An innovative antibiotic "Abaucin": Instigated by Artificial Intelligence
Abstract
Nosocomial Gram-negative pathogen, Acinetobacter baumannii repeatedly demonstrates multidrug resistance. Discovering novel antibiotics against A. baumannii has proven thought-provoking through conventional screening tactics. Providentially, machine learning approaches allow for the speedy exploration of chemical space, snowballing the probability of determining new antibacterial molecules. In the following research era, a neural network is accomplished with growth reserve dataset and accomplished in silico predictions for structurally unconventional molecules with commotion in divergence to A. baumannii. Through this method, Abaucin was exposed in the medicinal field, an antibacterial complex with narrow-spectrum activity against A. baumannii. Recent surveys and studies indicate that Abaucin disrupts the transportation of lipoproteins via a mechanism or pathway involving LolE. The machine learning (ML) has facilitated discovery of this new antibiotic in the field of medicine and pharmacology. This describes a hopeful lead with battered activity against a challenging Gram-negative microorganism. There is an insistent need for innovate as well as effective antibacterial drugs owing to the inevitable growth of resistance that tracks the outline of ground breaking antimicrobial to the entire medicinal and pharmac field. Abaucin will lead to dynamic resolution worldwide. The antibiotic resistance is now highly noticeable public health issue specially after pandemic COVID-19. During COVID-19 the use of anti-microbials has suddenly increased. Present review is a multidisciplinary approach which spot light the development of newer antibiotic-Abaucin with the help of artificial intelligence (AI). Medicine is the perfect combination of morden engineering and pharmacology. This article also explores the use of artificial intelligence to evaluate the development of new antibiotic, providing an in-depth look at the potential of these technologies to revolutionize healthcare.
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DOI: https://doi.org/10.37591/rrjomv.v13i3.3430
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