Developments in physical and biological technology have resulted in a rapid rise in the amount of data available on the 3D structure of protein-ligand complexes. The extraction of knowledge from this data is central to the design of new drugs. We extended the application of Inductive Logic Programming (ILP) in drug design to deal with such structure-based drug design (SBDD) problems. We first expanded the ILP pharmacophore representation to deal with protein active sites. Applying a combination of the ILP algorithm Aleph, and linear regression, we then formed quantitative models that can be interpretated chemically. We applied this approach to two test cases: Glycogen Phosphorylase inhibitors, and HIV protease inhibitors. In both cases we observed a significant (P < 0.05) improvement over both standard approaches, and use of only the ligand. We demonstrate that the theories produced are consistent with the existing chemical literature.
|Lecture Notes in Computer Science
|7th European Conference on Principles and Practice of Knowledge Discovery in Databases
|22 Sept 2003 → 26 Sept 2003