Method for low resolution prediction of small protein tertiary structure.
A new method for the de novo prediction of protein structures at low resolution has been developed. Starting from a multiple sequence alignment, protein secondary structure is predicted, and only those topological elements with high reliability are selected. Then, the multiple sequence alignment and the secondary structure prediction are combined to predict side chain contacts. Such contact map prediction is carried out in two stages. First, an analysis of correlated mutations is carried out to identify pairs of topological elements of secondary structure which are in contact. Then, inverse folding is used to select compatible fragments in contact, thereby enriching the number and identity of predicted side chain contacts. The final outcome of the procedure is a set of noisy secondary and tertiary restraints. These are used as a restrained potential in a Monte Carlo simulation of simplified protein models driven by statistical potentials. Low energy structures are then searched for by using simulated annealing techniques. Implementation of the restraints is carried out so as to take into account of their low resolution. Using this procedure, it has been possible to predict de novo the structure of three very different protein topologies: an alpha/beta protein, the bovine pancreatic trypsin inhibitor (6pti), an alpha-helical protein, calbindin (3icb), and an all beta- protein, the SH3 domain of spectrin (1shg). In all cases, low resolution folds have been obtained with a root mean square deviation (RMSD) of 4.5-5.5 A with respect to the native structure. Some misfolded topologies appear in the simulations, but it is possible to select the native one on energetic grounds. Thus, it is demonstrated that the methodology is general for all protein motifs. Work is in progress in order to test the methodology on a larger set of protein structures.
Ortiz
A R
AR
Department of Molecular Biology, Scripps Research Institute, La Jolla, CA 92037, USA.
Hu
W P
WP
Kolinski
A
A
Skolnick
J
J
D000595:Amino Acid Sequence; D000818:Animals; D007611:Aprotinin / Q000737:chemistry*; D064026:Calbindins; D002417:Cattle; D003198:Computer Simulation; D019992:Databases as Topic; D008958:Models, Molecular; D008969:Molecular Sequence Data; D009010:Monte Carlo Method; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D064030:S100 Calcium Binding Protein G / Q000737:chemistry*; D016415:Sequence Alignment; D013049:Spectrin / Q000737:chemistry*
D064026:Calbindins; D064030:S100 Calcium Binding Protein G; D013049:Spectrin; D007611:Aprotinin