In this study, we adopted the ''rank-by-number'' strategy in the consensus scoring to combine the results of multiple scoring functions. The ''rank-by-number'' strategy was previously found to outperform the ''rank-by-rank'' and ''rank-by-vote'' strategy because it can summarize most of the information [32] . For the ''rank-by-number'' strategy, the consensus score of each binding pose is an average of the values determined by each of the individual scoring functions in a given consensus scoring scheme. With this strategy, a moderate number of scoring functions (i.e., three or four) have been proposed to be sufficient for significantly improving the results. Therefore, we chose 4 of the 12 scoring functions (D_score, jain, and Ludi_1, Surflex_Score) to perform consensus scoring in the present study.