Probability Issues in Molecular Design: Predictive and Modeling Ability in 3D-QSAR Schemes

Author(s): Jaroslaw Polanski, Rafal Gieleciak, Andrzej Bak

Journal Name: Combinatorial Chemistry & High Throughput Screening
Accelerated Technologies for Biotechnology, Bioassays, Medicinal Chemistry and Natural Products Research

Volume 7 , Issue 8 , 2004

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In the current work we investigated 3D-QSAR data by the use of the coupled leave-several-out (LSO) and leave-one-out (LOO) cross-validation (CV) procedures. We verified the above mentioned scheme using both simulated data and real 3D QSAR data describing a series of CoMFA steroids, heterocyclic azo dyes and styrylquinoline HIV integrase inhibitors. Unlike in standard analyses, this technique characterizes individual method not by a single performance metrics but screens a whole possible modeling space by sampling different molecules into the training and test sets, respectively. This allowed us for the discussion of the information included in the estimators validating cross-validation procedures, as well as the comparison of the efficiency of several 3D QSAR schemes, in particular, Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Surface Analysis (CoMSA). Moreover, it allows one to acquire some general knowledge about predictive and modeling ability in 3D QSAR method.

Keywords: comfa, comsa, 3d qsar, steroids, hiv integrase inhibitors, heterocyclic azo dyes

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Article Details

Year: 2004
Page: [793 - 807]
Pages: 15
DOI: 10.2174/1386207043328292
Price: $65

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