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Benjamín-Rivera J, Otero MP, Tinoco AD. Reinforcing Protein Biochemistry: A Two-Week Experiment Studying Iron(III) Binding by the Transferrin Protein through Stoichiometric Determination, Stability Analysis, and Visualization of the Binding Site. JOURNAL OF CHEMICAL EDUCATION 2024; 101:1656-1664. [PMID: 38654892 PMCID: PMC11033862 DOI: 10.1021/acs.jchemed.3c01016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 02/29/2024] [Accepted: 03/01/2024] [Indexed: 04/26/2024]
Abstract
The two-week protein biochemistry experience described herein focuses on reinforcing key biochemical concepts and achieving significant learning domain accomplishments for students (Content Knowledge, Logical Mathematical Reasoning, Visualization, Information Literacy, and Knowledge Integration) and valuable teaching opportunities for instructors. The experience encompasses an exploration of the transport protein serum transferrin as an important regulator of Fe(III) biochemistry and incorporates techniques to assess protein-metal stoichiometry and protein stability and to perform molecular visualization. Students gain practical experience in utilizing spectrophotometric analysis for constructing stoichiometric curves, in performing urea-PAGE, and in applying the PyMOL program to evaluate metal coordination at a protein binding site and the associated protein structural change. The learning and teaching accomplishments provide valuable skills that can be extended into research and translated to other teaching formats.
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Affiliation(s)
- Josué
A. Benjamín-Rivera
- Department
of Chemistry, University of Puerto Rico, Río Piedras Campus, Río Piedras, Puerto Rico 00931, United States
| | - Mariela Pérez Otero
- Department
of Biology, University of Puerto Rico, Río Piedras Campus, Río Piedras, Puerto Rico 00931, United States
| | - Arthur D. Tinoco
- Department
of Chemistry, University of Puerto Rico, Río Piedras Campus, Río Piedras, Puerto Rico 00931, United States
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2
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Ding Y, Zhou Q, Ding B, Zhang Y, Shen Y. Transcriptome analysis reveals the clinical significance of CXCL13 in Pan-Gyn tumors. J Cancer Res Clin Oncol 2024; 150:116. [PMID: 38459390 PMCID: PMC10923744 DOI: 10.1007/s00432-024-05619-3] [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: 12/02/2023] [Accepted: 01/09/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Gynecologic and breast tumors (Pan-Gyn) exhibit similar characteristics, and the role of CXCL13 in anti-tumor immunity and it's potential as a biomarker for immune checkpoint blockade (ICB) therapy have been gradually revealed. However, the precise role of CXCL13 in Pan-Gyn remains unclear, lacking a systematic analysis. METHODS We analyzed 2497 Pan-Gyn samples from the TCGA database, categorizing them into high and low CXCL13 expression groups. Validation was conducted using tumor expression datasets sourced from the GEO database. Correlation between CXCL13 and tumor immune microenvironment (TIME) was evaluated using multiple algorithms. Finally, we established nomograms for 3-year and 5-year mortality. RESULTS High expression of CXCL13 in Pan-Gyn correlates with a favorable clinical prognosis, increased immune cell infiltration, and reduced intra-tumor heterogeneity. Model was assessed using the C-index [BRCA: 0.763 (0.732-0.794), UCEC: 0.821 (0.793-0.849), CESC: 0.736 (0.684-0.788), and OV: 0.728 (0.707-0.749)], showing decent prediction of discrimination and calibration. CONCLUSION Overall, this study provides comprehensive insights into the commonalities and differences of CXCL13 in Pan-Gyn, potentially opening new avenues for personalized treatment.
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Affiliation(s)
- Yue Ding
- Zhongda Hospital Southeast University, Nanjing, China
| | - Quan Zhou
- Zhongda Hospital Southeast University, Nanjing, China
| | - Bo Ding
- Zhongda Hospital Southeast University, Nanjing, China
| | - Yang Zhang
- Department of Obstetrics and Gynecology, First People's Hospital of Lianyungang, No. 6 East Zhenhua Road, Haizhou, Lianyungang, China
| | - Yang Shen
- Zhongda Hospital Southeast University, Nanjing, China.
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3
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Li H, Wei X. A Concise Review of Biomolecule Visualization. Curr Issues Mol Biol 2024; 46:1318-1334. [PMID: 38392202 PMCID: PMC10887528 DOI: 10.3390/cimb46020084] [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: 01/06/2024] [Revised: 01/27/2024] [Accepted: 01/31/2024] [Indexed: 02/24/2024] Open
Abstract
The structural characteristics of biomolecules are a major focus in the field of structural biology. Molecular visualization plays a crucial role in displaying structural information in an intuitive manner, aiding in the understanding of molecular properties. This paper provides a comprehensive overview of core concepts, key techniques, and tools in molecular visualization. Additionally, it presents the latest research findings to uncover emerging trends and highlights the challenges and potential directions for the development of the field.
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Affiliation(s)
- Hui Li
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
| | - Xinru Wei
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
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4
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Shahzadi A, Ashfaq UA, Khurshid M, Nisar MA, Syed A, Bahkali AH. Deciphering Multi-target Pharmacological Mechanism of Cucurbita pepo Seeds against Kidney Stones: Network Pharmacology and Molecular Docking Approach. Curr Pharm Des 2024; 30:295-309. [PMID: 38213175 DOI: 10.2174/0113816128271781231104151155] [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: 07/12/2023] [Revised: 09/17/2023] [Accepted: 10/03/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND Urolithiasis is a prevalent condition with significant morbidity and economic implications. The economic burden associated with urolithiasis primarily stems from medical expenses. Previous literature suggests that herbal plants, including Cucurbita pepo, have lithotriptic capabilities. C. pepo is an annual, herbaceous, widely grown, and monoecious vegetative plant known for its antioxidants, fibers, and fatty acids. Recent studies on C. pepo seeds have shown therapeutic potential in reducing bladder stones and urodynamic illnesses, like kidney stones. However, the precise molecular and pharmacological mechanisms are unclear. OBJECTIVE In this research, we employed network pharmacology and molecular docking to examine the active compounds and biological mechanisms of Cucurbita pepo against kidney stones. METHODS Active constituents were obtained from previous studies and the IMPPAT database, with their targets predicted using Swiss target prediction. Kidney stone-associated genes were collected from DisGeNET and GeneCards. The active constituent-target-pathway network was constructed using Cytoscape, and the target protein-protein interaction network was generated using the STRING database. Gene enrichment analysis of C. pepo core targets was conducted using DAVID. Molecular docking was performed to identify potential kidney stone-fighting agents. RESULTS The findings revealed that Cucurbita pepo contains 18 active components and has 192 potential gene targets, including AR, EGFR, ESR1, AKT1, MAPK3, SRC, and MTOR. Network analysis demonstrated that C. pepo seeds may prevent kidney stones by influencing disease-related signaling pathways. Molecular docking indicated that key kidney stone targets (mTOR, EGFR, AR, and ESR1) effectively bind with active constituents of C. pepo. CONCLUSION These findings provide insight into the anti-kidney stone effects of Cucurbita pepo at a molecular level. In conclusion, this study contributes to understanding the potential of Cucurbita pepo in combating kidney stones and lays the foundation for further research.
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Affiliation(s)
- Aqsa Shahzadi
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan
| | - Usman Ali Ashfaq
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan
| | - Mohsin Khurshid
- Institute of Microbiology, Government College University Faisalabad, Faisalabad, Pakistan
| | - Muhammad Atif Nisar
- College of Science and Engineering, Flinders University, Bedford Park 5042, Australia
| | - Asad Syed
- Department of Botany and Microbiology, College of Science, King Saud University, P.O. 2455, Riyadh 11451, Saudi Arabia
| | - Ali H Bahkali
- Department of Botany and Microbiology, College of Science, King Saud University, P.O. 2455, Riyadh 11451, Saudi Arabia
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5
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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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6
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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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7
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de Brevern AG. A Perspective on the (Rise and Fall of) Protein β-Turns. Int J Mol Sci 2022; 23:12314. [PMID: 36293166 PMCID: PMC9604201 DOI: 10.3390/ijms232012314] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 10/07/2022] [Accepted: 10/13/2022] [Indexed: 11/21/2022] Open
Abstract
The β-turn is the third defined secondary structure after the α-helix and the β-sheet. The β-turns were described more than 50 years ago and account for more than 20% of protein residues. Nonetheless, they are often overlooked or even misunderstood. This poor knowledge of these local protein conformations is due to various factors, causes that I discuss here. For example, confusion still exists about the assignment of these local protein structures, their overlaps with other structures, the potential absence of a stabilizing hydrogen bond, the numerous types of β-turns and the software's difficulty in assigning or visualizing them. I also propose some ideas to potentially/partially remedy this and present why β-turns can still be helpful, even in the AlphaFold 2 era.
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Affiliation(s)
- Alexandre G de Brevern
- Université Paris Cité and Université des Antilles and Université de la Réunion, INSERM UMR_S 1134, BIGR, DSIMB Team, F-75014 Paris, France
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8
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Online tools to easily build virtual molecular models for display in augmented and virtual reality on the web. J Mol Graph Model 2022; 114:108164. [PMID: 35325844 DOI: 10.1016/j.jmgm.2022.108164] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 03/05/2022] [Accepted: 03/07/2022] [Indexed: 11/20/2022]
Abstract
Several groups developed in the last years augmented and virtual reality (AR/VR) software to visualize 3D molecules, most rather static, limited in content, and requiring software installs, some even requiring expensive hardware. We launched in 2020 moleculARweb (https://molecularweb.epfl.ch), a website that offers interactive content for chemistry and structural biology education through commodity web-based AR that works on consumer devices like smartphones, tablets and laptops. Among thousands of users, teachers increasingly request more biological macromolecules to be available, a demand that we cannot address individually. Therefore, to allow users to build their own material, we built a web interface where they can create online AR experiences in few steps starting from Protein Data Bank, AlphaFold or custom uploaded structures, or from virtual objects/scenes exported from the Visual Molecular Dynamics program, without any programming knowledge. The web tool also returns WebXR sessions for viewing and manipulating the models in WebXR-compatible devices including smartphones, tablets, and also immersive VR headsets with WebXR-capable browsers, where models can be manipulated even with bare hands when supported by the device. The tool is accessible for free at https://molecularweb.epfl.ch/pages/pdb2ar.html.
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9
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Penev PI, McCann HM, Meade CD, Alvarez-Carreño C, Maddala A, Bernier CR, Chivukula VL, Ahmad M, Gulen B, Sharma A, Williams LD, Petrov AS. ProteoVision: web server for advanced visualization of ribosomal proteins. Nucleic Acids Res 2021; 49:W578-W588. [PMID: 33999189 PMCID: PMC8265156 DOI: 10.1093/nar/gkab351] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 04/11/2021] [Accepted: 04/21/2021] [Indexed: 11/26/2022] Open
Abstract
ProteoVision is a web server designed to explore protein structure and evolution through simultaneous visualization of multiple sequence alignments, topology diagrams and 3D structures. Starting with a multiple sequence alignment, ProteoVision computes conservation scores and a variety of physicochemical properties and simultaneously maps and visualizes alignments and other data on multiple levels of representation. The web server calculates and displays frequencies of amino acids. ProteoVision is optimized for ribosomal proteins but is applicable to analysis of any protein. ProteoVision handles internally generated and user uploaded alignments and connects them with a selected structure, found in the PDB or uploaded by the user. It can generate de novo topology diagrams from three-dimensional structures. All displayed data is interactive and can be saved in various formats as publication quality images or external datasets or PyMol Scripts. ProteoVision enables detailed study of protein fragments defined by Evolutionary Classification of protein Domains (ECOD) classification. ProteoVision is available at http://proteovision.chemistry.gatech.edu/.
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Affiliation(s)
- Petar I Penev
- NASA Center for the Origin of Life, Georgia Institute of Technology, Atlanta, GA 30332-0400, USA.,School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Holly M McCann
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Caeden D Meade
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Claudia Alvarez-Carreño
- NASA Center for the Origin of Life, Georgia Institute of Technology, Atlanta, GA 30332-0400, USA.,School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Aparna Maddala
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Chad R Bernier
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.,School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Vasanta L Chivukula
- NASA Center for the Origin of Life, Georgia Institute of Technology, Atlanta, GA 30332-0400, USA.,School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Maria Ahmad
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Burak Gulen
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Aakash Sharma
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Loren Dean Williams
- NASA Center for the Origin of Life, Georgia Institute of Technology, Atlanta, GA 30332-0400, USA.,School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.,School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Anton S Petrov
- NASA Center for the Origin of Life, Georgia Institute of Technology, Atlanta, GA 30332-0400, USA.,School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.,School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
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10
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Martinez X, Baaden M. UnityMol prototype for FAIR sharing of molecular-visualization experiences: from pictures in the cloud to collaborative virtual reality exploration in immersive 3D environments. Acta Crystallogr D Struct Biol 2021; 77:746-754. [PMID: 34076589 PMCID: PMC8171070 DOI: 10.1107/s2059798321002941] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Accepted: 03/19/2021] [Indexed: 11/14/2022] Open
Abstract
Motivated by the current COVID-19 pandemic, which has spurred a substantial flow of structural data, the use of molecular-visualization experiences to make these data sets accessible to a broad audience is described. Using a variety of technology vectors related to the cloud, 3D and virtual reality gear, how to share curated visualizations of structural biology, modeling and/or bioinformatics data sets for interactive and collaborative exploration is examined. FAIR is discussed as an overarching principle for sharing such visualizations. Four initial example scenes related to recent COVID-19 structural data are provided, together with a ready-to-use (and share) implementation in the UnityMol software.
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Affiliation(s)
- Xavier Martinez
- CNRS, Université de Paris, UPR 9080, Laboratoire de Biochimie Théorique, 13 Rue Pierre et Marie Curie, 75005 Paris, France
- Institut de Biologie Physico-Chimique–Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | - Marc Baaden
- CNRS, Université de Paris, UPR 9080, Laboratoire de Biochimie Théorique, 13 Rue Pierre et Marie Curie, 75005 Paris, France
- Institut de Biologie Physico-Chimique–Fondation Edmond de Rothschild, PSL Research University, Paris, France
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11
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Richardson JS, Richardson DC, Goodsell DS. Seeing the PDB. J Biol Chem 2021; 296:100742. [PMID: 33957126 PMCID: PMC8167287 DOI: 10.1016/j.jbc.2021.100742] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 04/26/2021] [Accepted: 04/30/2021] [Indexed: 01/21/2023] Open
Abstract
Ever since the first structures of proteins were determined in the 1960s, structural biologists have required methods to visualize biomolecular structures, both as an essential tool for their research and also to promote 3D comprehension of structural results by a wide audience of researchers, students, and the general public. In this review to celebrate the 50th anniversary of the Protein Data Bank, we present our own experiences in developing and applying methods of visualization and analysis to the ever-expanding archive of protein and nucleic acid structures in the worldwide Protein Data Bank. Across that timespan, Jane and David Richardson have concentrated on the organization inside and between the macromolecules, with ribbons to show the overall backbone "fold" and contact dots to show how the all-atom details fit together locally. David Goodsell has explored surface-based representations to present and explore biological subjects that range from molecules to cells. This review concludes with some ideas about the current challenges being addressed by the field of biomolecular visualization.
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Affiliation(s)
- Jane S Richardson
- Department of Biochemistry, Duke University, Durham, North Carolina, USA.
| | - David C Richardson
- Department of Biochemistry, Duke University, Durham, North Carolina, USA
| | - David S Goodsell
- Department of Integrative and Computational Biology, The Scripps Research Institute, La Jolla, California, USA; Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, the State University of New Jersey, Piscataway, New Jersey, USA.
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12
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Juárez-Jiménez J, Tew P, O Connor M, Llabrés S, Sage R, Glowacki D, Michel J. Combining Virtual Reality Visualization with Ensemble Molecular Dynamics to Study Complex Protein Conformational Changes. J Chem Inf Model 2020; 60:6344-6354. [PMID: 33180485 DOI: 10.1021/acs.jcim.0c00221] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Molecular dynamics (MD) simulations are increasingly used to elucidate relationships between protein structure, dynamics, and their biological function. Currently, it is extremely challenging to perform MD simulations of large-scale structural rearrangements in proteins that occur on millisecond timescales or beyond, as this requires very significant computational resources, or the use of cumbersome "collective variable" enhanced sampling protocols. Here, we describe a framework that combines ensemble MD simulations and virtual reality visualization (eMD-VR) to enable users to interactively generate realistic descriptions of large amplitude, millisecond timescale protein conformational changes in proteins. Detailed tests demonstrate that eMD-VR substantially decreases the computational cost of folding simulations of a WW domain, without the need to define collective variables a priori. We further show that eMD-VR generated pathways can be combined with Markov state models to describe the thermodynamics and kinetics of large-scale loop motions in the enzyme cyclophilin A. Our results suggest eMD-VR is a powerful tool for exploring protein energy landscapes in bioengineering efforts.
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Affiliation(s)
- Jordi Juárez-Jiménez
- EaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, United Kingdom
| | - Philip Tew
- Interactive Scientific, Engine Shed, Station Approach, Bristol BS1 6QH, United Kingdom
| | - Michael O Connor
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom.,Department of Computer Science, University of Bristol, Merchant Venture's Building, Bristol BS8 1UB, United Kingdom.,Centre for Computational Chemistry, School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Salomé Llabrés
- EaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, United Kingdom
| | - Rebecca Sage
- Interactive Scientific, Engine Shed, Station Approach, Bristol BS1 6QH, United Kingdom
| | - David Glowacki
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom.,Department of Computer Science, University of Bristol, Merchant Venture's Building, Bristol BS8 1UB, United Kingdom.,Centre for Computational Chemistry, School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Julien Michel
- EaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, United Kingdom
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13
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Sehnal D, Svobodová R, Berka K, Rose AS, Burley SK, Velankar S, Koča J. High-performance macromolecular data delivery and visualization for the web. Acta Crystallogr D Struct Biol 2020; 76:1167-1173. [PMID: 33263322 PMCID: PMC7709201 DOI: 10.1107/s2059798320014515] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 11/01/2020] [Indexed: 11/11/2022] Open
Abstract
Biomacromolecular structural data make up a vital and crucial scientific resource that has grown not only in terms of its amount but also in its size and complexity. Furthermore, these data are accompanied by large and increasing amounts of experimental data. Additionally, the macromolecular data are enriched with value-added annotations describing their biological, physicochemical and structural properties. Today, the scientific community requires fast and fully interactive web visualization to exploit this complex structural information. This article provides a survey of the available cutting-edge web services that address this challenge. Specifically, it focuses on data-delivery problems, discusses the visualization of a single structure, including experimental data and annotations, and concludes with a focus on the results of molecular-dynamics simulations and the visualization of structural ensembles.
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Affiliation(s)
- David Sehnal
- CEITEC – Central European Institute of Technology, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - Radka Svobodová
- CEITEC – Central European Institute of Technology, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
| | - Karel Berka
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc, Šlechtitelů 241/27, 779 00 Olomouc, Czech Republic
| | - Alexander S. Rose
- Research Collaboratory for Structural Bioinformatics (RCSB), San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, San Diego, CA 92093-0743, USA
| | - Stephen K. Burley
- RCSB Protein Data Bank, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854-8076, USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, 195 Little Albany Street, New Brunswick, NJ 08903-2681, USA
- RCSB Protein Data Bank, San Diego Supercomputer Center and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0654, USA
| | - Sameer Velankar
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - Jaroslav Koča
- CEITEC – Central European Institute of Technology, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
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14
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Lal K, Bermeo R, Perez S. Computational tools for drawing, building and displaying carbohydrates: a visual guide. Beilstein J Org Chem 2020; 16:2448-2468. [PMID: 33082879 PMCID: PMC7537382 DOI: 10.3762/bjoc.16.199] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 09/17/2020] [Indexed: 01/08/2023] Open
Abstract
Drawing and visualisation of molecular structures are some of the most common tasks carried out in structural glycobiology, typically using various software. In this perspective article, we outline developments in the computational tools for the sketching, visualisation and modelling of glycans. The article also provides details on the standard representation of glycans, and glycoconjugates, which helps the communication of structure details within the scientific community. We highlight the comparative analysis of the available tools which could help researchers to perform various tasks related to structure representation and model building of glycans. These tools can be useful for glycobiologists or any researcher looking for a ready to use, simple program for the sketching or building of glycans.
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Affiliation(s)
- Kanhaya Lal
- Univ. Grenoble Alpes, CNRS, CERMAV, 38000 Grenoble, France
- Dipartimento di Chimica, Università Degli Studi di Milano, via Golgi 19, I-20133, Italy
| | - Rafael Bermeo
- Univ. Grenoble Alpes, CNRS, CERMAV, 38000 Grenoble, France
- Dipartimento di Chimica, Università Degli Studi di Milano, via Golgi 19, I-20133, Italy
| | - Serge Perez
- Univ. Grenoble Alpes, CNRS, CERMAV, 38000 Grenoble, France
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