A structurally biased combinatorial approach for discovering new anti-picornaviral compounds

Background: Picornaviruses comprise a family of small. nonenveloped RNA vir uses. A common feature amongst many picornaviruses is a hydrophobic pocket in the core of VPI, one of the viral capsid proteins. The pocket is normall y occupied by a mixture of unidentified, fatty acid-like moieties, which ca n be competed out by a family of capsid-binding, antiviral compounds. Many members of the Picorncaviridae family are pathogenic to both humans and liv estock. yet no adequate therapeutics exist despite over a decade's worth of research in the field. To address this challenge, we developed a strategy for rapid identification of capsid-binding anti-picornaviral ligands. The a pproach we took involved synthesizing structurally biased combinatorial lib raries that had been targeted to the VPI pocket of poliovirus and rhinoviru s. The libraries are screened for candidate ligands with a high throughput mass spectrometry assay. Results: Using the mass spectrometry assay. we were able to identify eight compounds from a targeted library of 75 compounds. The antiviral activity o f these candidates was assessed by (i) measuring the effect on the: kinetic s of viral uncoating and (ii) the protective effect of each drug in traditi onal cell-based assays. All eight of the candidates exhibited antiviral act ivity, but three of them were particularly effective against poliovirus and rhinovirus. Conclusions: The results illustrate the utility of combining structure-base d design with combinatorial chemistry. The success of our approach suggests that assessment of small, targeted libraries, which query specific chemica l properties, may be the best strategy for surveying all of chemical space for ideal antipicornaviral compounds. (C) 2001 Elsevier Science Ltd. All ri ghts reserved.