ArticleScientific reports2013
Personalized prediction of EGFR mutation-induced drug resistance in lung cancer.
Article in Scientific reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- pSTAT3 transactivates EGFR in maintaining EGFR protein homeostasis and EGFR-TKI resistance.Acta biochimica et biophysica Sinica · 2024Article
- Implementation of Artificial Intelligence in Personalized Prognostic Assessment of Lung Cancer: A Narrative Review.Cancers · 2024Review
- D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer.Briefings in bioinformatics · 2024Article
- Multiomics-Based Feature Extraction and Selection for the Prediction of Lung Cancer Survival.International journal of molecular sciences · 2024Article
- Review
- Review
- Machine learning based personalized drug response prediction for lung cancer patients.Scientific reports · 2022Article
- Application of Artificial Intelligence in Lung Cancer.Cancers · 2022Review
- Multiomics and machine learning in lung cancer prognosis.Journal of thoracic disease · 2020Article
- 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
- Characterizing the Hot Spots Involved in RON-MSPβ Complex Formation UsingAdvanced pharmaceutical bulletin · 2017Article
- Identifying EGFR mutation-induced drug resistance based on alpha shape model analysis of the dynamics.Proteome science · 2016Article
- Classification of foodborne pathogens using near infrared (NIR) laser scatter imaging system with multivariate calibration.Scientific reports · 2015Article
- Understanding the molecular basis of EGFR kinase domain/MIG-6 peptide recognition complex using computational analyses.BMC bioinformatics · 2015Article
- Molecular determinants of drug-specific sensitivity for epidermal growth factor receptor (EGFR) exon 19 and 20 mutants in non-small cell lung cancer.Oncotarget · 2015Article
- EGFR Mutant Structural Database: computationally predicted 3D structures and the corresponding binding free energies with gefitinib and erlotinib.BMC bioinformatics · 2015Article
- Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
EGFR mutation-induced drug resistance has significantly impaired the potency of small molecule tyrosine kinase inhibitors in lung cancer treatment. Computational approaches can provide powerful and efficient techniques in the investigation of drug resistance. In our work, the EGFR mutation feature is characterized by the energy components of binding free energy (concerning the mutant-inhibitor complex), and we combine it with specific personal features for 168 clinical subjects to construct a personalized drug resistance prediction model. The 3D structure of an EGFR mutant is computationally predicted from its protein sequence, after which the dynamics of the bound mutant-inhibitor complex is simulated via AMBER and the binding free energy of the complex is calculated based on the dynamics. The utilization of extreme learning machines and leave-one-out cross-validation promises a successful identification of resistant subjects with high accuracy. Overall, our study demonstrates advantages in the development of personalized medicine/therapy design and innovative drug discovery.
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