Automated clustering of probe molecules from solvent mapping of protein surfaces: new algorithms applied to hot-spot mapping and structure-based drug design.
Use of solvent mapping, based on multiple-copy minimization (MCM) techniques, is common in structure-based drug discovery. The minima of small-molecule probes define locations for complementary interactions within a binding pocket. Here, we present improved methods for MCM. In particular, a Jarvis-Patrick (JP) method is outlined for grouping the final locations of minimized probes into physical clusters. This algorithm has been tested through a study of protein-protein interfaces, showing the process to be robust, deterministic, and fast in the mapping of protein "hot spots." Improvements in the initial placement of probe molecules are also described. A final application to HIV-1 protease shows how our automated technique can be used to partition data too complicated to analyze by hand. These new automated methods may be easily and quickly extended to other protein systems, and our clustering methodology may be readily incorporated into other clustering packages.
Lerner
Michael G
MG
Department of Biophysics, University of Michigan, 930 North University Avenue, Ann Arbor, MI 48109-1055, USA.
Meagher
Kristin L
KL
Carlson
Heather A
HA
D000465:Algorithms; D001554:Benzene / Q000737:chemistry; D020134:Catalytic Domain; D015195:Drug Design; D016333:HIV Protease / Q000737:chemistry; D006860:Hydrogen Bonding; D057927:Hydrophobic and Hydrophilic Interactions; D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry*; D012997:Solvents / Q000737:chemistry*; D055672:Static Electricity; D013499:Surface Properties
D011506:Proteins; D012997:Solvents; D016333:HIV Protease; C514803:p16 protease, Human immunodeficiency virus 1; D001554:Benzene