Scientists at MIT have used AI for developing a new antibiotic element that can destroy some antibiotic-resistant species of viruses. The team has developed a computer prototype, including millions of chemical composites. Even more, they have used a computer program or machine learning algorithm to select effective antibiotics. After that, the researches have chosen a specific compound for the experiment. Eventually, the compound has revealed effectiveness against E. coli and other viruses in mouse prototypes. Most of the time, researchers use the same methodology and form a blend of already existing drugs to develop new antibiotics. But newly-found antibiotic utilizes a different method than existing medications. It also means that the latest drug can cure the infections that present-day medicines cannot.
The particle, halicin, has formerly been a compound for curing many strong microbes, including TB. Even more, previously, researchers have tested the molecule for treating diabetes. But this time, it is on the mission to destroy superbugs or the bacteria having antibiotic resistance. The finding arrives at the time when antibiotics are becoming progressively complex to determine and rising concerns over drug-resistant viruses. Dr. James Collins from MIT is a co-author of the AI research. As per Collins, the platform will very straight lessen the price required for the discovery stage of antibiotic expansion. Collins added with these prototypes; one can gain after new chemistries in a short time, including less investment.
The novel approach of drug advancement can make recognizing various elements to which viruses become resistant earlier. The prototype has found one individual molecule as a probable target. After testing it in the laboratory, the researchers have found the compound could also destroy other superbugs like Acinetobacter baumannii, Clostridium difficile, and Mycobacterium tuberculosis. The team has experimented with halicin in mouse models. Further, scientists aim to utilize the prototype for enhancing modern medications as well as innovating new drugs. Apart from this, AI has recognized 23 other antibiotic compounds. Notably, eight of the candidates have revealed antibacterial activity in clinical trials. The team also aims to test those compounds in the future.