Use of molecular fields to compare series of potentially bioactive molecules designed by scientists or by computer

Abstract

Without 3D information on the structure of the target biomolecule, the rational design of bioactive compounds from 3D properties is based on structure-activity relationships. The design of the series of compounds tested will determine the amount of information gained. We compared a series of chemist-designed D2 agonists with a series designed by the computer by 3D searching and automated structure transformation. We described shape by the steric energies calculated on a 2Å lattice surrounding the molecules as is done in the Comparative Molecular Field Analysis Method. To select the series of computer-designed compounds from the total of 554, we used a cluster analysis based on the 25 highest principal components of the steric fields. Compared to the chemist-designed series, this series shows a larger variation in steric properties and has less correlation between steric properties. It explores all space explored by the former series. The mean and range of the forecast D1 and D2 dopaminergic receptor-binding affinities for the two series are not different. We conclude that multivariate statistical methods based on steric potential energy fields can be used to select the best possible series of molecules for a CoMFA analysis of shape properties. These methods also reduce a large set of suggested molecules to one that is reasonable to synthesize.