AIMC Topic: Quantum Theory

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A Machine Learning Protocol for Predicting Protein Infrared Spectra.

Journal of the American Chemical Society Oct 30, 2020
Infrared (IR) absorption provides important chemical fingerprints of biomolecules. Protein secondary structure determination from IR spectra is tedious since its theoretical interpretation requires repeated expensive quantum-mechanical calculations i...
Protein Structure, Secondary Protein Folding Ubiquitin Spectrophotometry, Infrared Temperature Peptides Machine Learning Amides Quantum Theory Proteins
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COSMO-RS-Based Descriptors for the Machine Learning-Enabled Screening of Nucleotide Analogue Drugs against SARS-CoV-2.

The journal of physical chemistry letters Oct 26, 2020
Chemical similarity-based approaches employed to repurpose or develop new treatments for emerging diseases, such as COVID-19, correlates molecular structure-based descriptors of drugs with those of a physiological counterpart or clinical phenotype. W...
Principal Component Analysis RNA, Viral SARS-CoV-2 Molecular Docking Simulation Coronavirus Infections Nucleotides Binding Sites Drug Evaluation, Preclinical Quantum Theory Humans Machine Learning Pandemics COVID-19 RNA-Dependent RNA Polymerase Betacoronavirus Pneumonia, Viral
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Site-Level Bioactivity of Small-Molecules from Deep-Learned Representations of Quantum Chemistry.

The journal of physical chemistry. A Oct 21, 2020
Atom- or bond-level chemical properties of interest in medicinal chemistry, such as drug metabolism and electrophilic reactivity, are important to understand and predict across arbitrary new molecules. Deep learning can be used to map molecular struc...
Quantum Theory Deep Learning Small Molecule Libraries
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Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications.

Journal of computer-aided molecular design Oct 9, 2020
Atomistic simulations have become an invaluable tool for industrial applications ranging from the optimization of protein-ligand interactions for drug discovery to the design of new materials for energy applications. Here we review recent advances in...
Machine Learning Pharmaceutical Preparations Drug Design Ligands Quantum Theory Drug Discovery Models, Molecular
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Neural Network Potential Energy Surfaces for Small Molecules and Reactions.

Chemical reviews Oct 6, 2020
We review progress in neural network (NN)-based methods for the construction of interatomic potentials from discrete samples (such as ab initio energies) for applications in classical and quantum dynamics including reaction dynamics and computational...
Algorithms Quantum Theory Chemistry Neural Networks, Computer
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Quantum machine learning using atom-in-molecule-based fragments selected on the fly.

Nature chemistry Sep 14, 2020
First-principles-based exploration of chemical space deepens our understanding of chemistry and might help with the design of new molecules, materials or experiments. Due to the computational cost of quantum chemistry methods and the immense number o...
Machine Learning Quantum Theory Organic Chemicals Molecular Structure
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Quantum neural networks model based on swap test and phase estimation.

Neural networks : the official journal of the International Neural Network Society Jul 8, 2020
In this paper, a neural networks model for quantum computer is proposed. The core of this model is quantum neuron. Firstly, the inner product of the input qubits and the weight qubits is mapped to the phase of the control qubits in the neuron by the ...
Neural Networks, Computer Quantum Theory
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The art of atom descriptor design.

Drug discovery today. Technologies Jul 3, 2020
This review provides an overview of descriptions of atoms applied to the understanding of phenomena like chemical reactivity and selectivity, pK values, Site of Metabolism prediction, or hydrogen bond strengths, but also the substitution of quantum m...
Pharmaceutical Preparations Quantum Theory Humans Machine Learning Drug Discovery
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Improving the binding affinity estimations of protein-ligand complexes using machine-learning facilitated force field method.

Journal of computer-aided molecular design Mar 17, 2020
Scoring functions are routinely deployed in structure-based drug design to quantify the potential for protein-ligand (PL) complex formation. Here, we present a new scoring function Bappl+ that is designed to predict the binding affinities of non-meta...
Ligands Databases, Protein Quantum Theory Computational Biology Proteins Metals Machine Learning Protein Binding Drug Design
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Finding Reactive Configurations: A Machine Learning Approach for Estimating Energy Barriers Applied to Sirtuin 5.

Journal of chemical theory and computation Nov 25, 2019
Sirtuin 5 is a class III histone deacetylase that, unlike its classification, mainly catalyzes desuccinylation and demanoylation reactions. It is an interesting drug target that we use here to test new ideas for calculating reaction pathways of large...
Protein Conformation Molecular Dynamics Simulation Sirtuins Thermodynamics Quantum Theory Humans Machine Learning
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