Zhao K, Sun Q, Chen J. Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning. Molecules 2024; 29:2681. [PMID: 38893554 PMCID: PMC11174096 DOI: 10.3390/molecules29112681] [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: 05/08/2024] [Revised: 05/29/2024] [Accepted: 06/03/2024] [Indexed: 06/21/2024] Open
Abstract
CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy landscapes (FELs). DL finds that the binding pocket as well as the T-loop binding to the Vcyclin protein are involved in obvious differences of conformation contacts. This result suggests that the binding pocket of inhibitors (LQQ and AP9) and the binding interface of CDK6 to the Vcyclin protein play a key role in the function of CDK6. The analyses of FELs reveal that the binding pocket and the T-loop of CDK6 have disordered states. The results from principal component analysis (PCA) indicate that the binding of the Vcyclin protein affects the fluctuation behavior of the T-loop in CDK6. Our QM/MM-GBSA calculations suggest that the binding ability of LQQ to CDK6 is stronger than AP9 with or without the binding of the Vcyclin protein. Interaction networks of inhibitors with CDK6 were analyzed and the results reveal that LQQ contributes more hydrogen binding interactions (HBIs) and hot interaction spots with CDK6. In addition, the binding pocket endures flexibility changes from opening to closing states and the Vcyclin protein plays an important role in the stabilizing conformation of the T-loop. We anticipate that this work could provide useful information for further understanding the function of CDK6 and developing new promising inhibitors targeting CDK6.
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Affiliation(s)
- Lu Zhao
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (K.Z.); (Q.S.)
| | | | | | | | | | - Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan 250357, China; (J.W.); (W.Y.); (K.Z.); (Q.S.)
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23
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Huang R, He Y, Zhang C, Luo Y, Chen C, Tan N, Ren Y, Xu K, Yuan L, Yang J. The mutation of Japanese encephalitis virus envelope protein residue 389 attenuates viral neuroinvasiveness. Virol J 2024; 21:128. [PMID: 38840203 PMCID: PMC11151615 DOI: 10.1186/s12985-024-02398-8] [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: 02/24/2024] [Accepted: 05/27/2024] [Indexed: 06/07/2024] Open
Abstract
The envelope (E) protein of the Japanese encephalitis virus (JEV) is a key protein for virus infection and adsorption of host cells, which determines the virulence of the virus and regulates the intensity of inflammatory response. The mutation of multiple aa residues in the E protein plays a critical role in the attenuated strain of JEV. This study demonstrated that the Asp to Gly, Ser, and His mutation of the E389 site, respectively, the replication ability of the viruses in cells was significantly reduced, and the viral neuroinvasiveness was attenuated to different degrees. Among them, the mutation at E389 site enhanced the E protein flexibility contributed to the attenuation of neuroinvasiveness. In contrast, less flexibility of E protein enhanced the neuroinvasiveness of the strain. Our results indicate that the mechanism of attenuation of E389 aa mutation attenuates neuroinvasiveness is related to increased flexibility of the E protein. In addition, the increased flexibility of E protein enhanced the viral sensitivity to heparin inhibition in vitro, which may lead to a decrease in the viral load entering brain. These results suggest that E389 residue is a potential site affecting JEV virulence, and the flexibility of the E protein of aa at this site plays an important role in the determination of neuroinvasiveness.
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Affiliation(s)
- Rong Huang
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Yajing He
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Chenghua Zhang
- School of Pharmacy, North Sichuan Medical College, Nanchong, 637100, China
| | - Yue Luo
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Chen Chen
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Ning Tan
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Yang Ren
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Kui Xu
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Lei Yuan
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Jian Yang
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
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24
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Kairys V, Baranauskiene L, Kazlauskiene M, Zubrienė A, Petrauskas V, Matulis D, Kazlauskas E. Recent advances in computational and experimental protein-ligand affinity determination techniques. Expert Opin Drug Discov 2024; 19:649-670. [PMID: 38715415 DOI: 10.1080/17460441.2024.2349169] [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: 03/18/2024] [Accepted: 04/25/2024] [Indexed: 05/22/2024]
Abstract
INTRODUCTION Modern drug discovery revolves around designing ligands that target the chosen biomolecule, typically proteins. For this, the evaluation of affinities of putative ligands is crucial. This has given rise to a multitude of dedicated computational and experimental methods that are constantly being developed and improved. AREAS COVERED In this review, the authors reassess both the industry mainstays and the newest trends among the methods for protein - small-molecule affinity determination. They discuss both computational affinity predictions and experimental techniques, describing their basic principles, main limitations, and advantages. Together, this serves as initial guide to the currently most popular and cutting-edge ligand-binding assays employed in rational drug design. EXPERT OPINION The affinity determination methods continue to develop toward miniaturization, high-throughput, and in-cell application. Moreover, the availability of data analysis tools has been constantly increasing. Nevertheless, cross-verification of data using at least two different techniques and careful result interpretation remain of utmost importance.
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Affiliation(s)
- Visvaldas Kairys
- Department of Bioinformatics, Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Lina Baranauskiene
- Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | | | - Asta Zubrienė
- Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Vytautas Petrauskas
- Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Daumantas Matulis
- Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Egidijus Kazlauskas
- Department of Biothermodynamics and Drug Design, Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
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25
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Ghosh D, Biswas A, Radhakrishna M. Advanced computational approaches to understand protein aggregation. BIOPHYSICS REVIEWS 2024; 5:021302. [PMID: 38681860 PMCID: PMC11045254 DOI: 10.1063/5.0180691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 03/18/2024] [Indexed: 05/01/2024]
Abstract
Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.
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Affiliation(s)
- Deepshikha Ghosh
- Department of Biological Sciences and Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
| | - Anushka Biswas
- Department of Chemical Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
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26
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Yu T, Sudhakar N, Okafor CD. Illuminating ligand-induced dynamics in nuclear receptors through MD simulations. BIOCHIMICA ET BIOPHYSICA ACTA. GENE REGULATORY MECHANISMS 2024; 1867:195025. [PMID: 38614450 DOI: 10.1016/j.bbagrm.2024.195025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 03/27/2024] [Accepted: 04/06/2024] [Indexed: 04/15/2024]
Abstract
Nuclear receptors (NRs) regulate gene expression in critical physiological processes, with their functionality finely tuned by ligand-induced conformational changes. While NRs may sometimes undergo significant conformational motions in response to ligand-binding, these effects are more commonly subtle and challenging to study by traditional structural or biophysical methods. Molecular dynamics (MD) simulations are a powerful tool to bridge the gap between static protein-ligand structures and dynamical changes that govern NR function. Here, we summarize a handful of recent studies that apply MD simulations to study NRs. We present diverse methodologies for analyzing simulation data with a detailed examination of the information each method can yield. By delving into the strengths, limitations and unique contributions of these tools, this review provides guidance for extracting meaningful data from MD simulations to advance the goal of understanding the intricate mechanisms by which ligands orchestrate a range of functional outcomes in NRs.
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Affiliation(s)
- Tracy Yu
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Nishanti Sudhakar
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - C Denise Okafor
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA; Department of Chemistry, Pennsylvania State University, University Park, PA 16802, USA.
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27
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Alberti M, Poli G, Broggini L, Sainas S, Rizzi M, Boschi D, Ferraris DM, Martino E, Ricagno S, Tuccinardi T, Lolli ML, Miggiano R. An alternative conformation of the N-terminal loop of human dihydroorotate dehydrogenase drives binding to a potent antiproliferative agent. Acta Crystallogr D Struct Biol 2024; 80:386-396. [PMID: 38805244 DOI: 10.1107/s2059798324004066] [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: 01/30/2024] [Accepted: 05/02/2024] [Indexed: 05/29/2024] Open
Abstract
Over the years, human dihydroorotate dehydrogenase (hDHODH), which is a key player in the de novo pyrimidine-biosynthesis pathway, has been targeted in the treatment of several conditions, including autoimmune disorders and acute myelogenous leukaemia, as well as in host-targeted antiviral therapy. A molecular exploration of its inhibitor-binding behaviours yielded promising candidates for innovative drug design. A detailed description of the enzymatic pharmacophore drove the decoration of well-established inhibitory scaffolds, thus gaining further in vitro and in vivo efficacy. In the present work, using X-ray crystallography, an atypical rearrangement was identified in the binding pose of a potent inhibitor characterized by a polar pyridine-based moiety (compound 18). The crystal structure shows that upon binding compound 18 the dynamics of a protein loop involved in a gating mechanism at the cofactor-binding site is modulated by the presence of three water molecules, thus fine-tuning the polarity/hydrophobicity of the binding pocket. These solvent molecules are engaged in the formation of a hydrogen-bond mesh in which one of them establishes a direct contact with the pyridine moiety of compound 18, thus paving the way for a reappraisal of the inhibition of hDHODH. Using an integrated approach, the thermodynamics of such a modulation is described by means of isothermal titration calorimetry coupled with molecular modelling. These structural insights will guide future drug design to obtain a finer Kd/logD7.4 balance and identify membrane-permeable molecules with a drug-like profile in terms of water solubility.
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Affiliation(s)
- Marta Alberti
- Department of Pharmaceutical Sciences, University of Piemonte Orientale, Via G. Bovio 6, 28100 Novara, Italy
| | - Giulio Poli
- Department of Pharmacy, University of Pisa, Via Bonanno 6, 56126 Pisa, Italy
| | - Luca Broggini
- Institute of Molecular and Translational Cardiology, IRCCS Policlinico San Donato, Piazza Malan, 20097 San Donato Milanese, Italy
| | - Stefano Sainas
- Department of Sciences and Drug Technology, University of Torino, Via P. Giuria 9, 10125 Torino, Italy
| | - Menico Rizzi
- Department of Pharmaceutical Sciences, University of Piemonte Orientale, Via G. Bovio 6, 28100 Novara, Italy
| | - Donatella Boschi
- Department of Sciences and Drug Technology, University of Torino, Via P. Giuria 9, 10125 Torino, Italy
| | - Davide M Ferraris
- Department of Pharmaceutical Sciences, University of Piemonte Orientale, Via G. Bovio 6, 28100 Novara, Italy
| | - Elena Martino
- Department of Sciences and Drug Technology, University of Torino, Via P. Giuria 9, 10125 Torino, Italy
| | - Stefano Ricagno
- Institute of Molecular and Translational Cardiology, IRCCS Policlinico San Donato, Piazza Malan, 20097 San Donato Milanese, Italy
| | - Tiziano Tuccinardi
- Department of Pharmacy, University of Pisa, Via Bonanno 6, 56126 Pisa, Italy
| | - Marco L Lolli
- Department of Sciences and Drug Technology, University of Torino, Via P. Giuria 9, 10125 Torino, Italy
| | - Riccardo Miggiano
- Department of Pharmaceutical Sciences, University of Piemonte Orientale, Via G. Bovio 6, 28100 Novara, Italy
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28
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Anjo SI, He Z, Hussain Z, Farooq A, McIntyre A, Laughton CA, Carvalho AN, Finelli MJ. Protein Oxidative Modifications in Neurodegenerative Diseases: From Advances in Detection and Modelling to Their Use as Disease Biomarkers. Antioxidants (Basel) 2024; 13:681. [PMID: 38929122 PMCID: PMC11200609 DOI: 10.3390/antiox13060681] [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: 05/02/2024] [Revised: 05/26/2024] [Accepted: 05/29/2024] [Indexed: 06/28/2024] Open
Abstract
Oxidation-reduction post-translational modifications (redox-PTMs) are chemical alterations to amino acids of proteins. Redox-PTMs participate in the regulation of protein conformation, localization and function, acting as signalling effectors that impact many essential biochemical processes in the cells. Crucially, the dysregulation of redox-PTMs of proteins has been implicated in the pathophysiology of numerous human diseases, including neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. This review aims to highlight the current gaps in knowledge in the field of redox-PTMs biology and to explore new methodological advances in proteomics and computational modelling that will pave the way for a better understanding of the role and therapeutic potential of redox-PTMs of proteins in neurodegenerative diseases. Here, we summarize the main types of redox-PTMs of proteins while providing examples of their occurrence in neurodegenerative diseases and an overview of the state-of-the-art methods used for their detection. We explore the potential of novel computational modelling approaches as essential tools to obtain insights into the precise role of redox-PTMs in regulating protein structure and function. We also discuss the complex crosstalk between various PTMs that occur in living cells. Finally, we argue that redox-PTMs of proteins could be used in the future as diagnosis and prognosis biomarkers for neurodegenerative diseases.
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Affiliation(s)
- Sandra I. Anjo
- CNC-Center for Neurosciences and Cell Biology, University of Coimbra, 3004-517 Coimbra, Portugal
- Centre for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, 3004-517 Coimbra, Portugal
- Institute for Interdisciplinary Research (IIIUC), University of Coimbra, 3030-789 Coimbra, Portugal
| | - Zhicheng He
- Biodiscovery Institute, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK
| | - Zohaib Hussain
- Biodiscovery Institute, School of Medicine, University of Nottingham, Nottingham NG7 2RD, UK
| | - Aruba Farooq
- Biodiscovery Institute, School of Medicine, University of Nottingham, Nottingham NG7 2RD, UK
| | - Alan McIntyre
- Biodiscovery Institute, School of Medicine, University of Nottingham, Nottingham NG7 2RD, UK
| | - Charles A. Laughton
- Biodiscovery Institute, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK
| | - Andreia Neves Carvalho
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, 1649-003 Lisbon, Portugal
- Department of Pharmaceutical Sciences and Medicines, Faculty of Pharmacy, Universidade de Lisboa, 1649-003 Lisbon, Portugal
| | - Mattéa J. Finelli
- Biodiscovery Institute, School of Medicine, University of Nottingham, Nottingham NG7 2RD, UK
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29
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Zhu X, Luo M, An K, Shi D, Hou T, Warshel A, Bai C. Exploring the activation mechanism of metabotropic glutamate receptor 2. Proc Natl Acad Sci U S A 2024; 121:e2401079121. [PMID: 38739800 PMCID: PMC11126994 DOI: 10.1073/pnas.2401079121] [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: 01/17/2024] [Accepted: 04/12/2024] [Indexed: 05/16/2024] Open
Abstract
Homomeric dimerization of metabotropic glutamate receptors (mGlus) is essential for the modulation of their functions and represents a promising avenue for the development of novel therapeutic approaches to address central nervous system diseases. Yet, the scarcity of detailed molecular and energetic data on mGlu2 impedes our in-depth comprehension of their activation process. Here, we employ computational simulation methods to elucidate the activation process and key events associated with the mGlu2, including a detailed analysis of its conformational transitions, the binding of agonists, Gi protein coupling, and the guanosine diphosphate (GDP) release. Our results demonstrate that the activation of mGlu2 is a stepwise process and several energy barriers need to be overcome. Moreover, we also identify the rate-determining step of the mGlu2's transition from the agonist-bound state to its active state. From the perspective of free-energy analysis, we find that the conformational dynamics of mGlu2's subunit follow coupled rather than discrete, independent actions. Asymmetric dimerization is critical for receptor activation. Our calculation results are consistent with the observation of cross-linking and fluorescent-labeled blot experiments, thus illustrating the reliability of our calculations. Besides, we also identify potential key residues in the Gi protein binding position on mGlu2, mGlu2 dimer's TM6-TM6 interface, and Gi α5 helix by the change of energy barriers after mutation. The implications of our findings could lead to a more comprehensive grasp of class C G protein-coupled receptor activation.
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Affiliation(s)
- Xiaohong Zhu
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong518172, People’s Republic of China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei230026, People's Republic of China
| | - Mengqi Luo
- College of Management, Shenzhen University, Shenzhen518060, People's Republic of China
| | - Ke An
- Chenzhu (MoMeD) Biotechnology Co., Ltd, Hangzhou, Zhejiang310005, People's Republic of China
| | - Danfeng Shi
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong518172, People’s Republic of China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei230026, People's Republic of China
| | - Tingjun Hou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, People's Republic of China
| | - Arieh Warshel
- Department of Chemistry, University of Southern California, Los Angeles, CA90089-1062
| | - Chen Bai
- Warshel Institute for Computational Biology, School of Life and Health Sciences, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong518172, People’s Republic of China
- Chenzhu (MoMeD) Biotechnology Co., Ltd, Hangzhou, Zhejiang310005, People's Republic of China
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30
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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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31
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Stracke K, Evans JD. The use of collective variables and enhanced sampling in the simulations of existing and emerging microporous materials. NANOSCALE 2024. [PMID: 38647659 DOI: 10.1039/d4nr01024h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2024]
Abstract
Microporous materials, including zeolites, metal-organic frameworks, and cage compounds, offer diverse functionalities due to their unique dynamics and guest confinement properties. These materials play a significant role in separation, catalysis, and sensing, but their complexity hinders exploration using traditional atomistic simulations. This review explores collective variables (CVs) paired with enhanced sampling as a powerful approach to enable efficient investigation of key features in microporous materials. We highlight successful applications of CVs in studying adsorption, diffusion, phase transitions, and mechanical properties, demonstrating their crucial role in guiding material design and optimisation. The future of CVs lies in integration with techniques like machine learning, allowing for enhanced efficiency and accuracy. By tailoring CVs to specific materials and developing multi-scale approaches we can further unlock the intricacies of these fascinating materials. Simulations are a cornerstone in unravelling the complexities of microporous materials and are crucial for our future understanding.
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Affiliation(s)
- Konstantin Stracke
- School of Physics, Chemistry and Earth Science, The University of Adelaide, 5005 Australia.
| | - Jack D Evans
- School of Physics, Chemistry and Earth Science, The University of Adelaide, 5005 Australia.
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32
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Ikizawa S, Hori T, Wijaya TN, Kono H, Bai Z, Kimizono T, Lu W, Tran DP, Kitao A. PaCS-Toolkit: Optimized Software Utilities for Parallel Cascade Selection Molecular Dynamics (PaCS-MD) Simulations and Subsequent Analyses. J Phys Chem B 2024; 128:3631-3642. [PMID: 38578072 PMCID: PMC11033871 DOI: 10.1021/acs.jpcb.4c01271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 03/26/2024] [Accepted: 03/26/2024] [Indexed: 04/06/2024]
Abstract
Parallel cascade selection molecular dynamics (PaCS-MD) is an enhanced conformational sampling method conducted as a "repetition of time leaps in parallel worlds", comprising cycles of multiple molecular dynamics (MD) simulations performed in parallel and selection of the initial structures of MDs for the next cycle. We developed PaCS-Toolkit, an optimized software utility enabling the use of different MD software and trajectory analysis tools to facilitate the execution of the PaCS-MD simulation and analyze the obtained trajectories, including the preparation for the subsequent construction of the Markov state model. PaCS-Toolkit is coded with Python, is compatible with various computing environments, and allows for easy customization by editing the configuration file and specifying the MD software and analysis tools to be used. We present the software design of PaCS-Toolkit and demonstrate applications of PaCS-MD variations: original targeted PaCS-MD to peptide folding; rmsdPaCS-MD to protein domain motion; and dissociation PaCS-MD to ligand dissociation from adenosine A2A receptor.
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Affiliation(s)
- Shinji Ikizawa
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Tatsuki Hori
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Tegar Nurwahyu Wijaya
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
- Department
of Chemistry, Universitas Pertamina, Jl. Teuku Nyak Arief, Simprug, Jakarta 12220, Indonesia
| | - Hiroshi Kono
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Zhen Bai
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Tatsuhiro Kimizono
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Wenbo Lu
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Duy Phuoc Tran
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
| | - Akio Kitao
- School
of Life Science and Technology, Tokyo Institute
of Technology, 2-12-2 Ookayama, Meguro, Tokyo 152-8550, Japan
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33
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Hazarika S, Yu T, Biswas A, Dube N, Villalona P, Okafor CD. Nuclear receptor interdomain communication is mediated by the hinge with ligand specificity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.10.579785. [PMID: 38405809 PMCID: PMC10888817 DOI: 10.1101/2024.02.10.579785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Nuclear receptors are ligand-induced transcription factors that bind directly to target genes and regulate their expression. Ligand binding initiates conformational changes that propagate to other domains, allosterically regulating their activity. The nature of this interdomain communication in nuclear receptors is poorly understood, largely owing to the difficulty of experimentally characterizing full-length structures. We have applied computational modeling approaches to describe and study the structure of the full length farnesoid X receptor (FXR), approximated by the DNA binding domain (DBD) and ligand binding domain (LBD) connected by the flexible hinge region. Using extended molecular dynamics simulations (> 10 microseconds) and enhanced sampling simulations, we provide evidence that ligands selectively induce domain rearrangement, leading to interdomain contact. We use protein-protein interaction assays to provide experimental evidence of these interactions, identifying a critical role of the hinge in mediating interdomain contact. Our results illuminate previously unknown aspects of interdomain communication in FXR and provide a framework to enable characterization of other full length nuclear receptors.
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Affiliation(s)
- Saurov Hazarika
- Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA
| | - Tracy Yu
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, 16802, USA
| | - Arumay Biswas
- Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA
| | - Namita Dube
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, 16802, USA
| | - Priscilla Villalona
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, 16802, USA
| | - C. Denise Okafor
- Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, 16802, USA
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34
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Chen J, Gou Q, Chen X, Song Y, Zhang F, Pu X. Exploring biased activation characteristics by molecular dynamics simulation and machine learning for the μ-opioid receptor. Phys Chem Chem Phys 2024; 26:10698-10710. [PMID: 38512140 DOI: 10.1039/d3cp05050e] [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: 03/22/2024]
Abstract
Biased ligands selectively activating specific downstream signaling pathways (termed as biased activation) exhibit significant therapeutic potential. However, the conformational characteristics revealed are very limited for the biased activation, which is not conducive to biased drug development. Motivated by the issue, we combine extensive accelerated molecular dynamics simulations and an interpretable deep learning model to probe the biased activation features for two complex systems constructed by the inactive μOR and two different biased agonists (G-protein-biased agonist TRV130 and β-arrestin-biased agonist endomorphin2). The results indicate that TRV130 binds deeper into the receptor core compared to endomorphin2, located between W2936.48 and D1142.50, and forms hydrogen bonding with D1142.50, while endomorphin2 binds above W2936.48. The G protein-biased agonist induces greater outward movements of the TM6 intracellular end, forming a typical active conformation, while the β-arrestin-biased agonist leads to a smaller extent of outward movements of TM6. Compared with TRV130, endomorphin2 causes more pronounced inward movements of the TM7 intracellular end and more complex conformational changes of H8 and ICL1. In addition, important residues determining the two different biased activation states were further identified by using an interpretable deep learning classification model, including some common biased activation residues across Class A GPCRs like some key residues on the TM2 extracellular end, ECL2, TM5 intracellular end, TM6 intracellular end, and TM7 intracellular end, and some specific important residues of ICL3 for μOR. The observations will provide valuable information for understanding the biased activation mechanism for GPCRs.
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Affiliation(s)
- Jianfang Chen
- College of Chemistry, Sichuan University, Chengdu 610064, China.
| | - Qiaoling Gou
- College of Chemistry, Sichuan University, Chengdu 610064, China.
| | - Xin Chen
- College of Chemistry, Sichuan University, Chengdu 610064, China.
| | - Yuanpeng Song
- College of Chemistry, Sichuan University, Chengdu 610064, China.
| | - Fuhui Zhang
- Graduate School, Sichuan University, Chengdu 610064, China
| | - Xuemei Pu
- College of Chemistry, Sichuan University, Chengdu 610064, China.
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35
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Onishi N, Mazzaferro N, Kunstelj Š, Alvarado DA, Muller AM, Vázquez FX. Flanking Domains Modulate α-Synuclein Monomer Structure: A Molecular Dynamics Domain Deletion Study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.23.586267. [PMID: 38586052 PMCID: PMC10996548 DOI: 10.1101/2024.03.23.586267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Aggregates of misfolded α-synuclein proteins (asyn) are key markers of Parkinson's disease. Asyn proteins have three domains: an N-terminal domain, a hydrophobic NAC core implicated in aggregation, and a proline-rich C-terminal domain. Proteins with truncated C-terminal domains are known to be prone to aggregation and suggest that studying domain-domain interactions in asyn monomers could help elucidate the role of the flanking domains in modulating protein structure. To this end, we used Gaussian accelerated molecular dynamics (GAMD) to simulate wild-type (WT), N-terminal truncated (DN), C-terminal truncated (ΔC), and isolated NAC domain variants (isoNAC). Using clustering and contact analysis, we found that N- and C-terminal domains interact via electrostatic interactions, while the NAC and N-terminal domains interact through hydrophobic contacts. Our work also suggests that the C-terminal domain does not interact directly with the NAC domain but instead interacts with the N-terminal domain. Removal of the N-terminal domain led to increased contacts between NAC and C-terminal domains and the formation of interdomain β-sheets. Removal of either flanking domain also resulted in increased compactness of every domain. We also found that the contacts between flanking domains results in an electrostatic potential (ESP) that could possibly lead to favorable interactions with anionic lipid membranes. Removal of the C-terminal domain disrupts the ESP in a way that is likely to over-stabilize protein-membrane interactions. All of this suggests that one of the roles of the flanking domains may be to modulate the protein structure in a way that helps maintain elongation, hide hydrophobic residue from the solvent, and maintain an ESP that aids favorable interactions with the membrane.
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Affiliation(s)
- Noriyo Onishi
- Department of Chemistry, St. John’s University, Queens, NY 11439, USA
| | | | - Špela Kunstelj
- Department of Chemistry, St. John’s University, Queens, NY 11439, USA
| | - Daisy A. Alvarado
- Department of Chemistry, St. John’s University, Queens, NY 11439, USA
| | - Anna M. Muller
- Department of Chemistry, St. John’s University, Queens, NY 11439, USA
| | - Frank X. Vázquez
- Department of Chemistry, St. John’s University, Queens, NY 11439, USA
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36
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Hazarika S, Fehrle M, Okafor CD. How nuclear receptors transition between active and inactive forms: An energetic perspective. J Chem Phys 2024; 160:115102. [PMID: 38501469 DOI: 10.1063/5.0189234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 02/28/2024] [Indexed: 03/20/2024] Open
Abstract
Nuclear receptors regulate transcriptional programs in response to the binding of natural and synthetic ligands. These ligands modulate the receptor by inducing dynamic changes in the ligand binding domain that shift the C-terminal helix (H12) between active and inactive conformations. Despite decades of study, many questions persist regarding the nature of the inactive state and how ligands shift receptors between different states. Here, we use molecular dynamics (MD) simulations to investigate the timescale and energetic landscape of the conformational transition between inactive and active forms of progesterone receptor (PR) bound to a partial agonist. We observe that the microsecond timescale is insufficient to observe any transitions; only at millisecond timescales achieved via accelerated MD simulations do we find the inactive PR switches to the active state. Energetic analysis reveals that both active and inactive PR states represent energy minima separated by a barrier that can be traversed. In contrast, little or no transition is observed between active and inactive states when an agonist or antagonist is bound, confirming that ligand identity plays a key role in defining the energy landscape of nuclear receptor conformations.
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Affiliation(s)
- Saurov Hazarika
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Matthew Fehrle
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - C Denise Okafor
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania 16802, USA
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA
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37
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Stan-Bernhardt A, Glinkina L, Hulm A, Ochsenfeld C. Exploring Chemical Space Using Ab Initio Hyperreactor Dynamics. ACS CENTRAL SCIENCE 2024; 10:302-314. [PMID: 38435517 PMCID: PMC10906254 DOI: 10.1021/acscentsci.3c01403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/20/2023] [Accepted: 12/21/2023] [Indexed: 03/05/2024]
Abstract
In recent years, first-principles exploration of chemical reaction space has provided valuable insights into intricate reaction networks. Here, we introduce ab initio hyperreactor dynamics, which enables rapid screening of the accessible chemical space from a given set of initial molecular species, predicting new synthetic routes that can potentially guide subsequent experimental studies. For this purpose, different hyperdynamics derived bias potentials are applied along with pressure-inducing spherical confinement of the molecular system in ab initio molecular dynamics simulations to efficiently enhance reactivity under mild conditions. To showcase the advantages and flexibility of the hyperreactor approach, we present a systematic study of the method's parameters on a HCN toy model and apply it to a recently introduced experimental model for the prebiotic formation of glycinal and acetamide in interstellar ices, which yields results in line with experimental findings. In addition, we show how the developed framework enables the study of complicated transitions like the first step of a nonenzymatic DNA nucleoside synthesis in an aqueous environment, where the molecular fragmentation problem of earlier nanoreactor approaches is avoided.
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Affiliation(s)
- Alexandra Stan-Bernhardt
- Chair
of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU), Butenandtstrasse 5, D-81377 München, Germany
| | - Liubov Glinkina
- Chair
of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU), Butenandtstrasse 5, D-81377 München, Germany
| | - Andreas Hulm
- Chair
of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU), Butenandtstrasse 5, D-81377 München, Germany
| | - Christian Ochsenfeld
- Chair
of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU), Butenandtstrasse 5, D-81377 München, Germany
- Max
Planck Institute for Solid State Research, Heisenbergstrasse 1, D-70569 Stuttgart, Germany
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38
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Rapallo A. Fractional Extended Diffusion Theory to capture anomalous relaxation from biased/accelerated molecular simulations. J Chem Phys 2024; 160:084114. [PMID: 38421066 DOI: 10.1063/5.0189518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/06/2024] [Indexed: 03/02/2024] Open
Abstract
Biased and accelerated molecular simulations (BAMS) are widely used tools to observe relevant molecular phenomena occurring on time scales inaccessible to standard molecular dynamics, but evaluation of the physical time scales involved in the processes is not directly possible from them. For this reason, the problem of recovering dynamics from such kinds of simulations is the object of very active research due to the relevant theoretical and practical implications of dynamics on the properties of both natural and synthetic molecular systems. In a recent paper [A. Rapallo et al., J. Comput. Chem. 42, 586-599 (2021)], it has been shown how the coupling of BAMS (which destroys the dynamics but allows to calculate average properties) with Extended Diffusion Theory (EDT) (which requires input appropriate equilibrium averages calculated over the BAMS trajectories) allows to effectively use the Smoluchowski equation to calculate the orientational time correlation function of the head-tail unit vector defined over a peptide in water solution. Orientational relaxation of this vector is the result of the coupling of internal molecular motions with overall molecular rotation, and it was very well described by correlation functions expressed in terms of weighted sums of suitable time-exponentially decaying functions, in agreement with a Brownian diffusive regime. However, situations occur where exponentially decaying functions are no longer appropriate to capture the actual dynamical behavior, which exhibits persistent long time correlations, compatible with the so called subdiffusive regimes. In this paper, a generalization of EDT will be given, exploiting a fractional Smoluchowski equation (FEDT) to capture the non-exponential character observed in the relaxation of intramolecular distances and molecular radius of gyration, whose dynamics depend on internal molecular motions only. The calculation methods, proper to EDT, are adapted to implement the generalization of the theory, and the resulting algorithm confirms FEDT as a tool of practical value in recovering dynamics from BAMS, to be used in general situations, involving both regular and anomalous diffusion regimes.
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Affiliation(s)
- Arnaldo Rapallo
- CNR - Istituto di Scienze e Tecnologie Chimiche "Giulio Natta" (SCITEC), via A. Corti 12, I-20133 Milano, Italy
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Fu H, Bian H, Shao X, Cai W. Collective Variable-Based Enhanced Sampling: From Human Learning to Machine Learning. J Phys Chem Lett 2024; 15:1774-1783. [PMID: 38329095 DOI: 10.1021/acs.jpclett.3c03542] [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: 02/09/2024]
Abstract
Enhanced-sampling algorithms relying on collective variables (CVs) are extensively employed to study complex (bio)chemical processes that are not amenable to brute-force molecular simulations. The selection of appropriate CVs characterizing the slow movement modes is of paramount importance for reliable and efficient enhanced-sampling simulations. In this Perspective, we first review the application and limitations of CVs obtained from chemical and geometrical intuition. We also introduce path-sampling algorithms, which can identify path-like CVs in a high-dimensional free-energy space. Machine-learning algorithms offer a viable approach to finding suitable CVs by analyzing trajectories from preliminary simulations. We discuss both the performance of machine-learning-derived CVs in enhanced-sampling simulations of experimental models and the challenges involved in applying these CVs to realistic, complex molecular assemblies. Moreover, we provide a prospective view of the potential advancements of machine-learning algorithms for the development of CVs in the field of enhanced-sampling simulations.
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Affiliation(s)
- Haohao Fu
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Hengwei Bian
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Xueguang Shao
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Wensheng Cai
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
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Falanga AP, Lupia A, Tripodi L, Morgillo CM, Moraca F, Roviello GN, Catalanotti B, Amato J, Pastore L, Cerullo V, D'Errico S, Piccialli G, Oliviero G, Borbone N. Exploring the DNA 2-PNA heterotriplex formation in targeting the Bcl-2 gene promoter: A structural insight by physico-chemical and microsecond-scale MD investigation. Heliyon 2024; 10:e24599. [PMID: 38317891 PMCID: PMC10839560 DOI: 10.1016/j.heliyon.2024.e24599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 01/04/2024] [Accepted: 01/10/2024] [Indexed: 02/07/2024] Open
Abstract
Peptide Nucleic Acids (PNAs) represent a promising tool for gene modulation in anticancer treatment. The uncharged peptidyl backbone and the resistance to chemical and enzymatic degradation make PNAs highly advantageous to form stable hybrid complexes with complementary DNA and RNA strands, providing higher stability than the corresponding natural analogues. Our and other groups' research has successfully shown that tailored PNA sequences can effectively downregulate the expression of human oncogenes using antigene, antisense, or anti-miRNA approaches. Specifically, we identified a seven bases-long PNA sequence, complementary to the longer loop of the main G-quadruplex structure formed by the bcl2midG4 promoter sequence, capable of downregulating the expression of the antiapoptotic Bcl-2 protein and enhancing the anticancer activity of an oncolytic adenovirus. Here, we extended the length of the PNA probe with the aim of including the double-stranded Bcl-2 promoter among the targets of the PNA probe. Our investigation primarily focused on the structural aspects of the resulting DNA2-PNA heterotriplex that were determined by employing conventional and accelerated microsecond-scale molecular dynamics simulations and chemical-physical analysis. Additionally, we conducted preliminary biological experiments using cytotoxicity assays on human A549 and MDA-MB-436 adenocarcinoma cell lines, employing the oncolytic adenovirus delivery strategy.
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Affiliation(s)
- Andrea P. Falanga
- Dipartimento di Farmacia, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
| | - Antonio Lupia
- Dipartimento di Farmacia, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
| | - Lorella Tripodi
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
- CEINGE-Biotecnologie Avanzate Franco Salvatore S.c.a.r.l., Naples, 80145, Italy
| | - Carmine M. Morgillo
- Dipartimento di Farmacia, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
| | - Federica Moraca
- Dipartimento di Farmacia, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
| | - Giovanni N. Roviello
- Istituto di Biostrutture e Bioimmagini, Consiglio Nazionale Delle Ricerche, Naples, 80131, Italy
| | - Bruno Catalanotti
- Dipartimento di Farmacia, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
| | - Jussara Amato
- Dipartimento di Farmacia, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
| | - Lucio Pastore
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
- CEINGE-Biotecnologie Avanzate Franco Salvatore S.c.a.r.l., Naples, 80145, Italy
| | - Vincenzo Cerullo
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
- ImmunoViroTherapy Lab (IVT), Drug Research Program (DRP), Faculty of Pharmacy, University of Helsinki, 00100, Helsinki, Finland
| | - Stefano D'Errico
- Dipartimento di Farmacia, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
| | - Gennaro Piccialli
- Dipartimento di Farmacia, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
| | - Giorgia Oliviero
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
| | - Nicola Borbone
- Dipartimento di Farmacia, Università Degli Studi di Napoli Federico II, Naples, 80131, Italy
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41
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Yang K, Chen G, Yu F, Fang X, Zhang J, Zhang Z, Shi Y, Zhang L. Molecular mechanism of specific HLA-A mRNA recognition by the RNA-binding-protein hMEX3B to promote tumor immune escape. Commun Biol 2024; 7:158. [PMID: 38326406 PMCID: PMC10850505 DOI: 10.1038/s42003-024-05845-y] [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: 07/07/2023] [Accepted: 01/23/2024] [Indexed: 02/09/2024] Open
Abstract
Immunotherapy, including immune checkpoint inhibitors and adoptive cell transfer, has obtained great progress, but their efficiencies vary among patients due to the genetic and epigenetic differences. Human MEX3B (hMEX3B) protein is an RNA-binding protein that contains two KH domains at the N-terminus and a RING domain at its C-terminus, which has the activity of E3 ubiquitin ligase and is essential for RNA degradation. Current evidence suggests that hMEX3B is involved in many important biological processes, including tumor immune evasion and HLA-A regulation, but the sequence of substrate RNA recognized by hMEX3B and the functional molecular mechanisms are unclear. Here, we first screened the optimized hMEX3B binding sequence on the HLA-A mRNA and reported that the two tandem KH domains can bind with their substrate one hundred times more than the individual KH domains. We systematically investigated the binding characteristics between the two KH domains and their RNA substrates by nuclear magnetic resonance (NMR). Based on this information and the small-angle X-ray scattering (SAXS) data, we used molecular dynamics simulations to obtain structural models of KH domains in complex with their corresponding RNAs. By analyzing the models, we noticed that on the KH domains' variable loops, there were two pairs of threonines and arginines that can disrupt the recognition of the RNA completely, and this influence had also been verified both in vitro and in vivo. Finally, we presented a functional model of the hMEX3B protein, which indicated that hMEX3B regulated the degradation of its substrate mRNAs in many biological processes. Taken together, our research illustrated how the hMEX3B protein played a key role in translation inhibition during the immune response to tumor cells and provided an idea and a lead for the study of the molecular mechanism and function of other MEX3 family proteins.
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Affiliation(s)
- Kanglong 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, PR China
- Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, PR China
- Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science & Technology of China, Hefei, Anhui, PR China
| | - Guanglin Chen
- Department of Physics, University of Science and Technology of China, Hefei, Anhui, PR China
| | - Fan Yu
- 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, PR China
- Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, PR China
- Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science & Technology of China, Hefei, Anhui, PR China
| | - Xianyang Fang
- Beijing Advanced Innovation Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, PR China
| | - Jiahai Zhang
- 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, PR China
- Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, PR China
- Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science & Technology of China, Hefei, Anhui, PR China
| | - Zhiyong Zhang
- Department of Physics, University of Science and Technology of China, Hefei, Anhui, PR 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, PR China.
- Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, PR China.
- Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science & Technology of China, Hefei, Anhui, PR China.
| | - Liang Zhang
- 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, PR China.
- Ministry of Education Key Laboratory for Membraneless Organelles and Cellular Dynamics, University of Science & Technology of China, Hefei, Anhui, PR China.
- Center for Advanced Interdisciplinary Science and Biomedicine of IHM, University of Science & Technology of China, Hefei, Anhui, PR China.
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42
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Rathee P, Moorkkannur SN, Prabhakar R. Structural studies of catalytic peptides using molecular dynamics simulations. Methods Enzymol 2024; 697:151-180. [PMID: 38816122 DOI: 10.1016/bs.mie.2024.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Many self-assembling peptides can form amyloid like structures with different sizes and morphologies. Driven by non-covalent interactions, their aggregation can occur through distinct pathways. Additionally, they can bind metal ions to create enzyme like active sites that allow them to catalyze diverse reactions. Due to the non-crystalline nature of amyloids, it is quite challenging to elucidate their structures using experimental spectroscopic techniques. In this aspect, molecular dynamics (MD) simulations provide a useful tool to derive structures of these macromolecules in solution. They can be further validated by comparing with experimentally measured structural parameters. However, these simulations require a multi-step process starting from the selection of the initial structure to the analysis of MD trajectories. There are multiple force fields, parametrization protocols, equilibration processes, software and analysis tools available for this process. Therefore, it is complicated for non-experts to select the most relevant tools and perform these simulations effectively. In this chapter, a systematic methodology that covers all major aspects of modeling of catalytic peptides is provided in a user-friendly manner. It will be helpful for researchers in this critical area of research.
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Affiliation(s)
- Parth Rathee
- Department of Chemistry, University of Miami, Coral Gables, FL, United States
| | | | - Rajeev Prabhakar
- Department of Chemistry, University of Miami, Coral Gables, FL, United States.
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43
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Shokhen M, Walikonis R, Uversky VN, Allbeck A, Zezelic C, Feldman D, Levy NS, Levy AP. Molecular modeling of ARF6 dysregulation caused by mutations in IQSEC2. J Biomol Struct Dyn 2024; 42:1268-1279. [PMID: 37078745 DOI: 10.1080/07391102.2023.2199085] [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: 12/10/2022] [Accepted: 03/29/2023] [Indexed: 04/21/2023]
Abstract
IQSEC2 gene mutations are associated with epilepsy, autism, and intellectual disability. The primary function IQSEC2, mediated via its Sec 7 domain, is to act as a guanine nucleotide exchange factor for ARF6. We sought to develop a molecular model, which may explain the aberrant Sec 7 activity on ARF6 of different human IQSEC2 mutations. We integrated experimental data of IQSEC2 mutants with protein structure prediction by the RaptorX server combined with molecular modeling and molecular dynamics simulations. Normally, apocalmodulin (apoCM) binds to IQSEC2 resulting in its N-terminal fragment inhibiting access of its Sec 7 domain to ARF6. An increase in Ca2+ concentration destabilizes the interaction of IQSEC2 with apoCM and removes steric hindrance of Sec 7 binding with ARF6. Mutations at amino acid residue 350 of IQSEC2 result in loss of steric hindrance of Sec 7 binding with ARF6 leading to constitutive activation of ARF6 by Sec 7. On the other hand, a mutation at amino acid residue 359 of IQSEC2 results in constitutive hindrance of Sec 7 binding to ARF6 leading to the loss of the ability of IQSEC2 to activate ARF6. These studies provide a model for dysregulation of IQSEC2 Sec 7 activity by mutant IQSEC2 proteins.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Michael Shokhen
- Department of Chemistry, Bar Ilan University, Ramat Gan, Israel
| | - Randall Walikonis
- Department of Physiology and Neurobiology, University of Connecticut, Storrs, Connecticut, USA
| | - Vladimir N Uversky
- Department of Molecular Medicine and Byrd Alzheimer's Center and Research Institute, University of South Florida, Tampa, Florida, USA
| | - Amnon Allbeck
- Department of Chemistry, Bar Ilan University, Ramat Gan, Israel
| | - Camryn Zezelic
- Technion Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Danielle Feldman
- Technion Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Nina S Levy
- Technion Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Andrew P Levy
- Technion Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
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44
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Ohnuki J, Jaunet-Lahary T, Yamashita A, Okazaki KI. Accelerated Molecular Dynamics and AlphaFold Uncover a Missing Conformational State of Transporter Protein OxlT. J Phys Chem Lett 2024; 15:725-732. [PMID: 38215403 DOI: 10.1021/acs.jpclett.3c03052] [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: 01/14/2024]
Abstract
Transporter proteins change their conformations to carry their substrate across the cell membrane. The conformational dynamics is vital to understanding the transport function. We have studied the oxalate transporter (OxlT), an oxalate:formate antiporter from Oxalobacter formigenes, significant in avoiding kidney stone formation. The atomic structure of OxlT has been recently solved in the outward-open and occluded states. However, the inward-open conformation is still missing, hindering a complete understanding of the transporter. Here, we performed a Gaussian accelerated molecular dynamics simulation to sample the extensive conformational space of OxlT and successfully predicted the inward-open conformation where cytoplasmic substrate formate binding was preferred over oxalate binding. We also identified critical interactions for the inward-open conformation. The results were complemented by an AlphaFold2 structure prediction. Although AlphaFold2 solely predicted OxlT in the outward-open conformation, mutation of the identified critical residues made it partly predict the inward-open conformation, identifying possible state-shifting mutations.
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Affiliation(s)
- Jun Ohnuki
- Research Center for Computational Science, Institute for Molecular Science, National Institutes of Natural Sciences, Okazaki 444-8585, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, Okazaki, Aichi 444-8585, Japan
| | - Titouan Jaunet-Lahary
- Research Center for Computational Science, Institute for Molecular Science, National Institutes of Natural Sciences, Okazaki 444-8585, Japan
| | - Atsuko Yamashita
- Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8530, Japan
| | - Kei-Ichi Okazaki
- Research Center for Computational Science, Institute for Molecular Science, National Institutes of Natural Sciences, Okazaki 444-8585, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, Okazaki, Aichi 444-8585, Japan
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45
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Kehrein J, Sotriffer C. Molecular Dynamics Simulations for Rationalizing Polymer Bioconjugation Strategies: Challenges, Recent Developments, and Future Opportunities. ACS Biomater Sci Eng 2024; 10:51-74. [PMID: 37466304 DOI: 10.1021/acsbiomaterials.3c00636] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
The covalent modification of proteins with polymers is a well-established method for improving the pharmacokinetic properties of therapeutically valuable biologics. The conjugated polymer chains of the resulting hybrid represent highly flexible macromolecular structures. As the dynamics of such systems remain rather elusive for established experimental techniques from the field of protein structure elucidation, molecular dynamics simulations have proven as a valuable tool for studying such conjugates at an atomistic level, thereby complementing experimental studies. With a focus on new developments, this review aims to provide researchers from the polymer bioconjugation field with a concise and up to date overview of such approaches. After introducing basic principles of molecular dynamics simulations, as well as methods for and potential pitfalls in modeling bioconjugates, the review illustrates how these computational techniques have contributed to the understanding of bioconjugates and bioconjugation strategies in the recent past and how they may lead to a more rational design of novel bioconjugates in the future.
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Affiliation(s)
- Josef Kehrein
- Institute of Pharmacy and Food Chemistry, University of Würzburg, Würzburg 97074, Germany
| | - Christoph Sotriffer
- Institute of Pharmacy and Food Chemistry, University of Würzburg, Würzburg 97074, Germany
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46
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Koirala K, Joshi K, Adediwura V, Wang J, Do H, Miao Y. Accelerating Molecular Dynamics Simulations for Drug Discovery. Methods Mol Biol 2024; 2714:187-202. [PMID: 37676600 DOI: 10.1007/978-1-0716-3441-7_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Accurate prediction of ligand binding thermodynamics and kinetics is crucial in drug design. However, it remains challenging for conventional molecular dynamics (MD) simulations due to sampling issues. Gaussian accelerated MD (GaMD) is an enhanced sampling method that adds a harmonic boost to overcome energy barriers, which has demonstrated significant benefits in exploring protein-ligand interactions. Especially, the ligand GaMD (LiGaMD) applies a selective boost potential to the ligand nonbonded potential energy, significantly improving sampling for ligand binding and dissociation. Furthermore, a selective boost potential is applied to the potential of both ligand and protein residues around binding pocket in LiGaMD2 to further increase the sampling of protein-ligand interaction. LiGaMD and LiGaMD2 simulations could capture repetitive ligand binding and unbinding events within microsecond simulations, allowing to simultaneously characterize ligand binding thermodynamics and kinetics, which is expected to greatly facilitate drug design. In this chapter, we provide a brief review of the status of LiGaMD in drug discovery and outline its usage.
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Affiliation(s)
- Kushal Koirala
- Computational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA
| | - Keya Joshi
- Computational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA
| | - Victor Adediwura
- Computational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA
| | - Jinan Wang
- Computational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA
| | - Hung Do
- Computational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA
| | - Yinglong Miao
- Computational Biology Program and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, USA.
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47
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Chen J, Wang W, Sun H, He W. Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters. Mini Rev Med Chem 2024; 24:1323-1333. [PMID: 38265367 DOI: 10.2174/0113895575252165231122095555] [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: 03/06/2023] [Revised: 09/05/2023] [Accepted: 10/16/2023] [Indexed: 01/25/2024]
Abstract
Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.
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Affiliation(s)
- Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan-250357, China
| | - Wei Wang
- School of Science, Shandong Jiaotong University, Jinan-250357, China
| | - Haibo Sun
- School of Science, Shandong Jiaotong University, Jinan-250357, China
| | - Weikai He
- School of Science, Shandong Jiaotong University, Jinan-250357, China
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48
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Tang X, Kokot J, Waibl F, Fernández-Quintero ML, Kamenik AS, Liedl KR. Addressing Challenges of Macrocyclic Conformational Sampling in Polar and Apolar Solvents: Lessons for Chameleonicity. J Chem Inf Model 2023; 63:7107-7123. [PMID: 37943023 PMCID: PMC10685455 DOI: 10.1021/acs.jcim.3c01123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 10/24/2023] [Accepted: 10/24/2023] [Indexed: 11/10/2023]
Abstract
We evaluated a workflow to reliably sample the conformational space of a set of 47 peptidic macrocycles. Starting from SMILES strings, we use accelerated molecular dynamics simulations to overcome high energy barriers, in particular, the cis-trans isomerization of peptide bonds. We find that our approach performs very well in polar solvents like water and dimethyl sulfoxide. Interestingly, the protonation state of a secondary amine in the ring only slightly influences the conformational ensembles of our test systems. For several of the macrocycles, determining the conformational distribution in chloroform turns out to be considerably more challenging. Especially, the choice of partial charges crucially influences the ensembles in chloroform. We address these challenges by modifying initial structures and the choice of partial charges. Our results suggest that special care has to be taken to understand the configurational distribution in apolar solvents, which is a key step toward a reliable prediction of membrane permeation of macrocycles and their chameleonic properties.
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Affiliation(s)
- Xuechen Tang
- Department
of General, Inorganic and Theoretical Chemistry, University of Innsbruck, A-6020 Innsbruck, Austria
| | - Janik Kokot
- Department
of General, Inorganic and Theoretical Chemistry, University of Innsbruck, A-6020 Innsbruck, Austria
| | - Franz Waibl
- Department
of General, Inorganic and Theoretical Chemistry, University of Innsbruck, A-6020 Innsbruck, Austria
- Department
of Chemistry and Applied Biosciences, ETH
Zürich, 8093 Zürich, Switzerland
| | | | - Anna S. Kamenik
- Department
of General, Inorganic and Theoretical Chemistry, University of Innsbruck, A-6020 Innsbruck, Austria
| | - Klaus R. Liedl
- Department
of General, Inorganic and Theoretical Chemistry, University of Innsbruck, A-6020 Innsbruck, Austria
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Fu H, Liu H, Xing J, Zhao T, Shao X, Cai W. Deep-Learning-Assisted Enhanced Sampling for Exploring Molecular Conformational Changes. J Phys Chem B 2023; 127:9926-9935. [PMID: 37947397 DOI: 10.1021/acs.jpcb.3c05284] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
We present a novel strategy to explore conformational changes and identify stable states of molecular objects, eliminating the need for a priori knowledge. The approach applies a deep learning method to extract information about the movement modes of the molecular object from a short, high-dimensional, and parameter-free preliminary enhanced-sampling simulation. The gathered information is described by a small set of deep-learning-based collective variables (dCVs), which steer the production-enhanced-sampling simulation. Considering the challenge of adequately exploring the configurational space using the low-dimensional, suboptimal dCVs, we incorporate a method designed for ergodic sampling, namely, Gaussian-accelerated molecular dynamics (MD), into the framework of CV-based enhanced sampling. MD simulations on both toy models and nontrivial examples demonstrate the remarkable computational efficiency of the strategy in capturing the conformational changes of molecular objects without a priori knowledge. Specifically, we achieved the blind folding of two fast folders, chignolin and villin, within a time scale of hundreds of nanoseconds and successfully reconstructed the free-energy landscapes that characterize their reversible folding. All in all, the presented strategy holds significant promise for investigating conformational changes in macromolecules, and it is anticipated to find extensive applications in the fields of chemistry and biology.
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Affiliation(s)
- Haohao Fu
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Han Liu
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Jingya Xing
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Tong Zhao
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
| | - Xueguang Shao
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Wensheng Cai
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
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50
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Ojha AA, Votapka LW, Amaro RE. QMrebind: incorporating quantum mechanical force field reparameterization at the ligand binding site for improved drug-target kinetics through milestoning simulations. Chem Sci 2023; 14:13159-13175. [PMID: 38023523 PMCID: PMC10664576 DOI: 10.1039/d3sc04195f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 10/22/2023] [Indexed: 12/01/2023] Open
Abstract
Understanding the interaction of ligands with biomolecules is an integral component of drug discovery and development. Challenges for computing thermodynamic and kinetic quantities for pharmaceutically relevant receptor-ligand complexes include the size and flexibility of the ligands, large-scale conformational rearrangements of the receptor, accurate force field parameters, simulation efficiency, and sufficient sampling associated with rare events. Our recently developed multiscale milestoning simulation approach, SEEKR2 (Simulation Enabled Estimation of Kinetic Rates v.2), has demonstrated success in predicting unbinding (koff) kinetics by employing molecular dynamics (MD) simulations in regions closer to the binding site. The MD region is further subdivided into smaller Voronoi tessellations to improve the simulation efficiency and parallelization. To date, all MD simulations are run using general molecular mechanics (MM) force fields. The accuracy of calculations can be further improved by incorporating quantum mechanical (QM) methods into generating system-specific force fields through reparameterizing ligand partial charges in the bound state. The force field reparameterization process modifies the potential energy landscape of the bimolecular complex, enabling a more accurate representation of the intermolecular interactions and polarization effects at the bound state. We present QMrebind (Quantum Mechanical force field reparameterization at the receptor-ligand binding site), an ORCA-based software that facilitates reparameterizing the potential energy function within the phase space representing the bound state in a receptor-ligand complex. With SEEKR2 koff estimates and experimentally determined kinetic rates, we compare and interpret the receptor-ligand unbinding kinetics obtained using the newly reparameterized force fields for model host-guest systems and HSP90-inhibitor complexes. This method provides an opportunity to achieve higher accuracy in predicting receptor-ligand koff rate constants.
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Affiliation(s)
- Anupam Anand Ojha
- Department of Chemistry and Biochemistry, University of California San Diego La Jolla California 92093 USA
| | - Lane William Votapka
- Department of Chemistry and Biochemistry, University of California San Diego La Jolla California 92093 USA
| | - Rommie Elizabeth Amaro
- Department of Molecular Biology, University of California San Diego La Jolla California 92093 USA
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