Chemical file enhancement assisted by computational filtration protocols.

Abstract

For the chemical file enhancement, it is quite important to acquire good compounds for drug discovery. One of the approaches to find the GOOD compounds is the visual inspection by the well-experienced medicinal chemists. Recently, due to drastic increase of the commercially available compounds, it has become impractical to inspect all of them solely by their eyes and knowledge. For last few years, we have introduced some computational filtration protocols, such as Lipinski Rule filter, Bayesian model-derived Drug-likeness Score filter, etc. They are employed for preprocessing steps in the inspection so that the medicinal chemists can skip unfavorable compounds automatically. By means of the filtration protocols, our inspection of compounds has become more exhaustive and efficient. Because of the size of the acquisition, its cost performance is another point of interest. In the sense of improving the cost performance, it is preferable to acquire compounds from one well-qualified supplier. A set of the filtration protocols can be employed as a tool for such qualification as well. In this presentation, the speaker will talk about some examples of these approaches.