DOVIS 2.0: an efficient and easy to use parallel virtual screening tool based on AutoDock 4.0

To keep DOVIS up-to-date, we upgraded the software's docking engine to the more accurate AutoDock 4.0 code. We developed a new parallelization scheme to improve runtime efficiency and modified the AutoDock code to reduce excessive file operations during large-scale virtual screening jobs. We also implemented an algorithm to output docked ligands in an industry standard format, sd-file format, which can be easily interfaced with other modeling programs. Finally, we constructed a wrapper-script interface to enable automatic rescoring of docked ligands by arbitrarily selected third-party scoring programs.The significance of the new DOVIS 2.0 software compared with the previous version lies in its improved performance and usability. The new version makes the computation highly efficient by automating load balancing, significantly reducing excessive file operations by more than 95%, providing outputs that conform to industry standard sd-file format, and providing a general wrapper-script interface for rescoring of docked ligands. The new DOVIS 2.0 package is freely available to the public under the GNU General Public License.Molecular docking is a computational method that predicts how a ligand interacts with a receptor. Hence, it is an important tool in studying receptor-ligand interactions and plays an essential role in drug design. Particularly, molecular docking has been used as an effective virtual screening tool and successfully applied in a number of therapeutic programs at the lead discovery stage [1].AutoDock [2,3] is a broadly used docking program. Previously, we developed a Linux cluster-based application termed DOVIS [4], which runs in parallel on hundreds of central processing units (CPUs), uses AutoDock 3.05 as the docking engine, and docks large numbers (millions) of ligands to a target receptor. It automatically partitions input ligands, prepares parameter files for AutoDock, launches parallel AutoDock runs, parses results, and saves a set of top-ranking