AIMC Topic: Drug Evaluation, Preclinical

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Development of Simplified in Vitro P-Glycoprotein Substrate Assay and in Silico Prediction Models To Evaluate Transport Potential of P-Glycoprotein.

Molecular pharmaceutics Apr 16, 2019
For efficient drug discovery and screening, it is necessary to simplify P-glycoprotein (P-gp) substrate assays and to provide in silico models that predict the transport potential of P-gp. In this study, we developed a simplified in vitro screening m...
Central Nervous System Agents Transfection Biological Availability Swine ATP Binding Cassette Transporter, Subfamily B, Member 1 Machine Learning Drug Evaluation, Preclinical Computer Simulation Intestinal Absorption Reproducibility of Results ATP Binding Cassette Transporter, Subfamily B Animals LLC-PK1 Cells Drug Discovery Data Accuracy Cell Membrane Permeability Protein Transport
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Improved Method of Structure-Based Virtual Screening via Interaction-Energy-Based Learning.

Journal of chemical information and modeling Mar 18, 2019
Virtual screening is a promising method for obtaining novel hit compounds in drug discovery. It aims to enrich potentially active compounds from a large chemical library for further biological experiments. However, the accuracy of current virtual scr...
User-Computer Interface Proteins Drug Evaluation, Preclinical Machine Learning Molecular Docking Simulation Cheminformatics Ligands Protein Conformation Thermodynamics
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De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping.

Journal of chemical information and modeling Mar 5, 2019
Here we show that Generative Topographic Mapping (GTM) can be used to explore the latent space of the SMILES-based autoencoders and generate focused molecular libraries of interest. We have built a sequence-to-sequence neural network with Bidirection...
Molecular Docking Simulation Drug Design Receptor, Adenosine A2A Ligands Catalytic Domain Small Molecule Libraries Deep Learning Drug Evaluation, Preclinical
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DeepChemStable: Chemical Stability Prediction with an Attention-Based Graph Convolution Network.

Journal of chemical information and modeling Feb 21, 2019
In the drug discovery process, unstable compounds in storage can lead to false positive or false negative bioassay conclusions. Prediction of the chemical stability of a compound by de novo methods is complex. Chemical instability prediction is commo...
Deep Learning Drug Evaluation, Preclinical Drug Stability Computer Graphics Cheminformatics
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Discovering highly selective and diverse PPAR-delta agonists by ligand based machine learning and structural modeling.

Scientific reports Jan 31, 2019
PPAR-δ agonists are known to enhance fatty acid metabolism, preserving glucose and physical endurance and are suggested as candidates for treating metabolic diseases. None have reached the clinic yet. Our Machine Learning algorithm called "Iterative ...
PPAR delta Databases, Protein Drug Evaluation, Preclinical Metabolic Diseases Machine Learning Molecular Docking Simulation Humans
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Prediction of Membrane Permeation of Drug Molecules by Combining an Implicit Membrane Model with Machine Learning.

Journal of chemical information and modeling Dec 27, 2018
Lipid membrane permeation of drug molecules was investigated with Heterogeneous Dielectric Generalized Born (HDGB)-based models using solubility-diffusion theory and machine learning. Free energy profiles were obtained for neutral molecules by the st...
Machine Learning Thermodynamics Models, Biological Drug Evaluation, Preclinical Cell Membrane Permeability
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Dry olive leaf extract attenuates DNA damage induced by estradiol and diethylstilbestrol in human peripheral blood cells in vitro.

Mutation research. Genetic toxicology and environmental mutagenesis Dec 21, 2018
Phenolic groups of steroidal or nonsteroidal estrogens can redox cycle, leading to oxidative stress, where creation of reactive oxygen species are recognized as the main mechanism of their DNA damage properties. Dry olive (Olea europaea L.) leaf extr...
DNA Damage Drug Evaluation, Preclinical Young Adult Oxidative Stress Olea Adult Estradiol Estrogen Antagonists Plant Leaves Male Antioxidants Free Radical Scavengers Oxidation-Reduction Humans Plant Extracts Blood Cells Female Dose-Response Relationship, Drug Comet Assay Reactive Oxygen Species Diethylstilbestrol
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Predicting tumor cell line response to drug pairs with deep learning.

BMC bioinformatics Dec 21, 2018
BACKGROUND: The National Cancer Institute drug pair screening effort against 60 well-characterized human tumor cell lines (NCI-60) presents an unprecedented resource for modeling combinational drug activity.
National Cancer Institute (U.S.) Cell Line, Tumor United States Drug Evaluation, Preclinical Neural Networks, Computer Deep Learning Humans
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Practical Model Selection for Prospective Virtual Screening.

Journal of chemical information and modeling Dec 18, 2018
Virtual (computational) high-throughput screening provides a strategy for prioritizing compounds for experimental screens, but the choice of virtual screening algorithm depends on the data set and evaluation strategy. We consider a wide range of liga...
Molecular Docking Simulation User-Computer Interface Proteins Drug Evaluation, Preclinical Protein Conformation Machine Learning Algorithms
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Exploring Alternative Strategies for the Identification of Potent Compounds Using Support Vector Machine and Regression Modeling.

Journal of chemical information and modeling Dec 14, 2018
Support vector regression (SVR) is a premier approach for the prediction of compound potency. Given the conceptual link between support vector machine (SVM) and SVR modeling, SVR is capable of accounting for continuous and discontinuous structure-act...
Support Vector Machine Regression Analysis Drug Evaluation, Preclinical Quantitative Structure-Activity Relationship
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