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.

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 / Ragno, R.. - In: JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN. - ISSN 0920-654X. - 33:9(2019), pp. 855-864. [10.1007/s10822-019-00231-x]

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

Ragno R.
2019

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1414261
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