The results of a Pfizer-PharmaDM collaboration aimed at the discovery of hydrogen-bonding rules in crystals have been published in Molecular Pharmaceutics (an ACS journal).
Discovering H-Bonding Rules in Crystals with Inductive Logic Programming
Howard Y. Ando, (*)
Luc Dehaspe, Walter Luyten, Elke Van Craenenbroeck, Henk Vandecasteele, (+)
and Luc Van Meervelt (#)
(*) Research Formulations, Pfizer Global Research and Development, Ann Arbor Laboratories, Ann Arbor, Michigan 48105,
(+) PharmaDM, Kapeldreef 60, B-3001 Leuven, Belgium, and
(#) Department of Chemistry, K.U.Leuven, Biomolecular Architecture, Celestijnenlaan 200F, B-3001 Leuven, Belgium
Abstract:
In the domain of crystal engineering, various schemes have been proposed for the classification of hydrogen bonding (H-bonding) patterns observed in 3D crystal structures. In this study, the aim is to complement these schemes with rules that predict H-bonding in crystals from 2D structural information only. Modern computational power and the advances in inductive logic programming (ILP) can now provide computational chemistry with the opportunity for extracting structure-specific rules from large databases that can be incorporated into expert systems. ILP technology is here applied to H-bonding in crystals to develop a self-extracting expert system utilizing data in the Cambridge Structural Database of small molecule crystal structures. A clear increase in performance was observed when the ILP system DMax was allowed to refer to the local structural environment of the possible H-bond donor/acceptor pairs. This ability distinguishes ILP from more traditional approaches that build rules on the basis of global molecular properties.
Keywords: Computer aided drug design; in silico modeling; crystal structure; solubility; hydrogen bonding; machine learning; inductive logic programming