A method to enhance the hit ratio by a combination of structure-based drug screening and ligand-based screening

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

Acknowledgments

This work was supported by grants from the New Energy and Industrial Technology Development Organization of Japan (NEDO) and the Ministry of Economy, Trade, and Industry (METI) of Japan.