Classification of Chemical Compounds by Protein-Compound Docking for Use in Designing a Focused Library

摘要

We developed a new method for the classification of chemical compounds and protein pockets and applied it to a random screening experiment for macrophage migration inhibitory factor (MIF).The principal component analysis (PCA) method was applied to the protein-compound interaction matrix,which was given by thorough docking calculations between a set of many protein pockets and chemical compounds.Each compound and protein pocket was depicted as a point in the PCA spaces of compounds and proteins,respectively.This method was applied to distinguish active compounds from negative compounds of MIF.A random screening experiment for MIF was performed,and our method revealed that the active compounds were localized in the PCA space of compounds,while the negative compounds showed a wide distribution.Furthermore,protein pockets,which bind similar compounds,were classified and were found to form a cluster in the PCA space.