In order to design novel non-peptidic inhibitors of BACE1, many research groups have attempted using computational studies including docking analyses. Since there are too many 3D structures for BACE1 in the protein database, the selection of suitable crystal structures is a key prerequisite for the successful application of molecular docking. We employed a multi-structure docking protocol. In which 615 ligands' structures were docked into 150 BACE1 structures. The large number of the resultant docking scores were post-processed by different data analysis methods including exploratory data analysis, regression analysis and discriminant analysis. It was found that using one crystal structure for docking did not result in high accuracy for predicting activity of the BACE1 inhibitors. Instead, using of the multi-structural docking scores, post-processed by chemometrics methods arrived to highly accurate predictive models. In this regards, the PDB accession codes of 4B70, 4DVF and 2WEZ could discriminate between active and inactive compounds, with higher accuracy. Clustering of the BACE1 structures based on principal component analysis of the crystallographic structures the revealed that the discriminant structures are in the center of the clusters. Thus, these structures can be selected as predominant crystal structures for docking studies of non-peptidic BACE1 inhibitors.
