SeqStruct : A New Amino Acid Similarity Matrix Based on Sequence Correlations and Structural Contacts Yields Sequence-Structure Congruence

Date
2018-02-21
Authors
Jia, Kejue
Jernigan, Robert
Jernigan, Robert
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
Authors
Research Projects
Organizational Units
Journal Issue
Series
Department
Biochemistry, Biophysics and Molecular BiologyBioinformatics and Computational Biology
Abstract

Protein sequence matching does not properly account for some well-known features of protein structures: surface residues being more variable than core residues, the high packing densities in globular proteins, and does not yield good matches of sequences of many proteins known to be close structural relatives. There are now abundant protein sequences and structures to enable major improvements to sequence matching. Here, we utilize structural frameworks to mount the observed correlated sequences to identify the most important correlated parts. The rationale is that protein structures provide the important physical framework for improving sequence matching. Combining the sequence and structure data in this way leads to a simple amino acid substitution matrix that can be readily incorporated into any sequence matching. This enables the incorporation of allosteric information into sequence matching and transforms it effectively from a 1-D to a 3-D procedure. The results from testing in over 3,000 sequence matches demonstrate a 37% gain in sequence similarity and a loss of 26% of the gaps when compared with the use of BLOSUM62. And, importantly there are major gains in the specificity of sequence matching across diverse proteins. Specifically, all known cases where protein structures match but sequences do not match well are resolved.

Comments

This is a preprint made available through bioRxiv: doi: 10.1101/268904.

Description
Keywords
Citation
DOI
Collections