在基于蛋白质结构的分子生成模型中应用人工智能的进展
Chengcheng Xu1, Lidan Zheng1, Qing Fan1
1Laboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, 211198, China.
European journal of medicinal chemistry
|August 4, 2024
概括
这项研究审查了人工智能 (AI) 分子生成模型,使用蛋白质结构用于药物发现. 它对模型进行了分类,详细介绍了它们的设计,并讨论了人工智能驱动的领域未来的机遇和挑战.
科学领域:
- 计算化学和生物信息学
- 人工智能在药物发现中的作用
背景情况:
- 分子生成模型正在推动药物发现.
- 基于蛋白质结构的方法是新的研究方向.
研究的目的:
- 总结基于蛋白质结构的分子生成模型的研究方法和发展情况.
- 为未来的模型开发提供一个框架.
主要方法:
- 基于蛋白质结构的分子生成模型的分类.
- 对建筑框架的分析.
- 模型设计和实施的详细示例.
主要成果:
- 各种基于蛋白质结构的分子生成模型的概述.
- 确定关键的架构组件.
- 讨论实际应用和设计方面的考虑.
结论:
- 基于蛋白质结构的分子生成是一种有前途的AI驱动的药物发现方法.
- 需要进一步的研究来应对当前的挑战,并释放充分的潜力.
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