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Computer-aided drug design platform using PyMOL

Journal of Computer-Aided Molecular Design volume 25, pages 13–19 (2011)Cite this article

Abstract

The understanding and optimization of protein-ligand interactions are instrumental to medicinal chemists investigating potential drug candidates. Over the past couple of decades, many powerful standalone tools for computer-aided drug discovery have been developed in academia providing insight into protein-ligand interactions. As programs are developed by various research groups, a consistent user-friendly graphical working environment combining computational techniques such as docking, scoring, molecular dynamics simulations, and free energy calculations is needed. Utilizing PyMOL we have developed such a graphical user interface incorporating individual academic packages designed for protein preparation (AMBER package and Reduce), molecular mechanics applications (AMBER package), and docking and scoring (AutoDock Vina and SLIDE). In addition to amassing several computational tools under one interface, the computational platform also provides a user-friendly combination of different programs. For example, utilizing a molecular dynamics (MD) simulation performed with AMBER as input for ensemble docking with AutoDock Vina. The overarching goal of this work was to provide a computational platform that facilitates medicinal chemists, many who are not experts in computational methodologies, to utilize several common computational techniques germane to drug discovery. Furthermore, our software is open source and is aimed to initiate collaborative efforts among computational researchers to combine other open source computational methods under a single, easily understandable graphical user interface.

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Acknowledgments

We would like to thank Ulf Ryde for access to the programs changepdb and changecrd that facilitate the estimation of entropic contributions to the free energy of binding.

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Affiliations

  1. Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, 575 Stadium Mall Drive, West Lafayette, IN, 47907, USA

    Markus A. Lill & Matthew L. Danielson

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  1. Markus A. Lill
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  2. Matthew L. Danielson
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Correspondence to Markus A. Lill.

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Lill, M.A., Danielson, M.L. Computer-aided drug design platform using PyMOL. J Comput Aided Mol Des 25, 13–19 (2011). https://doi.org/10.1007/s10822-010-9395-8

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  • DOI: https://doi.org/10.1007/s10822-010-9395-8

Keywords

  • Computer-aided drug discovery
  • Molecular modeling
  • Docking
  • Scoring
  • Free energies
  • PyMOL