Abstract
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
Combinatorial Chemistry & High Throughput Screening
Title: Probability Issues in Molecular Design: Predictive and Modeling Ability in 3D-QSAR Schemes
Volume: 7 Issue: 8
Author(s): Jaroslaw Polanski, Rafal Gieleciak and Andrzej Bak
Affiliation:
Keywords: comfa, comsa, 3d qsar, steroids, hiv integrase inhibitors, heterocyclic azo dyes
Abstract: 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.
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Cite this article as:
Polanski Jaroslaw, Gieleciak Rafal and Bak Andrzej, Probability Issues in Molecular Design: Predictive and Modeling Ability in 3D-QSAR Schemes, Combinatorial Chemistry & High Throughput Screening 2004; 7 (8) . https://dx.doi.org/10.2174/1386207043328292
DOI https://dx.doi.org/10.2174/1386207043328292 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
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