Back to Search
Start Over
Computational analysis of sequential and structural variations in stromelysins as an insight towards matrix metalloproteinase research
- Source :
- Informatics in Medicine Unlocked, Vol 11, Iss , Pp 28-35 (2018)
- Publication Year :
- 2018
- Publisher :
- Elsevier, 2018.
-
Abstract
- Matrix metalloproteinases are zinc-dependent protein and peptide hydrolases. They are broadly involved in metabolic regulation through both extensive protein degradation and selective peptide-bond hydrolysis. Stromelysins belong to this group of proteinases and involved in various physiological and pathological functioning of the cell. This study aims at assessing the sequential and structural aspects of stromelysins based on in silico approaches. Deduced stromelysin sequences were predicted to possess regulatory domain, protease domain, and proline-rich hinge regions. Sequential analysis revealed MMP-3 and 10 are more similar than MMP-11 regarding stability and aminoacid distribution. Secondary structure prediction showed that beta-sheets dominated other secondary structural elements (alpha helices, coils, and turns) in stromelysins. Validation of predicted models with different approaches confirms the accuracy and best quality of models. The binding mode of zinc atom provides information regarding their interaction with stromelysins. The predicted models showed little variation in binding mode with their natural inhibitor, TIMP-1. The predicted models will be used in an extensive range of studies for functional analysis and improvement activity of stromelysins. Keywords: Matrix metalloproteinases, Zinc-binding motif, Structure prediction, Ramachandran plot, Stromelysin, Superfamily
- Subjects :
- Computer applications to medicine. Medical informatics
R858-859.7
Subjects
Details
- Language :
- English
- ISSN :
- 23529148
- Volume :
- 11
- Issue :
- 28-35
- Database :
- Directory of Open Access Journals
- Journal :
- Informatics in Medicine Unlocked
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.09ea769575484797b3619f3cf3fbc9e0
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.imu.2017.12.003