AIMC Topic: Quantum Theory

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Practical High-Quality Electrostatic Potential Surfaces for Drug Discovery Using a Graph-Convolutional Deep Neural Network.

Journal of medicinal chemistry Sep 25, 2019
Inspecting protein and ligand electrostatic potential (ESP) surfaces in order to optimize electrostatic complementarity is a key activity in drug design. These ESP surfaces need to reflect the true electrostatic nature of the molecules, which typical...
Quantum Theory Ligands Protein Binding Organic Chemicals Hydrogen Bonding Static Electricity X-Linked Inhibitor of Apoptosis Protein Datasets as Topic Factor Xa Drug Discovery Deep Learning
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Energy-Geometry Dependency of Molecular Structures: A Multistep Machine Learning Approach.

ACS combinatorial science Aug 21, 2019
There is growing interest in estimating quantum observables while circumventing expensive computational overhead for facile in silico materials screening. Machine learning (ML) methods are implemented to perform such calculations in shorter times. He...
Computer Simulation Organic Chemicals Molecular Structure Machine Learning Thermodynamics Small Molecule Libraries Inorganic Chemicals Ions Databases, Chemical Models, Chemical Quantum Theory
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PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments, and Partial Charges.

Journal of chemical theory and computation May 14, 2019
In recent years, machine learning (ML) methods have become increasingly popular in computational chemistry. After being trained on appropriate ab initio reference data, these methods allow for accurately predicting the properties of chemical systems,...
Protein Conformation Static Electricity Molecular Dynamics Simulation Quantum Theory Thermodynamics Algorithms Proteins Neural Networks, Computer
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Computational methods and tools to predict cytochrome P450 metabolism for drug discovery.

Chemical biology & drug design Jan 15, 2019
In this review, we present important, recent developments in the computational prediction of cytochrome P450 (CYP) metabolism in the context of drug discovery. We discuss in silico models for the various aspects of CYP metabolism prediction, includin...
Quantitative Structure-Activity Relationship Substrate Specificity Quantum Theory Cytochrome P-450 Enzyme System Computational Biology Pharmaceutical Preparations Machine Learning Drug Discovery
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Solvation Free Energy Calculations with Quantum Mechanics/Molecular Mechanics and Machine Learning Models.

The journal of physical chemistry. B Jan 15, 2019
For exploration of chemical and biological systems, the combined quantum mechanics and molecular mechanics (QM/MM) and machine learning (ML) models have been developed recently to achieve high accuracy and efficiency for molecular dynamics (MD) simul...
Solvents Thermodynamics Molecular Dynamics Simulation Quantum Theory Machine Learning
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Toward Building Protein Force Fields by Residue-Based Systematic Molecular Fragmentation and Neural Network.

Journal of chemical theory and computation Jan 7, 2019
Accurate force fields are crucial for molecular dynamics investigation of complex biological systems. Building accurate protein force fields from quantum mechanical (QM) calculations is challenging due to the complexity of proteins and high computati...
Peptides Proteins Neural Networks, Computer Dipeptides Static Electricity Thermodynamics Molecular Dynamics Simulation Quantum Theory Models, Chemical Amino Acids
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Nonnegative/Binary matrix factorization with a D-Wave quantum annealer.

PloS one Dec 10, 2018
D-Wave quantum annealers represent a novel computational architecture and have attracted significant interest. Much of this interest has focused on the quantum behavior of D-Wave machines, and there have been few practical algorithms that use the D-W...
Quantum Theory Machine Learning Models, Theoretical
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qTorch: The quantum tensor contraction handler.

PloS one Dec 10, 2018
Classical simulation of quantum computation is necessary for studying the numerical behavior of quantum algorithms, as there does not yet exist a large viable quantum computer on which to perform numerical tests. Tensor network (TN) contraction is an...
Stochastic Processes Equipment Design Quantum Theory Software Algorithms Neural Networks, Computer Computers Computer Simulation
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Quantum weighted long short-term memory neural network and its application in state degradation trend prediction of rotating machinery.

Neural networks : the official journal of the International Neural Network Society Jul 25, 2018
Classical long short-term memory neural network (LSTMNN) generally faces the challenges of poor generalization property and low training efficiency in state degradation trend prediction of rotating machinery. In this paper, a novel quantum neural net...
Quantum Theory Neural Networks, Computer Algorithms Forecasting
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Multiqubit and multilevel quantum reinforcement learning with quantum technologies.

PloS one Jul 19, 2018
We propose a protocol to perform quantum reinforcement learning with quantum technologies. At variance with recent results on quantum reinforcement learning with superconducting circuits, in our current protocol coherent feedback during the learning ...
Machine Learning Quantum Theory Reinforcement, Psychology
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