A robot scientist for drug design and chemical genetics

药物设计和化学遗传学机器人科学家

• 批准号: BB/F008228/1
• 负责人: Ross King
• 金额: $ 131.19万
• 依托单位: Aberystwyth University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FF008228%2F1
• 关键词: robot; scientist; drug; design; chemical

In Aberystwyth we are developing the world's first 'Robot Scientists'. These are robotic system that can fully automate simple forms of scientific reasoning and experiment. Given a problem they can automatically execute cycles of: hypothesis formation, generation of experiments to discriminate between hypotheses, execution of these experiments using laboratory robotics, and analysis of results. We have previously demonstrated the proof-of-concept of this idea, and built the Robot Scientist 'Adam' which can automate growth experiments in bakers/brewers yeast (S. cerevisiae). This organism is used a 'model' for more complicated biological cells, such as our own. We have been given £540,000 from the University of Wales, Aberystwyth, to develop a Robot Scientists for chemical genomics and drug design - Eve. This money will only pay for the hardware and software for Eve. In this application we are requesting the salary and running costs necessary to demonstrate that chemical genomics and drug design can be successfully automated. Drug design is an ideal candidate for increased automation: automation is already far advanced, with large (relatively stupid) robotic systems widely deployed, and drug design experiments are arguably the most important type of experiment done in the UK / both medical and economically. The core of Eve will be a robotic assay platform that will allow the automated testing of thousands of compounds from a library using automated plate readers and microscopy. Eve will be linked to Adam to enable different types of mutant yeast cells to be tested. The AI brain of Eve will analyse the results of experiments, then design new experiments by choosing new chemical compounds from the library and requesting new yeast strains from Adam. This will result in the automatic accumulation of knowledge. We will look at two specific systems in yeast: pheromone/glucose detection, and the MAPK pathway. These are both intrinsic biological interest, and have significant links to human medicine. We will also make human/yeast chimeric systems that will allow us to test drugs that will work on humans.

在阿伯里斯特威斯，我们正在开发世界上第一个“机器人科学家”。这些机器人系统可以完全自动化简单形式的科学推理和实验。给定一个问题，它们可以自动执行以下循环：假设形成，生成实验以区分假设，使用实验室机器人执行这些实验，以及分析结果。我们之前已经证明了这一想法的概念验证，并建立了机器人科学家'亚当'，它可以自动化面包师/啤酒酵母的生长实验（S。cerevisiae）。这种生物体被用作更复杂的生物细胞的“模型”，比如我们自己的细胞。我们已经从威尔士大学阿伯里斯特威斯获得了54万英镑，用于开发一个用于化学基因组学和药物设计的机器人科学家-夏娃。这笔钱只会支付夏娃的硬件和软件。在这个应用程序中，我们要求的工资和必要的运行成本，以证明化学基因组学和药物设计可以成功地自动化。药物设计是增加自动化的理想候选者：自动化已经非常先进，大型（相对愚蠢）机器人系统广泛部署，药物设计实验可以说是英国最重要的实验类型/医学和经济学。Eve的核心将是一个机器人检测平台，可以使用自动化酶标仪和显微镜对库中的数千种化合物进行自动检测。夏娃将与亚当相连，使不同类型的突变酵母细胞得到测试。夏娃的人工智能大脑将分析实验结果，然后通过从库中选择新的化合物并向亚当请求新的酵母菌株来设计新的实验。这将导致知识的自动积累。我们将研究酵母中的两个特定系统：信息素/葡萄糖检测和MAPK途径。这些都是内在的生物学兴趣，并与人类医学有着重要的联系。我们还将制造人类/酵母嵌合系统，使我们能够测试对人类有效的药物。

项目成果

Plasmodium dihydrofolate reductase is a second enzyme target for the antimalarial action of triclosan.

二氢叶酸还原酶是三氯生的抗疟疾作用的第二个酶靶标。

• DOI: 10.1038/s41598-018-19549-x
• 发表时间: 2018-01-18
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Bilsland E;van Vliet L;Williams K;Feltham J;Carrasco MP;Fotoran WL;Cubillos EFG;Wunderlich G;Grøtli M;Hollfelder F;Jackson V;King RD;Oliver SG
• 通讯作者: Oliver SG

A Tool for Multiple Targeted Genome Deletions that Is Precise, Scar-Free, and Suitable for Automation.

• DOI: 10.1371/journal.pone.0142494
• 发表时间: 2015
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Aubrey W;Riley MC;Young M;King RD;Oliver SG;Clare A
• 通讯作者: Clare A

Additional file 1: of Antiplasmodial and trypanocidal activity of violacein and deoxyviolacein produced from synthetic operons

附加文件 1：由合成操纵子产生的紫罗兰素和脱氧紫罗兰素的抗疟原虫和杀锥虫活性

• DOI: 10.6084/m9.figshare.6131954
• 发表时间: 2018
• 作者: Bilsland E

Functional expression of parasite drug targets and their human orthologs in yeast.

• DOI: 10.1371/journal.pntd.0001320
• 发表时间: 2011-10
• 期刊: PLoS neglected tropical diseases
• 影响因子: 3.8
• 作者: Bilsland E;Pir P;Gutteridge A;Johns A;King RD;Oliver SG
• 通讯作者: Oliver SG

Yeast-based automated high-throughput screens to identify anti-parasitic lead compounds.

• DOI: 10.1098/rsob.120158
• 发表时间: 2013-02-27
• 期刊: Open biology
• 影响因子: 5.8
• 作者: Bilsland E;Sparkes A;Williams K;Moss HJ;de Clare M;Pir P;Rowland J;Aubrey W;Pateman R;Young M;Carrington M;King RD;Oliver SG
• 通讯作者: Oliver SG