MUSTER: Improving protein sequence profile-profile alignments by using multiple sources of structure information.

ABSTRACT: We develop a new threading algorithm MUSTER by extending the previous sequence profile-profile alignment method, PPA. It combines various sequence and structure information into single-body terms which can be conveniently used in dynamic programming search: (1) sequence profiles; (2) secondary structures; (3) structure fragment profiles; (4) solvent accessibility; (5) dihedral torsion angles; (6) hydrophobic scoring matrix. The balance of the weighting parameters is optimized by a grading search based on the average TM-score of 111 training proteins which shows a better performance than using the conventional optimization methods based on the PROSUP database. The algorithm is tested on 500 nonhomologous proteins independent of the training sets. After removing the homologous templates with

SUBMITTER: Wu S 

PROVIDER: S-EPMC2666101 | biostudies-literature | 2008 Aug

REPOSITORIES: biostudies-literature