Surface descriptors for protein-ligand affinity prediction

Abstract

Molecular descriptors calculated by the VolSurf program have been extensively used to model pharmacokinetic properties, e.g., passive permeability through the gastrointestinal tract or through the blood-brain barrier. These descriptors quantify steric, hydrophobic, and hydrogen bond interactions between model compounds and different environments. Since these interactions are the same as those involved in the ligand-receptor binding, VolSurf descriptors could potentially be relevant in modeling this process as well. We obtained a significant model (r2 = 0.85, q2 = 0.75) using VolSurf descriptors derived from the ligand, the protein, and the ligand-protein complex for a diverse set of 38 structures previously used in the VALIDATE (ref 23) training set. Furthermore, a statistically significant model (r2 = 0.94, q2 = 0.89) was obtained using the same type of descriptors for a homogeneous set of glycogen phosphorylase inhibitors (ref 25). Using the VolSurf computational framework, both ligand-receptor binding and the ligand's pharmacokinetic behavior can be modeled simultaneously during the preclinical aspects of drug discovery.