ArticleBMC bioinformatics2015
EGFR Mutant Structural Database: computationally predicted 3D structures and the corresponding binding free energies with gefitinib and erlotinib.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 38 citations in OpenAlex.
- Machine learning based personalized drug response prediction for lung cancer patients.Scientific reports · 2022Article
- Uncovering the Mechanism of Drug Resistance Caused by the T790M Mutation in EGFR Kinase From Absolute Binding Free Energy Calculations.Frontiers in molecular biosciences · 2022Article
- Genotype-determined EGFR-RTK heterodimerization and its effects on drug resistance in lung Cancer treatment revealed by molecular dynamics simulations.BMC molecular and cell biology · 2021Article
- Predicting the impacts of mutations on protein-ligand binding affinity based on molecular dynamics simulations and machine learning methods.Computational and structural biotechnology journal · 2020Article
- Molecular dynamics simulation-guided drug sensitivity prediction for lung cancer with rareProceedings of the National Academy of Sciences of the United States of America · 2019Article
- Altered conformational landscape and dimerization dependency underpins the activation of EGFR byProceedings of the National Academy of Sciences of the United States of America · 2018Article
- Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis.BMC bioinformatics · 2018Article
- Deciphering mechanisms of acquired T790M mutation after EGFR inhibitors for NSCLC by computational simulations.Scientific reports · 2017Article
- Computational and Experimental Characterization of Patient Derived Mutations Reveal an Unusual Mode of Regulatory Spine Assembly and Drug Sensitivity in EGFR Kinase.Biochemistry · 2017Article
- Selective Targeting of the L858R Mutation (EGFR) in Non-Small Cell Lung Cancer: A Mechanism for Advancing Targeted Chemotherapy.Frontiers in oncology · 2017Article
- Different EGFR Gene Mutations in Exon 18, 19 and 21 as Prognostic and Predictive Markers in NSCLC: A Single Institution Analysis.Molecular diagnosis & therapy · 2016Article
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEpidermal growth factor receptor (EGFR) mutation-induced drug resistance has caused great difficulties in the treatment of non-small-cell lung cancer (NSCLC). However, structural information is available for just a few EGFR mutants. In this study, we created an EGFR Mutant Structural Database (freely available at http://bcc.ee.cityu.edu.hk/data/EGFR.html ), including the 3D EGFR mutant structures and their corresponding binding free energies with two commonly used inhibitors (gefitinib and erlotinib).
resultsWe collected the information of 942 NSCLC patients belonging to 112 mutation types. These mutation types are divided into five groups (insertion, deletion, duplication, modification and substitution), and substitution accounts for 61.61% of the mutation types and 54.14% of all the patients. Among all the 942 patients, 388 cases experienced a mutation at residue site 858 with leucine replaced by arginine (L858R), making it the most common mutation type. Moreover, 36 (32.14%) mutation types occur at exon 19, and 419 (44.48%) patients carried a mutation at exon 21. In this study, we predicted the EGFR mutant structures using Rosetta with the collected mutation types. In addition, Amber was employed to refine the structures followed by calculating the binding free energies of mutant-drug complexes.
conclusionsThe EGFR Mutant Structural Database provides resources of 3D structures and the binding affinity with inhibitors, which can be used by other researchers to study NSCLC further and by medical doctors as reference for NSCLC treatment.
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