AIMC Topic: Drug Discovery

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In silico method and bioactivity evaluation to discover novel antimicrobial agents targeting FtsZ protein: Machine learning, virtual screening and antibacterial mechanism study.

Naunyn-Schmiedeberg's archives of pharmacology Jul 23, 2024
This research paper utilizes a fused-in-silico approach alongside bioactivity evaluation to identify active FtsZ inhibitors for drug discovery. Initially, ROC-guided machine learning was employed to obtain almost 13182 compounds from three libraries....
Cytoskeletal Proteins Molecular Docking Simulation Drug Discovery Bacterial Proteins Staphylococcus aureus Anti-Bacterial Agents Drug Evaluation, Preclinical Bacillus subtilis Computer Simulation Animals Humans Microbial Sensitivity Tests Machine Learning
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HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery.

Journal of chemical information and modeling Jul 22, 2024
We propose HydraScreen, a deep-learning framework for safe and robust accelerated drug discovery. HydraScreen utilizes a state-of-the-art 3D convolutional neural network designed for the effective representation of molecular structures and interactio...
Protein Binding Proteins Ligands Drug Discovery Deep Learning Neural Networks, Computer Drug Design
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Efficient Deep Model Ensemble Framework for Drug-Target Interaction Prediction.

The journal of physical chemistry letters Jul 22, 2024
Accurate prediction of Drug-Target Interactions (DTI) is crucial for drug development. Current state-of-the-art deep learning methods have significantly advanced the field; however, these methods exhibit limitations in predictive performance and the ...
Humans Drug Discovery NAD(P)H Dehydrogenase (Quinone) Deep Learning Sirtuin 1
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Machine learning in preclinical drug discovery.

Nature chemical biology Jul 19, 2024
Drug-discovery and drug-development endeavors are laborious, costly and time consuming. These programs can take upward of 12 years and cost US $2.5 billion, with a failure rate of more than 90%. Machine learning (ML) presents an opportunity to improv...
Humans Machine Learning Drug Discovery Drug Evaluation, Preclinical Algorithms
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AI-Powered Microfluidics: Shaping the Future of Phenotypic Drug Discovery.

ACS applied materials & interfaces Jul 17, 2024
Phenotypic drug discovery (PDD), which involves harnessing biological systems directly to uncover effective drugs, has undergone a resurgence in recent years. The rapid advancement of artificial intelligence (AI) over the past few years presents nume...
High-Throughput Screening Assays Phenotype Drug Discovery Humans Microfluidics Artificial Intelligence
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Near-Term Quantum Classification Algorithms Applied to Antimalarial Drug Discovery.

Journal of chemical information and modeling Jul 16, 2024
Computational approaches are widely applied in drug discovery to explore properties related to bioactivity, physiochemistry, and toxicology. Over at least the last 20 years, the exploitation of machine learning on molecular data sets has been used to...
Quantitative Structure-Activity Relationship Machine Learning Algorithms Quantum Theory Drug Discovery Antimalarials
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Computational approaches for lead compound discovery in dipeptidyl peptidase-4 inhibition using machine learning and molecular dynamics techniques.

Computational biology and chemistry Jul 10, 2024
The prediction of possible lead compounds from already-known drugs that may present DPP-4 inhibition activity imply a advantage in the drug development in terms of time and cost to find alternative medicines for the treatment of Type 2 Diabetes Melli...
Molecular Structure Molecular Dynamics Simulation Dipeptidyl-Peptidase IV Inhibitors Dipeptidyl Peptidase 4 Machine Learning Drug Discovery Diabetes Mellitus, Type 2 Humans
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Lung Adenocarcinoma Systems Biomarker and Drug Candidates Identified by Machine Learning, Gene Expression Data, and Integrative Bioinformatics Pipeline.

Omics : a journal of integrative biology Jul 9, 2024
Lung adenocarcinoma (LUAD) is a significant planetary health challenge with its high morbidity and mortality rate, not to mention the marked interindividual variability in treatment outcomes and side effects. There is an urgent need for robust system...
Prognosis Biomarkers, Tumor Molecular Docking Simulation Humans Machine Learning Adenocarcinoma Drug Repositioning Lung Neoplasms Drug Discovery Trifluoperazine Computational Biology Gene Expression Profiling Gene Expression Regulation, Neoplastic Adenocarcinoma of Lung
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Predicting blood-brain barrier permeability of molecules with a large language model and machine learning.

Scientific reports Jul 9, 2024
Predicting the blood-brain barrier (BBB) permeability of small-molecule compounds using a novel artificial intelligence platform is necessary for drug discovery. Machine learning and a large language model on artificial intelligence (AI) tools improv...
Blood-Brain Barrier Drug Discovery Permeability Machine Learning Computer Simulation Endothelial Cells Humans
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Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties.

Journal of medicinal chemistry Jul 8, 2024
Peptide-based drug discovery has surged with the development of peptide hormone-derived analogs for the treatment of diabetes and obesity. Machine learning (ML)-enabled quantitative structure-activity relationship (QSAR) approaches have shown great p...
Male Peptides Drug Discovery Machine Learning Animals Quantitative Structure-Activity Relationship Humans Mice, Obese Glucagon-Like Peptide-1 Receptor Agonists Mice, Inbred C57BL Mice Obesity
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