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arXiv 2024年

作者： Amaro, R. Åqvist, J. Bahar, I. Battistini, F. Bellaiche, A. Beltran, D. Biggin, P.C. Bonomi, M. Bowman, G.R. Bryce, R. Bussi, G. Carloni, P. Case, D. Cavalli, A. Chang, C.A. Cheatham, T.E. Cheung, M.S. Chipot, C. Chong, L.T. Choudhary, P. Cisneros, G.A. Clementi, C. Collepardo-Guevara, R. Coveney, P. Covino, R. Crawford, T.D. Dal Peraro, M. de Groot, B. Delemotte, L. De Vivo, M. Essex, J. Fraternali, F. Gao, J. Gelpí, J.L. Gervasio, F.L. Gonzalez-Nilo, F.D. Grubmüller, H. Guenza, M.G. Guzman, H.V. Harris, S. Head-Gordon, T. Hernandez, R. Hospital, A. Huang, N. Huang, X. Hummer, G. Iglesias-Fernández, J. Jensen, J.H. Jha, S. Jiao, W. Jorgensen, W.L. Kamerlin, S.C.L. Khalid, S. Laughton, C. Levitt, M. Limongelli, V. Lindahl, E. Lindorff-Larsen, K. Loverde, S. Lundborg, M. Luo, Y.L. Luque, F.J. Lynch, C.I. MacKerell, A. Magistrato, A. Marrink, S.J. Martin, H. McCammon, J.A. Merz, K. Moliner, V. Mulholland, A. Murad, S. Naganathan, A.N. Nangia, S. Noe, F. Noy, A. Oláh, J. O'Mara, M. Ondrechen, M.J. Onuchic, J.N. Onufriev, A. Osuna, S. Palermo, G. Panchenko, A.R. Pantano, S. Parish, C. Parrinello, M. Perez, A. Perez-Acle, T. Perilla, J.R. Pettitt, B.M. Pietropaolo, A. Piquemal, J.-P. Poma, A. Praprotnik, M. Ramos, M.J. Ren, P. Reuter, N. Roitberg, A. Rosta, E. Rovira, C. Roux, B. Röthlisberger, U. Sanbonmatsu, K. Schlick, T. Shaytan, A.K. Simmerling, C. Smith, J.C. Sugita, Y. Świderek, K. Taiji, M. Tao, P. Tikhonova, I.G. Tirado-Rives, J. Tuñón, I. Van Der Kamp, M.W. Van der Spoel, D. Velankar, S. Voth, G.A. Wade, R. Warshel, A. Welborn, V.V. Wetmore, S. Wong, C.F. Yang, L.-W. Zacharias, M. Orozco, M. Department of Molecular Biology University of California San DiegoCA United States Department of Cell and Molecular Biology Uppsala University Uppsala Sweden Laufer Center for Physical and Quantitative Biology Renaissance School of Medicine Stony Brook University Stony BrookNY United States Department of Biochemistry and Cell Biology Renaissance School of Medicine Stony Brook University Stony BrookNY United States Barcelona Spain European Molecular Biology Laboratory European Bioinformatics Institute Hinxton United Kingdom Structural Bioinformatics and Computational Biochemistry Department of Biochemistry University of Oxford Oxford United Kingdom Institut Pasteur Université Paris Cité CNRS UMR 3528 Computational Structural Biology Unit Paris France Department of Biochemistry and Biophysics University of Pennsylvania PhiladelphiaPA United States Division of Pharmacy and Optometry University of Manchester Manchester United Kingdom Scuola Internazionale Superiore di Studi Avanzati-SISSA Trieste Italy Computational Biomedicine Institute of Advanced Simulations IAS-5 Institute for Neuroscience and Medicine INM-9 Forschungszentrum Jülich GmbH Jülich Germany Department of Physics and Universitätsklinikum RWTH Aachen University Aachen Germany Department of Chemistry & Chemical Biology Rutgers University PiscatawayNJ United States Istituto Italiano di Tecnologia Drug Discovery and Development Bologna Italy Lausanne Switzerland Department of Chemistry University of California RiversideCA United States Department of Medicinal Chemistry College of Pharmacy University of Utah Salt Lake CityUT United States Department of Physics University of Washington SeattleWA United States Pacific Northwest National Laboratory RichlandWA United States LIA CNRS-UIUC UMR n°7019 Université de Lorraine Vandœuvre-lès-Nancy France Department of Physics University of Illinois at Urbana-Champaign UrbanaIL United States Department of Biochemistry and Molecular Biol

The communities that embraced data archiving efforts decades ago are now, in the era of data-driven biology, those gaining the most from the AI revolution. The structural biology community was a pioneer in this regard by establishing the Protein Data Bank (PDB) in 1971 and making data accessible using the FAIR (Findable, Accessible, Interoperable and Reusable) principles even before these were articulated [1, 2]. The genomics/bioinformatics community has followed the example, establishing many widely used databases [3, 4]. By contrast, molecular simulation has been anchored in usage paradigms dating back to the seventies, when molecular dynamics (MD) simulation was first applied to study biomacromolecules [5]. At that time, MD was used by theoretical physicists and chemists in "proof of concept" simulations. Still, fifty years later, MD has evolved into a cornerstone molecular biology technique that can provide accurate quantitative analysis and property prediction. MD is now employed by tens of thousands of researchers worldwide, accounting for roughly 15% of global supercomputer usage. Unfortunately, these rich and costly data are not systematically maintained, and when further analyses are required, simulations have to be rerun-an unacceptable situation from scientific, environmental and sustainability standpoints. In this letter, we argue for a collaborative endeavor to archive MD simulation data and describe ongoing efforts to establish cost-effective and sustainable data archiving strategies. © 2024, CC BY-NC-SA.

关键词： Biotic

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Front Cover: Design, Synthesis, and Characterization of Novel Styryl Dyes as Fluorescent Probes for Tau Aggregate Detectionin Vitroand in Cells (Chem. Asian J. 6/2024)

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Chemistry – An Asian Journal 2024年第6期19卷

作者： Withsakorn Sangsuwan Kriangsak Faikhruea Kotchakorn Supabowornsathit Don Sangsopon Praewphan Ingrungruanglert Hathaichanok Chuntakaruk Napatsaporn Nuntavanotayan Kittiporn Nakprasit Nipan Israsena Thanyada Rungrotmongkol Pitak Chuawong Tirayut Vilaivan Chanat Aonbangkhen Center of Excellence in Natural Products Chemistry (CENP) Department of Chemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Department of Chemistry and Center of Excellence for Innovation in Chemistry Faculty of Science Special Research Unit for Advanced Magnetic Resonance (AMR) Kasetsart University Bangkok 10900 Thailand These authors are contributed equally. Organic Synthesis Research Unit Department of Chemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Stem Cell and Cell Therapy Research Unit and Department of Pharmacology Faculty of Medicine Chulalongkorn University Bangkok 10330 Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok 10330 Thailand Center of Excellence in Structural and Computational Biology Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand

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Guidelines for public database submission of uncultivated virus genome sequences for taxonomic classification (vol 41, pg 898, 2023)

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NATURE BIOTECHNOLOGY 2023年第9期41卷 1346-1346页

作者： Adriaenssens, Evelien M. M. Roux, Simon Brister, J. Rodney Karsch-Mizrachi, Ilene Kuhn, Jens H. Varsani, Arvind Yigang, Tong Reyes, Alejandro Lood, Cedric Lefkowitz, Elliot J. Sullivan, Matthew B. B. Edwards, Robert A. A. Simmonds, Peter Rubino, Luisa Sabanadzovic, Sead Krupovic, Mart Dutilh, Bas E. E. Quadram Institute Bioscience Norwich Research Park Rosalind Franklin Road Norwich UK United States Department of Energy Joint Genome Institute Lawrence Berkeley National Laboratory Berkeley CA USA National Center for Biotechnology Information National Library of Medicine National Institutes of Health Bethesda MD USA Integrated Research Facility at Fort Detrick National Institute of Allergy and Infectious Diseases National Institutes of Health Fort Detrick Frederick MD USA The Biodesign Center for Fundamental and Applied Microbiomics Arizona State University Tempe AZ USA Structural Biology Research Unit Department of Clinical Laboratory Sciences University of Cape Town Cape Town South Africa Beijing Advanced Innovation Center for Soft Matter Science and Engineering College of Life Science and Technology Beijing University of Chemical Technology Beijing China Max Planck Tandem Group in Computational Biology Department of Biological Sciences Universidad de los Andes Bogotá Colombia Centre of Microbial and Plant Genetics Department of Microbial and Molecular Systems KU Leuven Leuven Belgium Laboratory of Gene Technology Department of Biosystems KU Leuven Leuven Belgium Institute of Biodiversity Faculty of Biological Sciences Cluster of Excellence Balance of the Microverse Friedrich Schiller University Jena Jena Germany Department of Microbiology University of Alabama at Birmingham Birmingham AL USA Department of Microbiology The Ohio State University Columbus OH USA Department of Civil Environmental and Geodetic Engineering The Ohio State University Columbus OH USA Center of Microbiome Science The Ohio State University Columbus OH USA College of Science and Engineering Flinders University Bedford Park South Australia Australia Nuffield Department of Medicine University of Oxford South Parks Road Oxford UK Consiglio Nazionale delle Ricerche Istituto per la Protezione Sostenibile delle Piante Bari Italy Department of Biochemistry Molecular Bio

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Known allosteric proteins have central roles in genetic disease

arXiv

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arXiv 2021年

作者： Abrusán, György Ascher, David B. Inouye, Michael Cambridge Baker Systems Genomics Initiative Department of Public Health and Primary Care School of Medicine University of Cambridge United Kingdom Department of Biochemistry University of Cambridge Cambridge United Kingdom Structural Biology and Bioinformatics Department of Biochemistry Bio21 Institute University of Melbourne Melbourne Australia Computational Biology and Clinical Informatics Baker Heart and Diabetes Institute Melbourne Australia Cambridge Baker Systems Genomics Initiative Baker Heart and Diabetes Institute Melbourne Australia British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge United Kingdom British Heart Foundation Centre of Research Excellence University of Cambridge Cambridge United Kingdom Health Data Research UK Cambridge Wellcome Genome Campus and University of Cambridge Cambridge United Kingdom The Alan Turing Institute London United Kingdom

Allostery is a form of protein regulation, where ligands that bind sites located apart from the active site can modify the activity of the protein. The molecular mechanisms of allostery have been extensively studied, because allosteric sites are less conserved than active sites, and drugs targeting them are more specific than drugs binding the active sites. Here we quantify the importance of allostery in genetic disease. We show that 1) known allosteric proteins are central in disease networks, and contribute to genetic disease and comorbidities much more than non-allosteric proteins, in many major disease types like hematopoietic diseases, cardiovascular diseases, cancers, diabetes, or diseases of the central nervous system. 2) variants from cancer genome-wide association studies are enriched near allosteric proteins, indicating their importance to polygenic traits;and 3) the importance of allosteric proteins in disease is due, at least partly, to their central positions in protein-protein interaction networks, and probably not due to their dynamical properties. © 2021, CC BY.

关键词： Diseases

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PDBe-KB: collaboratively defining the biological context of structural data

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NUCLEIC ACIDS RESEARCH 2022年第D1期50卷 D534-D542页

作者： Varadi, Mihaly Anyango, Stephen Armstrong, David Berrisford, John Choudhary, Preeti Deshpande, Mandar Nadzirin, Nurul Nair, Sreenath S. Pravda, Lukas Tanweer, Ahsan Al-Lazikani, Bissan Andreini, Claudia Barton, Geoffrey J. Bednar, David Berka, Karel Blundell, Tom Brock, Kelly P. Carazo, Jose Maria Damborsky, Jiri David, Alessia Dey, Sucharita Dunbrack, Roland Recio, Juan Fernandez Fraternali, Franca Gibson, Toby Helmer-Citterich, Manuela Hoksza, David Hopf, Thomas Jakubec, David Kannan, Natarajan Krivak, Radoslav Kumar, Manjeet Levy, Emmanuel D. London, Nir Macias, Jose Ramon Srivatsan, Madhusudhan M. Marks, Debora S. Martens, Lennart McGowan, Stuart A. McGreig, Jake E. Modi, Vivek Parra, R. Gonzalo Pepe, Gerardo Piovesan, Damiano Prilusky, Jaime Putignano, Valeria Radusky, Leandro G. Ramasamy, Pathmanaban Rausch, Atilio O. Reuter, Nathalie Rodriguez, Luis A. Rollins, Nathan J. Rosato, Antonio Rubach, Pawel Serrano, Luis Singh, Gulzar Skoda, Petr Sorzano, Carlos Oscar S. Stourac, Jan Sulkowska, Joanna, I Svobodova, Radka Tichshenko, Natalia Tosatto, Silvio C. E. Vranken, Wim Wass, Mark N. Xue, Dandan Zaidman, Daniel Thornton, Janet Sternberg, Michael Orengo, Christine Velankar, Sameer European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Wellcome Genome Campus Hinxton United Kingdom Cancer Research UK Cancer Therapeutics Unit Division of Cancer Therapeutics The Institute of Cancer Research London United Kingdom University of Florence C.I.R.M.M.P. Magnetic Resonance Center Sesto Fiorentino Italy School of Life Sciences University of Dundee Dundee United Kingdom Masaryk University International Centre for Clinical Research St. Anne’s University Hospital Brno Department of Experimental Biology and RECETOX Brno Czech Republic Palacky University Olomouc Department of Physical Chemistry Olomouc Czech Republic University of Cambridge Department of Biochemistry Cambridge United Kingdom Computational and Systems Biology Massachusetts Institute of Technology Cambridge MA United States CNB-CSIC Biocomputing Unit - Instruct Image Processing Center Madrid Spain Imperial College London London United Kingdom Weizmann Institute of Science Rehovot Israel Fox Chase Cancer Center Institute for Cancer Research Philadelphia PA United States Instituto de Ciencias de la Vid y del Vino (CSIC - Universidad de La Rioja - Gobierno de La Rioja) Oenology Barcelona Spain Randall Centre for Cell & Molecular Biophysics King’s College London London United Kingdom European Molecular Biology Laboratory Heidelberg Germany Centre for Molecular Bioinformatics Department of Biology University of Rome Tor Vergata Rome Italy Charles University Prague Czech Republic University of Georgia Department of Biochemistry and Molecular Biology Institute of Bioinformatics Athens United States Indian Institute of Science Education and Research Pune India Ghent University Department of Biomolecular Medicine Ghent Belgium VIB-UGent Center for Medical Biotechnology Ghent Belgium University of Kent Canterbury Kent United Kingdom Barcelona Supercomputing Center Life Sciences Department Barcelona Spain University of Padova Deptartment of Biomedical

The Protein Data Bank in Europe - Knowledge Base (PDBe-KB, https://***) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive.

关键词： mutation biophysics frustration internet libraries molecular structure phosphorylation graphical displays protein structure protein data bank molecule knowledge bases datasets

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How to learn from inconsistencies: Integrating molecular simulations with experimental data

arXiv

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arXiv 2019年

作者： Orioli, Simone Larsen, Andreas Haahr Bottaro, Sandro Lindorff-Larsen, Kresten Structural Biology NMR Laboratory Linderstrøm-Lang Centre for Protein Science Department of Biology University of Copenhagen Copenhagen Denmark Structural Biophysics Niels Bohr Institute Faculty of Science University of Copenhagen Copenhagen Denmark Structural Bioinformatics and Computational Biochemistry Unit Department of Biochemistry University of Oxford Oxford United Kingdom Atomistic Simulations Laboratory Istituto Italiano di Tecnologia Genova Italy

Molecular simulations and biophysical experiments can be used to provide independent and complementary insights into the molecular origin of biological processes. A particularly useful strategy is to use molecular simulations as a modelling tool to interpret experimental measurements, and to use experimental data to refine our biophysical models. Thus, explicit integration and synergy between molecular simulations and experiments is fundamental for furthering our understanding of biological processes. This is especially true in the case where discrepancies between measured and simulated observables emerge. In this chapter, we provide an overview of some of the core ideas behind methods that were developed to improve the consistency between experimental information and numerical predictions. We distinguish between situations where experiments are used to refine our understanding and models of specific systems, and situations where experiments are used more generally to refine transferable models. We discuss different philosophies and attempt to unify them in a single framework. Until now, such integration between experiments and simulations have mostly been applied to static data, and we discuss more recent developments aimed to analyse time-dependent or time-resolved data. Copyright © 2019, The Authors. All rights reserved.

关键词： Philosophical aspects

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Inhibition of topoisomerase IIα and induction of DNA damage in cholangiocarcinoma cells by altholactone and its halogenated benzoate derivatives

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Biomedicine and Pharmacotherapy 2020年 127卷 110149-110149页

作者： Kitdumrongthum, Sarunya Reabroi, Somrudee Suksen, Kanoknetr Tuchinda, Patoomratana Munyoo, Bamroong Mahalapbutr, Panupong Rungrotmongkol, Thanyada Ounjai, Puey Chairoungdua, Arthit Toxicology Graduate Program Faculty of Science Mahidol University Bangkok Thailand Excellent Center for Drug Discovery (ECDD) Mahidol University Bangkok Thailand Department of Pharmacology Faculty of Science Mahidol University Bangkok Thailand Department of Physiology Faculty of Science Mahidol University Bangkok Thailand Department of Chemistry Faculty of Science Mahidol University Bangkok Thailand Structural and Computational Biology Research Unit Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok Thailand Department of Biology Faculty of Science Mahidol University Bangkok Thailand

Topoisomerase IIα enzyme (Topo IIα) plays a critical function in DNA replication process and is considered to be a promising target of anti-cancer drugs. In the present study, we reported that the altholactone derivatives modified by adding a halogenated benzoate group showed greater inhibitory activity on Topo IIα enzyme in cell-free system concomitant with cytotoxicity against the CCA cell lines (KKU-M055 and KKU-M213) than those of the parent altholactone. However, the cytotoxic activities of four halogenated benzoate altholactone derivatives including iodo-, fluoro-, chloro-, and bromobenzoate derivatives (compound 1, 2, 3, and 4, respectively) were of equal potency. The fluorobenzoate derivative (compound 2) was chosen for investigating the underlying mechanism in CCA cells. Compound 2 arrested CCA cell cycle at sub G1 phase and induced apoptotic cell death. It markedly inhibited Topo IIα protein expression in both KKU-M055 and KKU-M213 cells, which was accompanied by DNA double-strand breaks demonstrated by an increase in phosphorylated H2A.X protein. Interestingly, KKU-M055 cells, which express higher Topo IIα mRNA compared to KKU-M213 cells, showed greater sensitivity to the compound, indicating the selectivity of the compound to Topo IIα enzyme. By computational docking analysis, the binding affinity of altholactone (-52.5 kcal/mol) and compound 2 (-56.7 kcal/mol) were similar to that of the Topo II poison salvicine (-53.7 kcal/mol). The aromatic moiety of both altholactones embedded in a hydrophobic pocket of Topo II ATPase domain. In addition, compound 2 induced the formation of linear DNA in Topo II-mediated cleavage assay. Collectively, our results demonstrate that the addition of fluorobenzoyl group to altholactone enhances potency and selectivity to inhibit type IIα topoisomerases. Atholactone and fluorobenzoate derivative act as Topo II cleavage complexes stabilizing compounds or Topo II poisons preferentially through binding at ATPase domain of Topo

关键词： Altholactone Cholangiocarcinoma Halogenated benzoate Topoisomerase IIα

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Publisher Correction: Atomistic mechanisms underlying the activation of the G protein-coupled sweet receptor heterodimer by sugar alcohol recognition

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Scientific reports 2019年第1期9卷 18996页

作者： Panupong Mahalapbutr Nitchakan Darai Wanwisa Panman Aunchan Opasmahakul Nawee Kungwan Supot Hannongbua Thanyada Rungrotmongkol Structural and Computational Biology Research Unit Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. Program in Biotechnology Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. Multidisciplinary Program of Petrochemistry and Polymer Science Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. Computational Chemistry Center of Excellent Department of Chemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. Department of Chemistry Faculty of Science Chiang Mai University Chiang Mai 50200 Thailand. Center of Excellence in Materials Science and Technology Chiang Mai University Chiang Mai 50200 Thailand. Structural and Computational Biology Research Unit Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. t.rungrotmongkol@***. Ph.D. Program in Bioinformatics and Computational Biology Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. t.rungrotmongkol@***. Molecular Sensory Science Center Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. t.rungrotmongkol@***.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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PLUMED Tutorials: a collaborative, community-driven learning ecosystem

arXiv

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arXiv 2024年

作者： Tribello, Gareth A. Bonomi, Massimiliano Bussi, Giovanni Camilloni, Carlo Armstrong, Blake I. Arsiccio, Andrea Aureli, Simone Ballabio, Federico Bernetti, Mattia Bonati, Luigi Brookes, Samuel G.H. Faidon Brotzakis, Z. Capelli, Riccardo Ceriotti, Michele Chan, Kam-Tung Cossio, Pilar Dasetty, Siva Donadio, Davide Ensing, Bernd Ferguson, Andrew L. Fraux, Guillaume Gale, Julian D. Gervasio, Francesco Luigi Giorgino, Toni Herringer, Nicholas S.M. Hocky, Glen M. Hoff, Samuel E. Invernizzi, Michele Languin-Cattoën, Olivier Leone, Vanessa Limongelli, Vittorio Lopez-Acevedo, Olga Marinelli, Fabrizio Martinez, Pedro Febrer Masetti, Matteo Mehdi, Shams Michaelides, Angelos Murtada, Mhd Hussein Parrinello, Michele Piaggi, Pablo M. Pietropaolo, Adriana Pietrucci, Fabio Pipolo, Silvio Pritchard, Claire Raiteri, Paolo Raniolo, Stefano Rapetti, Daniele Rizzi, Valerio Rydzewski, Jakub Salvalaglio, Matteo Schran, Christoph Seal, Aniruddha Zadeh, Armin Shayesteh Silva, Tomás F.D. Spiwok, Vojtěch Stirnemann, Guillaume Sucerquia, Daniel Tiwary, Pratyush Valsson, Omar Vendruscolo, Michele Voth, Gregory A. White, Andrew D. Wu, Jiangbo Centre for Quantum Materials and Technology School of Mathematics and Physics Queen’s University Belfast United Kingdom Institut Pasteur Université Paris Cité CNRS UMR 3528 Computational Structural Biology Unit Paris France Via Bonomea 265 Trieste34136 Italy Department of Biosciences University of Milano Milano Italy School of Molecular and Life Sciences Curtin University GPO Box U1987 PerthWA6845 Australia Coriolis Pharma Fraunhoferstrasse 18b Martinsried82152 Germany School of Pharmaceutical Sciences University of Geneva Rue Michel-Servet 1 GenevaCH-1206 Switzerland Institute of Pharmaceutical Sciences of Western Switzerland University of Geneva GenevaCH-1206 Switzerland Swiss Bioinformatics Institute University of Geneva GenevaCH-1206 Switzerland Via Celoria 26 Milan20133 Italy Department of Biomolecular Sciences University of Urbino "Carlo Bo" Piazza Rinascimento 6 Urbino61029 Italy Department of Pharmacy and Biotechnology Alma Mater Studiorum University of Bologna Via Belmeloro 6 Bologna40126 Italy Atomistic Simulations Italian Institute of Technology Genova Italy Yusuf Hamied Department of Chemistry University of Cambridge CambridgeCB2 1EW United Kingdom Institute for Bioinnovation Biomedical Sciences Research Center "Alexander Fleming" Vari16672 Greece Laboratory of Computational Science and Modeling Institut des Matériaux École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Chemistry University of California Davis DavisCA95616 United States Center for Computational Mathematics Flatiron Institute New YorkNY10010 United States Center for Computational Biology Flatiron Institute New YorkNY10010 United States Pritzker School of Molecular Engineering University of Chicago ChicagoIL60637 United States AI4Science Lab Informatics Institute University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Computational Chemistry Group Van’t Hoff Institute for Molecular Sciences Unive

In computational physics, chemistry, and biology, the implementation of new techniques in a shared and open source software lowers barriers to entry and promotes rapid scientific progress. However, effectively training new software users presents several challenges. Common methods like direct knowledge transfer and in-person workshops are limited in reach and comprehensiveness. Furthermore, while the COVID-19 pandemic highlighted the benefits of online training, traditional online tutorials can quickly become outdated and may not cover all the software’s functionalities. To address these issues, here we introduce "PLUMED Tutorials", a collaborative model for developing, sharing, and updating online tutorials. This initiative utilizes repository management and continuous integration to ensure compatibility with software updates. Moreover, the tutorials are interconnected to form a structured learning path and are enriched with automatic annotations to provide broader context. This paper illustrates the development, features, and advantages of PLUMED Tutorials, aiming to foster an open community for creating and sharing educational resources. © 2024, CC BY.

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Atomistic mechanisms underlying the activation of the G protein-coupled sweet receptor heterodimer by sugar alcohol recognition (vol 9, 10205, 2019)

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SCIENTIFIC REPORTS 2019年第1期9卷 1-11页

作者： Mahalapbutr, Panupong Darai, Nitchakan Panman, Wanwisa Opasmahakul, Aunchan Kungwan, Nawee Hannongbua, Supot Rungrotmongkol, Thanyada Structural and Computational Biology Research Unit Department of Biochemistry Faculty of Science Chulalongkorn University 10330 Bangkok Thailand Program in Biotechnology Faculty of Science Chulalongkorn University 10330 Bangkok Thailand Multidisciplinary Program of Petrochemistry and Polymer Science Faculty of Science Chulalongkorn University 10330 Bangkok Thailand Computational Chemistry Center of Excellent Department of Chemistry Faculty of Science Chulalongkorn University 10330 Bangkok Thailand Department of Chemistry Faculty of Science Chiang Mai University 50200 Chiang Mai Thailand Center of Excellence in Materials Science and Technology Chiang Mai University 50200 Chiang Mai Thailand Ph.D. Program in Bioinformatics and Computational Biology Faculty of Science Chulalongkorn University 10330 Bangkok Thailand Molecular Sensory Science Center Faculty of Science Chulalongkorn University 10330 Bangkok Thailand

The human T1R2-T1R3 sweet taste receptor (STR) plays an important role in recognizing various low-molecular-weight sweet-tasting sugars and proteins, resulting in the release of intracellular heterotrimeric G protein that in turn leads to the sweet taste perception. Xylitol and sorbitol, which are naturally occurring sugar alcohols (polyols) found in many fruits and vegetables, exhibit the potential caries-reducing effect and are widely used for diabetic patients as low-calorie sweeteners. In the present study, computational tools were applied to investigate the structural details of binary complexes formed between these two polyols and the T1R2-T1R3 heterodimeric STR. Principal component analysis revealed that the Venus flytrap domain (VFD) of T1R2 monomer was adapted by the induced-fit mechanism to accommodate the focused polyols, in which α-helical residues 233–268 moved significantly closer to stabilize ligands. This finding likely suggested that these structural transformations might be the important mechanisms underlying polyols-STR recognitions. The calculated free energies also supported the VFD of T1R2 monomer as the preferential binding site for such polyols, rather than T1R3 region, in accord with the lower number of accessible water molecules in the T1R2 pocket. The E302 amino acid residue in T1R2 was found to be the important recognition residue for polyols binding through a strongly formed hydrogen bond. Additionally, the binding affinity of xylitol toward the T1R2 monomer was significantly higher than that of sorbitol, making it a sweeter tasting molecule. [ABSTRACT FROM AUTHOR]

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