Reduction of false positives in structure-based virtual screening when receptor plasticity is considered.
Reduction of false positives in structure-based virtual screening when receptor plasticity is considered.
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DOI：
10.3390/molecules20035152
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发表时间：
2015-03-19
期刊：
影响因子：
--
通讯作者：
Mu Y
中科院分区：
文献类型：
--
作者：
Awuni Y;Mu Y
用于选择潜在候选药物的基于结构的虚拟筛选通常受到以下挑战：当考虑受体可塑性时，如何排除分子库中的许多假阳性。在这项研究中，结合能景观理论的基础上，提出了一个假设，一个真正的抑制剂可以结合到不同构象的结合位点有利的，并设计了相关的策略，以克服这一挑战，减少假阳性时，受体的可塑性考虑。研究中的受体是甲型流感核蛋白，其寡聚化是RNA结合的必要条件。通过分子动力学模拟研究了甲型流感病毒核蛋白的结构柔性。所得的独特结构和晶体结构被用作对接练习中的受体模型，其中两个结合位点，尾环结合口袋和RNA结合位点，使用GOLD软件用Otava PrimScreen1多样性分子文库靶向。从所有受体模型中选择在排名最高的分子中列出的交叉配体。这种选择策略成功地区分了添加到分子文库中的高亲和力和低亲和力对照分子。这项工作为减少假阳性和从分子库中选择真正的配体提供了一种适用的方法。
Structure-based virtual screening for selecting potential drug candidates is usually challenged by how numerous false positives in a molecule library are excluded when receptor plasticity is considered. In this study, based on the binding energy landscape theory, a hypothesis that a true inhibitor can bind to different conformations of the binding site favorably was put forth, and related strategies to defeat this challenge were devised; reducing false positives when receptor plasticity is considered. The receptor in the study is the influenza A nucleoprotein, whose oligomerization is a requirement for RNA binding. The structural flexibility of influenza A nucleoprotein was explored by molecular dynamics simulations. The resultant distinctive structures and the crystal structure were used as receptor models in docking exercises in which two binding sites, the tail-loop binding pocket and the RNA binding site, were targeted with the Otava PrimScreen1 diversity-molecule library using the GOLD software. The intersection ligands that were listed in the top-ranked molecules from all receptor models were selected. Such selection strategy successfully distinguished high-affinity and low-affinity control molecules added to the molecule library. This work provides an applicable approach for reducing false positives and selecting true ligands from molecule libraries.
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影响因子：
5.5
作者：
Hess, Berk;Kutzner, Carsten;Lindahl, Erik
通讯作者：
Lindahl, Erik
DOI：
10.1039/c0cp00111b
发表时间：
2010-07-28
期刊：
Physical chemistry chemical physics : PCCP
影响因子：
--
作者：
Dupradeau FY;Pigache A;Zaffran T;Savineau C;Lelong R;Grivel N;Lelong D;Rosanski W;Cieplak P
通讯作者：
Cieplak P
影响因子：
4.4
作者：
JORGENSEN, WL;CHANDRASEKHAR, J;KLEIN, ML
通讯作者：
KLEIN, ML
影响因子：
2.9
作者：
Huang, Sheng-You;Zou, Xiaoqin
通讯作者：
Zou, Xiaoqin
影响因子：
5.8
作者：
Arnold, K;Bordoli, L;Schwede, T
通讯作者：
Schwede, T