Application of Inductive Logic Programming to Structure-Based Drug Design


Autoria(s): Enot, David Pierre Louis; King, Ross Donald
Contribuinte(s)

Bioinformatics and Computational Biology Group

Department of Computer Science

Data(s)

25/04/2006

25/04/2006

2003

Resumo

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

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.

Formato

12

Identificador

Enot , D P L & King , R D 2003 , Application of Inductive Logic Programming to Structure-Based Drug Design . in Knowledge Discovery in Databases: PKDD 2003 : 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Cavtat-Dubrovnik, Croatia, September 22-26, 2003. Proceedings . Lecture Notes in Computer Science , Springer Nature , pp. 156-167 , 7th European Conference on Principles and Practice of Knowledge Discovery in Databases , Cavtat-Dubrovnik , Croatia , 22-26 September . DOI: 10.1007/978-3-540-39804-2_16

conference

978-3-540-20085-7

978-3-540-39804-2

0302-9743

PURE: 2387368

PURE UUID: 0e5019af-fe70-4c44-b215-d91222ab0a8c

dspace: 2160/145

http://hdl.handle.net/2160/145

http://dx.doi.org/10.1007/978-3-540-39804-2_16

Idioma(s)

eng

Publicador

Springer Nature

Relação

Knowledge Discovery in Databases: PKDD 2003

Lecture Notes in Computer Science

Tipo

/dk/atira/pure/researchoutput/researchoutputtypes/contributiontobookanthology/conference

Conference proceeding

Direitos