Artificial intelligence in cancer target identification and drug discovery

Y You, X Lai, Y Pan, H Zheng, J Vera, S Liu… - … and Targeted Therapy, 2022 - nature.com
Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …

Drug repositioning: a brief overview

JP Jourdan, R Bureau, C Rochais… - Journal of Pharmacy …, 2020 - academic.oup.com
Objectives Drug repositioning, that is, the use of a drug in an indication other than the one
for which it was initially marketed, is a growing trend. Its origins lie mainly in the attrition …

Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases

AS Rifaioglu, H Atas, MJ Martin… - Briefings in …, 2019 - academic.oup.com
The identification of interactions between drugs/compounds and their targets is crucial for
the development of new drugs. In vitro screening experiments (ie bioassays) are frequently …

Drug repurposing for antimicrobial discovery

MA Farha, ED Brown - Nature microbiology, 2019 - nature.com
Antimicrobial resistance continues to be a public threat on a global scale. The ongoing need
to develop new antimicrobial drugs that are effective against multi-drug-resistant pathogens …

On the Integration of In Silico Drug Design Methods for Drug Repurposing

E March-Vila, L Pinzi, N Sturm, A Tinivella… - Frontiers in …, 2017 - frontiersin.org
Drug repurposing has become an important branch of drug discovery. Several
computational approaches that help to uncover new repurposing opportunities and aid the …

LRSSL: predict and interpret drug–disease associations based on data integration using sparse subspace learning

X Liang, P Zhang, L Yan, Y Fu, F Peng, L Qu… - …, 2017 - academic.oup.com
Motivation Exploring the potential curative effects of drugs is crucial for effective drug
development. Previous studies have indicated that integration of multiple types of …

Improving drug response prediction by integrating multiple data sources: matrix factorization, kernel and network-based approaches

B Güvenç Paltun, H Mamitsuka… - Briefings in …, 2021 - academic.oup.com
Predicting the response of cancer cell lines to specific drugs is one of the central problems in
personalized medicine, where the cell lines show diverse characteristics. Researchers have …

Drug repositioning through integration of prior knowledge and projections of drugs and diseases

P Xuan, Y Cao, T Zhang, X Wang, S Pan… - Bioinformatics, 2019 - academic.oup.com
Motivation Identifying and developing novel therapeutic effects for existing drugs contributes
to reduction of drug development costs. Most of the previous methods focus on integration of …

4-Hydroxyphenylpyruvate dioxygenase and its inhibition in plants and animals: small molecules as herbicides and agents for the treatment of human inherited …

A Santucci, G Bernardini, D Braconi… - Journal of Medicinal …, 2017 - ACS Publications
This review mainly focuses on the physiological function of 4-hydroxyphenylpyruvate
dioxygenase (HPPD), as well as on the development and application of HPPD inhibitors of …

Drug repurposing against breast cancer by integrating drug-exposure expression profiles and drug–drug links based on graph neural network

C Cui, X Ding, D Wang, L Chen, F Xiao, T Xu… - …, 2021 - academic.oup.com
Motivation Breast cancer is one of the leading causes of cancer deaths among women
worldwide. It is necessary to develop new breast cancer drugs because of the shortcomings …