人工智能首次發(fā)現(xiàn)了一種強大的新型抗生素

人工智能首次發(fā)現(xiàn)了一種強大的新型抗生素

Artificial intelligence (AI) has proved to be a useful ally in the battle against antibiotic resistance. A powerful antibiotic that’s even able to kill superbugs has been discovered thanks to a machine-learning algorithm.

人工智能(AI)已被證明是對抗抗生素耐藥性的一個有用的盟友。一種強大的抗生素甚至可以殺死超級細菌，這多虧了一種機器學習算法。

Researchers from MIT used a novel computer algorithm to sift through a vast digital archive of over 100 million chemical compounds and spot those that were able to kill bacteria using different mechanisms from existing drugs.

麻省理工學院的研究人員使用了一種新的計算機算法，篩選了超過1億種化合物的龐大數(shù)字檔案，并找出那些能夠利用不同于現(xiàn)有藥物的機制殺死細菌的化合物。

Reported in the journal Cell, this method highlighted a molecule that appeared to possess some truly remarkable antibiotic properties. The team named the molecule halicin, a hat tip to the sentient AI system “Hal” from Stanley Kubrick’s film 2001: A Space Odyssey.

在《細胞》雜志上報道，這種方法突出了一種分子，它似乎具有一些真正非凡的抗生素特性。研究小組將這種分子命名為halicin，這是對斯坦利·庫布里克的電影《2001太空漫游》中有感知能力的人工智能系統(tǒng)“Hal”的致敬。

When tested in mice, halicin was able to effectively treat tuberculosis and drug-resistant Enterobacteriaceae, the family of bacteria that includes E. coli and Salmonella. It also proved extremely effective against Clostridium difficile, a "stomach bug" that often sweeps through hospitals, and another drug-resistant bacterium that can cause infections of the blood, urinary tract, and lungs.

當在老鼠身上進行試驗時，halicin能夠有效地治療肺結(jié)核和耐藥腸桿菌科，包括大腸桿菌和沙門氏菌。它還被證明對艱難梭狀芽胞桿菌(一種經(jīng)常席卷醫(yī)院的“胃病”)和另一種可導致血液、尿道和肺部感染的耐藥細菌非常有效。

Tom Hale

“Our approach revealed this amazing molecule which is arguably one of the more powerful antibiotics that has been discovered,” James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering, said in a statement.

麻省理工學院醫(yī)學工程與科學研究所(IMES)和生物工程系的Termeer醫(yī)學工程與科學教授詹姆斯·柯林斯在一份聲明中說:“我們的方法揭示了這種神奇的分子，它可能是目前發(fā)現(xiàn)的最強大的抗生素之一。”

Strangest of all, this potent antibiotic is structurally not like any other antibiotic seen before. If it were up to just humans, it’s very likely this antibiotic would not have been discovered at all because it looks so unusual.

最奇怪的是，這種強效抗生素在結(jié)構(gòu)上與以前見過的任何一種抗生素都不一樣。如果只是對人類來說，這種抗生素很可能根本就不會被發(fā)現(xiàn)，因為它看起來太不尋常了。

“This groundbreaking work signifies a paradigm shift in antibiotic discovery and indeed in drug discovery more generally,” added Roy Kishony, a professor of biology and computer science at Technion (the Israel Institute of Technology), who was not involved in the study.

以色列理工學院的生物學和計算機科學教授羅伊·基松尼補充道:“這項開創(chuàng)性的工作標志著抗生素發(fā)現(xiàn)乃至更廣泛意義上的藥物發(fā)現(xiàn)的范式轉(zhuǎn)變。”他沒有參與這項研究。

Following the success of halicin, the team returned to the database and used the AI algorithm to sniff out more potential candidates. Within just three days, it identified 23 candidates that were structurally dissimilar to existing antibiotics and non-toxic to human cells. Later tests proved at least eight of these molecules had antibacterial properties, and two were particularly powerful.

在halicin取得成功后，該團隊回到了數(shù)據(jù)庫，并使用人工智能算法來尋找更多的潛在候選者。在短短三天的時間里，它發(fā)現(xiàn)了23種候選藥物，它們的結(jié)構(gòu)與現(xiàn)有的抗生素不同，而且對人體細胞無毒。后來的試驗證明，這些分子中至少有八種具有抗菌性能，其中兩種特別強大。

All of these candidates could turn out to be invaluable tools for tackling superbugs and antibiotic-resistant infections. Due to the overuse of antibiotics, some potentially dangerous bacteria have evolved drug resistance, making them extremely tricky to treat. The Centers for Disease Control and Prevention currently estimate that at least 2.8 million people get an antibiotic-resistant infection each year in the US and more than 35,000 people die from one. This is a trend that’s not going to stop any time soon as more and more bacteria gain resistance to conventional drugs.

所有這些候選基因都可能成為對付超級細菌和耐抗生素感染的寶貴工具。由于抗生素的過度使用，一些潛在的危險細菌產(chǎn)生了耐藥性，使得治療變得極其棘手。美國疾病控制與預防中心(簡稱cdc)目前估計，美國每年至少有280萬人感染耐抗生素感染，超過3.5萬人因此死亡。隨著越來越多的細菌對傳統(tǒng)藥物產(chǎn)生耐藥性，這一趨勢在任何時候都不會停止。

Thankfully, as this study shows, AI could help researchers expand our current arsenal of antibiotics and keep this problem at bay.

值得慶幸的是，正如這項研究顯示的那樣，人工智能可以幫助研究人員擴大我們現(xiàn)有的抗生素庫，并將這個問題控制在一定范圍內(nèi)。