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Combining Experimental Data and Computational Methods for the Non-Computer Specialist

Experimental methods are indispensable for the study of the function of biological macromolecules, not just as static structures, but as dynamic systems that change conformation, bind partners, perform reactions, and respond to different stimulus. However, providing a detailed structural interpretat...

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Detalles Bibliográficos
Autores principales: Cárdenas, Reinier, Martínez-Seoane, Javier, Amero, Carlos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7594097/
https://www.ncbi.nlm.nih.gov/pubmed/33081072
http://dx.doi.org/10.3390/molecules25204783
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author Cárdenas, Reinier
Martínez-Seoane, Javier
Amero, Carlos
author_facet Cárdenas, Reinier
Martínez-Seoane, Javier
Amero, Carlos
author_sort Cárdenas, Reinier
collection PubMed
description Experimental methods are indispensable for the study of the function of biological macromolecules, not just as static structures, but as dynamic systems that change conformation, bind partners, perform reactions, and respond to different stimulus. However, providing a detailed structural interpretation of the results is often a very challenging task. While experimental and computational methods are often considered as two different and separate approaches, the power and utility of combining both is undeniable. The integration of the experimental data with computational techniques can assist and enrich the interpretation, providing new detailed molecular understanding of the systems. Here, we briefly describe the basic principles of how experimental data can be combined with computational methods to obtain insights into the molecular mechanism and expand the interpretation through the generation of detailed models.
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spelling pubmed-75940972020-10-30 Combining Experimental Data and Computational Methods for the Non-Computer Specialist Cárdenas, Reinier Martínez-Seoane, Javier Amero, Carlos Molecules Review Experimental methods are indispensable for the study of the function of biological macromolecules, not just as static structures, but as dynamic systems that change conformation, bind partners, perform reactions, and respond to different stimulus. However, providing a detailed structural interpretation of the results is often a very challenging task. While experimental and computational methods are often considered as two different and separate approaches, the power and utility of combining both is undeniable. The integration of the experimental data with computational techniques can assist and enrich the interpretation, providing new detailed molecular understanding of the systems. Here, we briefly describe the basic principles of how experimental data can be combined with computational methods to obtain insights into the molecular mechanism and expand the interpretation through the generation of detailed models. MDPI 2020-10-18 /pmc/articles/PMC7594097/ /pubmed/33081072 http://dx.doi.org/10.3390/molecules25204783 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Cárdenas, Reinier
Martínez-Seoane, Javier
Amero, Carlos
Combining Experimental Data and Computational Methods for the Non-Computer Specialist
title Combining Experimental Data and Computational Methods for the Non-Computer Specialist
title_full Combining Experimental Data and Computational Methods for the Non-Computer Specialist
title_fullStr Combining Experimental Data and Computational Methods for the Non-Computer Specialist
title_full_unstemmed Combining Experimental Data and Computational Methods for the Non-Computer Specialist
title_short Combining Experimental Data and Computational Methods for the Non-Computer Specialist
title_sort combining experimental data and computational methods for the non-computer specialist
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7594097/
https://www.ncbi.nlm.nih.gov/pubmed/33081072
http://dx.doi.org/10.3390/molecules25204783
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