@inproceedings{0e5019affe704c44b215d91222ab0a8c,
title = "Application of Inductive Logic Programming to Structure-Based Drug Design",
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 < 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.",
author = "Enot, {David Pierre Louis} and King, {Ross Donald}",
note = "Enot, D. and King, R. D. (2003) Application of Inductive Logic Programming to Structure-Based Drug Design. 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD '03). Springer LNAI 2838 p156-167; 7th European Conference on Principles and Practice of Knowledge Discovery in Databases ; Conference date: 22-09-2003 Through 26-09-2003",
year = "2003",
doi = "10.1007/978-3-540-39804-2_16",
language = "English",
isbn = "978-3-540-20085-7",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "156--167",
booktitle = "Knowledge Discovery in Databases: PKDD 2003",
address = "Switzerland",
}
