通过使用三种常规对接软件组合使用修改后的策略,提高了蛋白质与蛋白质相互作用的预测
Sungwoo Choi1, Seung Han Son1, Min Young Kim1
1Department of Life Science and Research Institute for Natural Sciences, Hanyang University, Seoul 04763, Republic of Korea.
International journal of biological macromolecules
|August 26, 2023
概括
我们开发了改进的计算对接方法 (3SD和3SD-RR),以准确预测蛋白质-相互作用 (PPI),即使是具有挑战性的蛋白质结构. 这一进展有助于发现与异常蛋白质-蛋白质相互作用 (PPI) 相关的疾病的药物.
科学领域:
- 计算生物学 计算生物学
- 结构生物信息学 结构生物信息学
- 药物发现 药物发现 药物发现
背景情况:
- 蛋白与蛋白相互作用 (PPI) 对生物功能至关重要,它们的失调与癌症等疾病有关.
- 试验性研究PPI是困难的,因为他们的动态和短暂的性质.
- 预测PPI的现有计算分子对接 (MD) 方法需要进一步改进.
研究的目的:
- 开发一种改进的计算方法来预测蛋白质-相互作用 (PPI).
- 提高MD在处理内在无序区域 (IDR) 的蛋白质时的准确性.
- 为PPI研究和药物开发提供强大的计算解决方案.
主要方法:
- 开发了一种新的三软件对接 (3SD) 方法,将CABS-dock,HPEPDOCK和HADDOCK结合起来,以获得一致的PPI预测质量.
- 引入了一个修改后的策略,3SD-RR (在删除随机卷曲IDR后进行三种软件对接),以改善IDR蛋白质的MD性能.
- 将3SD-RR应用于AlphaFold2预测的蛋白质结构,以通过人工智能生成的模型评估其有效性.
主要成果:
- 在已知的PPI数据集上验证了3SD方法的性能.
- 在晶体 PpI 结构上使用 3SD-RR 证明了增强的 MD 性能,特别是在具有 IDR 的结构上.
- 使用3SD-RR与AlphaFold2预测受体实现了高效和准确的PPI姿势预测,无论IDR或受体结构是否可用.
结论:
- 3SD和3SD-RR方法为计算PPI预测提供了改进的解决方案,解决了该领域的关键挑战.
- 这些增强方法确保了一致的质量,并处理复杂的蛋白质结构,包括具有IDR和AI预测模型的蛋白质结构.
- 开发的方法具有很大的潜力,可以推进针对PPI的药物发现.
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