Literature DB >> 31595406

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 Ragno1.   

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.

Entities:  

Keywords:  3D QSAR; CoMFA; Ligand based drug design

Year:  2019        PMID: 31595406     DOI: 10.1007/s10822-019-00231-x

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  51 in total

1.  Validation of DAPPER for 3D QSAR: conformational search and chirality metric.

Authors:  Scott A Wildman; Gordon M Crippen
Journal:  J Chem Inf Comput Sci       Date:  2003 Mar-Apr

2.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.

Authors:  R D Cramer; D E Patterson; J D Bunce
Journal:  J Am Chem Soc       Date:  1988-08-01       Impact factor: 15.419

3.  Molecular docking and 3D-QSAR studies of Yersinia protein tyrosine phosphatase YopH inhibitors.

Authors:  Xin Hu; C Erec Stebbins
Journal:  Bioorg Med Chem       Date:  2005-02-15       Impact factor: 3.641

4.  A comparison of methods for modeling quantitative structure-activity relationships.

Authors:  Jeffrey J Sutherland; Lee A O'Brien; Donald F Weaver
Journal:  J Med Chem       Date:  2004-10-21       Impact factor: 7.446

5.  Change correlations in structure-activity studies using multiple regression analysis.

Authors:  J G Topliss; R J Costello
Journal:  J Med Chem       Date:  1972-10       Impact factor: 7.446

6.  Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity.

Authors:  G Klebe; U Abraham; T Mietzner
Journal:  J Med Chem       Date:  1994-11-25       Impact factor: 7.446

7.  GRID formalism for the comparative molecular surface analysis: application to the CoMFA benchmark steroids, azo dyes, and HEPT derivatives.

Authors:  Jaroslaw Polanski; Rafal Gieleciak; Tomasz Magdziarz; Andrzej Bak
Journal:  J Chem Inf Comput Sci       Date:  2004 Jul-Aug

8.  Synthetic and computer-assisted analysis of the structural requirements for selective, high-affinity ligand binding to diazepam-insensitive benzodiazepine receptors.

Authors:  G Wong; K F Koehler; P Skolnick; Z Q Gu; S Ananthan; P Schönholzer; W Hunkeler; W Zhang; J M Cook
Journal:  J Med Chem       Date:  1993-06-25       Impact factor: 7.446

9.  Structural basis for the synthesis of indirubins as potent and selective inhibitors of glycogen synthase kinase-3 and cyclin-dependent kinases.

Authors:  Panagiotis Polychronopoulos; Prokopios Magiatis; Alexios-Leandros Skaltsounis; Vassilios Myrianthopoulos; Emmanuel Mikros; Aldo Tarricone; Andrea Musacchio; S Mark Roe; Laurence Pearl; Maryse Leost; Paul Greengard; Laurent Meijer
Journal:  J Med Chem       Date:  2004-02-12       Impact factor: 7.446

10.  A 3D QSAR study on a set of dopamine D4 receptor antagonists.

Authors:  Jonas Boström; Markus Böhm; Klaus Gundertofte; Gerhard Klebe
Journal:  J Chem Inf Comput Sci       Date:  2003 May-Jun
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  7 in total

1.  Transcriptomic and genomic studies classify NKL54 as a histone deacetylase inhibitor with indirect influence on MEF2-dependent transcription.

Authors:  Martina Minisini; Eros Di Giorgio; Emanuela Kerschbamer; Emiliano Dalla; Massimo Faggiani; Elisa Franforte; Franz-Josef Meyer-Almes; Rino Ragno; Lorenzo Antonini; Antonello Mai; Francesco Fiorentino; Dante Rotili; Monica Chinellato; Stefano Perin; Laura Cendron; Christian X Weichenberger; Alessandro Angelini; Claudio Brancolini
Journal:  Nucleic Acids Res       Date:  2022-03-21       Impact factor: 16.971

2.  Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal.

Authors:  Eleonora Proia; Alessio Ragno; Lorenzo Antonini; Manuela Sabatino; Milan Mladenovič; Roberto Capobianco; Rino Ragno
Journal:  J Comput Aided Mol Des       Date:  2022-06-18       Impact factor: 4.179

Review 3.  Drug Design by Pharmacophore and Virtual Screening Approach.

Authors:  Deborah Giordano; Carmen Biancaniello; Maria Antonia Argenio; Angelo Facchiano
Journal:  Pharmaceuticals (Basel)       Date:  2022-05-23

4.  Human Estrogen Receptor Alpha Antagonists, Part 3: 3-D Pharmacophore and 3-D QSAR Guided Brefeldin A Hit-to-Lead Optimization toward New Breast Cancer Suppressants.

Authors:  Nezrina Kurtanović; Nevena Tomašević; Sanja Matić; Elenora Proia; Manuela Sabatino; Lorenzo Antonini; Milan Mladenović; Rino Ragno
Journal:  Molecules       Date:  2022-04-28       Impact factor: 4.927

5.  In silico local QSAR modeling of bioconcentration factor of organophosphate pesticides.

Authors:  Purusottam Banjare; Balaji Matore; Jagadish Singh; Partha Pratim Roy
Journal:  In Silico Pharmacol       Date:  2021-04-04

6.  Teaching and Learning Computational Drug Design: Student Investigations of 3D Quantitative Structure-Activity Relationships through Web Applications.

Authors:  Rino Ragno; Valeria Esposito; Martina Di Mario; Stefano Masiello; Marco Viscovo; Richard D Cramer
Journal:  J Chem Educ       Date:  2020-06-23       Impact factor: 2.979

7.  Profile of Myracrodruon urundeuva Volatile Compounds Ease of Extraction and Biodegradability and In Silico Evaluation of Their Interactions with COX-1 and iNOS.

Authors:  Yuri G Figueiredo; Eduardo A Corrêa; Afonso H de Oliveira Junior; Ana C D C Mazzinghy; Henrique D O P Mendonça; Yan J G Lobo; Yesenia M García; Marcelo A D S Gouvêia; Ana C C F F de Paula; Rodinei Augusti; Luisa D C B Reina; Carlos H da Silveira; Leonardo H F de Lima; Júlio O F Melo
Journal:  Molecules       Date:  2022-03-01       Impact factor: 4.411

  7 in total

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