An efficient in silico screening method based on the protein-compound affinity matrix and its application to the design of a focused library for cytochrome P450 (CYP) ligands.
A new method has been developed to design a focused library based on available active compounds using protein-compound docking simulations. This method was applied to the design of a focused library for cytochrome P450 (CYP) ligands, not only to distinguish CYP ligands from other compounds but also to identify the putative ligands for a particular CYP. Principal component analysis (PCA) was applied to the protein-compound affinity matrix, which was obtained by thorough docking calculations between a large set of protein pockets and chemical compounds. Each compound was depicted as a point in the PCA space. Compounds that were close to the known active compounds were selected as candidate hit compounds. A machine-learning technique optimized the docking scores of the protein-compound affinity matrix to maximize the database enrichment of the known active compounds, providing an optimized focused library.
Fukunishi
Yoshifumi
Y
Biological Information Research Center (BIRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-41-6, Aomi, Koto-ku, Tokyo 135-0064, Japan. y-fukunishi@jbirc.aist.go.jp
Hojo
Shinichi
S
Nakamura
Haruki
H
D001185:Artificial Intelligence; D001665:Binding Sites; D002626:Chemistry, Pharmaceutical / Q000379:methods*; D020650:Combinatorial Chemistry Techniques; D003577:Cytochrome P-450 Enzyme System / Q000737:chemistry*; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D004345:Drug Industry; D006801:Humans; D008024:Ligands; D008956:Models, Chemical; D015233:Models, Statistical; D011110:Polymorphism, Genetic; D025341:Principal Component Analysis; D011506:Proteins / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D013678:Technology, Pharmaceutical / Q000379:methods*
D008024:Ligands; D011506:Proteins; D003577:Cytochrome P-450 Enzyme System