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

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 r_m² 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 r_m² metrics has been introduced here. The present study reports that the web application can be easily used for computation of r_m² metrics provided observed and QSAR‐predicted data for a set of compounds are available. Further, scaling of response data is recommended prior to r_m² calculation. © 2013 Wiley Periodicals, Inc.