This project aims at the exploration of chemical space from a network-centric perspective.
Funded by DST Science and Engineering Research Board (SERB) Project EMR 2016-002141 for a period of 3 years 2018-2021.
Principal Investigator: N. Sukumar
Co-Investigator: Subhabrata Sen
Co-Investigator: Sudeepto Bhattacharya (Mathematics)
This project aims at the exploration of chemical space from a network-centric perspective. We propose to investigate molecular similarity networks using different families of molecular descriptors and similarity measures. The application of various network measures to the design of diversity oriented molecular libraries is a major goal of this project. We have shown that exploration of protein binding site similarity networks hold great potential for predicting cross reactivity of drugs. Chemical transformation networks have thus far been relatively unexplored from a network perspective. We propose to make significant inroads in this direction using mathematical network measures, comparing the characteristics of these networks to those of molecular interaction and similarity networks. Finally, we intend to apply the outcome of our findings to generate two molecular libraries - the first via diversity oriented synthesis followed by biological evaluation against various phenotypes, and the second a target-based library against alpha-glucosidase.
Expected output and outcome of the proposal:
In this research proposal, we plan to investigate the distinguishing characteristics of different molecular networks, to explore their potential applications in the design of molecular libraries for drug design, and for predicting cross-reactivity of drugs. Application of network measures to the design of molecular libraries is a relatively unexplored area, with considerable promise and a major goal of this project. Application of protein binding site similarity networks for predicting cross reactivity of drugs is a second major goal of this project. The outcome of this work will be useful to develop a tool for the prediction of drug cross-reactivity. A specific application that will be targeted in this project is the use of network measures for molecular similarity networks and chemical transformation networks to design diversity-oriented molecular libraries. After benchmarking the usefulness of network measures for the design of a couple of test-bed molecular libraries, the network measures developed in this project can be applied to the design of larger molecular libraries and to selection of molecules from larger molecular databases for the development of global QSAR models.