AI Medical Compendium Journal:
Journal of chemical information and modeling

Showing 91 to 100 of 934 articles

Transition State Searching Accelerated by Neural Network Potential.

Journal of chemical information and modeling Feb 20, 2025
Understanding transition states is pivotal in the design of efficient chemical processes and catalysts. However, identifying transition states is challenging due to the resource-intensive and iterative nature of current computational methods. This st...
Neural Networks, Computer Algorithms
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Estimating Absolute Protein-Protein Binding Free Energies by a Super Learner Model.

Journal of chemical information and modeling Feb 20, 2025
Protein-protein binding is central to most biochemical processes of all living beings. Its importance underlies mechanisms ranging from cell interactions to metabolic control, but also to biotechnology, such as the development of therapeutic monoclo...
Machine Learning Protein Binding Proteins Thermodynamics
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RAG_MCNNIL6: A Retrieval-Augmented Multi-Window Convolutional Network for Accurate Prediction of IL-6 Inducing Epitopes.

Journal of chemical information and modeling Feb 19, 2025
Interleukin-6 (IL-6) is a critical cytokine involved in immune regulation, inflammation, and the pathogenesis of various diseases, including autoimmune disorders, cancer, and the cytokine storm associated with severe COVID-19. Identifying IL-6 induci...
Humans Neural Networks, Computer COVID-19 Interleukin-6 SARS-CoV-2 Deep Learning Epitopes
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T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein-Ligand Binding Affinity Prediction with Uncertainty-Aware Self-Learning for Protein-Specific Alignment.

Journal of chemical information and modeling Feb 18, 2025
There is significant interest in targeting disease-causing proteins with small molecule inhibitors to restore healthy cellular states. The ability to accurately predict the binding affinity of small molecules to a protein target in silico enables the...
Humans Neural Networks, Computer SARS-CoV-2 Drug Discovery Deep Learning Protein Binding Proteins Ligands ErbB Receptors Uncertainty
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Accurate Prediction of ωB97X-D/6-31G* Equilibrium Geometries from a Neural Net Starting from Merck Molecular Force Field (MMFF) Molecular Mechanics Geometries.

Journal of chemical information and modeling Feb 17, 2025
Starting from Merck Molecular Force Field (MMFF) geometries, a neural-net based model has been formulated to closely reproduce ωB97X-D/6-31G* equilibrium geometries for organic molecules. The model involves training to >6 million energy and force cal...
Neural Networks, Computer Biological Products Molecular Dynamics Simulation Molecular Conformation
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A Machine-Learned "Chemical Intuition" to Overcome Spectroscopic Data Scarcity.

Journal of chemical information and modeling Feb 17, 2025
Machine learning models for predicting IR spectra of molecular ions (infrared ion spectroscopy, IRIS) have yet to be reported owing to the relatively sparse experimental data sets available. To overcome this limitation, we employ the Graphormer-IR mo...
Machine Learning Spectrophotometry, Infrared
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AI-Augmented R-Group Exploration in Medicinal Chemistry.

Journal of chemical information and modeling Feb 17, 2025
Efficient R-group exploration in the vast chemical space, enabled by increasingly available building blocks or generative AI, remains an open challenge. Here, we developed an enhanced Free-Wilson QSAR model embedding R-groups by atom-centric pharmaco...
Artificial Intelligence Quantitative Structure-Activity Relationship Chemistry, Pharmaceutical Stereoisomerism
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High-Throughput Prediction of Metal-Embedded Complex Properties with a New GNN-Based Metal Attention Framework.

Journal of chemical information and modeling Feb 14, 2025
Metal-embedded complexes (MECs), including transition metal complexes (TMCs) and metal-organic frameworks (MOFs), are important in catalysis, materials science, and molecular devices due to their unique metal atom centrality and complex coordination ...
Neural Networks, Computer Algorithms Metals Metal-Organic Frameworks Coordination Complexes
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Dynamic Electronic Structure Fluctuations in the De Novo Peptide ACC-Dimer Revealed by First-Principles Theory and Machine Learning.

Journal of chemical information and modeling Feb 14, 2025
Recent studies have reported long-range charge transport in peptide- and protein-based fibers and wires, rendering this class of materials as promising charge-conducting interfaces between biological systems and electronic devices. In the complex mol...
Machine Learning Peptides Density Functional Theory Molecular Dynamics Simulation Electrons Protein Conformation Protein Multimerization
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metaCDA: A Novel Framework for CircRNA-Driven Drug Discovery Utilizing Adaptive Aggregation and Meta-Knowledge Learning.

Journal of chemical information and modeling Feb 12, 2025
In the emerging field of RNA drugs, circular RNA (circRNA) has attracted much attention as a novel multifunctional therapeutic target. Delving deeper into the intricate interactions between circRNA and disease is critical for driving drug discovery e...
Humans Machine Learning Drug Discovery RNA, Circular
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