Scoring noncovalent protein-ligand interactions: a continuous differentiable function tuned to compute binding affinities.
Exploitation of protein structures for potential drug leads by molecular docking is critically dependent on methods for scoring putative protein-ligand interactions. An ideal function for scoring must exhibit predictive accuracy and high computational speed, and must be tolerant of variations in the relative protein-ligand molecular alignment and conformation. This paper describes the development of an empirically derived scoring function, based on the binding affinities of protein-ligand complexes coupled with their crystallographically determined structures. The function's primary terms involve hydrophobic and polar complementarity, with additional terms for entropic and solvation effects. The issue of alignment/conformation dependence was solved by constructing a continuous differentiable nonlinear function with the requirement that maxima in ligand conformation/alignment space corresponded closely to crystallographically determined structures. The expected error in the predicted affinity based on cross-validation was 1.0 log unit. The function is sufficiently fast and accurate to serve as the objective function of a molecular-docking search engine. The function is particularly well suited to the docking problem, since it has spatially narrow maxima that are broadly accessible via gradient descent.
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Arris Pharmaceutical Corporation, San Francisco, CA 94080, USA.
D001426:Bacterial Proteins / Q000737:chemistry; D001710:Biotin / Q000737:chemistry; D003198:Computer Simulation; D017076:Computer-Aided Design; D016208:Databases, Factual; D015195:Drug Design; D019277:Entropy; D008024:Ligands; D008958:Models, Molecular; D015394:Molecular Structure; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012997:Solvents; D019809:Streptavidin
D001426:Bacterial Proteins; D008024:Ligands; D011506:Proteins; D012997:Solvents; D001710:Biotin; D019809:Streptavidin