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Comparative Occupancy Analysis (CoOAn) – A Straightforward and Directly Applicable 3D‐QSAR Formalism to Extract Molecular Features Obligatory for Designing Potent Leads
Author(s) -
Verma Jitender,
Malde Alpeshkumar,
Khedkar Santosh,
Coutinho Evans
Publication year - 2012
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201100134
Subject(s) - quantitative structure–activity relationship , chemical space , pharmacophore , computer science , formalism (music) , data mining , biological system , chemistry , artificial intelligence , machine learning , drug discovery , stereochemistry , biology , art , musical , biochemistry , visual arts
A simple and directly applicable 3D‐QSAR method, termed Comparative Occupancy Analysis (CoOAn), has been developed. The method is based on the comparison of local occupancies of fragments of an aligned set of molecules in a 3D‐grid space. The formalism commendably extracts the crucial position‐specific molecular features and correlates them quantitatively to their biological endpoints. The method has been effectively applied and efficaciously validated on three large and diverse datasetsthrombin, glycogen phosphorylase b (GPB), and thermolysin inhibitors. Several robust and statistically significant predictive 3D‐QSAR models were developed while simultaneously considering the influence of grid spacing on the accuracy of the results. The models, generated by the G/PLS chemometric method, not only unswervingly identified the obligatory chemical features but advantageously detected those that are unfavourable or detrimental for the molecular activity. The CoOAn models can profitably be used to optimize existing molecules as well as to design new leads with more desirable (and/or less detrimental) features. The activity‐modulating features (together with their distance‐constraints) extracted by the methodology can also be incorporated into a pharmacophore‐type query to search a chemical database for novel leads.