Graph convolutional network approach to investigate potential selective Limk1 inhibitors-Reference-Cited by-同舟云学术

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Graph convolutional network approach to investigate potential selective Limk1 inhibitors

Published:2021-09 Issue: Volume:107 Page:107965
ISSN:1093-3263
Container-title:Journal of Molecular Graphics and Modelling
language:en
Short-container-title:Journal of Molecular Graphics and Modelling

Author:

Zhong Weihe,Zhao Lu,Yang Ziduo,Yu-Chian Chen Calvin

Funder

Sun Yat-sen University

China Medical University Hospital

Guangzhou Municipal Science and Technology Project

Science, Technology and Innovation Commission of Shenzhen Municipality

Publisher

Elsevier BV

Subject

Materials Chemistry,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Spectroscopy

Reference62 articles.

1. New tricks for old drugs;Nosengo;Nature,2016

2. Cancer research in the United States: a critical review of current status and proposal for alternative models;Kantarjian;Cancer,2018

3. Structure-based virtual screening for drug discovery: principles, applications and recent advances;Lionta;Curr. Top. Med. Chem.,2014

4. Beware of docking!;Chen;Trends Pharmacol. Sci.,2015

5. Docking and scoring in virtual screening for drug discovery: methods and applications;Kitchen;Nat. Rev. Drug Discov.,2004

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1. Practical Three-Component Regioselective Synthesis of Drug-Like 3-Aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnolines as Potential Non-Covalent Multi-Targeting Inhibitors To Combat Neurodegenerative Diseases;ACS Chemical Neuroscience;2024-04-22

2. Machine Learning Empowering Drug Discovery: Applications, Opportunities and Challenges;Molecules;2024-02-18

3. Computer especially AI-assisted drug virtual screening and design in traditional Chinese medicine;Phytomedicine;2022-12

4. Pharmacophore-based virtual screening, molecular docking and molecular dynamics simulations study for the identification of LIM kinase-1 inhibitors;Journal of Biomolecular Structure and Dynamics;2022-07-21

5. MolNet: A Chemically Intuitive Graph Neural Network for Prediction of Molecular Properties;Chemistry – An Asian Journal;2022-07-20

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