Development of a comprehensive, validated pharmacophore hypothesis for anthrax toxin lethal factor (LF) inhibitors using genetic algorithms, Pareto scoring, and structural biology.
Development of a comprehensive, validated pharmacophore hypothesis for anthrax toxin lethal factor (LF) inhibitors using genetic algorithms, Pareto scoring, and structural biology.
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DOI：
10.1021/ci300121p
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发表时间：
2012-07-23
影响因子：
5.6
通讯作者：
Amin EA
中科院分区：
文献类型：
--
作者：
Chiu TL;Amin EA
炭疽是一种由芽孢杆菌引起的急性传染病。炭疽毒素致死因子（LF）是由炭疽杆菌分泌的一种89 kda的锌水解酶，是炭疽毒素致病机制的主要毒素成分，已成为合理和基于结构的药物设计的热门靶点。尽管已有数百种小分子化合物被设计用于靶向炭疽热活性位点，但在基于细胞的试验中，相对较少的抑制剂显示出活性，目前还没有可用于治疗或预防炭疽热的LF抑制剂。本研究提出了一种新的药效团图谱，通过实验验证，旨在快速识别和优先考虑虚拟化合物文库中有前途的LF抑制剂支架。新的假设结合了蛋白质数据库（PDB）中储存的所有五种可用的LF酶抑制剂复合物的结构信息，并且是迄今为止报道的第一个LF药效团图，其中包括代表LF催化结合区所有三个关键亚位相互作用的特征。在对546种已发表的LF生物活性数据存在的化合物进行的广泛验证研究中，该模型对纳米级LF抑制剂表现出很强的选择性，在无偏测试集中成功识别了72.1%的现有纳米级化合物，同时拒绝了100%的弱活性（bbb100µM）化合物。除了作为数据库搜索工具的功能外，这个综合模型还指出了一些关键的设计原则和以前未确定的可能影响化合物效价的配体-受体相互作用。
Anthrax is an acute infectious disease caused by the spore-forming bacterium Bacillus anthracis. The anthrax toxin lethal factor (LF), an 89-kDa zinc hydrolase secreted by the bacilli, is the toxin component chiefly responsible for pathogenesis and has been a popular target for rational and structure-based drug design. Although hundreds of small-molecule compounds have been designed to target the LF active site, relatively few reported inhibitors have exhibited activity in cell-based assays and no LF inhibitor is currently available to treat or prevent anthrax. This study presents a new pharmacophore map assembly, validated by experiment, designed to rapidly identify and prioritize promising LF inhibitor scaffolds from virtual compound libraries. The new hypothesis incorporates structural information from all five available LF enzyme-inhibitor complexes deposited in the Protein Data Bank (PDB) and is the first LF pharmacophore map reported to date that includes features representing interactions involving all three key subsites of the LF catalytic binding region. In a wide-ranging validation study on all 546 compounds for which published LF biological activity data exist, this model displayed strong selectivity toward nanomolar-level LF inhibitors, successfully identifying 72.1% of existing nanomolar-level compounds in an unbiased test set, while rejecting 100% of weakly active (>100 µM) compounds. In addition to its capabilities as a database searching tool, this comprehensive model points to a number of key design principles and previously unidentified ligand-receptor interactions that are likely to influence compound potency.
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影响因子：
5.6
作者：
Chiu TL;Solberg J;Patil S;Geders TW;Zhang X;Rangarajan S;Francis R;Finzel BC;Walters MA;Hook DJ;Amin EA
通讯作者：
Amin EA
影响因子：
4.1
作者：
Bardwell, AJ;Abdollahi, M;Bardwell, L
通讯作者：
Bardwell, L
影响因子：
5.1
作者：
Hanna, M. Leslie;Tarasow, Theodore M.;Perkins, Julie
通讯作者：
Perkins, Julie
影响因子：
2.9
作者：
Gillet, VJ;Willett, P;Green, DVS
通讯作者：
Green, DVS
影响因子：
3.4
作者：
Agrawal, Arpita;Johnson, Sherida L.;Jacobsen, Jennifer A.;Miller, Melissa T.;Chen, Li-Hsing;Pellecchia, Maurizio;Cohen, Seth M.
通讯作者：
Cohen, Seth M.