Ex Scientia: Commercialising Multi-Target Drug Design

Ex Scientia：多靶点药物设计商业化

• 批准号: BB/J010510/1
• 负责人: Andrew Hopkins
• 金额: $ 19.13万
• 依托单位: University of Dundee
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FJ010510%2F1
• 关键词: Ex; Scientia; Commercialising; Multi; Target

The clinical efficacy and safety of a drug is determined by its activity profile across multiple proteins in the proteome. Therefore methods to rationally design drugs a priori against polypharmacology profiles of multiple proteins would have immense value in drug discovery. We have developed and experimentally validated a new approach for the discovery of ligands, by automatically designing compounds by evolution. The design method has been tested with the synthesis of 40 novel compounds and the assaying of 800 ligand-target predictions, of which 75% were confirmed correct. We propose to commercialise the algorithm into an innovative drug discovery platform. In particular we propose to scale the algorithm onto a cloud computing infrastructure to identify a portfolio of multi-target drug design opportunities. In addition we propose to extend the validation data of the algorithm from GPCR to kinase polypharmacology predictions.

药物的临床疗效和安全性取决于其在蛋白质组中跨多个蛋白质的活性谱。因此，根据多种蛋白质的多药理学特征，先验地合理设计药物的方法在药物发现中具有巨大的价值。我们已经开发并实验验证了一种发现配体的新方法，即通过进化自动设计化合物。通过40个新化合物的合成和800个配体-靶标预测的分析，验证了该设计方法的正确性。我们建议将该算法商业化，成为一个创新的药物发现平台。特别是，我们建议将算法扩展到云计算基础设施上，以确定多靶点药物设计机会的组合。此外，我们建议将算法的验证数据从GPCR扩展到激酶多药理学预测。

项目成果

Automated design of ligands to polypharmacological profiles.

• DOI: 10.1038/nature11691
• 发表时间: 2012-12-13
• 期刊: Nature
• 影响因子: 64.8