The increasing use of information technology in the discovery of new molecular entities encourages the use of modern molecular-modeling tools to help teach important concepts of drug design to chemistry and pharmacy undergraduate students. In particular, statistical models such as quantitative structure activity relationships (QSAR)—often as its 3-D QSAR variant—are commonly used in the development and optimization of a leading compound. We describe how these drug discovery methods can be taught and learned by means of free and open-source web applications, specifically the online platform www.3d-qsar.com. This new suite of web application has been integrated into a drug design teaching course, one that provides both theoretical and practical perspectives. We include the teaching protocol by which pharmaceutical biotechnology master students at Pharmacy Faculty of Sapienza Rome University are introduced to drug design. Starting with a choice among recent articles describing the potencies of a series of molecules tested against a biological target, each student is expected to build a 3-D QSAR ligand-based model from their chosen publication, proceeding as follows: creating the initial data set (Py-MolEdit); generating the global minimum conformations (Py-ConfSearch); proposing a promising mutual alignment (Py-Align); and, finally, building and optimizing a robust 3-D QSAR models (Py-CoMFA). These student activities also help validate these new molecular modeling tools, especially for their usability by inexperienced hands. To more fully demonstrate the effectiveness of this protocol and its tools, we include the work performed by four of these students (four of the co-authors), detailing the satisfactory 3-D QSAR models they obtained. Such scientifically complete experiences by undergraduates, made possible by the efficiency of the 3-D QSAR methodology, provide exposure to computational tools in the same spirit as traditional laboratory exercises. With the obsolescence of the classic Comparative Molecular Field Analysis Sybyl host, the 3dqsar web portal offers one of the few available means of performing this well-established 3-D QSAR method.
Teaching and learning computational drug design: student investigations of 3D quantitative structure–activity relationships through web applications / Ragno, Rino; Esposito, Valeria; Di Mario, Martina; Masiello, Stefano; Viscovo, Marco; Cramer, Richard. - In: JOURNAL OF CHEMICAL EDUCATION. - ISSN 0021-9584. - 97:7(2020), pp. 1922-1930. [10.1021/acs.jchemed.0c00117]
Teaching and learning computational drug design: student investigations of 3D quantitative structure–activity relationships through web applications
Ragno, Rino
Primo
;Viscovo, Marco;
2020
Abstract
The increasing use of information technology in the discovery of new molecular entities encourages the use of modern molecular-modeling tools to help teach important concepts of drug design to chemistry and pharmacy undergraduate students. In particular, statistical models such as quantitative structure activity relationships (QSAR)—often as its 3-D QSAR variant—are commonly used in the development and optimization of a leading compound. We describe how these drug discovery methods can be taught and learned by means of free and open-source web applications, specifically the online platform www.3d-qsar.com. This new suite of web application has been integrated into a drug design teaching course, one that provides both theoretical and practical perspectives. We include the teaching protocol by which pharmaceutical biotechnology master students at Pharmacy Faculty of Sapienza Rome University are introduced to drug design. Starting with a choice among recent articles describing the potencies of a series of molecules tested against a biological target, each student is expected to build a 3-D QSAR ligand-based model from their chosen publication, proceeding as follows: creating the initial data set (Py-MolEdit); generating the global minimum conformations (Py-ConfSearch); proposing a promising mutual alignment (Py-Align); and, finally, building and optimizing a robust 3-D QSAR models (Py-CoMFA). These student activities also help validate these new molecular modeling tools, especially for their usability by inexperienced hands. To more fully demonstrate the effectiveness of this protocol and its tools, we include the work performed by four of these students (four of the co-authors), detailing the satisfactory 3-D QSAR models they obtained. Such scientifically complete experiences by undergraduates, made possible by the efficiency of the 3-D QSAR methodology, provide exposure to computational tools in the same spirit as traditional laboratory exercises. With the obsolescence of the classic Comparative Molecular Field Analysis Sybyl host, the 3dqsar web portal offers one of the few available means of performing this well-established 3-D QSAR method.File | Dimensione | Formato | |
---|---|---|---|
Ragno_postprint_Teaching_2020.pdf
Open Access dal 23/06/2021
Tipologia:
Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
590.97 kB
Formato
Adobe PDF
|
590.97 kB | Adobe PDF |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.