AIMC Topic: Acinetobacter baumannii

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Modeling Antibacterial Activity with Machine Learning and Fusion of Chemical Structure Information with Microorganism Metabolic Networks.

Journal of chemical information and modeling
Predicting the activity of new chemical compounds over pathogenic microorganisms with different metabolic reaction networks (MRN ) is an important goal due to the different susceptibility to antibiotics. The ChEMBL database contains >160 000 outcomes...

Pathogen Identification Direct From Polymicrobial Specimens Using Membrane Glycolipids.

Scientific reports
With the increased prevalence of multidrug-resistant Gram-negative bacteria, the use of colistin and other last-line antimicrobials is being revisited clinically. As a result, there has been an emergence of colistin-resistant bacterial species, inclu...

Synthesis and antimicrobial studies of novel derivatives of 4-(4-formyl-3-phenyl-1H-pyrazol-1-yl)benzoic acid as potent anti-Acinetobacter baumannii agents.

Bioorganic & medicinal chemistry letters
Microbial resistance to antibiotics is a global concern. The World Health Organization (WHO) has identified antimicrobial resistance as one the three greatest threats for human beings in the 21st century. Without urgent and coordinated action, the wo...

A Deep Learning Approach to Antibiotic Discovery.

Cell
Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed pr...