AIMC Topic: Molecular Docking Simulation

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Harnessing deep learning for enhanced ligand docking.

Trends in pharmacological sciences Dec 30, 2023
Ligand docking (LD), a technology for predicting protein-ligand (PL)-binding conformations and strengths, plays key roles in virtual screening (VS). However, the accuracy and speed of current LD methodologies remain suboptimal. Here, we discuss how d...
Ligands Protein Conformation Deep Learning Protein Binding Proteins Humans Molecular Docking 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 Quantitative Structure-Activity Relationship Methicillin-Resistant Staphylococcus aureus Bacterial Proteins Molecular Dynamics Simulation Biofilms Protein Binding Anti-Bacterial Agents Molecular Docking Simulation Machine Learning
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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...
Humans Molecular Docking Simulation Drug Design Structure-Activity Relationship Molecular Structure Pyrazines Deep Learning Protein Binding Molecular Dynamics Simulation Benzimidazoles Receptor, Adenosine A2B Adenosine A2 Receptor Antagonists
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AIDDISON: Empowering Drug Discovery with AI/ML and CADD Tools in a Secure, Web-Based SaaS Platform.

Journal of chemical information and modeling Dec 22, 2023
The widespread proliferation of artificial intelligence (AI) and machine learning (ML) methods has a profound effect on the drug discovery process. However, many scientists are reluctant to utilize these powerful tools due to the steep learning curve...
Drug Discovery Internet Artificial Intelligence Power, Psychological Molecular Docking Simulation Machine Learning
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1,3,4-oxadiazole derivatives: synthesis, characterization, antifungal activity, DNA binding investigations, TD-DFT calculations, and molecular modelling.

Journal of biomolecular structure & dynamics Dec 21, 2023
1,3,4-Oxadiazole-based heterocyclic analogs (3a-3m) were synthesized cyclization of Schiff bases with substituted aldehydes in the presence of bromine and acetic acid. The structural clarification of synthesized molecules was carried out with variou...
Molecular Structure Antifungal Agents Oxadiazoles Density Functional Theory Models, Molecular DNA Microbial Sensitivity Tests Antioxidants Structure-Activity Relationship Humans Molecular Docking Simulation
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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...
Binding Sites Sitagliptin Phosphate Dipeptidyl-Peptidase IV Inhibitors Molecular Dynamics Simulation Dipeptidyl Peptidase 4 Humans Diabetes Mellitus, Type 2 Protein Binding Structure-Activity Relationship Machine Learning Molecular Docking Simulation Neural Networks, Computer
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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...
High-Throughput Screening Assays Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Proto-Oncogene Proteins c-akt Molecular Dynamics Simulation Allosteric Regulation Humans Machine Learning Drug Discovery Protein Binding Molecular Docking Simulation
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A Multimodal Deep Learning Framework for Predicting PPI-Modulator Interactions.

Journal of chemical information and modeling Dec 1, 2023
Protein-protein interactions (PPIs) are essential for various biological processes and diseases. However, most existing computational methods for identifying PPI modulators require either target structure or reference modulators, which restricts thei...
NF-E2-Related Factor 2 Protein Interaction Mapping Kelch-Like ECH-Associated Protein 1 Molecular Docking Simulation Deep Learning
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Identification of new potential candidates to inhibit EGF via machine learning algorithm.

European journal of pharmacology Nov 23, 2023
One of the cost-effective alternative methods to find new inhibitors has been the repositioning approach of existing drugs. The advantage of computational drug repositioning method is saving time and cost to remove the pre-clinical step and accelerat...
Algorithms Molecular Docking Simulation Drug Repositioning Machine Learning Epidermal Growth Factor Gefitinib
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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 ...
Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation
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