AI Medical Compendium Journal:
Journal of chemical information and modeling

Showing 131 to 140 of 934 articles

Applications of Machine Learning Approaches for the Discovery of SARS-CoV-2 PLpro Inhibitors.

Journal of chemical information and modeling Jan 16, 2025
The global impact of SARS-CoV-2 highlights the need for treatments beyond vaccination, given the limited availability of effective medications. While Pfizer introduced , an FDA-approved antiviral targeting the SARS-CoV-2 main protease (Mpro), this st...
Small Molecule Libraries Coronavirus 3C Proteases Molecular Docking Simulation High-Throughput Screening Assays Drug Discovery Antiviral Agents Machine Learning Protease Inhibitors Coronavirus Papain-Like Proteases COVID-19 Drug Treatment Humans SARS-CoV-2
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MOCapsNet: Multiomics Data Integration for Cancer Subtype Analysis Based on Dynamic Self-Attention Learning and Capsule Networks.

Journal of chemical information and modeling Jan 16, 2025
: With the rapid development of the accumulation of large-scale multiomics data sets, integrating various omics data to provide a thorough study from multiple perspectives can significantly provide stronger support for precise treatment of diseases. ...
Multiomics Genomics Computational Biology Neural Networks, Computer Neoplasms Humans
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Active Learning to Select the Most Suitable Reagents and One-Step Organic Chemistry Reactions for Prioritizing Target-Specific Hits from Ultralarge Chemical Spaces.

Journal of chemical information and modeling Jan 16, 2025
Designing chemically novel and synthesizable ligands from the largest possible chemical space is a major issue in modern drug discovery to identify early hits that are easily amenable to medicinal chemistry optimization. Starting from the sole three-...
Molecular Docking Simulation Drug Discovery Proteins Ligands Machine Learning Indicators and Reagents
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MVCL-DTI: Predicting Drug-Target Interactions Using a Multiview Contrastive Learning Model on a Heterogeneous Graph.

Journal of chemical information and modeling Jan 15, 2025
Accurate prediction of drug-target interactions (DTIs) is pivotal for accelerating the processes of drug discovery and drug repurposing. MVCL-DTI, a novel model leveraging heterogeneous graphs for predicting DTIs, tackles the challenge of synthesizin...
Drug Discovery Drug Repositioning COVID-19 Drug Treatment Machine Learning SARS-CoV-2 Humans
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HIV OctaScanner: A Machine Learning Approach to Unveil Proteolytic Cleavage Dynamics in HIV-1 Protease Substrates.

Journal of chemical information and modeling Jan 14, 2025
The rise of resistance to antiretroviral drugs due to mutations in human immunodeficiency virus-1 (HIV-1) protease is a major obstacle to effective treatment. These mutations alter the drug-binding pocket of the protease and reduce the drug efficacy ...
HIV Protease Inhibitors Proteolysis Substrate Specificity HIV-1 HIV Protease Machine Learning Humans
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deep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities.

Journal of chemical information and modeling Jan 10, 2025
Antimicrobial peptides (AMPs) are small peptides that play an important role in disease defense. As the problem of pathogen resistance caused by the misuse of antibiotics intensifies, the identification of AMPs as alternatives to antibiotics has beco...
Computational Biology Antimicrobial Peptides Deep Learning
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Identifying Protein-Nucleotide Binding Residues via Grouped Multi-task Learning and Pre-trained Protein Language Models.

Journal of chemical information and modeling Jan 9, 2025
The accurate identification of protein-nucleotide binding residues is crucial for protein function annotation and drug discovery. Numerous computational methods have been proposed to predict these binding residues, achieving remarkable performance. H...
Deep Learning Protein Binding Nucleotides Binding Sites Proteins Databases, Protein
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Quotient Complex (QC)-Based Machine Learning for 2D Hybrid Perovskite Design.

Journal of chemical information and modeling Jan 9, 2025
With remarkable stability and exceptional optoelectronic properties, two-dimensional (2D) halide layered perovskites hold immense promise for revolutionizing photovoltaic technology. Effective data representations are key to the success of all learni...
Calcium Compounds Titanium Solar Energy Machine Learning Oxides
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Graph-Based Deep Learning Models for Thermodynamic Property Prediction: The Interplay between Target Definition, Data Distribution, Featurization, and Model Architecture.

Journal of chemical information and modeling Jan 9, 2025
In this contribution, we examine the interplay between target definition, data distribution, featurization approaches, and model architectures on graph-based deep learning models for thermodynamic property prediction. Through consideration of five cu...
Deep Learning Thermodynamics
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CovCysPredictor: Predicting Selective Covalently Modifiable Cysteines Using Protein Structure and Interpretable Machine Learning.

Journal of chemical information and modeling Jan 8, 2025
Targeted covalent inhibition is a powerful therapeutic modality in the drug discoverer's toolbox. Recent advances in covalent drug discovery, in particular, targeting cysteines, have led to significant breakthroughs for traditionally challenging targ...
Proteins Databases, Protein Machine Learning Drug Discovery Protein Conformation Cysteine Models, Molecular Ligands Humans
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