Application of Swarm algorithm for efficient in silico screening of chemical database

COMP 154

Lei Wang,, J. Graham1, and John O. Trent2. (1) Department of Computer Engineering and Computer Science and J.G. Brown Cancer Center, University of Louisville, Louisville, KY 40291, (2) J. G. Brown Cancer Center, University of Louisville, School of Medicine, Louisville, KY 40202
This work attempt to rise up the efficiency of docking based virtual screening job by application of swarm intelligence. Virtual screening is an important structure based drug screening method. It's complementary to the high through put screening method. There are two kind of docking: rigid docking and flexible docking. Rigid docking is faster but less accurate. Flexible docking is more accurate but slower. On the other hand, although the virtual chemical library normally contains more than millions of compound, the docking result is a small set of compounds. Our application attempt to explore the possibility of speeding up the Virtual Screening process by parallel computation and generate a heuristic method based on a rough Structure-Score-Relationship (SSR).