Binding recognition of substrates in NS2B/NS3 serine protease of Zika virus revealed by molecular dynamics simulations.

Clicks: 331
ID: 13529
2019
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Zika virus (ZIKV) has become a global public health concern. The recent epidemiological data has revealed a possible association of ZIKV infection with more serious complications, particularly for Guillain-Barré syndrome in adults and microcephaly in newborn children. Till now, there is no vaccine or effective drug commercially available to combat with ZIKV infection. An attractive drug target for the ZIKV treatment is the NS2B/NS3 serine protease, which is essential for viral polyprotein processing. Herein, classical molecular dynamics (MD) simulations were performed on the ZIKV NS2B/NS3 serine protease in complex with four peptide substrates to investigate the binding recognition and protein-substrate interactions. The obtained results indicate that the P1 and P2 positions of the substrate play a significant role in binding with the protease enzyme, while the P3 and P4 positions show a minor contribution in binding interaction. Moreover, the binding free energy calculation based on the MM/PBSA method suggests that among the four similar peptide substrates, the peptide Ac-D-RKOR-ACC displays the strongest binding affinity towards the ZIKV protease due to the high energy contribution at the S2 subsite particularly for the NS3 residue D75 with the P2(O) residue of this substrate, which is in line with the experimental data. Thus, the information derived from MD simulations presented here would be useful for the design of potent protease inhibitors.
Reference Key
nutho2019bindingjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Nutho, Bodee;Rungrotmongkol, Thanyada;
Journal journal of molecular graphics & modelling
Year 2019
DOI S1093-3263(19)30262-1
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.