Network pharmacology approach for medicinal plants: review and assessment
Natural products have played a critical role in medicine due to their ability to bind and
modulate cellular targets involved in disease. Medicinal plants hold a variety of bioactive …
modulate cellular targets involved in disease. Medicinal plants hold a variety of bioactive …
Machine learning approaches and databases for prediction of drug–target interaction: a survey paper
The task of predicting the interactions between drugs and targets plays a key role in the
process of drug discovery. There is a need to develop novel and efficient prediction …
process of drug discovery. There is a need to develop novel and efficient prediction …
Using MetaboAnalyst 4.0 for comprehensive and integrative metabolomics data analysis
Abstract MetaboAnalyst (https://www. metaboanalyst. ca) is an easy‐to‐use web‐based tool
suite for comprehensive metabolomic data analysis, interpretation, and integration with other …
suite for comprehensive metabolomic data analysis, interpretation, and integration with other …
DeepAffinity: interpretable deep learning of compound–protein affinity through unified recurrent and convolutional neural networks
Motivation Drug discovery demands rapid quantification of compound–protein interaction
(CPI). However, there is a lack of methods that can predict compound–protein affinity from …
(CPI). However, there is a lack of methods that can predict compound–protein affinity from …
Glabridin, a bioactive component of licorice, ameliorates diabetic nephropathy by regulating ferroptosis and the VEGF/Akt/ERK pathways
H Tan, J Chen, Y Li, Y Li, Y Zhong, G Li, L Liu, Y Li - Molecular Medicine, 2022 - Springer
Abstract Background Glabridin (Glab) is a bioactive component of licorice that can
ameliorate diabetes, but its role in diabetic nephropathy (DN) has seldom been reported …
ameliorate diabetes, but its role in diabetic nephropathy (DN) has seldom been reported …
Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling
Highlights•Drug discovery has been advanced to a big data era with a large amount of
public data sources available.•Ten V features (volume, velocity, variety, veracity, validity …
public data sources available.•Ten V features (volume, velocity, variety, veracity, validity …
BATMAN-TCM: a bioinformatics analysis tool for molecular mechANism of traditional Chinese medicine
Z Liu, F Guo, Y Wang, C Li, X Zhang, H Li, L Diao… - Scientific reports, 2016 - nature.com
Abstract Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical
practice, is gaining more and more attention and application worldwide. And TCM-based …
practice, is gaining more and more attention and application worldwide. And TCM-based …
[HTML][HTML] A guide to in silico drug design
Y Chang, BA Hawkins, JJ Du, PW Groundwater… - Pharmaceutics, 2023 - mdpi.com
The drug discovery process is a rocky path that is full of challenges, with the result that very
few candidates progress from hit compound to a commercially available product, often due …
few candidates progress from hit compound to a commercially available product, often due …
Multivariate genome-wide analysis of aging-related traits identifies novel loci and new drug targets for healthy aging
The concept of aging is complex, including many related phenotypes such as healthspan,
lifespan, extreme longevity, frailty and epigenetic aging, suggesting shared biological …
lifespan, extreme longevity, frailty and epigenetic aging, suggesting shared biological …
Resveratrol and its human metabolites—effects on metabolic health and obesity
M Springer, S Moco - Nutrients, 2019 - mdpi.com
Resveratrol is one of the most widely studied polyphenols and it has been assigned a
plethora of metabolic effects with potential health benefits. Given its low bioavailability and …
plethora of metabolic effects with potential health benefits. Given its low bioavailability and …