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Three scientists who developed methods to predict the structure of proteins and build new ones have won the Nobel Prize in Chemistry.
三位科学家获得了诺贝尔化学奖，他们开发了预测蛋白质结构并构建新结构的方法。
The winners were American David Baker, a professor at the University of Washington; Briton Demis Hassabis, head of Google’s DeepMind research laboratory in London; and American John Jumper, a top researcher at DeepMind.
获奖者是美国华盛顿大学的教授大卫·贝克；英国的戴米斯·哈萨比斯，他是谷歌在伦敦的DeepMind研究实验室负责人；以及美国的约翰·江珀，他是DeepMind的顶级研究员。
The lab centers on artificial intelligence (AI) methods.
该实验室的核心方法是人工智能(AI)。
Protein is one of the most important substances to life on Earth. Baker succeeded in building new kinds of proteins.
蛋白质是对地球上的生命而言最重要的物质之一。贝克成功地制造出了新种类的蛋白质。
Hassabis and Jumper solved a problem that had existed for 50 years.
哈萨比斯和江珀解决了一个存在了50年的问题。
They were finally able to use AI to predict the structure of proteins.
最终，他们可以使用人工智能来预测蛋白质的结构。
The Nobel Committee for Chemistry said the discoveries “hold enormous potential.”
诺贝尔化学委员会表示，这些发现“具有巨大的潜力”。
For example, committee members said the ability to build new proteins could lead to the discovery of new drugs and vaccines.
例如，委员会成员表示，制造新蛋白质的能力可能会引发新药物和疫苗的发现。
It could also help scientists develop extremely small materials, called nanomaterials, and small sensors.
它还能帮助科学家研发极小的材料，称为纳米材料，以及小型传感器。
Heiner Linke is Chair of the Nobel Committee for Chemistry.
海纳·林克是诺贝尔化学委员会主席。
He said the award honored research that made connections for the first time between amino acid sequences and protein structures.
他说，该奖项是为了表彰首次在氨基酸序列和蛋白质结构之间建立联系的研究。
“That was actually a grand challenge in chemistry, and in particular biochemistry” for many years, Linke said.
林克说，多年来，“这实际上是化学领域的一个巨大挑战，特别是生物化学领域”。
Baker first designed a new protein in 2003. Since then, his research group has produced many different proteins.
贝克在2003年首次设计了一种新的蛋白质。从那时起，他的研究小组已经生产了许多不同的蛋白质。
“It seems that you can almost construct any type of protein now with this technology,” said Professor Johan Aqvist of the Nobel committee.
诺贝尔委员会的约翰·阿克维斯特教授说：“现在看来，你几乎可以用这项技术构建任何类型的蛋白质。”
The committee said Hassabis and Jumper created an AI model called AlphaFold2.
该委员会表示，哈萨比斯和江珀创造了一个名为AlphaFold2的人工智能模型。
It has been able to predict the structure of nearly all 200 million proteins researchers have identified.
它能够预测研究人员确定的几乎所有2亿种蛋白质的结构。
Linke said, “Proteins are the molecules that enable life. Proteins are building blocks that form bones, skin, hair and tissue.”
林克说：“蛋白质是使生命得以存在的分子。蛋白质是构成骨骼、皮肤、头发和组织的积木。
He added, “To understand how life works, we first need to understand the shape of proteins.”
他补充说，“要了解生命是如何运作的，我们首先需要了解蛋白质的形状。”
Linke said that in 2020, Hassabis and Jumper were able to use AI methods to finally “crack the code.”
林克说，在2020年，哈萨比斯和江珀终于能够使用人工智能方法来“破解代码”。
That made it possible to predict the complex structure of “any known protein in nature.”
这使得预测“自然界中任何已知蛋白质”的复杂结构成为可能。
There are many possible uses for the technology.
这项技术有很多可能的用途。
Researchers should be able to use it to better understand how organisms develop resistance to antibiotics.
研究人员能够利用它来更好地了解生物体是如何对抗生素产生抗药性的。
They might also be able to create images of chemical substances called enzymes that can break down plastic.
他们还可能创造出一种名为酶的化学物质的图像，这种物质可以分解塑料。
The committee said Baker had developed “computational tools” that enable scientists to design new proteins with new shapes and functions.
该委员会表示，贝克已经开发出“计算工具”，让科学家能够设计出具有新形状和新功能的新蛋白质。
Baker noted that Hassabis and Jumper’s work in AI had greatly helped his team.
贝克指出，哈萨比斯和江珀在人工智能领域的工作极大地帮助了他的团队。
“The breakthroughs made by Demis and John on protein structure prediction really highlighted to us the power that AI could have,” he said.
他说，“戴米斯和约翰在蛋白质结构预测方面取得的突破真正向我们展示了人工智能的力量。”
“And that led us to apply these AI methods to protein design and that has greatly increased the power and accuracy.”
“这让我们得以把这些人工智能方法应用到蛋白质的设计中，从而大大提高了能力和准确性。”
Baker was asked during a phone call with Nobel officials and reporters if he had a favorite protein.
贝克在与诺贝尔奖官员和记者通电话时被问及他是否有最喜欢的蛋白质。
He said it would be difficult to choose. But he noted that one designed during the pandemic proved to be effective in protecting against the coronavirus.
他说，这很难抉择。但他指出，在大流行期间设计的一种疫苗被证明在预防冠状病毒方面是有效的。
“And I’ve been very excited about the idea of a nasal spray, of little designed proteins, that would protect against all possible pandemic viruses.” Baker said.
“我对鼻腔喷雾剂的想法很感兴趣，这种喷雾剂里的蛋白质很少，可以预防所有可能的大流行病毒。”贝克说。
Hassabis is a leader in Britain’s technology industry.
哈萨比斯是英国科技行业的领先者。
He received a knighthood earlier this year for his work in AI.
今年早些时候，他因在人工智能领域的工作而被授予爵士头衔。
He helped establish DeepMind in 2010. Google later bought the lab.
他在2010年帮助创建了DeepMind。谷歌后来买下了这个实验室。
DeepMind first gained wide attention by developing an AI system that was able to defeat the human world champion in the Chinese game of Go faster than expected.
DeepMind首次获得广泛关注是因为开发了一种人工智能系统，该系统能够以比预期更快的速度击败中国围棋世界冠军。
This year’s Nobel Prize in Chemistry is worth about $1 million. Half of the prize will go to Baker.
今年的诺贝尔化学奖价值约100万美元。奖金的一半将颁给贝克。
Hassabis and Jumper will share the other half.
另一半给哈萨比斯和江珀。
Award ceremonies for the 2024 Nobel Prize winners will be held on December 10.
2024年诺贝尔奖获得者的颁奖典礼将于12月10日举行。
I'm Mario Ritter, Jr.
我是小马里奥 · 里特。
