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Evans ML, Bergsma J, Merkys A, Andersen CW, Andersson OB, Beltrán D, Blokhin E, Boland TM, Castañeda Balderas R, Choudhary K, Díaz Díaz A, Domínguez García R, Eckert H, Eimre K, Fuentes Montero ME, Krajewski AM, Mortensen JJ, Nápoles Duarte JM, Pietryga J, Qi J, Trejo Carrillo FDJ, Vaitkus A, Yu J, Zettel A, de Castro PB, Carlsson J, Cerqueira TFT, Divilov S, Hajiyani H, Hanke F, Jose K, Oses C, Riebesell J, Schmidt J, Winston D, Xie C, Yang X, Bonella S, Botti S, Curtarolo S, Draxl C, Fuentes Cobas LE, Hospital A, Liu ZK, Marques MAL, Marzari N, Morris AJ, Ong SP, Orozco M, Persson KA, Thygesen KS, Wolverton C, Scheidgen M, Toher C, Conduit GJ, Pizzi G, Gražulis S, Rignanese GM, Armiento R. Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange. DIGITAL DISCOVERY 2024; 3:1509-1533. [PMID: 39118978 PMCID: PMC11305395 DOI: 10.1039/d4dd00039k] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/15/2024] [Indexed: 08/10/2024]
Abstract
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development.
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Affiliation(s)
- Matthew L Evans
- UCLouvain, Institut de la Matière Condensée et des Nanosciences (IMCN) Chemin des Étoiles 8, Louvain-la-Neuve 1348 Belgium
- Matgenix SRL 185 Rue Armand Bury 6534 Gozée Belgium
| | - Johan Bergsma
- Centre Européen de Calcul Atomique et Moléculaire (CECAM), École Polytechnique Fédérale de Lausanne Avenue de Forel 3 1015 Lausanne Switzerland
| | - Andrius Merkys
- Institute of Biotechnology, Life Sciences Center, Vilnius University Saulėtekio av. 7 LT-10257 Vilnius Lithuania
| | | | - Oskar B Andersson
- Materials Design and Informatics Unit, Department of Physics, Chemistry and Biology, Linköping University Sweden
| | - Daniel Beltrán
- Institute for Research in Biomedicine (IRB Barcelona) Baldiri i Reixac 10-12 08028 Barcelona Spain
| | - Evgeny Blokhin
- Tilde Materials Informatics Straßmannstraße 25 10249 Berlin Germany
- Materials Platform for Data Science Sepapaja 6 15551 Tallinn Estonia
| | - Tara M Boland
- Computational Atomic-Scale Materials Design, Technical University of Denmark Kgs. Lyngby Denmark
| | - Rubén Castañeda Balderas
- Centro de Investigación en Materiales Avanzados, S.C. (CIMAV) Av. Miguel de Cervantes 120, Complejo Industrial Chihuahua 31136 Chihuahua Chih. Mexico
| | - Kamal Choudhary
- Material Measurement Laboratory, National Institute of Standards and Technology Gaithersburg MD 20899 USA
| | - Alberto Díaz Díaz
- Centro de Investigación en Materiales Avanzados, S.C. (CIMAV) Av. Miguel de Cervantes 120, Complejo Industrial Chihuahua 31136 Chihuahua Chih. Mexico
| | - Rodrigo Domínguez García
- Centro de Investigación en Materiales Avanzados, S.C. (CIMAV) Av. Miguel de Cervantes 120, Complejo Industrial Chihuahua 31136 Chihuahua Chih. Mexico
| | - Hagen Eckert
- Department of Mechanical Engineering and Materials Science, Duke University Durham NC 27708 USA
- Center for Extreme Materials, Duke University Durham NC 27708 USA
| | - Kristjan Eimre
- Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
| | | | - Adam M Krajewski
- Department of Materials Science and Engineering, The Pennsylvania State University, University Park PA 16802 USA
| | - Jens Jørgen Mortensen
- Computational Atomic-Scale Materials Design, Technical University of Denmark Kgs. Lyngby Denmark
| | | | - Jacob Pietryga
- Department of Materials Science and Engineering, Northwestern University Evanston IL 60208 USA
| | - Ji Qi
- Department of NanoEngineering, University of California, San Diego 9500 Gilman Drive, La Jolla California 92093-0448 USA
| | - Felipe de Jesús Trejo Carrillo
- Centro de Investigación en Materiales Avanzados, S.C. (CIMAV) Av. Miguel de Cervantes 120, Complejo Industrial Chihuahua 31136 Chihuahua Chih. Mexico
| | - Antanas Vaitkus
- Institute of Biotechnology, Life Sciences Center, Vilnius University Saulėtekio av. 7 LT-10257 Vilnius Lithuania
| | - Jusong Yu
- Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
- Laboratory for Materials Simulations (LMS), Paul Scherrer Institute (PSI) 5232 Villigen PSI Switzerland
| | - Adam Zettel
- Department of Mechanical Engineering and Materials Science, Duke University Durham NC 27708 USA
- Center for Extreme Materials, Duke University Durham NC 27708 USA
| | | | - Johan Carlsson
- Dassault Systèmes Germany GmbH Am Kabellager 11-13 51063 Cologne Germany
| | - Tiago F T Cerqueira
- CFisUC, Department of Physics, University of Coimbra Rua Larga 3004-516 Coimbra Portugal
| | - Simon Divilov
- Department of Mechanical Engineering and Materials Science, Duke University Durham NC 27708 USA
- Center for Extreme Materials, Duke University Durham NC 27708 USA
| | - Hamidreza Hajiyani
- Dassault Systèmes Germany GmbH Am Kabellager 11-13 51063 Cologne Germany
| | - Felix Hanke
- Dassault Systèmes 22 Science Park CB4 0FJ UK
| | - Kevin Jose
- Theory of Condensed Matter, Cavendish Laboratory Cambridge UK
| | - Corey Oses
- Department of Materials Science and Engineering, Johns Hopkins University Baltimore MD 21218 USA
| | - Janosh Riebesell
- Theory of Condensed Matter, Cavendish Laboratory Cambridge UK
- Lawrence Berkeley National Lab Berkeley CA USA
| | - Jonathan Schmidt
- Materials Theory, ETH Zürich Wolfgang-Pauli-Strasse 27 8093 Zurich Switzerland
| | | | - Christen Xie
- Department of NanoEngineering, University of California, San Diego 9500 Gilman Drive, La Jolla California 92093-0448 USA
| | - Xiaoyu Yang
- Computer Network Information Center, Chinese Academy of Sciences Beijing 100083 China
- University of Chinese Academy of Sciences Beijing 101408 China
- Beijing MaiGao MatCloud Technology Co. Ltd Beijing 100149 China
| | - Sara Bonella
- Centre Européen de Calcul Atomique et Moléculaire (CECAM), École Polytechnique Fédérale de Lausanne Avenue de Forel 3 1015 Lausanne Switzerland
| | - Silvana Botti
- Research Center Future Energy Materials and Systems of the University Alliance Ruhr and Interdisciplinary Centre for Advanced Materials Simulation, Ruhr University Bochum, Universitätsstraße 150 D-44801 Bochum Germany
| | - Stefano Curtarolo
- Department of Mechanical Engineering and Materials Science, Duke University Durham NC 27708 USA
- Center for Extreme Materials, Duke University Durham NC 27708 USA
| | - Claudia Draxl
- Humboldt-Universität zu Berlin, Institut für Physik and IRIS Adlershof 12489 Berlin Germany
| | - Luis Edmundo Fuentes Cobas
- Centro de Investigación en Materiales Avanzados, S.C. (CIMAV) Av. Miguel de Cervantes 120, Complejo Industrial Chihuahua 31136 Chihuahua Chih. Mexico
| | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona) Baldiri i Reixac 10-12 08028 Barcelona Spain
| | - Zi-Kui Liu
- Department of Materials Science and Engineering, The Pennsylvania State University, University Park PA 16802 USA
| | - Miguel A L Marques
- Research Center Future Energy Materials and Systems of the University Alliance Ruhr and Interdisciplinary Centre for Advanced Materials Simulation, Ruhr University Bochum, Universitätsstraße 150 D-44801 Bochum Germany
| | - Nicola Marzari
- Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
- Laboratory for Materials Simulations (LMS), Paul Scherrer Institute (PSI) 5232 Villigen PSI Switzerland
| | - Andrew J Morris
- School of Metallurgy and Materials, University of Birmingham Edgbaston Birmingham B15 2TT UK
| | - Shyue Ping Ong
- Department of NanoEngineering, University of California, San Diego 9500 Gilman Drive, La Jolla California 92093-0448 USA
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona) Baldiri i Reixac 10-12 08028 Barcelona Spain
| | - Kristin A Persson
- Lawrence Berkeley National Lab Berkeley CA USA
- Department of Materials Science and Engineering, UC Berkeley Hearst Mining Memorial Building Berkeley 94720 CA USA
| | - Kristian S Thygesen
- Computational Atomic-Scale Materials Design, Technical University of Denmark Kgs. Lyngby Denmark
| | - Chris Wolverton
- Department of Materials Science and Engineering, Northwestern University Evanston IL 60208 USA
| | - Markus Scheidgen
- Humboldt-Universität zu Berlin, Institut für Physik and IRIS Adlershof 12489 Berlin Germany
| | - Cormac Toher
- Center for Extreme Materials, Duke University Durham NC 27708 USA
- Department of Materials Science and Engineering and Department of Chemistry and Biochemistry, The University of Texas at Dallas Richardson TX 75080 USA
| | - Gareth J Conduit
- Theory of Condensed Matter, Cavendish Laboratory Cambridge UK
- Intellegens Ltd French's Rd Cambridge CB4 3NP UK
| | - Giovanni Pizzi
- Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
- Laboratory for Materials Simulations (LMS), Paul Scherrer Institute (PSI) 5232 Villigen PSI Switzerland
| | - Saulius Gražulis
- Institute of Biotechnology, Life Sciences Center, Vilnius University Saulėtekio av. 7 LT-10257 Vilnius Lithuania
- Institute of Computer Science, Faculty of Mathematics and Informatics, Vilnius University Naugarduko g. 24 LT-03225 Vilnius Lithuania
| | - Gian-Marco Rignanese
- UCLouvain, Institut de la Matière Condensée et des Nanosciences (IMCN) Chemin des Étoiles 8, Louvain-la-Neuve 1348 Belgium
- Matgenix SRL 185 Rue Armand Bury 6534 Gozée Belgium
- School of Materials Science and Engineering, Northwestern Polytechnical University Xi'an Shaanxi 710072 China
| | - Rickard Armiento
- Materials Design and Informatics Unit, Department of Physics, Chemistry and Biology, Linköping University Sweden
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Das S, Merz KM. Molecular Gas-Phase Conformational Ensembles. J Chem Inf Model 2024; 64:749-760. [PMID: 38206321 DOI: 10.1021/acs.jcim.3c01309] [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: 01/12/2024]
Abstract
Accurately determining the global minima of a molecular structure is important in diverse scientific fields, including drug design, materials science, and chemical synthesis. Conformational search engines serve as valuable tools for exploring the extensive conformational space of molecules and for identifying energetically favorable conformations. In this study, we present a comparison of Auto3D, CREST, Balloon, and ETKDG (from RDKit), which are freely available conformational search engines, to evaluate their effectiveness in locating global minima. These engines employ distinct methodologies, including machine learning (ML) potential-based, semiempirical, and force field-based approaches. To validate these methods, we propose the use of collisional cross-section (CCS) values obtained from ion mobility-mass spectrometry studies. We hypothesize that experimental gas-phase CCS values can provide experimental evidence that we likely have the global minimum for a given molecule. To facilitate this effort, we used our gas-phase conformation library (GPCL) which currently consists of the full ensembles of 20 small molecules and can be used by the community to validate any conformational search engine. Further members of the GPCL can be readily created for any molecule of interest using our standard workflow used to compute CCS values, expanding the ability of the GPCL in validation exercises. These innovative validation techniques enhance our understanding of the conformational landscape and provide valuable insights into the performance of conformational generation engines. Our findings shed light on the strengths and limitations of each search engine, enabling informed decisions for their utilization in various scientific fields, where accurate molecular structure determination is crucial for understanding biological activity and designing targeted interventions. By facilitating the identification of reliable conformations, this study significantly contributes to enhancing the efficiency and accuracy of molecular structure determination, with particular focus on metabolite structure elucidation. The findings of this research also provide valuable insights for developing effective workflows for predicting the structures of unknown compounds with high precision.
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Affiliation(s)
- Susanta Das
- Department of Chemistry, Michigan State University, 578 S. Shaw Lane, East Lansing, Michigan 48824, United States
| | - Kenneth M Merz
- Department of Chemistry, Michigan State University, 578 S. Shaw Lane, East Lansing, Michigan 48824, United States
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3
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Beltrán D, Hospital A, Gelpí JL, Orozco M. A new paradigm for molecular dynamics databases: the COVID-19 database, the legacy of a titanic community effort. Nucleic Acids Res 2024; 52:D393-D403. [PMID: 37953362 PMCID: PMC10767965 DOI: 10.1093/nar/gkad991] [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: 08/14/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023] Open
Abstract
Molecular dynamics (MD) simulations are keeping computers busy around the world, generating a huge amount of data that is typically not open to the scientific community. Pioneering efforts to ensure the safety and reusability of MD data have been based on the use of simple databases providing a limited set of standard analyses on single-short trajectories. Despite their value, these databases do not offer a true solution for the current community of MD users, who want a flexible analysis pipeline and the possibility to address huge non-Markovian ensembles of large systems. Here we present a new paradigm for MD databases, resilient to large systems and long trajectories, and designed to be compatible with modern MD simulations. The data are offered to the community through a web-based graphical user interface (GUI), implemented with state-of-the-art technology, which incorporates system-specific analysis designed by the trajectory providers. A REST API and associated Jupyter Notebooks are integrated into the platform, allowing fully customized meta-analysis by final users. The new technology is illustrated using a collection of trajectories obtained by the community in the context of the effort to fight the COVID-19 pandemic. The server is accessible at https://bioexcel-cv19.bsc.es/#/. It is free and open to all users and there are no login requirements. It is also integrated into the simulations section of the BioExcel-MolSSI COVID-19 Molecular Structure and Therapeutics Hub: https://covid.molssi.org/simulations/ and is part of the MDDB effort (https://mddbr.eu).
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Affiliation(s)
- Daniel Beltrán
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Josep Lluís Gelpí
- Department of Biochemistry and Biomedicine. University of Barcelona, Barcelona, Spain
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Biochemistry and Biomedicine. University of Barcelona, Barcelona, Spain
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4
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Suriñach A, Hospital A, Westermaier Y, Jordà L, Orozco-Ruiz S, Beltrán D, Colizzi F, Andrio P, Soliva R, Municoy M, Gelpí JL, Orozco M. High-Throughput Prediction of the Impact of Genetic Variability on Drug Sensitivity and Resistance Patterns for Clinically Relevant Epidermal Growth Factor Receptor Mutations from Atomistic Simulations. J Chem Inf Model 2023; 63:321-334. [PMID: 36576351 DOI: 10.1021/acs.jcim.2c01344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Mutations in the kinase domain of the epidermal growth factor receptor (EGFR) can be drivers of cancer and also trigger drug resistance in patients receiving chemotherapy treatment based on kinase inhibitors. A priori knowledge of the impact of EGFR variants on drug sensitivity would help to optimize chemotherapy and design new drugs that are effective against resistant variants before they emerge in clinical trials. To this end, we explored a variety of in silico methods, from sequence-based to "state-of-the-art" atomistic simulations. We did not find any sequence signal that can provide clues on when a drug-related mutation appears or the impact of such mutations on drug activity. Low-level simulation methods provide limited qualitative information on regions where mutations are likely to cause alterations in drug activity, and they can predict around 70% of the impact of mutations on drug efficiency. High-level simulations based on nonequilibrium alchemical free energy calculations show predictive power. The integration of these "state-of-the-art" methods into a workflow implementing an interface for parallel distribution of the calculations allows its automatic and high-throughput use, even for researchers with moderate experience in molecular simulations.
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Affiliation(s)
- Aristarc Suriñach
- Nostrum Biodiscovery, Av. Josep Tarradellas 8-10, 08029 Barcelona, Spain
| | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona 08028, Spain
| | - Yvonne Westermaier
- Nostrum Biodiscovery, Av. Josep Tarradellas 8-10, 08029 Barcelona, Spain
| | - Luis Jordà
- Barcelona Supercomputing Center (BSC), Plaça Eusebi Güell, 1-3, Barcelona 08034, Spain
| | - Sergi Orozco-Ruiz
- Barcelona Supercomputing Center (BSC), Plaça Eusebi Güell, 1-3, Barcelona 08034, Spain
| | - Daniel Beltrán
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona 08028, Spain
| | - Francesco Colizzi
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona 08028, Spain
| | - Pau Andrio
- Barcelona Supercomputing Center (BSC), Plaça Eusebi Güell, 1-3, Barcelona 08034, Spain
| | - Robert Soliva
- Nostrum Biodiscovery, Av. Josep Tarradellas 8-10, 08029 Barcelona, Spain
| | - Martí Municoy
- Nostrum Biodiscovery, Av. Josep Tarradellas 8-10, 08029 Barcelona, Spain
| | - Josep Lluís Gelpí
- Barcelona Supercomputing Center (BSC), Plaça Eusebi Güell, 1-3, Barcelona 08034, Spain.,Department Biochemistry and Molecular Biomedicine, University of Barcelona, Barcelona 08029, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona 08028, Spain.,Department Biochemistry and Molecular Biomedicine, University of Barcelona, Barcelona 08029, Spain
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Wieczór M, Genna V, Aranda J, Badia RM, Gelpí JL, Gapsys V, de Groot BL, Lindahl E, Municoy M, Hospital A, Orozco M. Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case. WILEY INTERDISCIPLINARY REVIEWS. COMPUTATIONAL MOLECULAR SCIENCE 2022; 13:e1622. [PMID: 35935573 PMCID: PMC9347456 DOI: 10.1002/wcms.1622] [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: 02/02/2022] [Revised: 04/25/2022] [Accepted: 04/28/2022] [Indexed: 06/15/2023]
Abstract
Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under:Data Science > Computer Algorithms and ProgrammingData Science > Databases and Expert SystemsMolecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods.
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Affiliation(s)
- Miłosz Wieczór
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
- Department of Physical ChemistryGdansk University of TechnologyGdańskPoland
| | - Vito Genna
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | - Juan Aranda
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | | | - Josep Lluís Gelpí
- Barcelona Supercomputing CenterBarcelonaSpain
- Department of Biochemistry and BiomedicineUniversity of BarcelonaBarcelonaSpain
| | - Vytautas Gapsys
- Max Planck Institute for Multidisciplinary SciencesComputational Biomolecular Dynamics GroupGoettingenGermany
| | - Bert L. de Groot
- Max Planck Institute for Multidisciplinary SciencesComputational Biomolecular Dynamics GroupGoettingenGermany
| | - Erik Lindahl
- Department of Applied PhysicsSwedish e‐Science Research Center, KTH Royal Institute of TechnologyStockholmSweden
- Department of Biochemistry and Biophysics, Science for Life LaboratoryStockholm UniversityStockholmSweden
| | | | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and TechnologyBarcelonaSpain
- Department of Biochemistry and BiomedicineUniversity of BarcelonaBarcelonaSpain
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Zhou Y, Jiang Y, Chen SJ. RNA-ligand molecular docking: advances and challenges. WILEY INTERDISCIPLINARY REVIEWS. COMPUTATIONAL MOLECULAR SCIENCE 2022; 12:e1571. [PMID: 37293430 PMCID: PMC10250017 DOI: 10.1002/wcms.1571] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 07/20/2021] [Indexed: 12/16/2022]
Abstract
With rapid advances in computer algorithms and hardware, fast and accurate virtual screening has led to a drastic acceleration in selecting potent small molecules as drug candidates. Computational modeling of RNA-small molecule interactions has become an indispensable tool for RNA-targeted drug discovery. The current models for RNA-ligand binding have mainly focused on the docking-and-scoring method. Accurate docking and scoring should tackle four crucial problems: (1) conformational flexibility of ligand, (2) conformational flexibility of RNA, (3) efficient sampling of binding sites and binding poses, and (4) accurate scoring of different binding modes. Moreover, compared with the problem of protein-ligand docking, predicting ligand binding to RNA, a negatively charged polymer, is further complicated by additional effects such as metal ion effects. Thermodynamic models based on physics-based and knowledge-based scoring functions have shown highly encouraging success in predicting ligand binding poses and binding affinities. Recently, kinetic models for ligand binding have further suggested that including dissociation kinetics (residence time) in ligand docking would result in improved performance in estimating in vivo drug efficacy. More recently, the rise of deep-learning approaches has led to new tools for predicting RNA-small molecule binding. In this review, we present an overview of the recently developed computational methods for RNA-ligand docking and their advantages and disadvantages.
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Affiliation(s)
- Yuanzhe Zhou
- Department of Physics and Astronomy, Department of Biochemistry, Institute of Data Sciences and Informatics, University of Missouri, Columbia, MO 65211-7010, USA
| | - Yangwei Jiang
- Department of Physics and Astronomy, Department of Biochemistry, Institute of Data Sciences and Informatics, University of Missouri, Columbia, MO 65211-7010, USA
| | - Shi-Jie Chen
- Department of Physics and Astronomy, Department of Biochemistry, Institute of Data Sciences and Informatics, University of Missouri, Columbia, MO 65211-7010, USA
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7
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Steiner M, Reiher M. Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis. Top Catal 2022; 65:6-39. [PMID: 35185305 PMCID: PMC8816766 DOI: 10.1007/s11244-021-01543-9] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/17/2021] [Indexed: 12/11/2022]
Abstract
Autonomous computations that rely on automated reaction network elucidation algorithms may pave the way to make computational catalysis on a par with experimental research in the field. Several advantages of this approach are key to catalysis: (i) automation allows one to consider orders of magnitude more structures in a systematic and open-ended fashion than what would be accessible by manual inspection. Eventually, full resolution in terms of structural varieties and conformations as well as with respect to the type and number of potentially important elementary reaction steps (including decomposition reactions that determine turnover numbers) may be achieved. (ii) Fast electronic structure methods with uncertainty quantification warrant high efficiency and reliability in order to not only deliver results quickly, but also to allow for predictive work. (iii) A high degree of autonomy reduces the amount of manual human work, processing errors, and human bias. Although being inherently unbiased, it is still steerable with respect to specific regions of an emerging network and with respect to the addition of new reactant species. This allows for a high fidelity of the formalization of some catalytic process and for surprising in silico discoveries. In this work, we first review the state of the art in computational catalysis to embed autonomous explorations into the general field from which it draws its ingredients. We then elaborate on the specific conceptual issues that arise in the context of autonomous computational procedures, some of which we discuss at an example catalytic system.
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Affiliation(s)
- Miguel Steiner
- Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
| | - Markus Reiher
- Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
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8
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Bayarri G, Hospital A, Orozco M. 3dRS, a Web-Based Tool to Share Interactive Representations of 3D Biomolecular Structures and Molecular Dynamics Trajectories. Front Mol Biosci 2021; 8:726232. [PMID: 34485386 PMCID: PMC8414788 DOI: 10.3389/fmolb.2021.726232] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 08/03/2021] [Indexed: 11/13/2022] Open
Abstract
3D Representation Sharing (3dRS) is a web-based tool designed to share biomolecular structure representations, including 4D ensembles derived from Molecular Dynamics (MD) trajectories. The server offers a team working in different locations a single URL to share and discuss structural data in an interactive fashion, with the possibility to use it as a live figure for scientific papers. The web tool allows an easy upload of structures and trajectories in different formats. The 3D representation, powered by NGL viewer, offers an interactive display with smooth visualization in modern web browsers. Multiple structures can be loaded and superposed in the same scene. 1D sequences from the loaded structures are presented and linked to the 3D representation. Multiple, pre-defined 3D molecular representations are available. The powerful NGL selection syntax allows the definition of molecular regions that can be then displayed using different representations. Important descriptors such as distances or interactions can be easily added into the representation. Trajectory frames can be explored using a common video player control panel. Trajectories are efficiently stored and transferred to the NGL viewer thanks to an MDsrv-based data streaming. The server design offers all functionalities in one single web page, with a curated user experience, involving a minimum learning curve. Extended documentation is available, including a gallery with a collection of scenes. The server requires no registration and is available at https://mmb.irbbarcelona.org/3dRS.
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Affiliation(s)
- Genís Bayarri
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Departament de Bioquímica i Biomedicina, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain
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Moreno D, Zivanovic S, Colizzi F, Hospital A, Aranda J, Soliva R, Orozco M. DFFR: A New Method for High-Throughput Recalibration of Automatic Force-Fields for Drugs. J Chem Theory Comput 2020; 16:6598-6608. [PMID: 32856910 DOI: 10.1021/acs.jctc.0c00306] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We present drug force-field recalibration (DFFR), a new method for refining of automatic force-fields used to represent small drugs in docking and molecular dynamics simulations. The method is based on fine-tuning of torsional terms to obtain ensembles that reproduce observables derived from reference data. DFFR is fast and flexible and can be easily automatized for a high-throughput regime, making it useful in drug-design projects. We tested the performance of the method in a few model systems and also in a variety of druglike molecules using reference data derived from: (i) density functional theory coupled to a self-consistent reaction field (DFT/SCRF) calculations on highly populated conformers and (ii) enhanced sampling quantum mechanical/molecular mechanics (QM/MM) where the drug is reproduced at the QM level, while the solvent is represented by classical force-fields. Extension of the method to include other sources of reference data is discussed.
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Affiliation(s)
- David Moreno
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Sanja Zivanovic
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Francesco Colizzi
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Juan Aranda
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Robert Soliva
- Nostrum Biodiscovery, Nexus II Building, Barcelona 08034, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain.,Departament de Bioquímica i Biomedicina, Facultat de Biologia, Universitat de Barcelona, Barcelona E08028, Spain
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Zivanovic S, Colizzi F, Moreno D, Hospital A, Soliva R, Orozco M. Exploring the Conformational Landscape of Bioactive Small Molecules. J Chem Theory Comput 2020; 16:6575-6585. [DOI: 10.1021/acs.jctc.0c00304] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Sanja Zivanovic
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Francesco Colizzi
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - David Moreno
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Robert Soliva
- Nostrum Biodiscovery, Nexus II Building, 08034 Barcelona, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain
- Departament de Bioquímica i Biomedicina, Facultat de Biologia, Universitat de Barcelona, E08028 Barcelona, Spain
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