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Adigun TO, Danazumi AU, Umar HI, Na'Allah A, Alabi MA, Joel WO, Aberuagba A, Alejolowo OO, Bamidele JO, Omotayo OS, Medayedupin OA. In silico molecular modeling and simulations of black tea theaflavins revealed theaflavin-3'-gallate as putative liver X receptor-beta agonist. J Biomol Struct Dyn 2023; 41:13015-13028. [PMID: 36729100 DOI: 10.1080/07391102.2023.2175264] [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] [Received: 11/12/2022] [Accepted: 01/11/2023] [Indexed: 02/03/2023]
Abstract
The low constitutive activation of Liver X receptor, an endogenous nuclear receptor with two subtypes (α and β), is a condition lying at the crossroad of cancer and cardiovascular disease. Both natural and synthetic Liver X receptor agonists have reportedly shown remarkable antiproliferative and atheroprotective effects but the repeated doses of its synthetic ones are also paradoxically associated with hyperlipidaemic effects and neurotoxicity, though attributed to the alpha subtype. This highlights the need for novel, safe, and potent LXR-beta-selective agonists. Hypocholesterolaemic effects of black theaflavins have been widely reported, but data on the exact theaflavin compound (s) responsible for these effects is currently lacking. Neither is information on the possible modulatory effects of the compound (s) on LXR-beta nor its possible implications in the context of drug development for cardiovascular diseases and cancers is explored. On this account, we investigated the potential interaction of four main theaflavin monomers (TF1, TF2A, TF2B & TF3) with human LXR-beta through robust computational modelling that entails molecular docking, free energy calculations and molecular dynamics simulations. The ligands were further profiled (in silico) for absorption, distribution, metabolism, excretion, and toxicological properties. Our result revealed theaflavin TF2B as a putative LXR-beta agonist, possibly responsible for the widely observed hypocholesterolaemic effect in black tea. This finding, while encouraging, needs to be experimentally verified in wet studies.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Temidayo O Adigun
- Department of Biochemistry, Faculty of Life Sciences, University of Ilorin, Ilorin, Nigeria
| | - Ammar U Danazumi
- Faculty of Chemistry, Warsaw, University of Technology, Warsaw, Poland
- Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands
| | - Haruna I Umar
- Molecular Biology and Bioinformatics Lab, Department of Biochemistry, Federal University of Technology Akure, Akure, Nigeria
- Computer-aided Therapeutic Discovery and Design Group, Federal University of Technology Akure, Akure, Nigeria
| | - Asiat Na'Allah
- Department of Biochemistry, Faculty of Pure and Applied Sciences, Kwara State University, Malete, Nigeria
| | - Mutiu A Alabi
- Department of Biochemistry, Faculty of Pure and Applied Sciences, Kwara State University, Malete, Nigeria
| | - Wisdom O Joel
- Department of Biochemistry, College of Science and Technology, Covenant University, Ota, Nigeria
| | - Adepeju Aberuagba
- Department of Biochemistry, McPherson University, Seriki Sotayo, Nigeria
| | | | - Joy O Bamidele
- Science Laboratory Technology, The Federal Polytechnic Ilaro, Ilaro, Nigeria
| | - Olakunle S Omotayo
- Science Laboratory Technology, The Federal Polytechnic Ilaro, Ilaro, Nigeria
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Ulbrich P, Waldner M, Furmanova K, Marques SM, Bednar D, Kozlikova B, Byska J. sMolBoxes: Dataflow Model for Molecular Dynamics Exploration. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2023; 29:581-590. [PMID: 36155456 DOI: 10.1109/tvcg.2022.3209411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
We present sMolBoxes, a dataflow representation for the exploration and analysis of long molecular dynamics (MD) simulations. When MD simulations reach millions of snapshots, a frame-by-frame observation is not feasible anymore. Thus, biochemists rely to a large extent only on quantitative analysis of geometric and physico-chemical properties. However, the usage of abstract methods to study inherently spatial data hinders the exploration and poses a considerable workload. sMolBoxes link quantitative analysis of a user-defined set of properties with interactive 3D visualizations. They enable visual explanations of molecular behaviors, which lead to an efficient discovery of biochemically significant parts of the MD simulation. sMolBoxes follow a node-based model for flexible definition, combination, and immediate evaluation of properties to be investigated. Progressive analytics enable fluid switching between multiple properties, which facilitates hypothesis generation. Each sMolBox provides quick insight to an observed property or function, available in more detail in the bigBox View. The case studies illustrate that even with relatively few sMolBoxes, it is possible to express complex analytical tasks, and their use in exploratory analysis is perceived as more efficient than traditional scripting-based methods.
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Corey RA, Baaden M, Chavent M. A brief history of visualizing membrane systems in molecular dynamics simulations. FRONTIERS IN BIOINFORMATICS 2023; 3:1149744. [PMID: 37213533 PMCID: PMC10196259 DOI: 10.3389/fbinf.2023.1149744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 03/13/2023] [Indexed: 05/23/2023] Open
Abstract
Understanding lipid dynamics and function, from the level of single, isolated molecules to large assemblies, is more than ever an intensive area of research. The interactions of lipids with other molecules, particularly membrane proteins, are now extensively studied. With advances in the development of force fields for molecular dynamics simulations (MD) and increases in computational resources, the creation of realistic and complex membrane systems is now common. In this perspective, we will review four decades of the history of molecular dynamics simulations applied to membranes and lipids through the prism of molecular graphics.
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Affiliation(s)
- R. A. Corey
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
| | - M. Baaden
- Centre Nationale de la Recherche Scientifique, Laboratoire de Biochimie Théorique, Université Paris Cité, Paris, France
| | - M. Chavent
- Institut de Pharmacologie et Biologie Structurale, CNRS, Université de Toulouse, Toulouse, France
- *Correspondence: M. Chavent,
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Miller MD, Phillips GN. Moving beyond static snapshots: Protein dynamics and the Protein Data Bank. J Biol Chem 2021; 296:100749. [PMID: 33961840 PMCID: PMC8164045 DOI: 10.1016/j.jbc.2021.100749] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 04/28/2021] [Accepted: 04/30/2021] [Indexed: 01/02/2023] Open
Abstract
Proteins are the molecular machines of living systems. Their dynamics are an intrinsic part of their evolutionary selection in carrying out their biological functions. Although the dynamics are more difficult to observe than a static, average structure, we are beginning to observe these dynamics and form sound mechanistic connections between structure, dynamics, and function. This progress is highlighted in case studies from myoglobin and adenylate kinase to the ribosome and molecular motors where these molecules are being probed with a multitude of techniques across many timescales. New approaches to time-resolved crystallography are allowing simple “movies” to be taken of proteins in action, and new methods of mapping the variations in cryo-electron microscopy are emerging to reveal a more complete description of life’s machines. The results of these new methods are aided in their dissemination by continual improvements in curation and distribution by the Protein Data Bank and their partners around the world.
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Affiliation(s)
| | - George N Phillips
- Department of Biosciences, Rice University, Houston, Texas, USA; Department of Chemistry, Rice University, Houston, Texas, USA.
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Martinez X, Krone M, Alharbi N, Rose AS, Laramee RS, O'Donoghue S, Baaden M, Chavent M. Molecular Graphics: Bridging Structural Biologists and Computer Scientists. Structure 2019; 27:1617-1623. [PMID: 31564470 DOI: 10.1016/j.str.2019.09.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 08/02/2019] [Accepted: 09/10/2019] [Indexed: 01/20/2023]
Abstract
Visualization of molecular structures is one of the most common tasks carried out by structural biologists, typically using software, such as Chimera, COOT, PyMOL, or VMD. In this Perspective article, we outline how past developments in computer graphics and data visualization have expanded the understanding of biomolecular function, and we summarize recent advances that promise to further transform structural biology. We also highlight how progress in molecular graphics has been impeded by communication barriers between two communities: the computer scientists driving these advances, and the structural and computational biologists who stand to benefit. By pointing to canonical papers and explaining technical progress underlying new graphical developments in simple terms, we aim to improve communication between these communities; this, in turn, would help shape future developments in molecular graphics.
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Affiliation(s)
- Xavier Martinez
- Laboratoire de Biochimie Théorique, CNRS, UPR9080, Institut de Biologie Physico-Chimique, Paris, France
| | - Michael Krone
- Big Data Visual Analytics in Life Sciences, University of Tübingen, Tübingen, Germany
| | - Naif Alharbi
- Department of Computer Science, Swansea University, Swansea, Wales, United Kingdom
| | - Alexander S Rose
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, USA
| | - Robert S Laramee
- Department of Computer Science, Swansea University, Swansea, Wales, United Kingdom
| | - Sean O'Donoghue
- Garvan Institute of Medical Research, Sydney, Australia; University of New South Wales (UNSW), Sydney, Australia; CSIRO Data61, Sydney, Australia
| | - Marc Baaden
- Laboratoire de Biochimie Théorique, CNRS, UPR9080, Institut de Biologie Physico-Chimique, Paris, France
| | - Matthieu Chavent
- Institut de Pharmacologie et de Biologie Structurale IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France.
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Hermosilla P, Estrada J, Guallar V, Ropinski T, Vinacua A, Vazquez PP. Physics-Based Visual Characterization of Molecular Interaction Forces. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2017; 23:731-740. [PMID: 27875187 DOI: 10.1109/tvcg.2016.2598825] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Molecular simulations are used in many areas of biotechnology, such as drug design and enzyme engineering. Despite the development of automatic computational protocols, analysis of molecular interactions is still a major aspect where human comprehension and intuition are key to accelerate, analyze, and propose modifications to the molecule of interest. Most visualization algorithms help the users by providing an accurate depiction of the spatial arrangement: the atoms involved in inter-molecular contacts. There are few tools that provide visual information on the forces governing molecular docking. However, these tools, commonly restricted to close interaction between atoms, do not consider whole simulation paths, long-range distances and, importantly, do not provide visual cues for a quick and intuitive comprehension of the energy functions (modeling intermolecular interactions) involved. In this paper, we propose visualizations designed to enable the characterization of interaction forces by taking into account several relevant variables such as molecule-ligand distance and the energy function, which is essential to understand binding affinities. We put emphasis on mapping molecular docking paths obtained from Molecular Dynamics or Monte Carlo simulations, and provide time-dependent visualizations for different energy components and particle resolutions: atoms, groups or residues. The presented visualizations have the potential to support domain experts in a more efficient drug or enzyme design process.
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Skånberg R, Vázquez PP, Guallar V, Ropinski T. Real-Time Molecular Visualization Supporting Diffuse Interreflections and Ambient Occlusion. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2016; 22:718-727. [PMID: 26390480 DOI: 10.1109/tvcg.2015.2467293] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Today molecular simulations produce complex data sets capturing the interactions of molecules in detail. Due to the complexity of this time-varying data, advanced visualization techniques are required to support its visual analysis. Current molecular visualization techniques utilize ambient occlusion as a global illumination approximation to improve spatial comprehension. Besides these shadow-like effects, interreflections are also known to improve the spatial comprehension of complex geometric structures. Unfortunately, the inherent computational complexity of interreflections would forbid interactive exploration, which is mandatory in many scenarios dealing with static and time-varying data. In this paper, we introduce a novel analytic approach for capturing interreflections of molecular structures in real-time. By exploiting the knowledge of the underlying space filling representations, we are able to reduce the required parameters and can thus apply symbolic regression to obtain an analytic expression for interreflections. We show how to obtain the data required for the symbolic regression analysis, and how to exploit our analytic solution to enhance interactive molecular visualizations.
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Hirst JD, Glowacki DR, Baaden M. Molecular simulations and visualization: introduction and overview. Faraday Discuss 2014; 169:9-22. [DOI: 10.1039/c4fd90024c] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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López-Blanco JR, Aliaga JI, Quintana-Ortí ES, Chacón P. iMODS: internal coordinates normal mode analysis server. Nucleic Acids Res 2014; 42:W271-6. [PMID: 24771341 PMCID: PMC4086069 DOI: 10.1093/nar/gku339] [Citation(s) in RCA: 369] [Impact Index Per Article: 36.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Normal mode analysis (NMA) in internal (dihedral) coordinates naturally reproduces the collective functional motions of biological macromolecules. iMODS facilitates the exploration of such modes and generates feasible transition pathways between two homologous structures, even with large macromolecules. The distinctive internal coordinate formulation improves the efficiency of NMA and extends its applicability while implicitly maintaining stereochemistry. Vibrational analysis, motion animations and morphing trajectories can be easily carried out at different resolution scales almost interactively. The server is versatile; non-specialists can rapidly characterize potential conformational changes, whereas advanced users can customize the model resolution with multiple coarse-grained atomic representations and elastic network potentials. iMODS supports advanced visualization capabilities for illustrating collective motions, including an improved affine-model-based arrow representation of domain dynamics. The generated all-heavy-atoms conformations can be used to introduce flexibility for more advanced modeling or sampling strategies. The server is free and open to all users with no login requirement at http://imods.chaconlab.org.
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Affiliation(s)
- José Ramón López-Blanco
- Department of Biological Chemical Physics, Rocasolano Physical Chemistry Institute C.S.I.C., Serrano 119, 28006 Madrid, Spain
| | - José I Aliaga
- Department of Computer Science and Engineering, University Jaume I, 12071 Castellón, Spain
| | | | - Pablo Chacón
- Department of Biological Chemical Physics, Rocasolano Physical Chemistry Institute C.S.I.C., Serrano 119, 28006 Madrid, Spain
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