Article

Generating Optimal Linear PLS Estimations (GOLPE): An Advanced Chemometric Tool for Handling 3D-QSAR Problems

  1. Massimo Baroni1,
  2. Gabriele Costantino2,
  3. Gabriele Cruciani3,*,
  4. Daniela Riganelli3,
  5. Roberta Valigi3,
  6. Sergio Clementi3,*

Article first published online: 19 SEP 2006

DOI: 10.1002/qsar.19930120103

Issue

Quantitative Structure‐Activity Relationships

Quantitative Structure-Activity Relationships

Volume 12, Issue 1, pages 9–20, 1993

Additional Information

How to Cite

Baroni, M., Costantino, G., Cruciani, G., Riganelli, D., Valigi, R. and Clementi, S. (1993), Generating Optimal Linear PLS Estimations (GOLPE): An Advanced Chemometric Tool for Handling 3D-QSAR Problems. Quantitative Structure-Activity Relationships, 12: 9–20. doi: 10.1002/qsar.19930120103

Author Information

  1. 1

    Multivariate Infometric Analysis, Via Gigliarelli, 203, 06124 Perugia, Italy

  2. 2

    Faculty of Pharmacy, University of Perugia, Via del Liceo, 6, 06123 Perugia, Italy

  3. 3

    Department of Chemistry, University of Perugia, Via Elce di sotto, 8, 06123 Perugia, Italy

*Department of Chemistry, University of Perugia, Via Elce di sotto, 8, 06123 Perugia, Italy

Publication History

  1. Issue published online: 19 SEP 2006
  2. Article first published online: 19 SEP 2006
  3. Manuscript Accepted: 4 SEP 1992
  4. Manuscript Received: 17 FEB 1992

Funded by

  • MURST
  • CNR

SEARCH

SEARCH BY CITATION

ARTICLE TOOLS

Get PDF (1127K)

Keywords:

  • GOLPE;
  • PLS;
  • variable selection;
  • CoMFA;
  • 3D-QSAR

Abstract

An advanced variable selection procedure, called GOLPE, aimed at obtaining PLS regression models with the highest prediction ability is presented and illustrated with an application in 3D-QSAR. Key steps in the procedure are a preliminary variable selection by means of a D-optimal design in the loading space, and an iterative evaluation of the effects of individual variables on the model predictivity based on the validation of a number of reduced models, on variables combinations selected according to a FFD strategy.

The procedure is successfully applied to a real 3D-QSAR case study: the results obtained by GOLPE are compared with those obtained by CoMFA and found to be in good agreement in terms of variable importance, but with a much higher prediction ability. Accordingly, the results encourage to think that it might be used within the CoMFA framework in the place of the present PLS version there, or in CoMFA-like studies on the structures generated by GRID probes.

Get PDF (1127K)