A Multi-Advisor Evaluation Module for the Accurate Prediction of Alpha Helix Pairs

Abstract

Accurate 3D protein structure prediction is one of the most challenging problems facing bioinformaticians today. This thesis develops and examines an evaluation module for ranking predicted super-secondary structures – specifically a-helix pairs – as part of a case-based reasoning system. The proposed module is part of the Triptych project, which aims at the accurate prediction of the three-dimensional structure of proteins from contact maps. Triptych is an advanced case-based reasoning system that utilizes a library of existing protein structures and motifs to help predict the structure of a known polypeptide chain of amino acids that represents a target a-helix pair. The proposed module evaluates possible solutions by integrating multiple strategies, learning methods and sources of knowledge in the form of expert advisors. It uses advisors which integrate knowledge from the fields of biology, biochemistry, classical physics, and statistical data analysis obtained from pre-determined structures. Lastly, the proposed evaluation module would allow for the integration of more sources of knowledge, in the form of expert advisors, as well as serve as a framework for evaluating other structural motifs in future.