Comparison and Druggability Prediction of Protein–Ligand Binding Sites from Pharmacophore-Annotated Cavity Shapes

• Published in: Journal of chemical information and modeling 2012-08, Vol.52 (8), p.2287-2299
• Main Authors: Desaphy, Jérémy, Azdimousa, Karima, Kellenberger, Esther, Rognan, Didier
• Format: Article
• Language: English
• Subjects: Binding Sites; Biological and medical sciences; Chemical Sciences; Computational Biology - methods; Drug Evaluation, Preclinical; Drug-Related Side Effects and Adverse Reactions; Drugs; Fundamental and applied biological sciences. Psychology; General pharmacology; Humans; Interactions. Associations; Intermolecular phenomena; Ligands; Medical sciences; Models, Molecular; Molecular biophysics; Molecules; Other; Pharmaceutical Preparations - chemistry; Pharmaceutical Preparations - metabolism; Pharmaceutical technology. Pharmaceutical industry; Pharmacology; Pharmacology. Drug treatments; Protein Conformation; Proteins; Proteins - chemistry; Proteins - metabolism; User-Computer Interface
• ISSN: 1549-9596; 1549-960X; 1549-960X
• DOI: 10.1021/ci300184x

Estimating the pairwise similarity of protein–ligand binding sites is a fast and efficient way of predicting cross-reactivity and putative side effects of drug candidates. Among the many tools available, three-dimensional (3D) alignment-dependent methods are usually slow and based on simplified representations of binding site atoms or surfaces. On the other hand, fast and efficient alignment-free methods have recently been described but suffer from a lack of interpretability. We herewith present a novel binding site description (VolSite), coupled to an alignment and comparison tool (Shaper) combining the speed of alignment-free methods with the interpretability of alignment-dependent approaches. It is based on the comparison of negative images of binding cavities encoding both shape and pharmacophoric properties at regularly spaced grid points. Shaper approximates the resulting molecular shape with a smooth Gaussian function and aligns protein binding sites by optimizing their volume overlap. Volsite and Shaper were successfully applied to compare protein–ligand binding sites and to predict their structural druggability.