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We describe a general methodology for designing an empirical scoring function and provide smina, a version of AutoDock Vina specially optimized to support high-throughput scoring and user-specified custom scoring functions. Using our general method, the unique capabilities of smina, a set of default interaction terms from AutoDock Vina, and the CSAR (Community Structure-Activity Resource) 2010 dataset, we created a custom scoring function and evaluated it in the context of the CSAR 2011doi:10.1021/ci300604z pmid:23379370 pmcid:PMC3726561 fatcat:5is3fcqvifbfpbf7ipx5kd2vue