AIMC Topic: Molecular Conformation

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Picture-word order compound protein interaction: Predicting compound-protein interaction using structural images of compounds.

Journal of computational chemistry Nov 30, 2021
Identifying potential associations between proteins and compounds is significant and challenging in the drug discovery process. Existing deep-learning-based methods tend to treat compounds and proteins as sequences or graphs. Inspired by the rapid de...
Binding Sites Neural Networks, Computer Pharmaceutical Preparations Molecular Conformation Proteins
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Improvement of the Force Field for -d-Glucose with Machine Learning.

Molecules (Basel, Switzerland) Nov 5, 2021
While the construction of a dependable force field for performing classical molecular dynamics (MD) simulation is crucial for elucidating the structure and function of biomolecular systems, the attempts to do this for glycans are relatively sparse co...
Algorithms Models, Theoretical Machine Learning Molecular Structure Molecular Dynamics Simulation Molecular Conformation Glucose Static Electricity
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Biomolecular simulation based machine learning models accurately predict sites of tolerability to the unnatural amino acid acridonylalanine.

Scientific reports Sep 15, 2021
The incorporation of unnatural amino acids (Uaas) has provided an avenue for novel chemistries to be explored in biological systems. However, the successful application of Uaas is often hampered by site-specific impacts on protein yield and solubilit...
Machine Learning Proteins Protein Biosynthesis Structure-Activity Relationship Amino Acids Models, Molecular Molecular Conformation
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Prediction of N chemical shifts by machine learning.

Magnetic resonance in chemistry : MRC Aug 30, 2021
We demonstrate the potential for machine learning systems to predict three-dimensional (3D)-relevant NMR properties beyond traditional H- and C-based data, with comparable accuracy to density functional theory (DFT) (but orders of magnitude faster)...
Magnetic Resonance Spectroscopy Machine Learning Molecular Conformation
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Nuclear Quantum Effect and Its Temperature Dependence in Liquid Water from Random Phase Approximation via Artificial Neural Network.

The journal of physical chemistry letters Jul 7, 2021
We report structural and dynamical properties of liquid water described by the random phase approximation (RPA) correlation together with the exact exchange energy (EXX) within density functional theory. By utilizing thermostated ring polymer molecul...
Quantum Theory Molecular Conformation Water Models, Molecular Neural Networks, Computer Temperature
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A multi-conformational virtual screening approach based on machine learning targeting PI3Kγ.

Molecular diversity Jun 23, 2021
Nowadays, more and more attention has been attracted to develop selective PI3Kγ inhibitors, but the unique structural features of PI3Kγ protein make it a very big challenge. In the present study, a virtual screening strategy based on machine learning...
Molecular Conformation Binding Sites Molecular Dynamics Simulation Protein Binding Drug Discovery Models, Molecular Ligands Machine Learning Structure-Activity Relationship Phosphoinositide-3 Kinase Inhibitors ROC Curve Molecular Structure Class Ib Phosphatidylinositol 3-Kinase Molecular Docking Simulation Databases, Pharmaceutical
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Learning the Exciton Properties of Azo-dyes.

The journal of physical chemistry letters Jun 22, 2021
The determination of electronic excited state (ES) properties is the cornerstone of theoretical photochemistry. Yet, traditional ES methods become impractical when applied to fairly large molecules, or when used on thousands of systems. Machine lear...
Azo Compounds Molecular Conformation Quantum Theory Machine Learning Coloring Agents Models, Molecular
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ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted Bioactivities.

Journal of chemical information and modeling Jun 21, 2021
Computational methods such as machine learning approaches have a strong track record of success in predicting the outcomes of in vitro assays. In contrast, their ability to predict in vivo endpoints is more limited due to the high number of parameter...
Machine Learning Liver Biological Assay Molecular Conformation
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Machine Learning Strategies When Transitioning between Biological Assays.

Journal of chemical information and modeling Jun 21, 2021
Machine learning is widely used in drug development to predict activity in biological assays based on chemical structure. However, the process of transitioning from one experimental setup to another for the same biological endpoint has not been exten...
Biological Assay Machine Learning Retrospective Studies Molecular Conformation
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Algebraic graph-assisted bidirectional transformers for molecular property prediction.

Nature communications Jun 10, 2021
The ability of molecular property prediction is of great significance to drug discovery, human health, and environmental protection. Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Although s...
Databases, Chemical Molecular Conformation Drug-Related Side Effects and Adverse Reactions Neural Networks, Computer Machine Learning Computer Simulation Hydrophobic and Hydrophilic Interactions Drug Discovery Blood-Brain Barrier Algorithms Pharmaceutical Preparations
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