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Quantum Theory

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Machine Learning Classification of Chirality and Optical Rotation Using a Simple One-Hot Encoded Cartesian Coordinate Molecular Representation.

Journal of chemical information and modeling 40311114
Absolute stereochemical configurations and optical rotations were computed for 121,416 molecular structures from the QM9 quantum chemistry data set using density functional theory. A representation for the molecules was developed using Cartesian coor...
Algorithms Machine Learning Models, Molecular Optical Rotation Quantum Theory Stereoisomerism
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Quantum federated learning with pole-angle quantum local training and trainable measurement.

Neural networks : the official journal of the International Neural Network Society 40024047
Recently, quantum federated learning (QFL) has received significant attention as an innovative paradigm. QFL has remarkable features by employing quantum neural networks (QNNs) instead of conventional neural networks owing to quantum supremacy. In or...
Algorithms Federated Learning Machine Learning Neural Networks, Computer Quantum Theory
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Discriminating High from Low Energy Conformers of Druglike Molecules: An Assessment of Machine Learning Potentials and Quantum Chemical Methods.

Chemphyschem : a European journal of chemical physics and physical chemistry 40017058
Accurate and efficient prediction of high energy ligand conformations is important in structure-based drug discovery for the exclusion of unrealistic structures in docking-based virtual screening and de novo design approaches. In this work, we constr...
Density Functional Theory Ligands Machine Learning Molecular Conformation Pharmaceutical Preparations Quantum Theory Thermodynamics
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A semiempirical and machine learning approach for fragment-based structural analysis of non-hydroxamate HDAC3 inhibitors.

Biophysical chemistry 39978120
Interest in HDAC3 inhibitors (HDAC3i) for pharmacological applications outside of cancer is growing. However, concerns regarding the possible mutagenicity of the commonly used hydroxamates (zinc-binding groups, ZBGs) are also increasing. Considering ...
Histone Deacetylase Inhibitors Histone Deacetylases Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Molecular Structure Quantitative Structure-Activity Relationship Quantum Theory Thermodynamics
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Deep Learning Protocol for Predicting Full-Spectrum Infrared and Raman Spectra of Polypeptides and Proteins Using All-Atom Models.

The journal of physical chemistry letters 39966082
Infrared (IR) spectroscopy and Raman spectroscopy are powerful tools for probing protein and peptide structures due to their capability to provide molecular fingerprints. As a popular spectral simulation method, the quantum chemistry (QC) calculation...
Deep Learning Models, Molecular Peptides Proteins Quantum Theory Spectrophotometry, Infrared Spectrum Analysis, Raman
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Long-Range Electrostatics in Serine Proteases: Machine Learning-Driven Reaction Sampling Yields Insights for Enzyme Design.

Journal of chemical information and modeling 39928564
Computational enzyme design is a promising technique for producing novel enzymes for industrial and clinical needs. A key challenge that this technique faces is to consistently achieve the desired activity. Fundamental studies of natural enzymes reve...
Biocatalysis Catalytic Domain Machine Learning Models, Molecular Protein Engineering Quantum Theory Serine Proteases Static Electricity
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Machine Learning-Driven Quantum Sequencing of Natural and Chemically Modified DNA.

ACS applied materials & interfaces 40156522
Simultaneous identification of natural and chemically modified DNA nucleotides at molecular resolution remains a pivotal challenge in genomic science. Despite significant advances in current sequencing technologies, the ability to identify subtle cha...
DNA Graphite Machine Learning Nanopores Nucleotides Quantum Theory Sequence Analysis, DNA
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DeePMD-GNN: A DeePMD-kit Plugin for External Graph Neural Network Potentials.

Journal of chemical information and modeling 40150804
Machine learning potentials (MLPs) have revolutionized molecular simulation by providing efficient and accurate models for predicting atomic interactions. MLPs continue to advance and have had profound impact in applications that include drug discove...
Graph Neural Networks Molecular Dynamics Simulation Neural Networks, Computer Quantum Theory Software
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Predicting Fluorescence Emission Wavelengths and Quantum Yields via Machine Learning.

Journal of chemical information and modeling 40112343
The search for functional fluorescent organic materials can significantly benefit from the rapid and accurate predictions of photophysical properties. However, screening large numbers of potential fluorophore molecules in different solvents faces lim...
Fluorescence Fluorescent Dyes Machine Learning Quantum Theory
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QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials.

Journal of chemical information and modeling 40196990
Accurate prediction of protein-ligand binding affinities is crucial in drug discovery, particularly during hit-to-lead and lead optimization phases, however, limitations in ligand force fields continue to impact prediction accuracy. In this work, we ...
Ligands Molecular Dynamics Simulation Neural Networks, Computer Protein Binding Proteins Quantum Theory Thermodynamics
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