内容来源：https://www.wired.com/story/wired-health-2026-how-ai-is-powering-drug-discovery-max-jaderberg/

内容总结：

谷歌DeepMind的AlphaFold蛋白预测技术迈入临床验证阶段：AI设计药物即将开展人体试验

英国生物技术公司Isomorphic Labs（谷歌DeepMind旗下独立运营的子公司）近日宣布，其由诺贝尔奖获奖AI技术AlphaFold设计的药物即将进入人体临床试验阶段。该公司总裁马克斯·贾德伯格在4月16日于伦敦举行的《WIRED Health》大会上表示：“我们正积极筹备进入临床阶段，这将是一个激动人心的时刻，届时我们将验证这些分子的实际疗效。”

尽管贾德伯格未透露具体时间表，但这一进程已晚于公司原定计划。去年，首席执行官德米斯·哈萨比斯曾预期AI设计的药物将在2025年底前进入临床试验。

Isomorphic Labs成立于2021年，从Alphabet旗下AI研究子公司谷歌DeepMind剥离而来。其核心技术AlphaFold是一款开创性的AI平台，能够预测蛋白质结构。蛋白质由20种氨基酸构成，其三维折叠形态决定了生理功能。自20世纪70年代以来，研究人员一直试图预测蛋白质结构，但面临海量可能构象的挑战。

2020年，DeepMind的哈萨比斯与约翰·詹珀利用深度学习技术推出AlphaFold 2，取得突破性成果。2021年，公司发布开源版本。2024年，DeepMind与Isomorphic Labs联合发布AlphaFold 3，进一步将预测范围从单一蛋白质扩展至DNA、RNA等分子及其相互作用，哈萨比斯称：“这正是药物发现所需——了解小分子如何与药物结合、结合强度及潜在脱靶效应。”

目前，AlphaFold已能预测已知约2亿种蛋白质结构，全球190个国家超200万人使用该平台。这一突破为哈萨比斯和詹珀赢得了2024年诺贝尔化学奖，诺奖委员会指出，AlphaFold已在抗生素耐药性研究、可分解塑料的酶图像生成等领域实现重要应用。

今年早些时候，Isomorphic Labs推出更强大的专有药物设计引擎IsoDDE，据称其精度是AlphaFold 3的两倍以上。公司已与礼来、诺华等药企达成合作，并自主研发针对肿瘤学和免疫学的“广泛且令人兴奋的新药管线”。贾德伯格强调：“由于我们深入理解分子作用机制，设计的药物效力极强，能大幅降低剂量，从而减少副作用和脱靶效应。”

去年，Isomorphic任命了首席医学官，并在首轮融资中筹集6亿美元以筹备临床试验。公司正在组建临床开发团队，其使命是“攻克所有疾病”。贾德伯格坦言：“这是一个疯狂的使命，但我们认真对待，因为我们相信这是可以实现的。”

中文翻译：

谷歌DeepMind的AlphaFold已经彻底改变了科学家对蛋白质的理解。如今，该平台设计安全有效药物的能力即将经受考验。

谷歌DeepMind旗下英国生物技术衍生公司Isomorphic Labs，很快将开始对其诺贝尔奖获奖AI技术设计的药物进行人体试验。“我们正在准备进入临床阶段，”Isomorphic Labs总裁马克斯·贾德伯格于4月16日在伦敦举行的《连线》健康大会上表示，“进入临床试验并开始观察这些分子的疗效，那将是一个非常激动人心的时刻。”

贾德伯格并未详细说明时间表，但这一进度晚于该公司原计划启动人体研究的时间。去年，首席执行官戴米斯·哈萨比斯曾表示，预计在2025年底前将有AI设计的药物进入临床试验。

Isomorphic Labs成立于2021年，是从Alphabet的AI研究子公司谷歌DeepMind剥离出来的。该公司利用DeepMind的AlphaFold——一个能够预测蛋白质结构的突破性AI平台——进行药物发现。

蛋白质由20种不同的氨基酸构成，是所有生物体不可或缺的组成部分。长链氨基酸相互连接并折叠，形成决定蛋白质功能的3D结构。自20世纪70年代以来，研究人员一直试图预测蛋白质结构，但由于蛋白质链可能形成的形状数量极其庞大，这一过程十分艰巨。

2020年，DeepMind的哈萨比斯和约翰·乔珀展示了AlphaFold 2的惊人成果，该版本采用了深度学习技术，情况由此发生改变。一年后，该公司发布了AlphaFold的开源版本，供所有人使用。

2024年，DeepMind和Isomorphic Labs发布了AlphaFold 3，进一步加深了科学家对蛋白质的理解。它不再局限于单独模拟蛋白质结构，而是能够预测DNA、RNA等其他重要分子及其与蛋白质的相互作用。

“这正是药物发现所需要的：你需要了解一个小分子将如何与药物结合、结合强度如何，以及它还可能结合哪些其他物质，”哈萨比斯当时告诉《连线》杂志。

自发布以来，AlphaFold平台已能够预测研究人员已知的近2亿种蛋白质中几乎所有蛋白质的结构，并被来自190个国家的超过200万人使用。这一突破性成果使哈萨比斯和乔珀获得了2024年诺贝尔化学奖，诺贝尔委员会指出，AlphaFold促成了多项科学应用，包括更好地理解抗生素耐药性，以及创建能够分解塑料的酶图像。

今年早些时候，Isomorphic Labs宣布推出一款更为强大的工具，即其专有的药物设计引擎IsoDDE。在一篇技术论文中，该公司宣称该平台的准确率是AlphaFold 3的两倍以上。

这家初创公司已与礼来和诺华建立合作关系，共同开展AI药物发现，同时也在推进其自身在肿瘤学和免疫学领域“广泛且令人兴奋的新药管线”，贾德伯格说道。

“我们设计的分子令人兴奋之处在于，由于我们对这些分子的作用机制有了更深入的了解，我们可以将它们设计得极其有效，”贾德伯格在《连线》健康大会上对听众表示，“你可以使用更低的剂量，从而减少副作用和脱靶效应。”

去年，Isomorphic任命了一位首席医疗官，并宣布在首轮融资中筹集了6亿美元，为临床试验做好准备。与此同时，该公司一直在组建临床开发团队。其使命是“攻克所有疾病”。

“这是一个疯狂的使命，”贾德伯格说，“但我们确实是认真的。我们一脸严肃地这样说，因为我们相信这是有可能实现的。”

英文来源：

Google DeepMind’s AlphaFold has already revolutionized scientists’ understanding of proteins. Now, the ability of the platform to design safe and effective drugs is about to be put to the test.
Isomorphic Labs, the UK-based biotech spinoff of Google DeepMind, will soon begin human trials of drugs designed by its Nobel Prize–winning AI technology. “We're gearing up to go into the clinic,” Isomorphic Labs president Max Jaderberg said on April 16 at WIRED Health in London. “It's going to be a very exciting moment as we go into clinical trials and start seeing the efficacy of these molecules.”
Jaderberg did not elaborate on the timeline, but it’s later than the company had planned to initiate human studies. Last year, CEO Demis Hassabis said it would have AI-designed drugs in clinical trials by the end of 2025.
Isomorphic Labs was founded in 2021 as a spinoff from Alphabet’s AI research subsidiary, Google DeepMind. The company uses DeepMind’s AlphaFold, a groundbreaking AI platform that predicts protein structures, for drug discovery.
Built from 20 different amino acids, proteins are essential for all living organisms. Long strings of amino acids link together and fold up to make a protein’s three-dimensional structure, which dictates the protein’s function. Researchers had tried to predict protein structures since the 1970s, but this was a painstaking process given the astronomically high number of possible shapes a protein chain can take.
That changed in 2020, when DeepMind’s Hassabis and John Jumper presented stunning results from AlphaFold 2, which uses deep-learning techniques. A year later, the company released an open-source version of AlphaFold available to anyone.
In 2024, DeepMind and Isomorphic Labs released AlphaFold 3, which advanced scientists’ understanding of proteins even further. It moved beyond modeling proteins in isolation to predicting other important molecules, such as DNA and RNA, and their interactions with proteins.
“This is exactly what you need for drug discovery: You need to see how a small molecule is going to bind to a drug, how strongly, and also what else it might bind to,” Hassabis told WIRED at the time.
Since its release, the AlphaFold platform has been able to predict the structure of virtually all the 200 million proteins known to researchers and has been used by more than 2 million people from 190 countries. The breakthrough earned Hassabis and Jumper the Nobel Prize for chemistry in 2024, with the Nobel committee noting that AlphaFold has enabled a number of scientific applications, including a better understanding of antibiotic resistance and the creation of images of enzymes that can decompose plastic.
Earlier this year, Isomorphic Labs announced an even more powerful tool, what it calls IsoDDE, its proprietary drug-design engine. In a technical paper, the company touts that the platform more than doubles the accuracy of AlphaFold 3.
The startup has formed partnerships with Eli Lilly and Novartis to work together on AI drug discovery and is also advancing its own “broad and exciting pipeline of new medicines” in oncology and immunology, Jaderberg said.
“The exciting thing about the molecules that we're designing is because we have so much more of an understanding about how these molecules work, we've engineered them to be very, very potent,” Jaderberg told the audience at WIRED Health. “You can take them at a much lower dose, and they'll have lower side effects, off target effects.”
Last year, Isomorphic appointed a chief medical officer and announced it had raised $600 million in its first funding round to gear up for clinical trials. Meanwhile, the company has been building a clinical development team. Its mission is to “solve all disease.”
“It's a crazy mission,” Jaderberg said. “But we really mean it. We say it with a straight face, because we believe this should be possible.”