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A Pilot Study of All-Computational Drug Design Protocol–From Structure Prediction to Interaction Analysis
Speeding up the drug discovery process is of great significance. To achieve that, high-efficiency methods should be exploited. The conventional wet-bench methods hardly meet the high-speed demand due to time-consuming experiments. Conversely, in silico approaches are much more efficient for drug dis...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7028743/ https://www.ncbi.nlm.nih.gov/pubmed/32117898 http://dx.doi.org/10.3389/fchem.2020.00081 |
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author | Wu, Yifei Lou, Lei Xie, Zhong-Ru |
author_facet | Wu, Yifei Lou, Lei Xie, Zhong-Ru |
author_sort | Wu, Yifei |
collection | PubMed |
description | Speeding up the drug discovery process is of great significance. To achieve that, high-efficiency methods should be exploited. The conventional wet-bench methods hardly meet the high-speed demand due to time-consuming experiments. Conversely, in silico approaches are much more efficient for drug discovery and design. However, in silico approaches usually serve as a supportive role in research processes. To fully exert the strength of computational methods, we propose a protocol which integrates various in silico approaches, from de novo protein structure prediction to ligand-protein interaction simulation. As a proof of concept, human SK2/calmodulin complex was used as a target for validation. First, we obtained a predicted structure of SK2/calmodulin and predicted binding sites which were consistent with the literature data. Then we investigated the ligand-protein interaction via virtual mutagenesis, flexible docking, and binding affinity calculation. As a result, the binding energies of mutants have similar trends compared with the EC(50) values (R = 0.6 for NS309 in V481 mutants). The results indicate that our protocol can be applied to the drug design of structure unknown proteins. Our study also demonstrates that the integration of in silico approaches is feasible and it facilitates the acceleration of new drug discovery. |
format | Online Article Text |
id | pubmed-7028743 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-70287432020-02-28 A Pilot Study of All-Computational Drug Design Protocol–From Structure Prediction to Interaction Analysis Wu, Yifei Lou, Lei Xie, Zhong-Ru Front Chem Chemistry Speeding up the drug discovery process is of great significance. To achieve that, high-efficiency methods should be exploited. The conventional wet-bench methods hardly meet the high-speed demand due to time-consuming experiments. Conversely, in silico approaches are much more efficient for drug discovery and design. However, in silico approaches usually serve as a supportive role in research processes. To fully exert the strength of computational methods, we propose a protocol which integrates various in silico approaches, from de novo protein structure prediction to ligand-protein interaction simulation. As a proof of concept, human SK2/calmodulin complex was used as a target for validation. First, we obtained a predicted structure of SK2/calmodulin and predicted binding sites which were consistent with the literature data. Then we investigated the ligand-protein interaction via virtual mutagenesis, flexible docking, and binding affinity calculation. As a result, the binding energies of mutants have similar trends compared with the EC(50) values (R = 0.6 for NS309 in V481 mutants). The results indicate that our protocol can be applied to the drug design of structure unknown proteins. Our study also demonstrates that the integration of in silico approaches is feasible and it facilitates the acceleration of new drug discovery. Frontiers Media S.A. 2020-02-12 /pmc/articles/PMC7028743/ /pubmed/32117898 http://dx.doi.org/10.3389/fchem.2020.00081 Text en Copyright © 2020 Wu, Lou and Xie. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Chemistry Wu, Yifei Lou, Lei Xie, Zhong-Ru A Pilot Study of All-Computational Drug Design Protocol–From Structure Prediction to Interaction Analysis |
title | A Pilot Study of All-Computational Drug Design Protocol–From Structure Prediction to Interaction Analysis |
title_full | A Pilot Study of All-Computational Drug Design Protocol–From Structure Prediction to Interaction Analysis |
title_fullStr | A Pilot Study of All-Computational Drug Design Protocol–From Structure Prediction to Interaction Analysis |
title_full_unstemmed | A Pilot Study of All-Computational Drug Design Protocol–From Structure Prediction to Interaction Analysis |
title_short | A Pilot Study of All-Computational Drug Design Protocol–From Structure Prediction to Interaction Analysis |
title_sort | pilot study of all-computational drug design protocol–from structure prediction to interaction analysis |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7028743/ https://www.ncbi.nlm.nih.gov/pubmed/32117898 http://dx.doi.org/10.3389/fchem.2020.00081 |
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