On Predicting Protein Secondary Structure from their Aminoacid Sequences using Inductive Logic Programming

We address the problem of predicting the stability of secondary structure motifs of proteins given their linear sequence of residues. Our study is restricted to the prediction of helix structures. We have applied an inductive logic programming (ILP) system to automatically synthesise the predictive rules. ILP systems are well known for being able to induce comprehensible models for data. Furthermore, the models components are definitions provided by a domain expert which makes the model more likely to be helpful in the understanding of the underlying process that produced the data. Our methodology has two stages. First, the system induces a model (set of rules) using just structural information and groupings of the residues to avoid biases by the domain expert. In the second stage, the residues properties are used to make the induced rules chemically/biologically appealing. We claim that this methodology is also valuable for general structure-activity relationship (SAR) problems