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Idea2Data: Toward a New Paradigm for Drug Discovery.从想法到数据:迈向药物发现的新范式
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Organic synthesis in a modular robotic system driven by a chemical programming language.化学编程语言驱动的模块化机器人系统中的有机合成。
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Automating drug discovery.自动化药物发现。
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D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.D3R 大挑战 2:蛋白质-配体构象、亲和力排序和相对结合自由能的盲预测。
J Comput Aided Mol Des. 2018 Jan;32(1):1-20. doi: 10.1007/s10822-017-0088-4. Epub 2017 Dec 4.
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Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2.在药物设计数据资源重大挑战 2 中诱导契合对接和元动力学中获得的经验教训。
J Comput Aided Mol Des. 2018 Jan;32(1):45-58. doi: 10.1007/s10822-017-0081-y. Epub 2017 Nov 10.
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Integrated Platform for Expedited Synthesis-Purification-Testing of Small Molecule Libraries.小分子文库快速合成-纯化-测试集成平台
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Integration of in silico and in vitro tools for scaffold optimization during drug discovery: predicting P-glycoprotein efflux.在药物发现过程中,通过计算和体外工具的整合来优化支架:预测 P-糖蛋白外排。
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10
Kinase inhibitor data modeling and de novo inhibitor design with fragment approaches.激酶抑制剂数据建模与基于片段方法的全新抑制剂设计
J Med Chem. 2009 Oct 22;52(20):6456-66. doi: 10.1021/jm901147e.

创建一个用于药物化学的虚拟助手。

Creating a Virtual Assistant for Medicinal Chemistry.

作者信息

Vidler Lewis R, Baumgartner Matthew P

机构信息

Research and Development, Eli Lilly and Company Ltd., Sunninghill Road, Windlesham, Surrey GU20 6PH, United Kingdom.

Lilly Biotechnology Center, Eli Lilly and Company, San Diego, California 92121, United States.

出版信息

ACS Med Chem Lett. 2019 Jun 7;10(7):1051-1055. doi: 10.1021/acsmedchemlett.9b00151. eCollection 2019 Jul 11.

DOI:10.1021/acsmedchemlett.9b00151
PMID:31312407
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6627723/
Abstract

The virtual assistant concept is one that many technology companies have taken on despite having other well-developed and popular user interfaces. We wondered whether it would be possible to create an effective virtual assistant for a medicinal chemistry organization, the key being delivering the information the user would want to see, directly to them, at the right time. We introduce Kernel, an early prototype virtual assistant created at Lilly, and a number of examples of the scenarios that have been implemented to try to demonstrate the concept. A biochemical assay summary email is described that brings together new results and some basic analysis, delivered within an hour of new data appearing for that assay, and an email delivering new compound design ideas directly to the original submitter of a compound shortly after their compound was tested for the first time. We conclude with a high level description of the first example of a Design-Make-Test-Analyze cycle completed in the absence of any human intellectual input at Lilly. We believe that this concept has much potential in changing the way that computational results and analysis are delivered and consumed within a medicinal chemistry group, and we hope to inspire others to implement their own similar solutions.

摘要

尽管许多科技公司已经拥有其他成熟且受欢迎的用户界面,但它们仍采用了虚拟助手的概念。我们想知道是否有可能为药物化学组织创建一个有效的虚拟助手,关键在于在合适的时间直接向用户提供他们想要查看的信息。我们介绍了Kernel,这是礼来公司创建的一个早期虚拟助手原型,以及一些已实施的场景示例,以试图证明这一概念。描述了一种生化分析总结电子邮件,它在该分析出现新数据后的一小时内汇集新结果和一些基本分析,还有一种电子邮件在化合物首次测试后不久将新的化合物设计思路直接发送给该化合物的原始提交者。我们最后对礼来公司在没有任何人类智力投入的情况下完成的设计 - 制造 - 测试 - 分析循环的第一个示例进行了高层次描述。我们相信这个概念在改变药物化学团队中计算结果和分析的交付与使用方式方面具有很大潜力,并且我们希望激励其他人实施他们自己类似的解决方案。