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Structure-Activity Relationship

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Classification of FLT3 inhibitors and SAR analysis by machine learning methods.

Molecular diversity 37142889
FMS-like tyrosine kinase 3 (FLT3) is a type III receptor tyrosine kinase, which is an important target for anti-cancer therapy. In this work, we conducted a structure-activity relationship (SAR) study on 3867 FLT3 inhibitors we collected. MACCS finge...
Algorithms fms-Like Tyrosine Kinase 3 Humans Machine Learning Neural Networks, Computer Protein Kinase Inhibitors Structure-Activity Relationship Support Vector Machine
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One-pot multicomponent synthesis of novel pyridine derivatives for antidiabetic and antiproliferative activities.

Future medicinal chemistry 37503685
Due to the close relationship of diabetes with hypertension reported in various research, a set of pyridine derivatives with US FDA-approved drug cores were designed and integrated by artificial intelligence. Novel pyridines were designed and synth...
Artificial Intelligence Hypoglycemic Agents Molecular Docking Simulation Molecular Structure Pyridines Structure-Activity Relationship
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Hallucinating hallucinogens.

Science (New York, N.Y.) 37943903
Fighting the designer drug epidemic with generative AI.
Artificial Intelligence Designer Drugs Epidemics Hallucinations Hallucinogens Humans Structure-Activity Relationship
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Anatomy of Potency Predictions Focusing on Structural Analogues with Increasing Potency Differences Including Activity Cliffs.

Journal of chemical information and modeling 37943257
Potency predictions are popular in compound design and optimization but are complicated by intrinsic limitations. Moreover, even for nonlinear methods, activity cliffs (ACs, formed by structural analogues with large potency differences) represent cha...
Artificial Intelligence Machine Learning Structure-Activity Relationship
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Deep learning-based design and screening of benzimidazole-pyrazine derivatives as adenosine A receptor antagonists.

Journal of biomolecular structure & dynamics 38133953
The Adenosine A receptor (AAR) is considered a novel potential target for the immunotherapy of cancer, and AAR antagonists have an inhibitory effect on tumor growth, proliferation, and metastasis. In our previous studies, we identified a class of ben...
Adenosine A2 Receptor Antagonists Benzimidazoles Deep Learning Drug Design Humans Molecular Docking Simulation Molecular Dynamics Simulation Molecular Structure Protein Binding Pyrazines Receptor, Adenosine A2B Structure-Activity Relationship
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Identification of active compounds as novel dipeptidyl peptidase-4 inhibitors through machine learning and structure-based molecular docking simulations.

Journal of biomolecular structure & dynamics 38100571
The enzyme dipeptidyl peptidase 4 (DPP4) is a potential therapeutic target for type 2 diabetes (T2DM). Many synthetic anti-DPP4 medications are available to treat T2DM. The need for secure and efficient medicines has been unmet due to the adverse sid...
Binding Sites Diabetes Mellitus, Type 2 Dipeptidyl Peptidase 4 Dipeptidyl-Peptidase IV Inhibitors Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Neural Networks, Computer Protein Binding Sitagliptin Phosphate Structure-Activity Relationship
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Discovery of hematopoietic progenitor kinase 1 inhibitors using machine learning-based screening and free energy perturbation.

Journal of biomolecular structure & dynamics 38198294
Hematopoietic progenitor kinase 1 (HPK1) is a key negative regulator of T-cell receptor (TCR) signaling and a promising target for cancer immunotherapy. The development of novel HPK1 inhibitors is challenging yet promising. In this study, we used a c...
Drug Discovery Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Protein Binding Protein Kinase Inhibitors Protein Serine-Threonine Kinases Signal Transduction Structure-Activity Relationship T-Lymphocytes Thermodynamics
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Using deep learning and molecular dynamics simulations to unravel the regulation mechanism of peptides as noncompetitive inhibitor of xanthine oxidase.

Scientific reports 38168773
Xanthine oxidase (XO) is a crucial enzyme in the development of hyperuricemia and gout. This study focuses on LWM and ALPM, two food-derived inhibitors of XO. We used molecular docking to obtain three systems and then conducted 200 ns molecular dynam...
Deep Learning Enzyme Inhibitors Humans Hyperuricemia Molecular Docking Simulation Molecular Dynamics Simulation Peptides Structure-Activity Relationship Xanthine Oxidase
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Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design.

European journal of medicinal chemistry 38387334
Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and li...
Deep Learning Drug Development Peptides Structure-Activity Relationship Technology
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Machine learning and genetic algorithm-guided directed evolution for the development of antimicrobial peptides.

Journal of advanced research 38431124
INTRODUCTION: Antimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics, possess a variety of potent biological activities and exhibit immunomodulatory effects that alleviate difficult-to-treat infections. Clarifying the stru...
Algorithms Animals Anti-Bacterial Agents Antimicrobial Cationic Peptides Antimicrobial Peptides Directed Molecular Evolution Genetic Algorithms Lipopolysaccharides Machine Learning Microbial Sensitivity Tests Penaeidae Staphylococcus aureus Structure-Activity Relationship
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