Literature DB >> 28347746

Matrix metalloproteinases - From the cleavage data to the prediction tools and beyond.

Piotr Cieplak1, Alex Y Strongin2.   

Abstract

Understanding the physiological role of any protease requires identification of both its cleavage substrates and their relative cleavage efficacy as compared with other substrates and other proteinases. Our review manuscript is focused on the cleavage preferences of the individual matrix metalloproteinases (MMPs) and the cleavage similarity and distinction that exist in the human MMP family. The recent in-depth analysis of MMPs by us and many others greatly increased knowledge of the MMP biology and structural-functional relationships among this protease family members. A better knowledge of cleavage preferences of MMPs has led us to the development of the prediction tools that are now capable of the high throughput reliable prediction and ranking the MMP cleavage sites in the peptide sequences in silico. Our software unifies and consolidates volumes of the pre-existing data. Now this prediction-ranking in silico tool is ready to be used by others. The software we developed may facilitate both the identification of the novel proteolytic regulatory pathways and the discovery of the previously uncharacterized substrates of the individual MMPs. Because now the MMP research may be based on the mathematical probability parameters rather than on either random luck or common sense alone, the researchers armed with this novel in silico tool will be better equipped to fine-tune or, at least, to sharply focus their wet chemistry experiments. This article is part of a Special Issue entitled: Matrix Metalloproteinases edited by Rafael Fridman.
Copyright © 2017. Published by Elsevier B.V.

Entities:  

Keywords:  CleavPredict; MMPs; cleavage prediction tools; matrix metalloproteinases; software; substrate cleavage; substrate phage display

Mesh:

Substances:

Year:  2017        PMID: 28347746      PMCID: PMC5831720          DOI: 10.1016/j.bbamcr.2017.03.010

Source DB:  PubMed          Journal:  Biochim Biophys Acta Mol Cell Res        ISSN: 0167-4889            Impact factor:   4.739


  100 in total

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