Prediction of protein tertiary structure using PROFESY, a novel method based on fragment assembly and conformational space annealing.
A novel method for ab initio prediction of protein tertiary structures, PROFESY (PROFile Enumerating SYstem), is proposed. This method utilizes the secondary structure prediction information of a query sequence and the fragment assembly procedure based on global optimization. Fifteen-residue-long fragment libraries are constructed using the secondary structure prediction method PREDICT, and fragments in these libraries are assembled to generate full-length chains of a query protein. Tertiary structures of 50 to 100 conformations are obtained by minimizing an energy function for proteins, using the conformational space annealing method that enables one to sample diverse low-lying local minima of the energy. We apply PROFESY for benchmark tests to proteins with known structures to demonstrate its feasibility. In addition, we participated in CASP5 and applied PROFESY to four new-fold targets for blind prediction. The results are quite promising, despite the fact that PROFESY was in its early stages of development. In particular, PROFESY successfully provided us the best model-one structure for the target T0161.
Lee
Julian
J
School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea.
Kim
Seung-Yeon
SY
Joo
Keehyoung
K
Kim
Ilsoo
I
Lee
Jooyoung
J
D020169:Caspases / Q000737:chemistry / Q000378:metabolism; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D003546:Cysteine Endopeptidases / Q000737:chemistry / Q000378:metabolism; D010446:Peptide Fragments / Q000737:chemistry*; D010455:Peptides / Q000378:metabolism; D011237:Predictive Value of Tests; D011485:Protein Binding; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D012984:Software; D013816:Thermodynamics
D010446:Peptide Fragments; D010455:Peptides; C099217:CASP5 protein, human; D020169:Caspases; D003546:Cysteine Endopeptidases