AIMC Topic: Quantum Theory

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Substrate Activation Efficiency in Active Sites of Hydrolases Determined by QM/MM Molecular Dynamics and Neural Networks.

International journal of molecular sciences May 26, 2025
The active sites of enzymes are able to activate substrates and perform chemical reactions that cannot occur in solutions. We focus on the hydrolysis reactions catalyzed by enzymes and initiated by the nucleophilic attack of the substrate's carbonyl ...
Substrate Specificity Catalytic Domain Hydrolases Quantum Theory Hydrolysis Neural Networks, Computer Molecular Dynamics Simulation
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On the Difficulty to Rescore Hits from Ultralarge Docking Screens.

Journal of chemical information and modeling May 22, 2025
Docking-based virtual screening tools customized to mine ultralarge chemical spaces are consistently reported to yield both higher hit rates and more potent ligands than that achieved by conventional docking of smaller million-sized compound librarie...
Machine Learning Molecular Docking Simulation Drug Evaluation, Preclinical Quantum Theory Protein Binding Proteins Ligands
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QMGBP-DL: a deep learning and machine learning approach for quantum molecular graph band-gap prediction.

Molecular diversity Apr 19, 2025
Predicting molecular and quantum material properties, especially the band gap, is crucial for accelerating discoveries in drug design and material science. Although graph neural networks and probabilistic encoders are well established in molecular da...
Machine Learning Quantum Theory Deep Learning Neural Networks, Computer
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QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials.

Journal of chemical information and modeling Apr 8, 2025
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 ...
Thermodynamics Proteins Molecular Dynamics Simulation Quantum Theory Ligands Neural Networks, Computer Protein Binding
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Exploring quantum neural networks for binary classification on MNIST dataset: A swap test approach.

Neural networks : the official journal of the International Neural Network Society Apr 4, 2025
In this study, we propose a novel modularized Quantum Neural Network (mQNN) model tailored to address the binary classification problem on the MNIST dataset. The mQNN organizes input information using quantum images and trainable quantum parameters e...
Neurons Neural Networks, Computer Quantum Theory
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Machine Learning-Driven Quantum Sequencing of Natural and Chemically Modified DNA.

ACS applied materials & interfaces Mar 29, 2025
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...
Quantum Theory Nucleotides Graphite Nanopores Sequence Analysis, DNA DNA Machine Learning
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DeePMD-GNN: A DeePMD-kit Plugin for External Graph Neural Network Potentials.

Journal of chemical information and modeling Mar 27, 2025
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 Mar 20, 2025
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...
Quantum Theory Machine Learning Fluorescence Fluorescent Dyes
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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...
Quantum Theory Ligands Density Functional Theory Molecular Conformation Machine Learning Pharmaceutical Preparations 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 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...
Deep Learning Spectrum Analysis, Raman Peptides Quantum Theory Spectrophotometry, Infrared Proteins Models, Molecular
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