AIMC Topic: Trimethoprim

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Holistic understanding of trimethoprim resistance in using an integrative approach of genome-wide association study, resistance reconstruction, and machine learning.

mBio Aug 9, 2024
UNLABELLED: Antimicrobial resistance (AMR) is a public health threat worldwide. Next-generation sequencing (NGS) has opened unprecedented opportunities to accelerate AMR mechanism discovery and diagnostics. Here, we present an integrative approach to...
High-Throughput Nucleotide Sequencing Pneumococcal Infections Mutation Genome, Bacterial Trimethoprim Resistance Trimethoprim Streptococcus pneumoniae Anti-Bacterial Agents Humans Machine Learning Microbial Sensitivity Tests Genome-Wide Association Study
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MANORAA: A machine learning platform to guide protein-ligand design by anchors and influential distances.

Structure (London, England : 1993) Oct 5, 2021
The MANORAA platform uses structure-based approaches to provide information on drug design originally derived from mapping tens of thousands of amino acids on a grid. In-depth analyses of the pockets, frequently occurring atoms, influential distances...
Proteins Databases, Protein Computational Biology Ligands Crystallography, X-Ray Protein Domains Models, Molecular SARS-CoV-2 Protein Binding Drug Design Pandemics COVID-19 Machine Learning Humans Trimethoprim Tetrahydrofolate Dehydrogenase
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Amino acid conjugated antimicrobial drugs: Synthesis, lipophilicity- activity relationship, antibacterial and urease inhibition activity.

European journal of medicinal chemistry Dec 29, 2017
Present work describes the in vitro antibacterial evaluation of some new amino acid conjugated antimicrobial drugs. Structural modification was attempted on the three existing antimicrobial pharmaceuticals namely trimethoprim, metronidazole, isoniazi...
Trimethoprim Bacillus Isoniazid Amino Acids Staphylococcus aureus Enzyme Inhibitors Urease Microbial Sensitivity Tests Molecular Structure Structure-Activity Relationship Anti-Bacterial Agents Escherichia coli Salmonella typhi Metronidazole Dose-Response Relationship, Drug Pseudomonas aeruginosa Hydrophobic and Hydrophilic Interactions
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Improving the accuracy and convergence of drug permeation simulations via machine-learned collective variables.

The Journal of chemical physics Jul 28, 2021
Understanding the permeation of biomolecules through cellular membranes is critical for many biotechnological applications, including targeted drug delivery, pathogen detection, and the development of new antibiotics. To this end, computer simulation...
Lipid Bilayers Algorithms Phosphatidylcholines Trimethoprim Cholesterol Pharmacokinetics Molecular Dynamics Simulation Thermodynamics Unsupervised Machine Learning
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