AI Medical Compendium Journal:
Journal of chemical information and modeling

Showing 121 to 130 of 934 articles

Chemically Informed Deep Learning for Interpretable Radical Reaction Prediction.

Journal of chemical information and modeling Jan 28, 2025
Organic radical reactions are crucial in many areas of chemistry, including synthetic, biological, and atmospheric chemistry. We develop a predictive framework based on the interaction of molecular orbitals that operates on mechanistic-level radical ...
Free Radicals Deep Learning
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Transformer Decoder Learns from a Pretrained Protein Language Model to Generate Ligands with High Affinity.

Journal of chemical information and modeling Jan 27, 2025
The drug discovery process can be significantly accelerated by using deep learning methods to suggest molecules with druglike features and, more importantly, that are good candidates to bind specific proteins of interest. We present a novel deep lear...
Ligands Models, Molecular Deep Learning Proteins Drug Discovery Protein Binding
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Deep Learning of CYP450 Binding of Small Molecules by Quantum Information.

Journal of chemical information and modeling Jan 27, 2025
Drug-drug interaction can lead to diminished therapeutic effects or increased toxicity, posing significant risks, especially in polypharmacy, and cytochrome P450 plays an indispensable role in this interaction. Cytochrome P450, responsible for the me...
Small Molecule Libraries Humans Cytochrome P-450 CYP1A2 Cytochrome P-450 Enzyme System Drug Interactions Deep Learning Quantum Theory Protein Binding
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Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.

Journal of chemical information and modeling Jan 25, 2025
Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, le...
Machine Learning Neural Networks, Computer Thermodynamics Quantum Theory Graph Neural Networks
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Essential Oils as Antimicrobials against : Experimental and Literature Data to Definite Predictive Quantitative Composition-Activity Relationship Models Using Machine Learning Algorithms.

Journal of chemical information and modeling Jan 22, 2025
Essential oils (EOs) exhibit a broad spectrum of biological activities; however, their clinical application is hindered by challenges, such as variability in chemical composition and chemical/physical instability. A critical limitation is the lack of...
Oils, Volatile Microbial Sensitivity Tests Quantitative Structure-Activity Relationship Acinetobacter baumannii Machine Learning Anti-Bacterial Agents
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Deciphering Protein Secondary Structures and Nucleic Acids in Cryo-EM Maps Using Deep Learning.

Journal of chemical information and modeling Jan 21, 2025
With the resolution revolution of cryo-electron microscopy (cryo-EM) and the rapid development of image processing technology, cryo-EM has become an indispensable experimental method for determining the three-dimensional structures of biological macr...
Nucleic Acids Protein Structure, Secondary Cryoelectron Microscopy Proteins Deep Learning Models, Molecular
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Comparative Analysis of Recurrent Neural Networks with Conjoint Fingerprints for Skin Corrosion Prediction.

Journal of chemical information and modeling Jan 21, 2025
Skin corrosion assessment is an essential toxicity end point that addresses safety concerns for topical dosage forms and cosmetic products. Previously, skin corrosion assessments required animal testing; however, differences in skin architecture and ...
Neural Networks, Computer Deep Learning Humans Recurrent Neural Networks Corrosion Skin
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MMPD-DTA: Integrating Multi-Modal Deep Learning with Pocket-Drug Graphs for Drug-Target Binding Affinity Prediction.

Journal of chemical information and modeling Jan 20, 2025
Predicting drug-target binding affinity (DTA) is a crucial task in drug discovery research. Recent studies have demonstrated that pocket features and interactions between targets and drugs significantly improve the understanding of DTA. However, chal...
Humans Pharmaceutical Preparations Proteins Binding Sites Deep Learning Drug Discovery Protein Binding
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An Intelligent Prediction Model for the Synthesis Conditions of Metal-Organic Frameworks Utilizing Artificial Neural Networks Enhanced by Genetic Algorithm Optimization.

Journal of chemical information and modeling Jan 19, 2025
In the field of emerging materials, metal-organic frameworks (MOFs) have gained prominence due to their unique porous structures, showing versatility in gas adsorption, storage, separation, and liquid processes. However, their decomposition, collapse...
Metal-Organic Frameworks Genetic Algorithms Algorithms Neural Networks, Computer
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ABCoRT: Retention Time Prediction for Metabolite Identification via Atom-Bond Co-Learning.

Journal of chemical information and modeling Jan 16, 2025
Liquid chromatography retention time (RT) prediction plays a crucial role in metabolite identification, a challenging and essential task in untargeted metabolomics. Accurate molecular representation is vital for reliable RT prediction. To address thi...
Metabolomics Chromatography, Liquid Time Factors Machine Learning
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