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Molecular Conformation

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Enhanced Deep-Learning Prediction of Molecular Properties via Augmentation of Bond Topology.

ChemMedChem Aug 23, 2019
Deep learning has made great strides in tackling chemical problems, but still lacks full-fledged representations for three-dimensional (3D) molecular structures for its inner working. For example, the molecular graph, commonly used in chemistry and r...
Ligands Datasets as Topic Deep Learning Models, Molecular Molecular Conformation
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Evaluation of different virtual screening strategies on the basis of compound sets with characteristic core distributions and dissimilarity relationships.

Journal of computer-aided molecular design Aug 21, 2019
In this work, computational compound screening strategies on the basis of two- and three-dimensional (2D and 3D) molecular representations were investigated including similarity searching and support vector machine (SVM) ranking. Calculations based o...
Protein Binding Support Vector Machine Machine Learning Molecular Conformation User-Computer Interface Computational Chemistry Structure-Activity Relationship
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A Scalable Molecular Force Field Parameterization Method Based on Density Functional Theory and Quantum-Level Machine Learning.

Journal of chemical information and modeling Aug 8, 2019
Fast and accurate molecular force field (FF) parameterization is still an unsolved problem. Accurate FF are not generally available for all molecules, like novel druglike molecules. While methods based on quantum mechanics (QM) exist to parameterize ...
Density Functional Theory Models, Molecular Molecular Conformation Neural Networks, Computer
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Targeting HIV/HCV Coinfection Using a Machine Learning-Based Multiple Quantitative Structure-Activity Relationships (Multiple QSAR) Method.

International journal of molecular sciences Jul 22, 2019
Human immunodeficiency virus type-1 and hepatitis C virus (HIV/HCV) coinfection occurs when a patient is simultaneously infected with both human immunodeficiency virus type-1 (HIV-1) and hepatitis C virus (HCV), which is common today in certain popul...
Molecular Structure Bayes Theorem Protein Binding Models, Molecular HIV-1 Molecular Conformation Quantitative Structure-Activity Relationship Hepacivirus Hepatitis C Algorithms Drug Discovery Anti-HIV Agents Antiviral Agents HIV Infections Humans Machine Learning Databases, Pharmaceutical Polypharmacology
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Predicting Reaction Products and Automating Reactive Trajectory Characterization in Molecular Simulations with Support Vector Machines.

Journal of chemical information and modeling May 15, 2019
A machine learning-based methodology for the prediction of chemical reaction products, along with automated elucidation of mechanistic details via phase space analysis of reactive trajectories, is introduced using low-dimensional heuristic models and...
Molecular Conformation Acetaldehyde Models, Molecular Automation Support Vector Machine
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Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods.

Chemical research in toxicology Apr 9, 2019
Saponins are a type of compounds bearing a hydrophobic steroid/triterpenoid moiety and hydrophilic carbohydrate branches. The majority of the saponins demonstrate a broad range of prominent pharmacological activities. Nevertheless, many saponins also...
Molecular Conformation Hemolysis Saponins Hydrophobic and Hydrophilic Interactions Erythrocytes Humans Machine Learning
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Drug Analogs from Fragment-Based Long Short-Term Memory Generative Neural Networks.

Journal of chemical information and modeling Apr 8, 2019
Several recent reports have shown that long short-term memory generative neural networks (LSTM) of the type used for grammar learning efficiently learn to write Simplified Molecular Input Line Entry System (SMILES) of druglike compounds when trained ...
Pharmaceutical Preparations Molecular Conformation Cheminformatics Neural Networks, Computer Models, Molecular
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Machine Learning Prediction of H Adsorption Energies on Ag Alloys.

Journal of chemical information and modeling Apr 2, 2019
Adsorption energies on surfaces are excellent descriptors of their chemical properties, including their catalytic performance. High-throughput adsorption energy predictions can therefore help accelerate first-principles catalyst design. To this end, ...
Machine Learning Molecular Conformation Alloys Adsorption Models, Molecular Hydrogen Thermodynamics Silver
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DeepIce: A Deep Neural Network Approach To Identify Ice and Water Molecules.

Journal of chemical information and modeling Mar 27, 2019
Computer simulation studies of multiphase systems rely on the accurate identification of local molecular structures and arrangements in order to extract useful insights. Local order parameters, such as Steinhardt parameters, are widely used for this ...
Molecular Conformation Ice Deep Learning Models, Molecular
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Shape-Based Generative Modeling for de Novo Drug Design.

Journal of chemical information and modeling Feb 28, 2019
In this work, we propose a machine learning approach to generate novel molecules starting from a seed compound, its three-dimensional (3D) shape, and its pharmacophoric features. The pipeline draws inspiration from generative models used in image ana...
Pharmaceutical Preparations Models, Molecular Quantitative Structure-Activity Relationship Machine Learning Molecular Conformation Hydrophobic and Hydrophilic Interactions Hydrogen Bonding Molecular Structure Drug Design
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