Contents
Introduction
Antibiotics are key in treatment of bacterial infections that can even be fatal (eg, sepsis). However, overuse and misuse of antibiotics has led to antibiotic resistance. It can lead to a dangerous condition where no antibiotics work against the deadly microbes. By 2050, drug resistant infections can lead to around 10 million annual deaths. This led to the necessity of discovering novel agents for treatment against such deadly organisms. Fortunately, technologies like Machine learning (ML) provides faster discovery of antibiotics that specifically targets such resistant microbes. Acinetobacter baumannii (a deadly multidrug resistant species (MDRAB)) causes infections in critically ill ICU patients with resistance to even last resort antibiotics (eg, carbapenems). Abaucin is an AI developed antibiotic that shows a potential in treating deadly Acinetobacter baumannii infections. This article discusses AI driven discovery of Abaucin: a narrow spectrum antibiotic.
Machine Learning in Drug Discovery: Abaucin
Machine learning and AI are used for advancements in scientific fields. ML and AI algorithms are used in developing drug leads with precision, quality, and efficacy. The drug developed binds to target to produce therapeutic effects with minimal side effects. Data Mining and Predictive Models with incorporation of big data helps to detect drug targets, and to predict ideal drug candidates for the target. Furthermore, Virtual screening and online information are also used in drug lead synthesis.
In the Abaucin Identification Process, researchers trained an ML model to identify the molecular structure of chemical compounds that inhibit bacterial (MDRAB) growth. They discovered Abaucin, also known as RS102895, by initially exposing the superbug to 7,500 chemical compounds. From these, they evaluated 6,680 unknown chemical compounds and generated 240 hits for experimental testing. After testing, they identified 9 compounds, with Abaucin being the most potent one.
Abaucin’s Mechanism of Action
Abaucin works by inhibiting the lipoprotein transport (LO1E transmembrane protein) of cell envelope in the bacteria. This inhibition can lead to enlargement of the bacterial cell (abnormal cell morphology) thereby inhibiting the growth of A. baumannii. Abaucin is a narrow spectrum antibiotic that targets only A. baumannii. This narrow spectrum activity provides its ability to minimize inter-pathogen resistance making the drug effective.
A. baumannii, an opportunistic pathogen, causes hospital-acquired infections such as pulmonary infections, bloodstream infections, wound infections, and ventilator-associated pneumonia, which have a high mortality rate of 42.6%. In a clinical trial on mice, Abaucin effectively eradicated wound infections associated with A. baumannii.
Challenges and Future Directions
Abaucin demonstrated its use in treating wound infections in mice, but researchers need to conduct more studies on human subjects to validate Abaucin’s efficacy. They also need to perform toxicity level testing in humans to identify the safe and effective dose of the drug. Furthermore, researchers should study the drug’s interaction profile and its effectiveness as an empirical therapy.
The discovery of Abaucin with ML and AI paves the way to the development of targeted therapy against specific pathogens. ML and AI algorithms can analyze and predict the characteristics of the drugs including mechanism of action ensuring speed in development of the correct drugs, thereby ensuring timely delivery of the drugs into the market. Furthermore, in the era of vast information, AI can assist doctors in selection of the correct agents in treating the deadly pathogenic infections.
Reference
- https://pubmed.ncbi.nlm.nih.gov/38841115/
- https://pubmed.ncbi.nlm.nih.gov/33198233/
- Drug-Resistant Infections Could Kill 10 Million People Annually by 2050 | Smithsonian (smithsonianmag.com)
Written By: Ayoob Mansoor, PharmD, RPh
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