AIMC Topic: Drug Evaluation, Preclinical
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Network-based screen in iPSC-derived cells reveals therapeutic candidate for heart valve disease.
Science (New York, N.Y.)
Dec 10, 2020
Mapping the gene-regulatory networks dysregulated in human disease would allow the design of network-correcting therapies that treat the core disease mechanism. However, small molecules are traditionally screened for their effects on one to several o...
Aortic Valve Stenosis
Aortic Valve
Drug Evaluation, Preclinical
Thiazoles
Disease Models, Animal
Mice, Inbred C57BL
Calcinosis
Induced Pluripotent Stem Cells
Receptor, Notch1
Haploinsufficiency
Aortic Valve Disease
Humans
Drug Discovery
Machine Learning
RNA-Seq
Gene Expression Regulation
Algorithms
Animals
Nitriles
Gene Regulatory Networks
Small Molecule Libraries
Mice
Analysis of Biological Screening Compounds with Single- or Multi-Target Activity via Diagnostic Machine Learning.
Biomolecules
Nov 27, 2020
Predicting compounds with single- and multi-target activity and exploring origins of compound specificity and promiscuity is of high interest for chemical biology and drug discovery. We present a large-scale analysis of compound promiscuity including...
HDAC3i-Finder: A Machine Learning-based Computational Tool to Screen for HDAC3 Inhibitors.
Molecular informatics
Nov 23, 2020
Histone deacetylase 3 (HDAC3) is a potential drug target for treatment of human diseases such as cancer, chronic inflammation, neurodegenerative diseases and diabetes. Machine learning (ML) as an essential cheminformatics approach has been widely use...
Virtual screening of anti-HIV1 compounds against SARS-CoV-2: machine learning modeling, chemoinformatics and molecular dynamics simulation based analysis.
Scientific reports
Nov 23, 2020
COVID-19 caused by the SARS-CoV-2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour. 3-chymotrypsin-like cysteine protease (3CLpro) enzyme is the vital molecular target against the SAR...
Comprehensive evaluation of the combined extracts of Epimedii Folium and Ligustri Lucidi Fructus for PMOP in ovariectomized rats based on MLP-ANN methods.
Journal of ethnopharmacology
Nov 8, 2020
ETHNOPHARMACOLOGICAL RELEVANCE: Kidney deficiency is the main pathogenesis of osteoporosis based on the theory of "kidney governing bones" in traditional Chinese medicine (TCM). Osteoporosis is a systemic disease; kidney deficiency influences the gro...
Virtual Screening for Reactive Natural Products and Their Probable Artifacts of Solvolysis and Oxidation.
Biomolecules
Oct 27, 2020
Chemically unstable natural products are prone to show their reactivity in the procedures of extraction, purification, or identification and turn into contaminants as so-called "artifacts". However, identification of artifacts requires considerable i...
COSMO-RS-Based Descriptors for the Machine Learning-Enabled Screening of Nucleotide Analogue Drugs against SARS-CoV-2.
The journal of physical chemistry letters
Oct 26, 2020
Chemical similarity-based approaches employed to repurpose or develop new treatments for emerging diseases, such as COVID-19, correlates molecular structure-based descriptors of drugs with those of a physiological counterpart or clinical phenotype. W...
Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies.
The journal of physical chemistry letters
Aug 14, 2020
The current pandemic demands a search for therapeutic agents against the novel coronavirus SARS-CoV-2. Here, we present an efficient computational strategy that combines machine learning (ML)-based models and high-fidelity ensemble docking studies to...
Machine learning classification can reduce false positives in structure-based virtual screening.
Proceedings of the National Academy of Sciences of the United States of America
Jul 15, 2020
With the recent explosion in the size of libraries available for screening, virtual screening is positioned to assume a more prominent role in early drug discovery's search for active chemical matter. In typical virtual screens, however, only about 1...
Probing the characteristics and biofunctional effects of disease-affected cells and drug response via machine learning applications.
Critical reviews in biotechnology
Jul 7, 2020
Drug-induced transformations in disease characteristics at the cellular and molecular level offers the opportunity to predict and evaluate the efficacy of pharmaceutical ingredients whilst enabling the optimal design of new and improved drugs with en...
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