Protein Association in Dilute and Crowded Solutions
Most biological processes are mediated by protein association, which is often under kinetic rather than thermodynamic control . We have developed the transient-complex theory for protein association, which presents a framework for elucidating the mechanisms of protein association and for predicting the association rate constants . The transient complex refers to an intermediate along the association process, in which the two associating molecules have near-native separation and relative orientation but have yet to form the short-range specific interactions of the native complex. Our theory rationalizes the variations in association rate constants over 10 orders of magnitude and its computational implementation gives accurate prediction of the rate constants based on the structures of the native complexes [2-4]. We find that disordered proteins bind to their targets often via a dock-and-coalesce mechanism, whereby a segment of the disordered protein first docks to its cognate subsite and the remaining segments subsequently explore conformational space and coalesce around their cognate subsites . We propose that intrinsic disorder allows proteins to form complexes that are highly specific and yet short-lived, twin requirements for signaling and regulatory purposes . In the cellular context, association processes occur in the presence of a high concentration of background macromolecules . We have developed methods to model the effects of the crowded cellular environments on the affinities and rate constants of protein association [8,9]. These studies allow us to achieve a quantitative understanding of biological processes in the cellular context, based on fundamental physical principles.
1. H.-X. Zhou and P. A. Bates (2013). Modeling Protein Association Mechanisms and Kinetics. Curr. Opin. Struct. Biol. (in press).
2. R. Alsallaq and H.-X. Zhou (2008). Electrostatic rate enhancement and transient complex of protein-protein association. Proteins 71, 320-335.
3. G. Schreiber, G. Haran, and H.-X. Zhou (2009). Fundamental aspects of protein-protein association kinetics. Chem. Rev. 109, 839-860.
4. S. Qin, X. Pang, and H.-X. Zhou (2011). Automated prediction of protein association rate constants. Structure 19, 1744-1751.
5. H.-X. Zhou, X. Pang, and L. Cai (2012). Rate constants and mechanisms of intrinsically disordered proteins binding to structured targets. Phys. Chem. Chem. Phys. 14, 10466-10476.
6. H.-X. Zhou (2012). Intrinsic disorder: signaling via highly specific but short-lived association. Trends Biochem. Sci. 37, 43-48.
7. H.-X. Zhou, G. Rivas, and A. P. Minton (2008). Macromolecular crowding and confinement: biochemical, biophysical, and potential physiological consequences. Annu. Rev. Biophys. 37, 375-397.
8. S. Qin and H.-X. Zhou (2009). Atomistic modeling of macromolecular crowding predicts modest increases in protein folding and binding stability. Biophys. J. 97, 12-19.
9. S. Qin, L. Cai, and H.-X. Zhou (2012). A method for computing association rate constants of atomistically represented proteins under macromolecular crowding. Phys. Biol. 9, 066008.