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类化学信息学工具:在类药物发现中,使计算任务可用
Vanessa Erckes1, Massina Abderrahmane2, Maud Jusot2
1ETH Zurich, Department of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences, Zurich, Sbitzerland.
计算方法加速了复杂疾病的类药物发现. 本综述涵盖了计算方法,工具及其整合到新疗法的发现管道中.
科学领域:
- 生物技术是生物技术.
- 计算化学的计算化学
- 药物发现 药物发现 药物发现
背景情况:
- 对于治疗复杂疾病至关重要.
- 计算方法对于有效的类药物发现至关重要.
- 需要具备计算机和编程方面的专业知识.
研究的目的:
- 审查当前化物研究中的计算方法.
- 为了突出现有的信息学工具.
- 为了促进整合到药物发现管道.
主要方法:
- 计算管道阶段的概述:表示,相似性评估,ML/DL模型和设计.
- 突出信息学工具的关键特征.
主要成果:
- 在酸研究中的计算策略的全面概述.
- 一个精心策划的类信息学工具列表及其特征.
结论:
- 计算工具显著简化了类药物发现.
- 这些工具的有效整合加速了有前途的候选者的识别.
- 本综述有助于研究人员选择和应用用于治疗的计算方法.
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