New antibiotic using artificial intelligence
Image: MIT

New antibiotic using artificial intelligence

New antibiotic using artificial intelligence- the MIT research is a landmark one in the medicinal world. The ever-increasing field of artificial intelligence has tapped into an important area of research. And as nature, its biological data, and computer algorithms complement each other researchers have well-trained algorithms that help create new antibiotics.

What is antibiotic resistance?

Antibiotic resistance is a grave issue that is increasingly posing threat to humans. It is because of the reckless drug usage pattern that has shot up recently. This has made many bacterial strands non-yielding to drugs. The stronger or more resistant a bacteria grows against a particular drug, it becomes tougher to overcome it. Graver bacterial infections such as pneumonia, tuberculosis, etc. have now gotten even tougher to be treated because of antibacterial resistance. Thus the new antibiotic using artificial intelligence seems promising to deal with stubborn bacteria.

The computer model:

The model that scientists use, is potent enough to conduct screening of over a hundred million compounds only in days. It filters out the most efficient drugs that destroy bacteria using more lethal mechanisms than existing drugs. The researchers like James Collins reveal that this research has brought to light the strongest molecule ever discovered.

New antibiotic using artificial intelligence-The Halicin:

After training the model well with machine learning and neural network, it was tested on an extensive library of around 6000 compounds. And the system selected one compound that had stronger antibacterial properties than the existing compounds. With the help of this model, researchers found that it also had an extremely low toxicity for humans. And called it the Halicin compound. The compound was found to be extremely effective against many lethal and resistant bacteria. Halicin emerged successful in combatting almost all the pathogenic strains including Clostridium difficile, Acinetobacter baumannii, and also Mycobacterium tuberculosis. But Pseudomonas aeruginosa is an exception, which affects the lungs and is still a challenge to deal with.

The real test:

Baumannii is a bacterial strain that is lethal and resistant to all the drugs. The U.S. tested Halicin with mice and found that the compound relinquished its growth in less than 24 hours completely.

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How Halicin kills bacteria:

The compound impedes the bacterium’s functioning and blocks its ability to create the electrochemical gradient. The gradient is an integral ingredient that helps cells to produce energy. Thus, when an infected cell receives no energy, it dies. This mechanism is a winner against all other existing drug mechanisms as it does not allow bacteria to incite drug resistance.

Example of E.coli

When E.coli was treated with the Halicin compound, it failed to develop resistance against the compound even after a long treatment of 30 days. On the other hand, the same bacteria could develop strong resistance against “ciprofloxacin”, which is a drug of an antibiotic family in only 2-3 days of treatment. And not just this, the bacteria emerged nearly 200 times stronger than before. Thus developing new antibiotics using artificial intelligence is proving to be a smarter method.

The other compounds:

The researchers also scrutinized another set of 100 million compounds taken from the ZINC15 database. ZINC15 is an online bevy of similar chemical compounds. Now, there were another 23 potential compound candidates that hold non-toxic properties for humans and also exhibit different properties from existing antibiotic compounds.

The hope for the future:

The dedicated researchers found that 8 out of these 23, have strong antibacterial properties, with 2 being extremely powerful. Foraging the database is being carried away to build stronger antibiotics and test them successfully on humans. They aim to selectively train the existing drugs in a way that they kill only harmful bacteria and steer clear of the good bacteria in the digestive system. This is a strong shift in the complete scenario of the antibiotic world. Here, deep learning is used across all stages in antibiotic development and thus making systems stronger. The research was conducted by a multi-organizational set up funded the research with a special mention of Abdul Latif Jameel Clinic of Machine learning in health funded the research.


New antibiotic using artificial intelligence, machine learning, and deep learning has created waves in the antibiotic world. The compound called Halicin has been tested well for a varied range of bacteria and has also proved to be innocuous to humans. Though awareness and the change in ways of antibiotics should change to deal with antibiotic resistance. But at the same time, stronger antibiotics are needed to curb drug-resistant bacteria such as Baumanni.

Disclaimer: The above article has been aggregated by a computer program and summarised by an Steamdaily specialist. You can read the original article at mit
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