Showing papers by "David Enot published in 2003"
22 Sep 2003
TL;DR: This work expanded the ILP pharmacophore representation to deal with protein active sites and formed quantitative models that can be interpretated chemically, and demonstrates that the theories produced are consistent with the existing chemical literature.
Abstract: 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 < 005) improvement over both standard approaches, and use of only the ligand We demonstrate that the theories produced are consistent with the existing chemical literature
7 citations