AIMC Topic: Bacterial Proteins

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A generalized platform for artificial intelligence-powered autonomous enzyme engineering.

Nature communications
Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we r...

Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication.

Nature communications
Bio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare settings. Since bacterial surface attachment is sensitive to surface topography, we experimentally surveyed...

Enzymatic carbon-fluorine bond cleavage by human gut microbes.

Proceedings of the National Academy of Sciences of the United States of America
Fluorinated compounds are used for agrochemical, pharmaceutical, and numerous industrial applications, resulting in global contamination. In many molecules, fluorine is incorporated to enhance the half-life and improve bioavailability. Fluorinated co...

Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach.

Scientific reports
The bacterial cell division protein FtsZ, a crucial GTPase, plays a vital role in the formation of the contractile Z-ring, which is essential for bacterial cytokinesis. Consequently, inhibiting FtsZ could prevent the formation of proto-filaments and ...

Role of electrostatics in cold adaptation: A comparative study of eury- and stenopsychrophilic triose phosphate isomerase.

Biochimica et biophysica acta. Proteins and proteomics
Psychrophilic (cold-active) organisms have developed enzymes that facilitate sufficient metabolic activity at low temperatures to sustain life. This occurs through molecular adaptations that tend to increase protein flexibility at the expense of stab...

An integrated AI knowledge graph framework of bacterial enzymology and metabolism.

Proceedings of the National Academy of Sciences of the United States of America
The study of bacterial metabolism holds immense significance for improving human health and advancing agricultural practices. The prospective applications of genomically encoded bacterial metabolism present a compelling opportunity, particularly in t...

deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria.

mSystems
Selenoproteins are a special group of proteins with major roles in cellular antioxidant defense. They contain the 21st amino acid selenocysteine (Sec) in the active sites, which is encoded by an in-frame UGA codon. Compared to eukaryotes, identificat...

Targeting Bacterial RNA Polymerase: Harnessing Simulations and Machine Learning to Design Inhibitors for Drug-Resistant Pathogens.

Biochemistry
The increase in antimicrobial resistance presents a major challenge in treating bacterial infections, underscoring the need for innovative drug discovery approaches and novel inhibitors. Bacterial RNA polymerase (RNAP) has emerged as a crucial target...

Cloning, Characterization, and Computer-Aided Evolution of a Thermostable Laccase of the DUF152 Family From Klebsiella michiganensis.

Proteins
Bacterial laccases exhibit relatively high optimal reaction temperatures and possess a broad substrate spectrum, thereby expanding the range of potential applications for laccase enzymes. This study aims to investigate the molecular evolution of bact...

SHASI-ML: a machine learning-based approach for immunogenicity prediction in vaccine development.

Frontiers in cellular and infection microbiology
INTRODUCTION: Accurate prediction of immunogenic proteins is crucial for vaccine development and understanding host-pathogen interactions in bacterial diseases, particularly for Salmonella infections which remain a significant global health challenge...