Binary QSAR: a new method for the determination of quantitative structure activity relationships.
A new method (particularly suited to the analysis of High Throughput Screening data) is presented for the determination of quantitative structure activity relationships. The method, termed "Binary QSAR," accepts binary activity measurements (e.g., pass/fail or active/inactive) and molecular descriptor vectors as input. A Bayesian inference technique is used to predict whether or not a new compound will be active or inactive. Experiments were conducted on a data set of 1947 molecules. The results show that the method exhibits high accuracy and is robust to measurement errors.
Labute
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Chemical Computing Group Inc., Montreal, Quebec, Canada.
D001499:Bayes Theorem; D003198:Computer Simulation; D003205:Computing Methodologies; D016208:Databases, Factual; D004353:Drug Evaluation, Preclinical; D008024:Ligands; D008956:Models, Chemical; D015203:Reproducibility of Results; D013329:Structure-Activity Relationship
D008024:Ligands