Insight into Discovery of Next Generation Reversible TMLR Inhibitors Targeting EGFR Activating and Drug Resistant T790M Mutants
Author:
Affiliation:
1. Bioinformatics Division, ICMR-Institute of Cytology and Preventive Oncology, I-7, Sector-39, Noida-201301, India
Publisher
Bentham Science Publishers Ltd.
Subject
Cancer Research,Drug Discovery,Pharmacology,Oncology
Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Machine Learning, Molecular Docking, and Dynamics-Based Computational Identification of Potential Inhibitors against Lung Cancer;ACS Omega;2024-01-17
2. A systematic pipeline of protein structure selection for computer‐aided drug discovery: A case study on T790M/L858R mutant EGFR structures;Protein Science;2023-08-22
3. Exploring binding stability of hydroxy-3-(4-hydroxyphenyl)-5-(4-nitrophenyl)-5,5a,7,8,9,9a-hexahydrothiazolo[2,3-b] quinazolin-6-one with T790M/L858R EGFR-TKD;Journal of Biomolecular Structure and Dynamics;2022-03-28
4. Computational identification of natural product inhibitors against EGFR double mutant (T790M/L858R) by integrating ADMET, machine learning, molecular docking and a dynamics approach;RSC Advances;2022
5. TMLRpred: A machine learning classification model to distinguish reversible EGFR double mutant inhibitors;Chemical Biology & Drug Design;2020-09
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