AIMC Topic: Drug Discovery

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Computer-Aided Drug Discovery for Undruggable Targets.

Chemical reviews Jul 9, 2025
Undruggable targets are those of therapeutical significance but challenging for conventional drug design approaches. Such targets often exhibit unique features, including highly dynamic structures, a lack of well-defined ligand-binding pockets, the p...
Proteins Ligands Allosteric Regulation Computer-Aided Design Humans Intrinsically Disordered Proteins Drug Design Artificial Intelligence Drug Discovery
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AIoptamer: Artificial Intelligence-Driven Aptamer Optimization Pipeline for Targeted Therapeutics in Healthcare.

Molecular pharmaceutics Jul 7, 2025
Aptamers are short, single-stranded DNA or RNA molecules known for their high specificity and affinity toward target biomolecules, making them powerful tools in drug discovery, diagnostics, and biosensing. However, conventional aptamer selection meth...
Artificial Intelligence Machine Learning Humans Aptamers, Nucleotide Drug Discovery Ligands Deep Learning SELEX Aptamer Technique
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A deep learning model for structure-based bioactivity optimization and its application in the bioactivity optimization of a SARS-CoV-2 main protease inhibitor.

European journal of medicinal chemistry Jul 5, 2025
Bioactivity optimization is a crucial and technical task in the early stages of drug discovery, traditionally carried out through iterative substituent optimization, a process that is often both time-consuming and expensive. To address this challenge...
COVID-19 Drug Treatment COVID-19 Humans Protease Inhibitors SARS-CoV-2 Deep Learning Drug Discovery Structure-Activity Relationship Coronavirus 3C Proteases Antiviral Agents Molecular Structure
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Computer-aided drug discovery of a dual-target inhibitor for ovarian cancer: therapeutic intervention targeting CDK1/TTK signaling pathway and structural insights in the NCI-60.

Computers in biology and medicine Jul 1, 2025
Ovarian cancer remains the third most prevalent and deadliest gynecologic malignancy worldwide, with most patients eventually developing resistance to platinum-based chemotherapy. This highlights a critical unmet need for innovative multitargeted the...
Antineoplastic Agents Cell Line, Tumor Signal Transduction Female Drug Discovery Humans Protein Kinase Inhibitors Cell Cycle Proteins CDC2 Protein Kinase Protein Serine-Threonine Kinases Protein-Tyrosine Kinases Ovarian Neoplasms
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Adaptive debiasing learning for drug repositioning.

Journal of biomedical informatics Jul 1, 2025
Drug repositioning, pivotal in current pharmaceutical development, aims to find new uses for existing drugs, offering an efficient and cost-effective path to drug discovery. In recent years, graph neural network-based deep learning methods have achie...
Deep Learning Drug Repositioning Humans Neural Networks, Computer Databases, Factual Drug Discovery Algorithms
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On the application of artificial intelligence in virtual screening.

Expert opinion on drug discovery Jul 1, 2025
INTRODUCTION: Artificial intelligence (AI) has emerged as a transformative tool in drug discovery, particularly in virtual screening (VS), a crucial initial step in identifying potential drug candidates. This article highlights the significance of AI...
Humans Artificial Intelligence Molecular Docking Simulation Drug Evaluation, Preclinical Ligands Quantitative Structure-Activity Relationship Drug Discovery Molecular Dynamics Simulation
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Interpretable machine learning and graph attention network based model for predicting PAMPA permeability.

Journal of molecular graphics & modelling Jul 1, 2025
Parallel artificial membrane permeability assay (PAMPA) is widely used in the early phases of drug discovery as it is quite robust and offers high throughput. It serves as a platform for assessing the permeability and absorption of pharmaceutical com...
Permeability Machine Learning Membranes, Artificial Drug Discovery
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DTBA-net: Drug-Target Binding Affinity prediction using feature selection in hybrid CNN model.

Journal of computer-aided molecular design Jun 16, 2025
In drug discovery, virtual screening and repositioning rely on accurate Drug-Target Binding Affinity (DTBA) prediction to develop effective therapies. However, DTBA prediction remains challenging due to limited annotated datasets, high-dimensional bi...
Proteins Binding Sites Protein Binding Algorithms Humans Drug Discovery Neural Networks, Computer Deep Learning
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Discovery of naturally inspired antimicrobial peptides using deep learning.

Bioorganic chemistry Jun 15, 2025
Non-ribosomal peptides (NRPs) are promising lead compounds for novel antibiotics. Bioinformatic mining of silent microbial NRPS gene clusters provide crucial insights for the discovery and de novo design of bioactive peptides. Here, we describe the e...
Molecular Structure Multigene Family Antimicrobial Peptides Dose-Response Relationship, Drug Structure-Activity Relationship Drug Discovery Deep Learning Humans Microbial Sensitivity Tests Anti-Bacterial Agents
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Cyclic Peptide Therapeutic Agents Discovery: Computational and Artificial Intelligence-Driven Strategies.

Journal of medicinal chemistry Jun 12, 2025
Cyclic peptides have emerged as promising modulators of protein-protein interactions due to their unique pharmacological properties and ability to target extensive flat binding interfaces. However, traditional strategies for developing cyclic peptide...
Humans Artificial Intelligence Deep Learning Peptides, Cyclic Drug Discovery
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