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A perspective on the sharing of docking data
Computational approaches are nowadays largely applied in drug discovery projects. Among these, molecular docking is the most used for hit identification against a drug target protein. However, many scientists in the field shed light on the lack of availability and reproducibility of the data obtaine...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365938/ https://www.ncbi.nlm.nih.gov/pubmed/37492229 http://dx.doi.org/10.1016/j.dib.2023.109386 |
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author | Aci-Sèche, Samia Bourg, Stéphane Bonnet, Pascal Rebehmed, Joseph de Brevern, Alexandre G. Diharce, Julien |
author_facet | Aci-Sèche, Samia Bourg, Stéphane Bonnet, Pascal Rebehmed, Joseph de Brevern, Alexandre G. Diharce, Julien |
author_sort | Aci-Sèche, Samia |
collection | PubMed |
description | Computational approaches are nowadays largely applied in drug discovery projects. Among these, molecular docking is the most used for hit identification against a drug target protein. However, many scientists in the field shed light on the lack of availability and reproducibility of the data obtained from such studies to the whole community. Consequently, sustaining and developing the efforts toward a large and fully transparent sharing of those data could be beneficial for all researchers in drug discovery. The purpose of this article is first to propose guidelines and recommendations on the appropriate way to conduct virtual screening experiments and second to depict the current state of sharing molecular docking data. In conclusion, we have explored and proposed several prospects to enhance data sharing from docking experiment that could be developed in the foreseeable future. |
format | Online Article Text |
id | pubmed-10365938 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103659382023-07-25 A perspective on the sharing of docking data Aci-Sèche, Samia Bourg, Stéphane Bonnet, Pascal Rebehmed, Joseph de Brevern, Alexandre G. Diharce, Julien Data Brief Perspective Article Computational approaches are nowadays largely applied in drug discovery projects. Among these, molecular docking is the most used for hit identification against a drug target protein. However, many scientists in the field shed light on the lack of availability and reproducibility of the data obtained from such studies to the whole community. Consequently, sustaining and developing the efforts toward a large and fully transparent sharing of those data could be beneficial for all researchers in drug discovery. The purpose of this article is first to propose guidelines and recommendations on the appropriate way to conduct virtual screening experiments and second to depict the current state of sharing molecular docking data. In conclusion, we have explored and proposed several prospects to enhance data sharing from docking experiment that could be developed in the foreseeable future. Elsevier 2023-07-07 /pmc/articles/PMC10365938/ /pubmed/37492229 http://dx.doi.org/10.1016/j.dib.2023.109386 Text en © 2023 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Perspective Article Aci-Sèche, Samia Bourg, Stéphane Bonnet, Pascal Rebehmed, Joseph de Brevern, Alexandre G. Diharce, Julien A perspective on the sharing of docking data |
title | A perspective on the sharing of docking data |
title_full | A perspective on the sharing of docking data |
title_fullStr | A perspective on the sharing of docking data |
title_full_unstemmed | A perspective on the sharing of docking data |
title_short | A perspective on the sharing of docking data |
title_sort | perspective on the sharing of docking data |
topic | Perspective Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365938/ https://www.ncbi.nlm.nih.gov/pubmed/37492229 http://dx.doi.org/10.1016/j.dib.2023.109386 |
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