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  • Title: Cross-docking benchmark for automated pose and ranking prediction of ligand binding.
    Author: Wierbowski SD, Wingert BM, Zheng J, Camacho CJ.
    Journal: Protein Sci; 2020 Jan; 29(1):298-305. PubMed ID: 31721338.
    Abstract:
    Significant efforts have been devoted in the last decade to improving molecular docking techniques to predict both accurate binding poses and ranking affinities. Some shortcomings in the field are the limited number of standard methods for measuring docking success and the availability of widely accepted standard data sets for use as benchmarks in comparing different docking algorithms throughout the field. In order to address these issues, we have created a Cross-Docking Benchmark server. The server is a versatile cross-docking data set containing 4,399 protein-ligand complexes across 95 protein targets intended to serve as benchmark set and gold standard for state-of-the-art pose and ranking prediction in easy, medium, hard, or very hard docking targets. The benchmark along with a customizable cross-docking data set generation tool is available at http://disco.csb.pitt.edu. We further demonstrate the potential uses of the server in questions outside of basic benchmarking such as the selection of the ideal docking reference structure.
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