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Cheminformatics and Data Mining in Drug Discovery Targeting Bacterial Enoyl-ACP Reductase.

机译：针对细菌Enoyl-ACP还原酶的药物发现中的化学信息学和数据挖掘。

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摘要

The enzymes of the bacterial fatty acid biosynthetic pathway (FAS II), represent attractive targets for antimicrobial drug design, because their mammalian counterpart (FAS I) uses a single, multifunctional enzyme with low sequence and structural similarity. This provides an opportunity to selectively target this essential bacterial pathway without interfering with mammalian enzymes that could result in off-target effects. The enoyl-[acyl-carrier-protein] reductase enzyme, FabI, catalyzes the reduction of a double bond in enoyl-ACP to acyl-ACP as a key step in the bacterial production of fatty acids. The FabI essentiality in the two target bacteria in this dissertation, F. tularensis and S. aureus, has been strongly proven in vivo.;This thesis project is divided into three parts. The first part of the thesis project is to perform computer aided drug design techniques (virtual screening and data mining algorithms) to identify novel scaffolds FabI inhibitors, as highlighted in Chapter 2. In this hit discovery part, three novel FabI inhibitor scaffolds showed FabI enzymatic inhibitory activities. Among these three inhibitors, the initial SAR extension suggests that the benzimidazole scaffold inhibitors have tractable SAR in enzymatic activities and show Gram-positive and --negative anti-bacterial activities. Therefore, the benzimidazole scaffold was selected for further optimization.;The second part is to build structure based computational models (both implicit and explicit solvent methods) to predict FabI benzimidazole inhibitors' activities and to prioritize inhibitors to synthesize, as detailed in Chapter 3 & 4. The last part (Chapter 5) is to use bioinformatics analysis to identify more bacterial pathogens, of which FabI would be their only enoyl acyl reductase, in the hope to expand the inhibitory spectrum and clinical values of the developed FabI inhibitors. In summary, it is anticipated that the above computer aided lead optimization cycle will help generate benzimidazole inhibitors in sub-nM range for FabI enzymatic activities, and single digit or lower MICs (microg/mL) against the tested Gram-positive and --negative bacteria. Promising benzimidazole inhibitors will be selected for animal challenge and pharmacokinetic tests. We believe that FabI inhibitors will be developed into a FDA-approved antibiotic, and ease the biodefense and public health threats that our society is facing.
机译：细菌脂肪酸生物合成途径的酶（FAS II）代表了抗微生物药物设计的诱人靶标，因为它们的哺乳动物对应物（FAS I）使用具有低序列和结构相似性的单一多功能酶。这提供了选择性靶向这一基本细菌途径的机会，而不会干扰可能导致脱靶效应的哺乳动物酶。烯酰基-[酰基-载体-蛋白质]还原酶FabI催化将烯酰基-ACP中的双键还原为酰基-ACP，这是细菌细菌生产脂肪酸的关键步骤。本文已经在体内证明了两种靶细菌Fab。tularensis和金黄色葡萄球菌的FabI必需性。本论文分为三个部分。论文项目的第一部分是执行计算机辅助药物设计技术（虚拟筛选和数据挖掘算法）以识别新型支架FabI抑制剂，如第2章所述。在这一热门发现部分，三个新型FabI抑制剂支架显示了FabI酶促抑制活性。在这三种抑制剂中，最初的SAR扩展表明，苯并咪唑支架抑制剂在酶促活性方面具有可控的SAR，并显示出革兰氏阳性和阴性细菌的活性。因此，选择了苯并咪唑支架进行进一步优化。第二部分是建立基于结构的计算模型（隐式和显式溶剂方法），以预测FabI苯并咪唑抑制剂的活性，并优先考虑抑制剂的合成，如第3章和4.最后一部分（第5章）将使用生物信息学分析来鉴定更多细菌病原体，其中FabI将是它们唯一的烯酰基酰基还原酶，以期扩大已开发FabI抑制剂的抑制谱和临床价值。总而言之，预计上述计算机辅助的铅优化周期将有助于产生亚nM范围内的苯并咪唑抑制剂，从而实现FabI酶促活性，以及​​针对测试的革兰氏阳性和-阴性的一位数或更低的MIC（微克/毫升）菌。将选择有前景的苯并咪唑抑制剂进行动物攻击和药代动力学测试。我们相信，FabI抑制剂将被开发成FDA批准的抗生素，并缓解我们社会面临的生物防御和公共健康威胁。

著录项

  • 作者

    Su, Pin-Chih.;

  • 作者单位

    University of Illinois at Chicago.;

  • 授予单位 University of Illinois at Chicago.;
  • 学科 Chemistry.;Physical chemistry.;Bioinformatics.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 242 p.
  • 总页数 242
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 遥感技术;
  • 关键词

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