GAUK 154613

Many areas of chemical biology, e.g. drug discovery, largely rely on libraries of molecules for production processes. Since the space of all molecules, called the chemical space, is huge, those libraries contain only small subspace of the whole space. An alternative to statical libraries is dynamic exploration of the space. The exploration generates molecules dynamically based on paths between given molecules in the chemical space. One of a few tools to explore the chemical space is Molpher which has been developed at Charles University in Prague. Molpher’s drawback is the limited possibility of influencing the exploration process. Possible approach to affect the exploration is to minimize the exploration of the subspaces that are not interesting. This calls for effective molecule representation allowing the distinction of interested molecules based on their structure. Here, by effectiveness we understand both accuracy and low computation complexity. Because a lot of molecules are being generated during the exploration processes it is crucial to be able to compare two molecules very fast which helps to restrict the chemical space that needs to be explored. Our goal is to develop a new molecular representation and related algorithms enabling its use in Molpher and similar projects.