AIMC Topic: Molecular Dynamics Simulation

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Investigating the bispecific lead compounds against methicillin-resistant SarA and CrtM using machine learning and molecular dynamics approach.

Journal of biomolecular structure & dynamics Dec 26, 2023
Methicillin-resistant Staphylococcus aureus (MRSA) is a notorious pathogen that has emerged as a serious global health concern over the past few decades. Staphylococcal accessory regulator A (SarA) and 4,4'-diapophytoene synthase (CrtM) play a crucia...
Hydrogen Bonding Protein Binding Methicillin-Resistant Staphylococcus aureus Molecular Dynamics Simulation Quantitative Structure-Activity Relationship Anti-Bacterial Agents Bacterial Proteins Machine Learning Molecular Docking Simulation Biofilms
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Deep learning-based design and screening of benzimidazole-pyrazine derivatives as adenosine A receptor antagonists.

Journal of biomolecular structure & dynamics Dec 22, 2023
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...
Receptor, Adenosine A2B Benzimidazoles Adenosine A2 Receptor Antagonists Protein Binding Pyrazines Molecular Structure Molecular Dynamics Simulation Structure-Activity Relationship Molecular Docking Simulation Drug Design Deep Learning Humans
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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 Dec 15, 2023
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...
Humans Neural Networks, Computer Machine Learning Dipeptidyl Peptidase 4 Protein Binding Dipeptidyl-Peptidase IV Inhibitors Binding Sites Structure-Activity Relationship Sitagliptin Phosphate Molecular Dynamics Simulation Molecular Docking Simulation Diabetes Mellitus, Type 2
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Interpreting forces as deep learning gradients improves quality of predicted protein structures.

Biophysical journal Dec 15, 2023
Protein structure predictions from deep learning models like AlphaFold2, despite their remarkable accuracy, are likely insufficient for direct use in downstream tasks like molecular docking. The functionality of such models could be improved with a c...
Deep Learning Proteins Molecular Dynamics Simulation Protein Conformation
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Integrating machine learning and high throughput screening for the discovery of allosteric AKT1 inhibitors.

Journal of biomolecular structure & dynamics Dec 14, 2023
Evidence from clinical and experimental investigations reveals the role of AKT in oral cancer, which has led to the development of therapeutic and pharmacological medications for inhibiting AKT protein. Despite prodigious effort, researchers are sear...
Drug Discovery Quantitative Structure-Activity Relationship Humans Protein Binding Protein Kinase Inhibitors Machine Learning Molecular Dynamics Simulation Proto-Oncogene Proteins c-akt Allosteric Regulation Molecular Docking Simulation High-Throughput Screening Assays
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Discovery of potential RIPK1 inhibitors by machine learning and molecular dynamics simulations.

Physical chemistry chemical physics : PCCP Nov 22, 2023
Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) plays a crucial role in inflammation and cell death, so it is a promising candidate for the treatment of autoimmune, inflammatory, neurodegenerative, and ischemic diseases. So far, there ...
Molecular Dynamics Simulation Machine Learning Molecular Docking Simulation
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Calculation of Protein Folding Thermodynamics Using Molecular Dynamics Simulations.

Journal of chemical information and modeling Nov 13, 2023
Despite advances in artificial intelligence methods, protein folding remains in many ways an enigma to be solved. Accurate computation of protein folding energetics could help drive fields such as protein and drug design and genetic interpretation. H...
Molecular Dynamics Simulation Thermodynamics Artificial Intelligence Protein Folding Proteins
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Exploring the potential of machine learning to design antidiabetic molecules: a comprehensive study with experimental validation.

Journal of biomolecular structure & dynamics Nov 8, 2023
Recent advances in hardware and software algorithms have led to the rise of data-driven approaches for designing therapeutic modalities. One of the major causes of human mortality is diabetes. Thus, there is a tremendous opportunity for research into...
Small Molecule Libraries alpha-Amylases Quantitative Structure-Activity Relationship Thermodynamics Humans Molecular Docking Simulation Machine Learning Molecular Dynamics Simulation Drug Design Enzyme Inhibitors Algorithms Hypoglycemic Agents Reproducibility of Results
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Cell-free biosynthesis combined with deep learning accelerates de novo-development of antimicrobial peptides.

Nature communications Nov 8, 2023
Bioactive peptides are key molecules in health and medicine. Deep learning holds a big promise for the discovery and design of bioactive peptides. Yet, suitable experimental approaches are required to validate candidates in high throughput and at low...
DNA Replication Deep Learning Protein Biosynthesis Molecular Dynamics Simulation Antimicrobial Peptides
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Generation of focused drug molecule library using recurrent neural network.

Journal of molecular modeling Nov 6, 2023
CONTEXT: With the wide application of deep learning in drug research and development, de novo molecular design methods based on recurrent neural network (RNN) have strong advantages in drug molecule generation. The RNN model can be used to learn the ...
Neural Networks, Computer Molecular Docking Simulation Drug Design SARS-CoV-2 Molecular Dynamics Simulation
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