Some case studies on application of "rm2" metrics for judging quality of quantitative structure-activity relationship predictions: Emphasis on scaling of response data

Kunal Roy, Pratim Chakraborty, Indrani Mitra, Probir Kumar Ojha, Supratik Kar, Rudra Narayan Das

Research output: Contribution to journalArticlepeer-review

396 Scopus citations

Abstract

Quantitative structure-activity relationship (QSAR) techniques have found wide application in the fields of drug design, property modeling, and toxicity prediction of untested chemicals. A rigorous validation of the developed models plays the key role for their successful application in prediction for new compounds. The rm2 metrics introduced by Roy et al. have been extensively used by different research groups for validation of regression-based QSAR models. This concept has been further advanced here with introduction of scaling of response data prior to computation of r m2. Further, a web application (accessible from http://aptsoftware.co.in/rmsquare/ and http://203.200.173.43:8080/rmsquare/) for calculation of the rm2 metrics has been introduced here. The present study reports that the web application can be easily used for computation of rm2 metrics provided observed and QSAR-predicted data for a set of compounds are available. Further, scaling of response data is recommended prior to rm2 calculation.

Original languageEnglish
Pages (from-to)1071-1082
Number of pages12
JournalJournal of Computational Chemistry
Volume34
Issue number12
DOIs
StatePublished - 5 May 2013

Keywords

  • open access
  • QSAR
  • r
  • software
  • validation
  • web-based application

Fingerprint

Dive into the research topics of 'Some case studies on application of "rm2" metrics for judging quality of quantitative structure-activity relationship predictions: Emphasis on scaling of response data'. Together they form a unique fingerprint.

Cite this