ASTRO-FOLD: Ab-initio Secondary and Tertiary Structure Prediction in Protein Folding

摘要

The ability to predict protein structures from gene sequence data through computational means has significant implications in the fields of computational chemistry, structural biology and medicinal chemistry, as well as in expanding the impact of the research on the human genome. Current challenges for this task, also known as ab-initio protein structure prediction, include validity of the available molecular models and complexity of the search space. A novel four stage ab-initio approach for the structure prediction of single chain polypeptides is introduced. The methodology combines the classical and new views of protein folding, while using free energy calculations and integer linear optimization to predict helical and β-sheet structures. Detailed atomistic modeling and the deterministic global optimization method, αBB, coupled with torsion angle dynamics, form the basis for the final tertiary structure prediction. The excellent performance of the proposed approach is illustrated using the bovine pancreatic trypsin inhibitor protein.