"OEDocking 3.1: Pose Prediction in One Awesome Package" presented by Gregory Warren, Ph.D., Senior Applications Scientist from OpenEye
The webinar was originally held on Wednesday, July 23, 2014. Access this on-demand webinar recording by filling out the for below.
Historically, the development of molecular docking tools has been focused on the generation of a single algorithm that is applied similarly to each docking task. This strategy ignores the fact that the two tasks for which docking has been successfully applied (pose prediction and virtual screening) are fundamentally very different problems. OpenEye's strategy is to develop applications that are optimized to produce the best performance for their specific individual tasks. We will present the first of these applications, POSIT, and show that this application is the best-in-class for generating pose predictions for lead optimization.
