AIMC Topic: Bacterial Proteins

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Artificial intelligence in protein-based detection and inhibition of AMR pathways.

Journal of computer-aided molecular design
Antimicrobial Resistance (AMR) is a global concern demanding high-throughput and precise AMR surveillance strategies. This review provides a comprehensive list of Artificial Intelligence (AI) driven frameworks widely employed in the early detection, ...

Autocatalytic Circular DNA Powered Plasmonic CRISPR/Cas12a Platform for Ultrasensitive Non-Nucleic Acid Target Sensing.

Angewandte Chemie (International ed. in English)
CRISPR/Cas12a-based detection of non-nucleic acid targets faces two major challenges: 1) limited sensitivity due to the inherent inability to pre-amplify non-nucleic acid targets, and 2) suboptimal performance of traditional reporters caused by photo...

Unveiling the landscape of prokaryotic global regulators through deep protein language models.

mSystems
Global regulators (GRs) are key transcription factors that orchestrate the expression of multiple genes, playing essential roles in stress responses, virulence, secondary metabolism, and antibiotic resistance-traits that make them powerful tools for ...

Characterization of a Novel Mutansucrase (MUT-I) from G29: Enzymatic Properties and Product Analysis.

Journal of agricultural and food chemistry
Glucansucrases are extracellular enzymes capable of synthesizing diverse α-glucan polymers and oligosaccharides, including the industrially relevant mutan. The I-encoded mutansucrase (MUT-I) from G29 was biochemically characterized as a robust bioca...

Coevolutionary signals in multiple sequence alignments improve virulence factor prediction with an MSA Transformer.

Scientific reports
Identification of virulence factors (VFs) is critical for expanding our knowledge on bacterial pathogenesis and also for developing targeted strategies for the prevention and treatment of related infectious diseases. Understanding virulence factors r...

CarbaDetector: a machine learning model for detecting carbapenemase-producing Enterobacterales from disk diffusion tests.

Nature communications
Carbapenemase-producing Enterobacterales (CPE) are considered among the highest threats to global health by WHO. Their detection is difficult and time-consuming. We developed a random-forest machine learning (ML) model, CarbaDetector, to predict carb...

TXSelect: A multi-task learning model to identify secretory effectors.

PLoS computational biology
Secretory effectors from pathogenic microorganisms significantly influence pathogen survival and pathogenicity by manipulating host signalling, immune responses, and metabolic processes. However, because of sequence and structural heterogeneity among...

Mycobacterium tuberculosis FAS-II pathway targeted integrative deep learning based identification of potential anti-tubercular agents.

Journal of computer-aided molecular design
Mycobacterium tuberculosis (Mtb) continues to be one of the major contributors to the global burden of infectious diseases. Many drugs used in the current treatment regime have fallen prey to the puzzling phenomenon of antimicrobial resistance. Despi...

Probing the Gate-Opening Transition in the Bacterial ClpP Peptidase Using Molecular Dynamics Simulations and Machine Learning.

Biochemistry
Preserving proteome integrity is crucial for maintaining cell viability across all kingdoms of life. The bacterial caseinolytic protease (ClpP) plays a critical role in maintaining protein homeostasis by degrading misfolded or damaged proteins within...

Amplification-free detection of mycoplasma pneumoniae via CRISPR-Cas12a and deep learning-optimized crRNAs on a lateral flow platform.

Journal of pharmaceutical and biomedical analysis
Accurate and rapid diagnosis of Mycoplasma pneumoniae infection is essential for reducing its significant health burden. An amplification-free CRISPR-Cas12a-mediated detection platform has been developed, incorporating a deep learning-optimized crRNA...