AIMC Topic: 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 Feb 27, 2025
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...
Ligands Molecular Conformation Thermodynamics Pharmaceutical Preparations Quantum Theory Machine Learning Density Functional Theory
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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 Feb 18, 2025
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...
Proteins Models, Molecular Quantum Theory Spectrophotometry, Infrared Deep Learning Spectrum Analysis, Raman Peptides
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A semiempirical and machine learning approach for fragment-based structural analysis of non-hydroxamate HDAC3 inhibitors.

Biophysical chemistry Feb 15, 2025
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 ...
Molecular Structure Molecular Dynamics Simulation Machine Learning Molecular Docking Simulation Thermodynamics Histone Deacetylase Inhibitors Quantum Theory Quantitative Structure-Activity Relationship Humans Histone Deacetylases
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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 Feb 10, 2025
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...
Quantum Theory Biocatalysis Machine Learning Models, Molecular Static Electricity Protein Engineering Catalytic Domain Serine Proteases
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Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data Augmentation.

Journal of chemical information and modeling Jan 28, 2025
In the field of computational chemistry, predicting bond dissociation energies (BDEs) presents well-known challenges, particularly due to the multireference character of reactive systems. Many chemical reactions involve configurations where single-re...
Quantum Theory Thermodynamics Machine Learning Methane
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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 Cytochrome P-450 CYP1A2 Humans Quantum Theory Deep Learning Protein Binding Cytochrome P-450 Enzyme System Drug Interactions
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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...
Graph Neural Networks Quantum Theory Neural Networks, Computer Thermodynamics Machine Learning
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Machine Learning Quantum Mechanical/Molecular Mechanical Potentials: Evaluating Transferability in Dihydrofolate Reductase-Catalyzed Reactions.

Journal of chemical theory and computation Jan 15, 2025
Integrating machine learning potentials (MLPs) with quantum mechanical/molecular mechanical (QM/MM) free energy simulations has emerged as a powerful approach for studying enzymatic catalysis. However, its practical application has been hindered by t...
Machine Learning Tetrahydrofolate Dehydrogenase Molecular Dynamics Simulation Biocatalysis Quantum Theory Thermodynamics
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Machine Learning Recognition of Artificial DNA Sequence with Quantum Tunneling Nanogap Junction.

The journal of physical chemistry. B Jan 9, 2025
Artificially synthesized DNA holds significant promise in addressing fundamental biochemical questions and driving advancements in biotechnology, genetics, and DNA digital data storage. Rapid and precise electric identification of these artificial DN...
Machine Learning DNA Quantum Theory
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Quantum mixed-state self-attention network.

Neural networks : the official journal of the International Neural Network Society Jan 8, 2025
Attention mechanisms have revolutionized natural language processing. Combining them with quantum computing aims to further advance this technology. This paper introduces a novel Quantum Mixed-State Self-Attention Network (QMSAN) for natural language...
Natural Language Processing Quantum Theory Attention Neural Networks, Computer Algorithms Humans
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