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通过SymDOCK与对称堆结合的分子进行对接.

Matthew S Smith1,2, Ian S Knight1, Rian C Kormos1,2

  • 1Department of Pharmaceutical Chemistry, University of California, UCSF Genentech Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States.

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概括

研究人员开发了SymDOCK,这是一种新的计算方法,用于发现与蛋白等粉样纤维结合的配体. 这种方法利用分子对称性来预测结合姿势,加速神经退行性疾病的药物发现.

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科学领域:

  • 生物化学 生物化学
  • 计算化学的计算化学
  • 结构生物学 结构生物学

背景情况:

  • 粉样纤维素,特别是蛋白聚合物,与神经退行性疾病有关.
  • 与这些纤维结合的连接物往往表现出对称性和堆叠,主要与彼此相互作用,而不是蛋白质.

研究的目的:

  • 开发一种计算方法,SymDOCK,利用粉样纤维内的配体对称性和堆叠.
  • 提高鉴定病的潜在候选药物的准确性和效率.

主要方法:

  • SymDOCK 应用了对称性运算来产生自我相互作用的联结体堆,评估了固态碰撞和联结体-联结体相互作用.
  • 对接分数由范德瓦尔斯能量增强,使用ANI进行量子力学验证.
  • 该方法被追溯测试在已知的TAU PET标记物上,并被前性测试在MK-6240.

主要成果:

  • 赛姆多克成功地复制了已知的TAU PET标记物的结合姿势.
  • 在实验确定之前,它前性地预测了MK-6240在AD PHF纤维中的结合结构.
  • 该方法证明了在屏幕中的诱上丰富已知的配体,而不会影响速度.

结论:

  • SymDOCK是一种有效的工具,用于识别粉样纤维中的对称堆叠物.
  • 这种方法加速了针对陶蛋白的配体的发现,并有可能在神经退行性疾病的大规模药物查中得到应用.