Literature DB >> 17191945

Application of 3D-QSAR in the rational design of receptor ligands and enzyme inhibitors.

Marco Mor1, Silvia Rivara, Alessio Lodola, Simone Lorenzi, Fabrizio Bordi, Pier Vincenzo Plazzi, Gilberto Spadoni, Annalida Bedini, Andrea Duranti, Andrea Tontini, Giorgio Tarzia.   

Abstract

Quantitative structure-activity relationships (QSARs) are frequently employed in medicinal chemistry projects, both to rationalize structure-activity relationships (SAR) for known series of compounds and to help in the design of innovative structures endowed with desired pharmacological actions. As a difference from the so-called structure-based drug design tools, they do not require the knowledge of the biological target structure, but are based on the comparison of drug structural features, thus being defined ligand-based drug design tools. In the 3D-QSAR approach, structural descriptors are calculated from molecular models of the ligands, as interaction fields within a three-dimensional (3D) lattice of points surrounding the ligand structure. These descriptors are collected in a large X matrix, which is submitted to multivariate analysis to look for correlations with biological activity. Like for other QSARs, the reliability and usefulness of the correlation models depends on the validity of the assumptions and on the quality of the data. A careful selection of compounds and pharmacological data can improve the application of 3D-QSAR analysis in drug design. Some examples of the application of CoMFA and CoMSIA approaches to the SAR study and design of receptor or enzyme ligands is described, pointing the attention to the fields of melatonin receptor ligands and FAAH inhibitors.

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Year:  2005        PMID: 17191945     DOI: 10.1002/cbdv.200590117

Source DB:  PubMed          Journal:  Chem Biodivers        ISSN: 1612-1872            Impact factor:   2.408


  2 in total

1.  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.

Authors:  Rino Ragno
Journal:  J Comput Aided Mol Des       Date:  2019-10-08       Impact factor: 3.686

2.  Synthesis and quantitative structure-activity relationship of fatty acid amide hydrolase inhibitors: modulation at the N-portion of biphenyl-3-yl alkylcarbamates.

Authors:  Marco Mor; Alessio Lodola; Silvia Rivara; Federica Vacondio; Andrea Duranti; Andrea Tontini; Silvano Sanchini; Giovanni Piersanti; Jason R Clapper; Alvin R King; Giorgio Tarzia; Daniele Piomelli
Journal:  J Med Chem       Date:  2008-05-29       Impact factor: 7.446

  2 in total

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