Comparative occupancy analysis (CoOAn)- a straightforward and directly applicable 3D-QSAR formalism to extract molecular features obligatory for designing potent leads

Verma, Jitender, Malde, Alpeshkumar, Khedkar, Santosh and Coutinho, Evans (2012) Comparative occupancy analysis (CoOAn)- a straightforward and directly applicable 3D-QSAR formalism to extract molecular features obligatory for designing potent leads. Molecular Informatics, 31 6-7: 431-442. doi:10.1002/minf.201100134


Author Verma, Jitender
Malde, Alpeshkumar
Khedkar, Santosh
Coutinho, Evans
Title Comparative occupancy analysis (CoOAn)- a straightforward and directly applicable 3D-QSAR formalism to extract molecular features obligatory for designing potent leads
Journal name Molecular Informatics   Check publisher's open access policy
ISSN 1868-1743
1868-1751
Publication date 2012-07
Sub-type Article (original research)
DOI 10.1002/minf.201100134
Volume 31
Issue 6-7
Start page 431
End page 442
Total pages 12
Place of publication Wiley-VCH Verlag
Publisher Weinheim, Germany
Collection year 2013
Language eng
Formatted abstract
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 datasets—thrombin, 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.
Keyword QSAR
Occupancy
Pharmacophore
Thrombin
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
School of Chemistry and Molecular Biosciences
 
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