Literature DB >> 33505952

Application of In Silico and HTS Approaches to Identify Nuclear Import Inhibitors for Venezuelan Equine Encephalitis Virus Capsid Protein: A Case Study.

Sharon Shechter1,2, David R Thomas3, David A Jans3.   

Abstract

The development of new drugs is costly and time-consuming, with estimates of over $US1 billion and 15 years for a product to reach the market. As understanding of the molecular basis of disease improves, various approaches have been used to target specific molecular interactions in the search for effective drugs. These include high-throughput screening (HTS) for novel drug identification and computer-aided drug design (CADD) to assess the properties of putative drugs before experimental work begins. We have applied conventional HTS and CADD approaches to the problem of identifying antiviral compounds to limit infection by Venezuelan equine encephalitis virus (VEEV). Nuclear targeting of the VEEV capsid (CP) protein through interaction with the host nuclear import machinery has been shown to be essential for viral pathogenicity, with viruses incapable of this interaction being greatly attenuated. Our previous conventional HTS and in silico structure-based drug design (SBDD) screens were successful in identifying novel inhibitors of CP interaction with the host nuclear import machinery, thus providing a unique opportunity to assess the relative value of the two screening approaches directly. This focused review compares and contrasts the two screening approaches, together with the properties of the inhibitors identified, as a case study for parallel use of the two approaches to identify antivirals. The utility of SBDD screens, especially when used in parallel with traditional HTS, in identifying agents of interest to target the host-pathogen interface is highlighted.
Copyright © 2020 Shechter, Thomas and Jans.

Entities:  

Keywords:  Venezuelan equine encephalitis virus (VEEV); antiviral agents; computational modeling; highthroughput screening; in silico screening

Year:  2020        PMID: 33505952      PMCID: PMC7832173          DOI: 10.3389/fchem.2020.573121

Source DB:  PubMed          Journal:  Front Chem        ISSN: 2296-2646            Impact factor:   5.221


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