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MAMMOTH Introduction

MAMMOTH stands for MAtching Molecular Models Obtained from THeory. This program was originally developed for comparing models produced from structure prediction since it is tolerant of large unalignable regions. However, it has proven to work well with experimental models, especially when looking for remote homology. Benchmarks on targets of blind structure prediction and automated GO annotation have shown it to tightly rank correlated with human curated annotation. A largely complete database of MAMMOTH based structure annotation for the predicted structures of unknown proteins covering 150 genomes facilitates genomic scale normalization.

MAMMOTH Method

MAMMOTH based structure alignment methods decompose the protein structure into short peptides (heptapeptides for example) which are compared with the same length peptides of another protein. Similarity scores between the two polypeptides is then calculated using a unit-vector RMS (URMS) method. These cores are stored in a similarity matrix, and with a hybrid (local-global) dynamic programming, the optimal residue alignment is calculated. Protein similarity scores calculated with MAMMOTH are derived from the likelihood of obtaining a given structural alignment by chance.

MAMMOTH-mult

MAMMOTH-mult is an extension of the MAMMOTH algorithm used to align related families of protein structures. This algorithm is very quick and produces consistent high quality structural alignments. Multiple structural alignments calculated with MAMMOTH-mult produce structurally implied sequence alignments that can be further used for multiple-template homology modeling, HMM-based (Hidden Markov model) protein structure prediction, and profile-type PSI-BLAST searches.

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In diesen PublikationenStructural Biochemistry

SprachenEnglish

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