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AI小分子药物发现的最新综述登上Nature子刊

康奈尔大学、剑桥大学和洛桑联邦理工学院(EPFL)的研究人员在《Nature Machine Intelligence》发表了一篇题为《Machine learning-aided generative molecule design for drug discovery》的综述文章,该文章被视为AI小分子药物发现的“百科全书”。

文章概述了机器学习在生成式分子设计中的应用,详细探讨了AI如何助力小分子药物发现。分子发现是一个复杂的组合优化问题,搜索空间庞大且崎岖,验证分子属性又十分困难。随着机器学习的高速发展,大量算法被研发出来,包括组合优化、搜索、采样算法和连续优化算法等。

该综述指出,现有较为完备的算法衡量基准和客观公平的比较方式,为开发机器学习算法开拓了广阔的空间。随着AI for Science受到越来越多的关注,AI如何解冔一系列科学问题并且被成功借鉴到其他相近的领域也引起了人们的关注。此次研究提供了一个成功的范例,展现了AI在小分子药物发现领域的巨大潜力。

此次研究的成果对于推动AI在药物发现领域的应用具有里程碑意义,标志着人工智能在解决复杂科学问题方面的能力得到了进一步提升。期待未来有更多的研究能够借鉴此成果,进一步推动AI在科研领域的发展。

英语如下:

News Title: AI Technology Solves the Problem of Discovering Small-molecule Drugs: Cornell et al.’s Review Hits Nature Sub-journal

Keywords: 1. AI and Drug Discovery

News Content:

The latest review on AI small-molecule drug discovery has been published in a Nature sub-journal.

Researchers from Cornell University, Cambridge University, and École Polytechnique Fédérale de Lausanne (EPFL) published a review article titled “Machine learning-aided generative molecule design for drug discovery” in Nature Machine Intelligence, which is regarded as an “encyclopedia” of AI small-molecule drug discovery.

The article outlines the application of machine learning in generative molecule design and delves into how AI facilitates the discovery of small-molecule drugs. Molecular discovery is a complex combination optimization problem, with a vast and rugged search space and difficult validation of molecular properties. With the rapid development of machine learning, numerous algorithms have been developed, including combination optimization, search, sampling algorithms, and continuous optimization algorithms.

The review points out that the existing relatively complete algorithm benchmarking and objective comparison methods have opened up广阔的空间for the development of machine learning algorithms. As AI for Science receives increasing attention, how AI can solve a series of scientific problems and be successfully applied to other related fields has also attracted attention. This research provides a successful example, demonstrating the enormous potential of AI in the field of small-molecule drug discovery.

The achievements of this research are milestone-making in promoting the application of AI in drug discovery, marking a further advancement in artificial intelligence’s ability to solve complex scientific problems. We look forward to more research building on this achievement and further promoting the development of AI in the scientific research field.

【来源】https://www.jiqizhixin.com/articles/2024-06-24-13

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