β-Amino acid substitutions and structure-based CoMFA modeling of hepatitis C virus NS3 protease inhibitors

Nurbo, Johanna (author): Uppsala universitet,Avdelningen för organisk farmaceutisk kemi

Peterson, Shane D. (author): Uppsala universitet,Avdelningen för organisk farmaceutisk kemi

Dahl, Göran (author): Uppsala universitet,Institutionen för biokemi och organisk kemi

Danielson, U. Helena (author): Uppsala universitet,Institutionen för biokemi och organisk kemi

Karlén, Anders (author): Uppsala universitet,Avdelningen för organisk farmaceutisk kemi

Sandström, Anja (author): Uppsala universitet,Avdelningen för organisk farmaceutisk kemi

(creator_code:org_t)

Elsevier BV, 2008
2008
English.
In: Bioorganic & Medicinal Chemistry. - : Elsevier BV. - 0968-0896 .- 1464-3391. ; 16:10, s. 5590-5605

Related links:: https://urn.kb.se/re...; show more...; https://doi.org/10.1...; show less...

Abstract Subject headings

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.

By the author/editor: Nurbo, Johanna; Peterson, Shane ...; Dahl, Göran; Danielson, U. He ...; Karlén, Anders; Sandström, Anja

About the subject

MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Basic Medicine; and Pharmaceutical S ...

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