Novel method for pharmacophore analysis by examining the joint pharmacophore space

We propose a novel method for pharmacophore analysis by examining the Joint Pharmacophore Space of chemical compounds, targets, and chemical/biological properties. The proposed approach is a notable deviation from existing techniques that analyze compounds on a target-by-target basis, aimed at extracting and optimizing a specific pharmacophore. The underlying geometry of the pharmacophores is responsible for binding between compounds and targets as well as properties of compounds such as Blood Brain Barrier permeability. The identification of this joint space enables us to cluster and classify similar pharmacophores based on geometric arrangements, analyze the diversity of this space, ascribe positive/negative properties to the subspaces, and query and mine a database of compounds for presence or absence of activity. Extensive experiments are carried out to validate the presence of subspaces that uniquely identify geometric configurations conforming to certain biological activities. The discriminative potential of these subspaces is also verified by employing them as a molecular descriptor. Empirical results show promising performance in terms of classification quality highlighting the utility of mining the joint pharmacophore space.