The Drug Design Resource (D3R; drugdesigndata.org) is a NIH funded resource aimed at providing benchmark datasets and blinded challenges to assist in the evaluation and improvement of computational algorithms such as small molecule protein docking. A recent change in the type of data pre-released from the Research Collaboratory for Structural Bioinformatics (RCSB) and the World Wide Protein Data Bank (wwPDB) provides compound International Chemical Identifiers (INCHI) strings in addition to the protein polymer sequence five days prior to the release of their 3D coordinates, thereby giving an opportunity to predict small molecule protein docked poses each week. D3R has developed Continuous Evaluation of Ligand Pose Prediction (CELPP), an automated workflow to process and evaluate these docking challenges. CELPP is a python based application that consumes the wwPDB INCHI strings, selects appropriate docking targets, and prepares the proteins and ligands for weekly automated docking challenges. CELPP challenge participants will perform the docking and send the results to CELPP to be evaluated against weekly released “answers.” With the goal of improving docking algorithms and their scoring functions, we will report the CELPP protocols developed and provide an assessment of the accuracy of weekly results compared to the annual D3R Grand Challenges.

Continuous evaluation of ligand pose prediction (CELPP): An automated workflow for weekly cross-docking blinded challenges

251st National Meeting (2016)

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