AIMC Journal:
Journal of chemical information and modeling

Showing 491 to 500 of 953 articles

Modified Electrostatic Complementary Score Function and Its Application Boundary Exploration in Drug Design.

Journal of chemical information and modeling Sep 7, 2022
In recent years, machine learning (ML) models have been found to quickly predict various molecular properties with accuracy comparable to high-level quantum chemistry methods. One such example is the calculation of electrostatic potential (ESP). Diff...
Machine Learning Drug Design Ligands Static Electricity
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Multitask Deep Neural Networks for Ames Mutagenicity Prediction.

Journal of chemical information and modeling Sep 6, 2022
The Ames mutagenicity test constitutes the most frequently used assay to estimate the mutagenic potential of drug candidates. While this test employs experimental results using various strains of , the vast majority of the published in silico models ...
Neural Networks, Computer Computer Simulation Reproducibility of Results Mutagens Mutagenesis Mutagenicity Tests
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gr Predictor: A Deep Learning Model for Predicting the Hydration Structures around Proteins.

Journal of chemical information and modeling Sep 6, 2022
Among the factors affecting biological processes such as protein folding and ligand binding, hydration, which is represented by a three-dimensional water site distribution function around the protein, is crucial. The typical methods for computing the...
Deep Learning Water Proteins Molecular Dynamics Simulation Ligands Thermodynamics
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SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning.

Journal of chemical information and modeling Aug 31, 2022
Machine learning as a tool for chemical space exploration broadens horizons to work with known and unknown molecules. At its core lies molecular representation, an essential key to improve learning about structure-property relationships. Recently, co...
Machine Learning
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Editorial on Machine Learning.

Journal of chemical information and modeling Aug 31, 2022
Artificial Intelligence Machine Learning
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-Complex-Based Machine Learning (HCML) for the Prediction of Protein-Protein Binding Affinity Changes upon Mutation.

Journal of chemical information and modeling Aug 30, 2022
Protein-protein interactions (PPIs) are involved in almost all biological processes in the cell. Understanding protein-protein interactions holds the key for the understanding of biological functions, diseases and the development of therapeutics. Rec...
Humans Artificial Intelligence Machine Learning COVID-19 SARS-CoV-2 Protein Binding Mutation
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Determination of Molecule Category of Ligands Targeting the Ligand-Binding Pocket of Nuclear Receptors with Structural Elucidation and Machine Learning.

Journal of chemical information and modeling Aug 30, 2022
The mechanism of transcriptional activation/repression of the nuclear receptors (NRs) involves two main conformations of the NR protein, namely, the active (agonistic) and inactive (antagonistic) conformations. Binding of agonists or antagonists to t...
Machine Learning Ligands Receptors, Cytoplasmic and Nuclear Binding Sites
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Correlated RNN Framework to Quickly Generate Molecules with Desired Properties for Energetic Materials in the Low Data Regime.

Journal of chemical information and modeling Aug 23, 2022
Motivated by the challenging of deep learning on the low data regime and the urgent demand for intelligent design on highly energetic materials, we explore a correlated deep learning framework, which consists of three recurrent neural networks (RNNs)...
Neural Networks, Computer Software Explosive Agents
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Predicting Total Drug Clearance and Volumes of Distribution Using the Machine Learning-Mediated Multimodal Method through the Imputation of Various Nonclinical Data.

Journal of chemical information and modeling Aug 22, 2022
Pharmacokinetic research plays an important role in the development of new drugs. Accurate predictions of human pharmacokinetic parameters are essential for the success of clinical trials. Clearance (CL) and volume of distribution (Vd) are important ...
Humans Machine Learning Animals Pharmaceutical Preparations Models, Biological Drug Elimination Routes
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Investigation of a Data Split Strategy Involving the Time Axis in Adverse Event Prediction Using Machine Learning.

Journal of chemical information and modeling Aug 16, 2022
Adverse events are a serious issue in drug development, and many prediction methods using machine learning have been developed. The random split cross-validation is the de facto standard for model building and evaluation in machine learning, but care...
Machine Learning Algorithms Forecasting Drug-Related Side Effects and Adverse Reactions Datasets as Topic
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