Predicting drug promiscuity using spherical harmonic surface shape-based similarity comparisons

Abstract

Polypharmacology is becoming an increasingly important aspect in drug design. Pharmaceutical companies are discovering more and more cases in which multiple drugs bind to a given target (promiscuous targets) and in which a given drug binds to more than one target (promiscuous ligands). These phenomena are clearly of great importance when considering drug side-effects. In the last 4 years, more than 30 drugs have been tested against more than 40 novel secondary targets based on promiscuity predictions. Current methods for predicting promiscuity typically aim to relate protein receptors according to their primary sequences, the similarity of their ligands, and more recently, the similarity of their ligand binding pockets. Here, we present a spherical harmonic (SH) surface shape-based approach to predict rapidly promiscuous ligands and targets by comparing sets of SH ligand and protein shapes, respectively. We present details of our approach applied to a wide range of PDB complexes comprising ligands in a selected subset of the MDL Drug Data Report (MDDR) database which are distributed over 249 diverse pharmacological targets. The shape similarity of each ligand to each target’s ligand set is quantified and used to predict promiscuity. We also analyse the correlation between binding pocket and ligand shapes. We compare our promiscuity predictions with experimental activity values extracted from the BindingDB database.