SVIMS Bioinformatics Centre, Department of Bioinformatics, SVIMS University, Tirupati, 517507, AP, India.
Interdiscip Sci. 2011 Mar;3(1):64-77. doi: 10.1007/s12539-011-0064-y. Epub 2011 Mar 3.
Yellow fever is among one of the most lethal viral diseases for which approved antiviral therapies were yet to be discovered. Herein, functional assignment of complete YFV proteome was done through support vector machine. Major envelope (E) protein that mediates entry of YFV into host cell was selected as a potent molecular target. Three dimensional structure of the molecular target was predicted using Modeller9v7. The model was optimized in Maestro9.0 applying OPLS AA force field and was evaluated using PROCHECK, ProSA, ProQ and Profile 3D. The BOG pocket residues Val48, Glu197, Thr200, Ile204, Thr265, Thr268 and Gly278 were located in YFV E protein using SiteMap2.3. More than one million compounds of Ligandinfo Meta database were explored using a computational virtual screening protocol targeting BOG pocket of the E protein. Finally, ten top ranked lead molecules with strong binding affinity to BOG pocket of YFV E protein were identified based on XP Gscore. Drug likeliness and comparative bioactivity analysis for these leads using QikProp3.2 had shown that these molecules would have the potential to act as better drug. Thus, the 10 lead molecules suggested in the present study would be of interest as promising starting point for designing antiviral compound against yellow fever.
黄热病是最致命的病毒性疾病之一，目前尚未发现有效的抗病毒治疗方法。在此，通过支持向量机对 YFV 全基因组的功能进行了分配。介导 YFV 进入宿主细胞的主要包膜 (E) 蛋白被选为有效的分子靶标。使用 Modeller9v7 预测了分子靶标的三维结构。在 Maestro9.0 中应用 OPLS AA 力场对模型进行了优化，并使用 PROCHECK、ProSA、ProQ 和 Profile 3D 进行了评估。使用 SiteMap2.3 在 YFV E 蛋白中定位了 BOG 口袋残基 Val48、Glu197、Thr200、Ile204、Thr265、Thr268 和 Gly278。使用针对 E 蛋白 BOG 口袋的计算虚拟筛选方案，探索了 Ligandinfo Meta 数据库中的超过一百万种化合物。最后，根据 XP Gscore 从 YFV E 蛋白的 BOG 口袋中确定了十个具有强结合亲和力的排名前十的先导分子。使用 QikProp3.2 对这些先导物进行药物相似性和比较生物活性分析表明，这些分子有可能成为更好的药物。因此，本研究中提出的 10 个先导分子将作为设计抗黄热病抗病毒化合物的有前途的起点引起关注。
