Identification of curcumin derivatives as human LMTK3 inhibitors for breast cancer: a docking, dynamics, and MM/PBSA approach
- PMID: 29719770
- PMCID: PMC5924428
- DOI: 10.1007/s13205-018-1239-6
Identification of curcumin derivatives as human LMTK3 inhibitors for breast cancer: a docking, dynamics, and MM/PBSA approach
Abstract
Human lemur tyrosine kinase-3 (LMTK3) is primarily involved in regulation of estrogen receptor-α (ERα) by phosphorylation activity. LMTK3 acts as key biomarker for ERα positive breast cancer and identified as novel drug target for breast cancer. Due to the absence of experimental reports, the computational approach has been followed to screen LMTK3 inhibitors from natural product curcumin derivatives based on rational inhibitor design. The initial virtual screening and re-docking resulted in identification of top three leads with favorable binding energy and strong interactions in critical residues of ATP-binding cavity. ADME prediction confirmed the pharmacological activity of the leads with various properties. The stability and binding affinity of leads were well refined in dynamic system from 25 ns MD simulations. The behavior of protein motion towards closure of ATP-binding cavity was evaluated based on eigenvectors by PCA. In addition, MM/PBSA calculations also confirmed the relative binding free energy of LMTK3-lead complexes in favor of the effective binding. From our study, novel LMTK3 inhibitors tetrahydrocurcumin, curcumin 4,4'-diacetate, and demethoxycurcumin have been proposed with inhibition mechanism. Further experimental evaluation on reported lead candidates might prove its role in breast cancer therapeutics.
Keywords: Free energy calculation; LMTK3; Molecular dynamics simulation; Principal component analysis; Virtual screening.
Conflict of interest statement
Compliance with ethical standardsThe authors declare no conflict of interest.
Figures
![Fig. 1](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/5924428/bin/13205_2018_1239_Fig1_HTML.gif)
![Fig. 2](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/5924428/bin/13205_2018_1239_Fig2_HTML.gif)
![Fig. 3](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/5924428/bin/13205_2018_1239_Fig3_HTML.gif)
![Fig. 4](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/5924428/bin/13205_2018_1239_Fig4_HTML.gif)
![Fig. 5](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/5924428/bin/13205_2018_1239_Fig5_HTML.gif)
![Fig. 6](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/5924428/bin/13205_2018_1239_Fig6_HTML.gif)
Similar articles
-
Chemoinformatics and machine learning techniques to identify novel inhibitors of the lemur tyrosine kinase-3 receptor involved in breast cancer.Front Mol Biosci. 2024 Apr 4;11:1366763. doi: 10.3389/fmolb.2024.1366763. eCollection 2024. Front Mol Biosci. 2024. PMID: 38638686 Free PMC article.
-
Designing and optimization of novel human LMTK3 inhibitors against breast cancer - a computational approach.J Recept Signal Transduct Res. 2017 Feb;37(1):51-59. doi: 10.3109/10799893.2016.1155069. Epub 2016 Apr 8. J Recept Signal Transduct Res. 2017. PMID: 27056562
-
Structural modeling and molecular dynamics studies on the human LMTK3 domain and the mechanism of ATP binding.Mol Biosyst. 2014 May;10(5):1139-45. doi: 10.1039/c4mb00063c. Mol Biosyst. 2014. PMID: 24619340
-
Structure-Based Virtual Screening of High-Affinity ATP-Competitive Inhibitors Against Human Lemur Tyrosine Kinase-3 (LMTK3) Domain: A Novel Therapeutic Target for Breast Cancer.Interdiscip Sci. 2019 Sep;11(3):527-541. doi: 10.1007/s12539-018-0302-7. Epub 2018 Jul 31. Interdiscip Sci. 2019. PMID: 30066129
-
The multifaceted role of lemur tyrosine kinase 3 in health and disease.Open Biol. 2021 Sep;11(9):210218. doi: 10.1098/rsob.210218. Epub 2021 Sep 29. Open Biol. 2021. PMID: 34582708 Free PMC article. Review.
Cited by
-
The search for an antiviral lead molecule to combat the neglected emerging Oropouche virus.Curr Res Microb Sci. 2024 Apr 27;6:100238. doi: 10.1016/j.crmicr.2024.100238. eCollection 2024. Curr Res Microb Sci. 2024. PMID: 38745914 Free PMC article.
-
Chemoinformatics and machine learning techniques to identify novel inhibitors of the lemur tyrosine kinase-3 receptor involved in breast cancer.Front Mol Biosci. 2024 Apr 4;11:1366763. doi: 10.3389/fmolb.2024.1366763. eCollection 2024. Front Mol Biosci. 2024. PMID: 38638686 Free PMC article.
-
A combination of virtual screening, molecular dynamics simulation, MM/PBSA, ADMET, and DFT calculations to identify a potential DPP4 inhibitor.Sci Rep. 2024 Apr 2;14(1):7749. doi: 10.1038/s41598-024-58485-x. Sci Rep. 2024. PMID: 38565703 Free PMC article.
-
Identification of Potent Acetylcholinesterase Inhibitors as New Candidates for Alzheimer Disease via Virtual Screening, Molecular Docking, Dynamic Simulation, and Molecular Mechanics-Poisson-Boltzmann Surface Area Calculations.Molecules. 2024 Mar 10;29(6):1232. doi: 10.3390/molecules29061232. Molecules. 2024. PMID: 38542869 Free PMC article.
-
Acridones as promising drug candidates against Oropouche virus.Curr Res Microb Sci. 2023 Dec 23;6:100217. doi: 10.1016/j.crmicr.2023.100217. eCollection 2024. Curr Res Microb Sci. 2023. PMID: 38234431 Free PMC article.
References
-
- Berendsen HJC, van der Spoel D, van Drunen R. Gromacs: a message-passing parallel molecular dynamics implementation. Comput Phys Commun. 1995;91:43–56. doi: 10.1016/0010-4655(95)00042-E. - DOI
LinkOut - more resources
Full Text Sources
Other Literature Sources
Miscellaneous