SCHEDULE: NOV 12-18, 2011

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Study of protein-ligand binding geometries using a scalable and accurate octree-based algorithm in MapReduce

SESSION: Research Poster Reception

EVENT TYPE: ACM Student Research Competition Poster, Poster, Electronic Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR: Bernd Mohr

AUTHOR(S):Trilce Estrada, Boyu Zhang, Roger Armen, Michela Taufer

ROOM:WSCC North Galleria 2nd/3rd Floors

ABSTRACT:
We present a scalable and accurate algorithm for classifying protein-ligand binding geometries in molecular docking. Our algorithm is a three-step algorithm: the first step encodes the geometry of a 3D ligand conformation into a single 3D point in space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our algorithm for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allows screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for a dataset of HIV protease inhibitors and demonstrate significant improvement over “energy-only” scoring for the accurate identification of native ligand geometries. The advantages of this approach make it attractive for complex applications in real-world drug design efforts.

Chair/Author Details:

Bernd Mohr (Chair) - Juelich Supercomputing Centre

Trilce Estrada - University of Delaware

Boyu Zhang - University of Delaware

Roger Armen - Thomas Jefferson University School of Pharmacy

Michela Taufer - University of Delaware

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