MODEL - Molecular descriptor lab: A web-based server for computing structural and physicochemical features of compounds

Z. R. Li, L. Y. Han, Y. Xue, C. W. Yap, H. Li, L. Jiang, Y. Z. Chen

Research output: Contribution to journalArticle

55 Scopus citations

Abstract

Molecular descriptors represent structural and physicochemical features of compounds. They have been extensively used for developing statistical models, such as quantitative structure activity relationship (QSAR) and artificial neural networks (NN), for computer prediction of the pharmacodynamic, pharmacokinetic, or toxicological properties of compounds from their structure. While computer programs have been developed for computing molecular descriptors, there is a lack of a freely accessible one. We have developed a web-based server, MODEL (Molecular Descriptor Lab), for computing a comprehensive set of 3,778 molecular descriptors, which is significantly more than the ∼1,600 molecular descriptors computed by other software. Our computational algorithms have been extensively tested and the computed molecular descriptors have been used in a number of published works of statistical models for predicting variety of pharmacodynamic, pharmacokinetic, and toxicological properties of compounds. Several testing studies on the computed molecular descriptors are discussed. MODEL is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/ model/model.cgi free of charge for academic use.

Original languageEnglish (US)
Pages (from-to)389-396
Number of pages8
JournalBiotechnology and Bioengineering
Volume97
Issue number2
DOIs
StatePublished - Jun 1 2007

Keywords

  • Molecular descriptors
  • Pharmacodynamic
  • Pharmacokinetic
  • QSAR
  • QSPR
  • Statistical learning methods
  • Structural diversity
  • Toxicology

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology

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