College of Life Science and Biotechnology, Department of Biotechnology, Seoul 120-749, South Korea.
Expert Opin Drug Discov. 2013 Apr;8(4):411-26. doi: 10.1517/17460441.2013.767795. Epub 2013 Feb 4.
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.
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.
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 in silico 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.
高致病性禽流感(HPAI)H5N1 病毒的出现以及 2009 年全球范围内流通的 H1N1 猪源流感病毒,凸显了开发新的抗流感疗法的必要性。随着抗病毒耐药株的出现,这一点变得尤为重要。近年来,实现流感病毒蛋白三维(3D)晶体结构和基于药效团的虚拟筛选等高效工具的进展,正在帮助我们发现和设计新的抗病毒化合物。
本文讨论了药效团模型作为一种有潜力的具有成本效益和节省时间的新药发现技术,可替代高通量筛选。基于这一技术平台,作者讨论了针对现有或新兴新型靶标开发新型流感抗病毒药物的当前进展和未来前景。
尽管它可能处于发展的婴儿期,但流感病毒蛋白的 3D 晶体结构的可用性有望加速基于结构的药物设计(SBDD)和药效团模型的应用。此外,神经氨酸酶抑制剂是 SBDD 最成功的例子之一,由于其出色的抗病毒活性和流感株对奥司他韦的耐药性,仍然受到广泛关注。然而,尽管取得了很大的成功,但基于药效团的虚拟筛选在命中鉴定方面的预测能力有限。改进药效团检测算法、适当结合计算方法以及明智地选择化合物,有望提高命中率。在这些技术的帮助下,抗流感药物的发现将得到加速。