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Revealing the fundamental principles of protein interactions is essential for the basic knowledge of molecular processes and designing better predictive tools. Protein docking procedures allow systematic sampling of intermolecular energy landscapes, revealing the distribution of energy basins and their characteristics. A systematic search docking procedure GRAMM-X was applied to a comprehensive nonredundant database of nonobligate protein-protein complexes to determine the size of the intermolecular energy funnel. The unbound structures were simulated using rotamer library. The procedure generated grid-based matches, based on a smoothed Lennard-Jones potential, and minimized them off the grid with the same potential. The minimization generated a distribution of distances, based on a variety of metrics, between the grid-based and the minimized matches. The metric selected for the analysis, ligand interface RMSD, provided three independent estimates of the funnel size: based on the distribution amplitude for the near-native matches, deviation from random, and correlation with the energy values. The three methods converge to similar estimates of approximately 6-8 A ligand interface RMSD. The results indicated dependence of the funnel size on the type of the complex (smaller for antigen-antibody, medium for enzyme-inhibitor, and larger for the rest of the complexes) and the funnel size correlation with the size of the interface. Guidelines for the optimal sampling of docking coordinates, based on the funnel size estimates, were explored.

Proteins display a broad peak in 250-300 nm region of their UV spectrum containing multiple overlapping bands arising from the aromatic rings of phenylalanine, tyrosine, and tryptophan residues. Employing high resolution 2 nd derivative absorbance spectroscopy, these overlapping absorption bands can be highly resolved and therefore provide a very sensitive measure of changes in the local microenvironment of the aromatic side chains. This has traditionally been used to detect both subtle and dramatic (i.e., unfolding) conformational alterations of proteins. Herein, we show that plots of the temperature dependent 2 nd derivative peak positions of aromatic residues have measurable slopes before protein unfolding and that these slopes are sensitive to the dielectric properties of the surrounding microenvironment. We further demonstrate that these slopes correlate with hydration of the buried aromatic residues in protein cores and can therefore be used as qualitative probes of protein dynamics.

Locating the global minimum of a complex potential energy surface is facilitated by considering a homotopy, namely a family of surfaces that interpolate continuously from an arbitrary initial potential to the system under consideration. Different strategies can be used to follow the evolving minima. It is possible to enhance the probability of locating the global minimum through a heuristic choice of interpolation schemes and parameters, and the continuously evolving potential landscape reduces the probability of trapping in local minima. In application to a model problem, finding the ground-state configuration and energy of rare-gas (LennardJones) atomic clusters, we demonstrate the utility and efficacy of this method.