bioRxiv ScienceSearch

Biology subjects

Chittur, K.

Publications and source records attributed to Chittur, K..

2 recordsLinked to original sources

Improving protein alignment algorithms using amino-acid hydrophobicities - Applications of TMATCH, A new algorithm

MotivationSequence database search and matching algorithms are an important tool when trying to understand the structure (and so the function) of proteins. Proteins with similar structure and function often have very similar primary structure. There are however many cases where proteins with similar structure have very different primary structures. Substitution matrices (PAM, BLOSUM, Gonnett) can be used to identify proteins of similar structure, but they fail when the sequence similarity falls below about 25%. ResultsWe have described a new algorithm for examining the the primary structure of proteins against a database of known proteins with a new hydrophobicity index. In this paper, we examine the ability of TMATCH to identify proteins of similar structure using sequence matching with the hydrophobicity index. We compare results from TMATCH with those obtained using FASTA and PSI-BLAST. We show that by using similarity patterns spread across the entire length of two proteins we get a more robust indicator of remote relatedness than relying upon high similarity scoring pair regions. AvailabilityThe program TMATCH is available on request Contactchitturk@uah.edu

bioinformatics

TMATCH: A New Algorithm for Protein Alignments using amino-acid hydrophobicities

The identification of proteins of similar structure using sequence alignment is an important problem in bioinformatics. We decribe TMATCH, a basic dynamic programming alignment algorithm which can rapidly identify proteins of similar structure from a database. TMATCH was developed to utilize an optimal hydrophobicity metric for alignments traceable to fundamental properties of amino-acids. Standard alignment algorithms use affine gap penalties as contrasted with the TMATCH algorithm adaptation of local alignment score reinforcement of favorable diagonal paths (transitions) and punishment of unfavorable transitions paired with fixed gap opening penalties. The TMATCH algorithm is especially designed to take advantage of the extra information available within the hydrophobicity scale to detect homologies, as opposed to the probabilities derived from raw percent identities.

bioinformatics