AIMC Topic: Drug Evaluation, Preclinical
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Automated evaluation of tumor spheroid behavior in 3D culture using deep learning-based recognition.
Biomaterials
Mar 22, 2021
Three-dimensional in vitro tumor models provide more physiologically relevant responses to drugs than 2D models, but the lack of proper evaluation indices and the laborious quantitation of tumor behavior in 3D have limited the use of 3D tumor models ...
Artificial Intelligence Applied to the Rapid Identification of New Antimalarial Candidates with Dual-Stage Activity.
ChemMedChem
Mar 16, 2021
Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making ...
Screening of a novel free fatty acid receptor 1 (FFAR1) agonist peptide by phage display and machine learning based-amino acid substitution.
Biochemical and biophysical research communications
Mar 9, 2021
Free fatty acid receptor 1 (FFAR1 or GPR40) has attracted attention for the treatment of type 2 diabetes mellitus, and various small-molecule agonists have been developed. However, most FFAR1 agonists as well as endogenous ligands, such as linoleic a...
TranSynergy: Mechanism-driven interpretable deep neural network for the synergistic prediction and pathway deconvolution of drug combinations.
PLoS computational biology
Feb 12, 2021
Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. The fast-growing number of anti-cancer drugs has caused the experimental investigation of all drug combinations...
Predicting Potential SARS-COV-2 Drugs-In Depth Drug Database Screening Using Deep Neural Network Framework SSnet, Classical Virtual Screening and Docking.
International journal of molecular sciences
Feb 4, 2021
Severe Acute Respiratory Syndrome Corona Virus 2 has altered life on a global scale. A concerted effort from research labs around the world resulted in the identification of potential pharmaceutical treatments for CoVID-19 using existing drugs, as we...
Antiviral Agents
Spike Glycoprotein, Coronavirus
Drug Repositioning
Drug Evaluation, Preclinical
SARS-CoV-2
Molecular Docking Simulation
Drug Discovery
COVID-19 Drug Treatment
Angiotensin-Converting Enzyme 2
Databases, Pharmaceutical
Humans
COVID-19
Algorithms
Neural Networks, Computer
Machine Learning
Evaluating Deep Learning models for predicting ALK-5 inhibition.
PloS one
Jan 28, 2021
Computational methods have been widely used in drug design. The recent developments in machine learning techniques and the ever-growing chemical and biological databases are fertile ground for discoveries in this area. In this study, we evaluated the...
Prediction of pharmacological activities from chemical structures with graph convolutional neural networks.
Scientific reports
Jan 12, 2021
Many therapeutic drugs are compounds that can be represented by simple chemical structures, which contain important determinants of affinity at the site of action. Recently, graph convolutional neural network (GCN) models have exhibited excellent res...
Anti-senescent drug screening by deep learning-based morphology senescence scoring.
Nature communications
Jan 11, 2021
Advances in deep learning technology have enabled complex task solutions. The accuracy of image classification tasks has improved owing to the establishment of convolutional neural networks (CNN). Cellular senescence is a hallmark of ageing and is im...
Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2 leading to universal blueprints for vaccine designs.
Scientific reports
Dec 23, 2020
The global population is at present suffering from a pandemic of Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The goal of this study was to use artificial intellige...
Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening.
Molecules (Basel, Switzerland)
Dec 15, 2020
Beta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtaine...
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