A test for prorelaxin-processing enzymes using unmodified peptide substrates

1995 ◽  
Vol 2 (2) ◽  
pp. 83-92 ◽  
Author(s):  
Selena S. Layden ◽  
Geoffrey W. Tregear
Keyword(s):  
Peptide Substrates ◽  
Unmodified Peptide ◽  
Processing Enzymes

scholarly journals Human and rat testis express two mRNA species encoding variants of NRD convertase, a metalloendopeptidase of the insulinase family

1997 ◽  
Vol 327 (3) ◽  
pp. 773-779 ◽  
Author(s):  
Véronique HOSPITAL ◽  
Annik PRAT ◽  
Catherine JOULIE ◽  
Dorra CHÉRIF ◽  
Robert DAY ◽  
...  
Keyword(s):  
Significant Degree ◽  
Human Testis ◽  
Mrna Levels ◽  
Gene Encoding ◽  
Peptide Substrates ◽  
Rat Testis ◽  
Processing Enzymes ◽  
Nucleotide Insertion ◽  
Testis Cdna

Rat testis NRD convertase (EC 3.4.24.61) is a Zn2+-dependent endopeptidase that cleaves, in vitro, peptide substrates at the N-terminus of Arg residues in dibasic sites. This putative processing enzyme of the insulinase family of metallopeptidases exhibits a significant degree of similarity to insulinase and two yeast processing enzymes, Axl1 and Ste23. We report the cloning of two human testis cDNA species encoding isoforms of NRD convertase, hNRD1 and hNRD2. Whereas the hNRD1 transcript (3.7 kb) is equivalent to the previously characterized rat cDNA (rNRD1), hNRD2 and rNRD2 are 3.9 kb novel forms containing a nucleotide insertion encoding a 68-residue segment. This motif, which is inserted N-terminal of the Zn2+-binding site, HXXEH, is contained within the most conserved region among the insulinase family members. Analysis of the deduced primary sequences revealed 92% identity between rat and human orthologues. The human gene encoding NRD convertase was localized to chromosome 1p32.1-p32.2. Whereas NRD convertase is mostly expressed in testis and in 24 cell lines, low mRNA levels were detected in most of the 27 other tissues tested.

scholarly journals An automated protocol for modelling peptide substrates to proteases

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Rodrigo Ochoa ◽  
Mikhail Magnitov ◽  
Roman A. Laskowski ◽  
Pilar Cossio ◽  
Janet M. Thornton
Keyword(s):  
Substrate Recognition ◽  
Accessible Surface Area ◽  
Conformational Sampling ◽  
Structural Determinants ◽  
Peptide Substrates ◽  
The Family ◽  
Protease Substrate ◽  
Peptide Complexes ◽  
Accessible Surface ◽  
Automated Protocol

Abstract Background Proteases are key drivers in many biological processes, in part due to their specificity towards their substrates. However, depending on the family and molecular function, they can also display substrate promiscuity which can also be essential. Databases compiling specificity matrices derived from experimental assays have provided valuable insights into protease substrate recognition. Despite this, there are still gaps in our knowledge of the structural determinants. Here, we compile a set of protease crystal structures with bound peptide-like ligands to create a protocol for modelling substrates bound to protease structures, and for studying observables associated to the binding recognition. Results As an application, we modelled a subset of protease–peptide complexes for which experimental cleavage data are available to compare with informational entropies obtained from protease–specificity matrices. The modelled complexes were subjected to conformational sampling using the Backrub method in Rosetta, and multiple observables from the simulations were calculated and compared per peptide position. We found that some of the calculated structural observables, such as the relative accessible surface area and the interaction energy, can help characterize a protease’s substrate recognition, giving insights for the potential prediction of novel substrates by combining additional approaches. Conclusion Overall, our approach provides a repository of protease structures with annotated data, and an open source computational protocol to reproduce the modelling and dynamic analysis of the protease–peptide complexes.

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