A knowledge-based scoring function for protein-ligand interactions: Probing the reference state

摘要

Knowledge-based scoring functions have recently emerged as an alternative and very promising way of ranking protein-ligand complexes with known 3D structure according to their binding affinities. These simplified potential-based approaches use the structural information stored in databases of protein-ligand complexes to derive atom pair interaction potentials also known as potentials of mean force (PMF). The derived PMF depend on the definition of a suitable reference state. The reference states vary among suggested knowledge-based scoring functions. Therefore, we attempt here to shed some light on the influence of different reference state definitions on the predictive power of a knowledge-based scoring function that has been introduced by us very recently [J. Med. Chem., 42 (1999) 791]. It is shown that a reference state that implicitly and more comprehensively accounts for protein and ligand solvation gives the most consistent scoring results for four test sets of diverse protein-ligand complexes taken from Brookhaven Protein Data Bank. It is also shown that a reference sphere radius of at least 7-8 A is needed to effectively capture solvation effects that are treated implicitly in the scoring function.