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Journal of Computer-Aided Molecular Design

, Volume 33, Issue 9, pp 855–864 | Cite as

www.3d-qsar.com: a web portal that brings 3-D QSAR to all electronic devices—the Py-CoMFA web application as tool to build models from pre-aligned datasets

  • Rino RagnoEmail author
Article
  • 121 Downloads

Abstract

Comparative molecular field analysis (CoMFA), introduced in 1988, was the first 3-D QSAR method ever published and sold. Since then thousands of application, articles and citation have proved 3-D QSAR as a valuable method to be used in drug design. Several other 3-D QSAR methods have appeared, but still CoMFA remains the most used and cited. Nevertheless from a survey on the Certara® web site it seems that CoMFA is no more available. Herein is presented a python implementation of the CoMFA (Py-CoMFA). Py-CoMFA is usable through the www.3d-qsar.com web applications suites portal by mean of any electronic device that can run a web browser. As benchmark, 30 different publicly available datasets were used to assess the Py-CoMFA usability and robustness. Comparisons with published results proved Py-COMFA to be in very good agreement with those obtained with the original CoMFA. Although the used datasets were pre-aligned, by means of the other web application available through the portal, 3-D QSAR models can be easily build from scratch. In conclusion, although CoMFA is a well known methodology and given the availability of several publicly available Hansch type QSAR web portals, Py-CoMFA represents a valuable tools for any chemoinformatics and informatics non-skilled user that can also be used as support to teach 3-D QSAR. Importantly, Py-CoMFA is the first and unique tool publicly available to build 3-D QSAR models.

Keywords

CoMFA 3D QSAR Ligand based drug design 

Notes

Acknowledgements

Many thanks are due to Alessio Ragno and Dylan Savoia, two former software engineering bachelor students that technically supported the development of www.3d-qsar.com. Many thanks are also due to the RCMD former PhD students Manuela Sabatino and Alexandros Patsilinakos for their help in testing the Py-CoMFA module.

Supplementary material

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Drug Chemistry and Technologies, Rome Center for Molecular DesignSapienza Rome UniversityRomaItaly

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