Book of Abstracts: Albany 2005
Protein Folding In Silico: A Computational Pathway from Secondary to Tertiary Structure
Impressive advances in the applications of bioinformatics for protein structure prediction coupled with growing structural databases on one hand and the insurmountable time-scale problem with ab initio computational methods on the other continue to raise doubts whether a computational solution to the protein folding -- categorized as the holy grail of modern biology and as an NP hard problem -- is within reach in the near future. Combining some specially designed biophysical filters and bioinformatics tools with ab initio methods, we present here a promising computational pathway for bracketing native-like tertiary structures of small alpha helical globular proteins.
Starting from the sequence and secondary structural information, all-atom models of the protein are built in different conformations by varying loop dihedrals based on a grid search method. The trial structures thus generated are screened to eliminate improbable candidates via a set of biophysical filters (persistence length, radius of gyration, hydrophobicity ratio, and packing fraction) calibrated on 1000 globular proteins. The resulting structures are energy optimized and ranked according to an empirical energy-based scoring function, validated on a wide variety of publicly available as well as our own decoys, comprising 69 protein sequences and 61,955 decoys. Studies on 10 small proteins (consisting of 36 to 68 amino acids) demonstrate that a few candidates within a root mean square deviation of 3 to 5 Å of the native are captured in the 100 lowest energy structures in each case without exception. Thus the formidable ?needle in a hay-stack? problem is narrowed down to finding an optimal solution amongst a smaller number of alternatives. Further refinement and assessment of the candidate structures via all atom explicit solvent molecular simulations and post facto free energy analyses are envisaged to reach the native structure to a better resolution.
Department of Chemistry and Supercomputing Facility for Bioinformatics and Computational Biology