Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study.

ABSTRACT:

Background

There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions.

Results

The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a prev

SUBMITTER: A Santos JC 

PROVIDER: S-EPMC3458898 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature