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Protein binding sites for drug design

Drug development is a lengthy and challenging process that can be accelerated at early stages by new mathematical approaches and modern computers. To address this important issue, we are developing new mathematical solutions for the detection and characterization of protein binding sites that are im...

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Detalles Bibliográficos
Autores principales: Konc, Janez, Janežič, Dušanka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9734416/
https://www.ncbi.nlm.nih.gov/pubmed/36532870
http://dx.doi.org/10.1007/s12551-022-01028-3
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author Konc, Janez
Janežič, Dušanka
author_facet Konc, Janez
Janežič, Dušanka
author_sort Konc, Janez
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description Drug development is a lengthy and challenging process that can be accelerated at early stages by new mathematical approaches and modern computers. To address this important issue, we are developing new mathematical solutions for the detection and characterization of protein binding sites that are important for new drug development. In this review, we present algorithms based on graph theory combined with molecular dynamics simulations that we have developed for studying biological target proteins to provide important data for optimizing the early stages of new drug development. A particular focus is the development of new protein binding site prediction algorithms (ProBiS) and new web tools for modeling pharmaceutically interesting molecules—ProBiS Tools (algorithm, database, web server), which have evolved into a full-fledged graphical tool for studying proteins in the proteome. ProBiS differs from other structural algorithms in that it can align proteins with different folds without prior knowledge of the binding sites. It allows detection of similar binding sites and can predict molecular ligands of various types of pharmaceutical interest that could be advanced to drugs to treat a disease, based on the entire Protein Data Bank (PDB) and AlphaFold database, including proteins not yet in the PDB. All ProBiS Tools are freely available to the academic community at http://insilab.org and https://probis.nih.gov.
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spelling pubmed-97344162022-12-12 Protein binding sites for drug design Konc, Janez Janežič, Dušanka Biophys Rev Review Drug development is a lengthy and challenging process that can be accelerated at early stages by new mathematical approaches and modern computers. To address this important issue, we are developing new mathematical solutions for the detection and characterization of protein binding sites that are important for new drug development. In this review, we present algorithms based on graph theory combined with molecular dynamics simulations that we have developed for studying biological target proteins to provide important data for optimizing the early stages of new drug development. A particular focus is the development of new protein binding site prediction algorithms (ProBiS) and new web tools for modeling pharmaceutically interesting molecules—ProBiS Tools (algorithm, database, web server), which have evolved into a full-fledged graphical tool for studying proteins in the proteome. ProBiS differs from other structural algorithms in that it can align proteins with different folds without prior knowledge of the binding sites. It allows detection of similar binding sites and can predict molecular ligands of various types of pharmaceutical interest that could be advanced to drugs to treat a disease, based on the entire Protein Data Bank (PDB) and AlphaFold database, including proteins not yet in the PDB. All ProBiS Tools are freely available to the academic community at http://insilab.org and https://probis.nih.gov. Springer Berlin Heidelberg 2022-12-09 /pmc/articles/PMC9734416/ /pubmed/36532870 http://dx.doi.org/10.1007/s12551-022-01028-3 Text en © International Union for Pure and Applied Biophysics (IUPAB) and Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
spellingShingle Review
Konc, Janez
Janežič, Dušanka
Protein binding sites for drug design
title Protein binding sites for drug design
title_full Protein binding sites for drug design
title_fullStr Protein binding sites for drug design
title_full_unstemmed Protein binding sites for drug design
title_short Protein binding sites for drug design
title_sort protein binding sites for drug design
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9734416/
https://www.ncbi.nlm.nih.gov/pubmed/36532870
http://dx.doi.org/10.1007/s12551-022-01028-3
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