Open AccessNew Insights to Understand the CoMFA Analysis within the Density Functional Theory Framework
Author(s) -
Roya Momen,
Alejandro MoralesBayuelo
Publication year - 2021
Publication title -
journal of biomedical research and environmental sciences
Language(s) - English
Resource type - Journals
ISSN - 2766-2276
DOI - 10.37871/jbres1349
Subject(s) - quantitative structure–activity relationship , similarity (geometry) , steric effects , density functional theory , set (abstract data type) , reactivity (psychology) , quantum chemical , computer science , range (aeronautics) , field (mathematics) , theoretical computer science , computational chemistry , biological system , chemistry , mathematics , artificial intelligence , molecule , machine learning , materials science , biology , stereochemistry , medicine , alternative medicine , organic chemistry , pathology , composite material , pure mathematics , image (mathematics) , programming language
The Three-Dimensional Quantitative Structure-Activity Relationship (3D QSAR) models now have a wide range of applications; however, new methodologies are required due to the complexity in understanding their results. This research presents a generalized version of quantum similarity field and chemical reactivity descriptors within the density functional theory framework. By taking reference compounds, this generalized methodology can be used to understand the biological activity of a molecular set. In this sense, this methodology allows to study of the CoMFA in quantum similarity and chemical reactivity. It is feasible to investigate steric and electrostatic effects on local substitutions using this method. They were considering that how these methodologies could be used when the receptor is known or unknown.