Recent advances in pharmacophore modeling and its application to anti-influenza drug discovery. (April 2013)

• Record Type: Journal Article
• Authors: Shin, Woo-Jin; Seong, Baik Lin
• Is Part Of: Expert opinion on drug discovery. Volume 8:Number 4(2013:Apr.)
• Page Start: 411
• Page End: 426
• Publication Date: 2013-04
• Subjects: 615.1
• DOI: 10.1517/17460441.2013.767795
• Languages: English
• ISSNs: 1746-0441

Abstract

<abstract> <title> <x xml:space="preserve">Abstract</x> </title> <p> <bold> <italic>Introduction:</italic> </bold> The emergence of the highly pathogenic avian influenza (HPAI) H5N1 virus and the recent global circulation of H1N1 swine-origin influenza virus in 2009 have highlighted the need for new anti-influenza therapies. This has been made all the more important with the emergence of antiviral-resistant strains. Recent progress in achieving three-dimensional (3D) crystal structures of influenza viral proteins and efficient tools available for pharmacophore-based virtual screening are aiding us in the discovery and design of new antiviral compounds.</p> <p> <bold> <italic>Areas covered:</italic> </bold> This review discusses pharmacophore modeling as a potential cost-effective and time-saving technology for new drug discovery as an alternative to high-throughput screening. Based on this technical platform, the authors discuss current progress and future prospects for developing novel influenza antivirals against pre-existing or emerging novel targets.</p> <p> <bold> <italic>Expert opinion:</italic> </bold> Although it might be at an infant stage of development, the availability of the 3D crystal structures of influenza viral proteins is expected to accelerate the application of structure-based drug design (SBDD) and pharmacophore modeling. Furthermore, the neuraminidase inhibitor, one of the most successful examples of a SBDD, still receives great attention because of its superb antiviral activities and the resistance of influenza strains to oseltamivir. However, despite much success, pharmacophore-based virtual screening exhibits limited predictive power in hit identification. Further improvements in pharmacophore detection algorithms, proper combinations of <italic>in silico</italic> methods as well as judicious choosing of compounds are expected to improve the hit rate. With the help of these technologies, the discovery of anti-influenza agents will be accelerated.</p> </abstract>