AIMC Topic: Drug Discovery

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The Role of Artificial Intelligence and Machine Learning in Accelerating the Discovery and Development of Nanomedicine.

Pharmaceutical research Dec 2, 2024
The unique potential of nanomedicine to address challenging health issues is rapidly advancing the field, leading to the generation of more effective products. However, these complex systems often pose several challenges with respect to their design ...
Artificial Intelligence Machine Learning Animals Humans Nanomedicine Drug Discovery Drug Development
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Structure-Aware Graph Attention Diffusion Network for Protein-Ligand Binding Affinity Prediction.

IEEE transactions on neural networks and learning systems Dec 2, 2024
Accurate prediction of protein-ligand binding affinities can significantly advance the development of drug discovery. Several graph neural network (GNN)-based methods learn representations of protein-ligand complexes via modeling intermolecule intera...
Neural Networks, Computer Algorithms Humans Proteins Drug Discovery Protein Binding Databases, Protein Ligands
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A versatile attention-based neural network for chemical perturbation analysis and its potential to aid surgical treatment: an experimental study.

International journal of surgery (London, England) Dec 1, 2024
Deep learning models have emerged as rapid, accurate, and effective approaches for clinical decisions. Through a combination of drug screening and deep learning models, drugs that may benefit patients before and after surgery can be discovered to red...
COVID-19 Drug Treatment Neural Networks, Computer COVID-19 Transcriptome Deep Learning Drug Discovery Humans
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A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds.

SAR and QSAR in environmental research Nov 28, 2024
Identifying new compounds with minimal side effects to enhance patients' quality of life is the ultimate goal of drug discovery. Due to the expensive and time-consuming nature of experimental investigations and the scarcity of data in traditional QSA...
Cell Line, Tumor Cell Proliferation Quantitative Structure-Activity Relationship Antineoplastic Agents Deep Learning Humans Drug Discovery
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Machine Learning-Driven Discovery and Database of Cyanobacteria Bioactive Compounds: A Resource for Therapeutics and Bioremediation.

Journal of chemical information and modeling Nov 27, 2024
Cyanobacteria strains have the potential to produce bioactive compounds that can be used in therapeutics and bioremediation. Therefore, compiling all information about these compounds to consider their value as bioresources for industrial and researc...
Databases, Factual Cyanobacteria Machine Learning Software Humans Molecular Docking Simulation Biodegradation, Environmental Drug Discovery Databases, Chemical
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Mining biology for antibiotic discovery.

PLoS biology Nov 26, 2024
The rise of antibiotic resistance calls for innovative solutions. The realization that biology can be mined digitally using artificial intelligence has revealed a new paradigm for antibiotic discovery, offering hope in the fight against superbugs.
Artificial Intelligence Anti-Bacterial Agents Humans Drug Resistance, Microbial Data Mining Drug Resistance, Bacterial Drug Discovery
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ConfRank: Improving GFN-FF Conformer Ranking with Pairwise Training.

Journal of chemical information and modeling Nov 20, 2024
Conformer ranking is a crucial task for drug discovery, with methods for generating conformers often based on molecular (meta)dynamics or sophisticated sampling techniques. These methods are constrained by the underlying force computation regarding r...
Drug Discovery Molecular Dynamics Simulation Molecular Conformation Machine Learning
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CPIScore: A Deep Learning Approach for Rapid Scoring and Interpretation of Protein-Ligand Binding Interactions.

Journal of chemical information and modeling Nov 19, 2024
Protein-ligand binding affinity prediction is a crucial and challenging task in the field of drug discovery. However, traditional simulation-based computational approaches are often prohibitively time-consuming, limiting their practical utility. In t...
Proteins Ligands Deep Learning Protein Binding Small Molecule Libraries Drug Discovery
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vScreenML v2.0: Improved Machine Learning Classification for Reducing False Positives in Structure-Based Virtual Screening.

International journal of molecular sciences Nov 18, 2024
The enthusiastic adoption of make-on-demand chemical libraries for virtual screening has highlighted the need for methods that deliver improved hit-finding discovery rates. Traditional virtual screening methods are often inaccurate, with most compoun...
Drug Evaluation, Preclinical Small Molecule Libraries Drug Discovery User-Computer Interface Machine Learning Software Humans
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DMHGNN: Double multi-view heterogeneous graph neural network framework for drug-target interaction prediction.

Artificial intelligence in medicine Nov 17, 2024
Accurate identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared with traditional experimental methods that are labor-intensive and time-consuming, computational methods for drug-target interactions predicti...
Drug Interactions Proteins Pharmaceutical Preparations Humans Neural Networks, Computer Drug Discovery Computational Biology Algorithms
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