DockingPie: a consensus docking plugin for PyMOL.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
02 09 2022
02 09 2022
Historique:
received:
13
04
2022
revised:
28
06
2022
accepted:
05
07
2022
pubmed:
7
7
2022
medline:
15
11
2022
entrez:
6
7
2022
Statut:
ppublish
Résumé
The primary strategy for predicting the binding mode of small molecules to their receptors and for performing receptor-based virtual screening studies is protein-ligand docking, which is undoubtedly the most popular and successful approach in computer-aided drug discovery. The increased popularity of docking has resulted in the development of different docking algorithms and scoring functions. Nonetheless, it is unlikely that a single approach outperforms the others in terms of reproducibility and precision. In this ground, consensus docking techniques are taking hold. We have developed DockingPie, an open source PyMOL plugin for individual, as well as consensus docking analyses. Smina, AutoDock Vina, ADFR and RxDock are the four docking engines that DockingPie currently supports in an easy and extremely intuitive way, thanks to its integrated docking environment and its GUI, fully integrated within PyMOL. https://github.com/paiardin/DockingPie. Supplementary data are available at Bioinformatics online.
Identifiants
pubmed: 35792827
pii: 6632656
doi: 10.1093/bioinformatics/btac452
doi:
Substances chimiques
Ligands
0
Proteins
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4233-4234Subventions
Organisme : Associazione Italiana Ricerca sul Cancro
ID : 20447
Organisme : Sapienza University
ID : RP12017275CED09F
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.