A novel workflow for the inverse QSPR problem using multiobjective optimization.
A workflow for the inverse quantitative structure-property relationship (QSPR) problem is reported in this paper for the de novo design of novel chemical entities (NCE) in silico through the application of existing QSPR models to calculate multiple objectives, including prediction confidence measures, to be optimized during the de novo design process. Two physical property datasets are applied as case studies of the inverse QSPR workflow (IQW): mean molecular polarizability and aqueous solubility. The case studies demonstrate the optimization of molecular structures to within a property range of interest; the optimized structures are then validated against QSPR models that are generated from sets of alternative descriptors to those used in the IQW. The paper concludes with a discussion of the results from the case studies.
Brown
Nathan
N
Avantium Technologies B.V., P.O. Box 2915, 1000 CX Amsterdam, The Netherlands. nathan.brown@novartis.com
McKay
Ben
B
Gasteiger
Johann
J
D016018:Least-Squares Analysis; D008956:Models, Chemical; D021281:Quantitative Structure-Activity Relationship; D012995:Solubility