A method to enhance the hit ratio by a combination of structure-based drug screening and ligand-based screening
Katsumi Omagari1,5, Daisuke Mitomo1, Satoru Kubota1, Haruki Nakamura2,3, Yoshifumi Fukunishi2,4
1Japan Biological Informatics Consortium (JBiC), Koto-ku, Tokyo, Japan; 2Biomedicinal Information Research Center (BIRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan; 3Institute for Protein Research, Osaka University, Suita, Osaka, Japan; 4Pharmaceutical Innovation Value Chain, BioGrid Center Kansai, Toyonaka, Osaka, Japan; 5Department of Virology, Medical School, Nagoya City University, Mizuho-ku, Nagoya, Japan
Abstract: We examined the procedures to combine two different in silico drug-screening results to achieve a high hit ratio. When the 3D structure of the target protein and some active compounds are known, both structure-based and ligand-based in silico screening methods can be applied. In the present study, the machine-learning score modification multiple target screening (MSM-MTS) method was adopted as a structure-based screening method, and the machine-learning docking score index (ML-DSI) method was adopted as a ligand-based screening method. To combine the predicted compound’s sets by these two screening methods, we examined the product of the sets (consensus set) and the sum of the sets. As a result, the consensus set achieved a higher hit ratio than the sum of the sets and than either individual predicted set. In addition, the current combination was shown to be robust enough for the structural diversities both in different crystal structure and in snapshot structures during molecular dynamics simulations.
Keywords: in silico screening, consensus score, protein-based screening, protein-ligand docking, conformation of active site
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