Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2008 May 15;16(10):5590-605.
doi: 10.1016/j.bmc.2008.04.005. Epub 2008 Apr 6.

Beta-amino acid substitutions and structure-based CoMFA modeling of hepatitis C virus NS3 protease inhibitors

Affiliations

Beta-amino acid substitutions and structure-based CoMFA modeling of hepatitis C virus NS3 protease inhibitors

Johanna Nurbo et al. Bioorg Med Chem. .

Abstract

In an effort to develop a new type of HCV NS3 peptidomimetic inhibitor, a series of tripeptide inhibitors incorporating a mix of alpha- and beta-amino acids has been synthesized. To understand the structural implications of beta-amino acid substitution, the P(1), P(2), and P(3) positions of a potent tripeptide scaffold were scanned and combined with carboxylic acid and acyl sulfonamide C-terminal groups. Inhibition was evaluated and revealed that the structural changes resulted in a loss in potency compared with the alpha-peptide analogues. However, several compounds exhibited muM potency. Inhibition data were compared with modeled ligand-protein binding poses to understand how changes in ligand structure affected inhibition potency. The P(3) position seemed to be the least sensitive position for beta-amino acid substitution. Moreover, the importance of a proper oxyanion hole interaction for good potency was suggested by both inhibition data and molecular modeling. To gain further insight into the structural requirements for potent inhibitors, a three-dimensional quantitative structure-activity relationship (3D-QSAR) model has been constructed using comparative molecular field analysis (CoMFA). The most predictive CoMFA model has q(2)=0.48 and r(pred)(2)=0.68.

PubMed Disclaimer

Publication types

LinkOut - more resources