编码DNA图书馆数据解释的挑战和前景
Moreno Wichert1, Laura Guasch1, Raphael M Franzini2,3
1Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070 Basel, Switzerland.
Chemical reviews
|November 7, 2024
概括
DNA编码图书馆 (DEL) 技术通过选庞大的分子图书馆来加速药物发现. 本综述阐明了影响DEL数据质量和计算集成的因素,以改善匹配识别.
科学领域:
- 药物发现 药物发现 药物发现
- 药用化学 医学化学
- 计算化学的计算化学
背景情况:
- 用DNA编码的图书馆 (DEL) 技术可以快速选大量的化学图书馆,用于药物发现.
- 了解影响DEL数据的技术因素对于计算药物发现至关重要.
- 目前的DEL数据解释在将序列计数与绑定亲属关系和对文物进行核算方面面临挑战.
研究的目的:
- 系统地审查影响DEL数据中化学信息的关键参数.
- 检查这些参数对命中分类和机器学习集成的影响.
- 提供关于DEL数据分析和计算工具集成最佳实践的指导.
主要方法:
- 对DNA编码图书馆技术的文献进行系统审查.
- 分析影响DEL数据生成和解释的因素.
- 在DEL数据处理中讨论机器学习应用.
主要成果:
- 确定了影响DEL数据的关键参数,包括库组成,DNA损伤和实验文物.
- 在关联序列计数与绑定亲和关系以及解决频繁撞击者的突出挑战.
- 展示了使用机器学习来否定DEL数据和预测候选药物的进展.
结论:
- 标准化方法和严格的数据处理对于成功的基于DEL的药物发现至关重要.
- 整合强大的方法,全面的分析和计算工具可以提高 DEL 的准确性和有效性.
- 解决技术因素和文物对于可靠的DEL数据解释和命中发现至关重要.
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