Automated Prediction of Protein Association Rate Constants

摘要

The association rate constants (k_a) of proteins with other proteins or other macromolecular targets are a fundamental biophysical property. Observed rate constants span over ten orders of magnitude, from 1 to 10~(10) M~(-1)s~(-1). Protein association can be rate limited either by the diffusional approach of the subunits to form a transient complex, with near-native separation and orientation but without short-range native interactions, or by the subsequent conformational rearrangement to form the native complex. Our transient-complex theory showed promise in predicting k_ in the diffusion-limited regime. Here, we develop it into a web server called TransComp (http://pipe.sc.fsu.edu/transcomp/) and report on the server's accuracy and robustness based on applications to over 100 protein complexes. We expect this server to be a valuable tool for systems biology applications and for kinetic characterization of protein-protein and protein-nucleic acid association in general.