Motivation: 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.
Results: 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.
Availability and implementation: https://github.com/paiardin/DockingPie.
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.