Cite this article: Keyes RM, Pejo E, Katagiri K, Huynh K, Rudnitskaya A, et al. (2016) Shape Matters: Improving Docking Results by Prior Analysis of Geometric Attributes of Binding Sites. JSM Chem 4(1): 1020. Central Bringing Excellence in Open Access   JSM Chemistry *Corresponding author Kimb e rly A Stie g litz, De p a rtme nt o f Bio te c hno lo g y, Ro xb ury C o mmunity C o lle g e , 1234 C o lumb us Ave , Bo sto n, MA, USA, Ema il: Submitte d: 21 Marc h 2016 Accepted: 07 April 2016 Publishe d: 16 April 2016 ISSN: 2333-6633 Copyright © 2016 Stie g litz e t a l. OPEN ACCESS Research Article Shape Matters: Improving Docking Results by Prior Analysis of Geometric Attributes of Binding Sites Renee M Keyes 1 , Ervin Pejo 2 , Kazuo Katagiri 2 , Ken Huynh 2 , Aleksandra Rudnitskaya 2 , Boguslaw Stec 3 and Kimberly A Stieglitz 1 * 1 Department of Biotechnology, Roxbury Community College, USA 2 Department of Chemistry, University of Massachusetts, USA 3 Department of Chemistry, Burnham Institute for Medical Research, USA Abstract An important improvement for selection of docking programs has been found. Correlating the attributes of ligand binding pocket shape with an appropriate program in the early stages of automated docking has been proven to increase the success of the procedure. This potentially constitutes an important improvement in structure-based drug design process. A two-stage approach: (1) computing attributes of the binding site and (2) running the appropriate docking algorithm, has been used to screen ~one hundred structures from the Protein Data Bank (PDB). The attributes of the binding pockets used in this study were: the ratio of the volume of the solvent accessible surface to the volume of the molecular surface (Vsa/ms) and the area of the solvent accessible surface to the area of the molecular surface (Asa/ms). This study doesn’t look at charges and H-bonding or hydrophobic interactions. However it is still very useful to aid in choosing the best docking program possible. The results of initial screening within the bounds of optimally selected parameters indicated that, it is possible to use an algorithm that performs better than others. The study shows that for high numerical values of both ratios all the docking computer programs produced poor results, for medium and medium high values of those ratios, Auto dock and DOCK were the best choice. However, with small values of the ratios all four programs GOLD, Surfex, DOCK and Auto dock produced agreement within 10% difference comparing RMSD of docked versus crystallographic ligand. INTRODUCTION Structure-based virtual screening has been thoroughly tested, with substantial success. The automated docking procedure is a vital part of virtual screening and is now a widely used technique in the early stages of drug discovery in most academic and commercial (Big Pharmacy) environments. Improvements in computer processing speeds and multiprocessing methods as well as distributed computational methods using multiple workstations permit en masse screening with storage of large quantities of data. This enables investigators to screen large numbers of compounds available in online libraries [1-3] by docking them into the binding pocket of the target enzyme. Concurrently, the experimental emergence of the ‘high-throughput’ automated X-ray crystallographic screening techniques has dramatically increased the rate at which researchers can progress from the over-expression of a target protein to an inhibitor protein complex. The combination of high-throughput X-ray crystallography and molecular docking techniques allows investigators to work efficiently to design potent inhibitors to medically relevant enzyme targets. In automated docking procedures the success critically depends on the accuracy and precision of the process of in silico molecular docking. This, in turn, depends on the choice of software, the protein, how the binding site and search space is defined, and the ligands. The software choice may become the weak link in the process. Many other research groups [4-21] worked on comparisons, and improvement to correlate predicted docking results of ligands with experimental results (x-ray data). The problem of disagreement between virtual versus actual screening of small molecules for tight binding to proteins, remains an active area of investigation. Reliance on software