AIMC Topic: Tetrahydrofolate Dehydrogenase

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GeoEvoBuilder: A deep learning framework for efficient functional and thermostable protein design.

Proceedings of the National Academy of Sciences of the United States of America Oct 10, 2025
While deep learning has advanced protein sequence and function design, engineering highly active and stable proteins still requires labor-intensive iterative computational design and experimentation. There is a critical need for methods capable of di...
Models, Molecular Protein Stability Deep Learning Green Fluorescent Proteins Protein Engineering Tetrahydrofolate Dehydrogenase Glutathione Peroxidase Protein Conformation
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Evolutionary selection of trimethoprim-resistant genes in lytic phages affects phage and host fitness during infection.

Science advances Sep 26, 2025
Temperate phages and prophages are well-known carriers of antibiotic resistance genes (ARGs) facilitating their transmission. In contrast, lytic phages rarely harbor functional ARGs. However, by a lenient threshold search strategy combined with a mac...
Trimethoprim Resistance Escherichia coli Evolution, Molecular Bacteriophages Tetrahydrofolate Dehydrogenase Trimethoprim
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Machine Learning Quantum Mechanical/Molecular Mechanical Potentials: Evaluating Transferability in Dihydrofolate Reductase-Catalyzed Reactions.

Journal of chemical theory and computation Jan 15, 2025
Integrating machine learning potentials (MLPs) with quantum mechanical/molecular mechanical (QM/MM) free energy simulations has emerged as a powerful approach for studying enzymatic catalysis. However, its practical application has been hindered by t...
Machine Learning Molecular Dynamics Simulation Thermodynamics Quantum Theory Biocatalysis Tetrahydrofolate Dehydrogenase
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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...
Protein Domains Ligands Databases, Protein Models, Molecular Tetrahydrofolate Dehydrogenase Crystallography, X-Ray Trimethoprim SARS-CoV-2 Drug Design Computational Biology Proteins Protein Binding Pandemics COVID-19 Humans Machine Learning
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Deep-learning based repurposing of FDA-approved drugs against dihydrofolate reductase and molecular dynamics study.

Journal of biomolecular structure & dynamics Apr 21, 2021
causes the fatal fungal bloodstream infection in humans called Candidiasis. Most of the species are resistant to the antifungals used to treat them. Drug-resistant poses very serious public health issues. To overcome this, the development of effec...
Drug Repositioning Candidiasis Molecular Dynamics Simulation Sulfonamides Antifungal Agents Candida albicans Rifampin Humans Cyclopropanes Folic Acid Antagonists Molecular Docking Simulation Deep Learning Tetrahydrofolate Dehydrogenase United States Benzodioxoles Lactams, Macrocyclic Aminopyridines United States Food and Drug Administration Drug Approval Proline
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Application of molecular docking and PSO-SVR intelligent approaches in antimalarial activity prediction of enantiomeric cycloguanil analogues.

SAR and QSAR in environmental research Nov 1, 2018
A series of antifolate compounds, i.e. 1-(4-chlorophenyl)-6,6-dimethyl-1,3,5-triazine-2,4-diamine, or cycloguanil analogues, have shown effective inhibiting properties against Plasmodium falciparum dihydrofolate reductase (PfDHFR). In this work, the ...
Folic Acid Antagonists Substrate Specificity Quantitative Structure-Activity Relationship Stereoisomerism Tetrahydrofolate Dehydrogenase Protein Binding Triazines Reproducibility of Results Plasmodium falciparum Proguanil Antimalarials Molecular Docking Simulation Molecular Structure Enzyme Inhibitors Machine Learning Algorithms
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