Cheng Lily S, Amaro Rommie E, Xu Dong, Li Wilfred W, Arzberger Peter W, McCammon J Andrew
National Biomedical Computation Resource, University of California, San Diego, La Jolla, California 92093, USA.
J Med Chem. 2008 Jul 10;51(13):3878-94. doi: 10.1021/jm8001197. Epub 2008 Jun 18.
Avian influenza virus subtype H5N1 is a potential pandemic threat with human-adapted strains resistant to antiviral drugs. Although virtual screening (VS) against a crystal or relaxed receptor structure is an established method to identify potential inhibitors, the more dynamic changes within binding sites are neglected. To accommodate full receptor flexibility, we use AutoDock4 to screen the NCI diversity set against representative receptor ensembles extracted from explicitly solvated molecular dynamics simulations of the neuraminidase system. The top hits are redocked to the entire nonredundant receptor ensemble and rescored using the relaxed complex scheme (RCS). Of the 27 top hits reported, half ranked very poorly if only crystal structures are used. These compounds target the catalytic cavity as well as the newly identified 150- and 430-cavities, which exhibit dynamic properties in electrostatic surface and geometric shape. This ensemble-based VS and RCS approach may offer improvement over existing strategies for structure-based drug discovery.
H5N1亚型禽流感病毒是一种具有对抗病毒药物耐药的人源适应株的潜在大流行威胁。尽管针对晶体或松弛受体结构的虚拟筛选(VS)是一种识别潜在抑制剂的既定方法,但结合位点内更动态的变化被忽略了。为了适应受体的完全灵活性,我们使用AutoDock4针对从神经氨酸酶系统的显式溶剂化分子动力学模拟中提取的代表性受体集合筛选NCI多样性集。将顶级命中物重新对接至整个非冗余受体集合,并使用松弛复合物方案(RCS)重新评分。在报告的27个顶级命中物中,如果仅使用晶体结构,一半的排名会非常低。这些化合物靶向催化腔以及新发现的150腔和430腔,它们在静电表面和几何形状方面表现出动态特性。这种基于集合的VS和RCS方法可能比现有的基于结构的药物发现策略有所改进。