Method for Predicting Homology Modeling Accuracy from Amino AcidSequence Alignment: the Power Function

摘要

We have devised a power function (PF) that can predict the accuracy of a three-dimensional (3D) structuremodel of a protein using only amino acid sequence alignments. This Power Function (PF) consists of three parts;(1) the length of a model, (2) a homology identity percent value and (3) the agreement rate between PSI-PREDsecondary structure prediction and the secondary structure judgment of a reference protein. The PF value ismathematically computed from the execution process of homology search tools, such as FASTA or variousBLAST programs, to obtain the amino acid sequence alignments. There is a high correlation between the globaldistance test-total score (GDT_TS) value of the protein model based upon the PF score and the GDT_TS,A,value used as an index of protein modeling accuracy in the international contest Critical Assessment of Tech-niques for Protein Structure Prediction (CASP). Accordingly, the PF method is valuable for constructing ahighly accurate model without wasteful calculations of homology modeling that is normally performed by an it-erative method to move the main chain and side chains in the modeling process. Moreover, a model with higheraccuracy can be obtained by combining the models ordered by the PF score with models sorted by the size of theCIRCLE score. The CIRCLE software is a 3D-1D program, in which energetic stabilization is estimated basedupon the experimental environment of each amino acid residue in the protein solution or protein crystals.