Main Article Content
Abstract
This study aims to predict structural stability changes and to identify the molecular determinants of ligand-bromodomain complex interactions that undergo mutations in the ligand binding site (LBS) using computational chemistry methods. The stability changes of the complexes were investigated using Molecular Dynamics (MD) simulations during a 25 ns production run. The identification of molecular interaction determinants was performed by decoding the interaction fingerprint, utilizing the output of trajectory data of the MD simulations, which were converted into a series of pdb files along the time step. The system preparations were done using CHARMM-GUI. The MD simulations were carried out using the GROMACS program. Protein-ligand interaction fingerprints (PLIF) were identified using the PyPLIF-HIPPOS program. This study successfully predicted the stability of both wild-type and mutated ligand-bromodomain complex structures, where the W81A mutation led to a decrease in complex stability. The key residues and non-hydrophobic interaction types responsible for the stabilities were identified as TRP81 aromatic edge-to-face, TYR139 aromatic edge-to-face, and TYR139 aromatic face-to-face.
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References
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- Zhao, J., Cao, Y., & Zhang, L. (2020). Exploring the computational methods for protein-ligand binding site prediction. Computational and Structural Biotechnology Journal, 18, 417. https://doi.org/10.1016/J.CSBJ.2020.02.008
References
Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindah, E. (2015). GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1–2, 19–25. https://doi.org/10.1016/J.SOFTX.2015.06.001
Ammar, A., Cavill, R., Evelo, C., & Willighagen, E. (2022). PSnpBind: a database of mutated binding site protein–ligand complexes constructed using a multithreaded virtual screening workflow. Journal of Cheminformatics, 14(1), 1–16. https://doi.org/10.1186/S13321-021-00573-5/TABLES/4
Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., Shindyalov, I. N., & Bourne, P. E. (2000). The Protein Data Bank. Nucleic Acids Research, 28(1), 235–242. https://doi.org/10.1093/NAR/28.1.235
Bosserman, M. A., Downey, T., Noinaj, N., Buchanan, S. K., & Rohr, J. (2013). Molecular Insight into Substrate Recognition and Catalysis of Baeyer–Villiger Monooxygenase MtmOIV, the Key Frame Modifying Enzyme in the Biosynthesis of Anticancer Agent Mithramycin. ACS Chemical Biology, 8(11), 2466–2477. https://doi.org/10.1021/CB400399B
Boyson, S. P., Gao, C., Quinn, K., Boyd, J., Paculova, H., Frietze, S., & Glass, K. C. (2021). Functional roles of bromodomain proteins in cancer. Cancers, 13(14). https://doi.org/10.3390/CANCERS13143606/S1
Brand, L. J., & Dehm, S. M. (2013). Androgen Receptor Gene Rearrangements: New Perspectives on Prostate Cancer Progression. Current Drug Targets, 14(4), 441. https://doi.org/10.2174/1389450111314040005
Cochran, A. G., Conery, A. R., & Sims, R. J. (2019). Bromodomains: a new target class for drug development. Nature Reviews Drug Discovery 2019 18:8, 18(8), 609–628. https://doi.org/10.1038/s41573-019-0030-7
Istyastono, E. P., Radifar, M., Yuniarti, N., Prasasty, V. D., & Mungkasi, S. (2020). PyPLIF HIPPOS: A Molecular Interaction Fingerprinting Tool for Docking Results of AutoDock Vina and PLANTS. Journal of Chemical Information and Modeling, 60(8), 3697–3702. https://doi.org/10.1021/acs.jcim.0c00305
Istyastono, E. P., & Riswanto, F. D. O. (2022). Molecular Dynamics Simulations of The Caffeic Acid Interactions to Dipeptidyl Peptidase IV. International Journal of Applied Pharmaceutics, 274–278. https://doi.org/10.22159/ijap.2022v14i4.44631
Jo, S., Kim, T., Iyer, V. G., & Im, W. (2008). CHARMM-GUI: A web-based graphical user interface for CHARMM. Journal of Computational Chemistry, 29(11), 1859–1865. https://doi.org/10.1002/JCC.20945
Jung, M., Philpott, M., Müller, S., Schulze, J., Badock, V., Eberspächer, U., Moosmayer, D., Bader, B., Schmees, N., Fernández-Montalván, A., & Haendler, B. (2014). Affinity Map of Bromodomain Protein 4 (BRD4) Interactions with the Histone H4 Tail and the Small Molecule Inhibitor JQ1. The Journal of Biological Chemistry, 289(13), 9304. https://doi.org/10.1074/JBC.M113.523019
Kim, P., Zhao, J., Lu, P., & Zhao, Z. (2017). mutLBSgeneDB: mutated ligand binding site gene DataBase. Nucleic Acids Research, 45(Database issue), D256. https://doi.org/10.1093/NAR/GKW905
Lee, J., Cheng, X., Swails, J. M., Yeom, M. S., Eastman, P. K., Lemkul, J. A., Wei, S., Buckner, J., Jeong, J. C., Qi, Y., Jo, S., Pande, V. S., Case, D. A., Brooks, C. L., MacKerell, A. D., Klauda, J. B., & Im, W. (2016). CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field. Journal of Chemical Theory and Computation, 12(1), 405–413. https://doi.org/10.1021/ACS.JCTC.5B00935/ASSET/IMAGES/LARGE/CT-2015-00935E_0005.JPEG
Lee, J., Hitzenberger, M., Rieger, M., Kern, N. R., Zacharias, M., & Im, W. (2020). CHARMM-GUI supports the Amber force fields. The Journal of Chemical Physics, 153(3), 035103. https://doi.org/10.1063/5.0012280
McKeown, M. R., Shaw, D. L., Fu, H., Liu, S., Xu, X., Marineau, J. J., Huang, Y., Zhang, X., Buckley, D. L., Kadam, A., Zhang, Z., Blacklow, S. C., Qi, J., Zhang, W., & Bradner, J. E. (2014). Biased multicomponent reactions to develop novel bromodomain inhibitors. Journal of Medicinal Chemistry, 57(21), 9019–9027. https://doi.org/10.1021/JM501120Z
Muller, S., Filippakopoulos, P., & Knapp, S. (2011). Bromodomains as therapeutic targets. Expert Reviews in Molecular Medicine, 13, e29. https://doi.org/10.1017/S1462399411001992
Sandy, J., Holton, S., Fullam, E., Sim, E., & Noble, M. (2005). Binding of the anti-tubercular drug isoniazid to the arylamine N-acetyltransferase protein from Mycobacterium smegmatis. Protein Science : A Publication of the Protein Society, 14(3), 775. https://doi.org/10.1110/PS.041163505
Stenson, P. D., Ball, E. V., Mort, M., Phillips, A. D., Shiel, J. A., Thomas, N. S. T., Abeysinghe, S., Krawczak, M., & Cooper, D. N. (2003). Human Gene Mutation Database (HGMD): 2003 update. Human Mutation, 21(6), 577–581. https://doi.org/10.1002/HUMU.10212
Taniguchi, Y. (2016). The Bromodomain and Extra-Terminal Domain (BET) Family: Functional Anatomy of BET Paralogous Proteins. International Journal of Molecular Sciences, 17(11). https://doi.org/10.3390/IJMS17111849
Yu, Y., Wang, J., Shao, Q., Shi, J., & Zhu, W. (2015). Effects of drug-resistant mutations on the dynamic properties of HIV-1 protease and inhibition by Amprenavir and Darunavir. Scientific Reports 2015 5:1, 5(1), 1–14. https://doi.org/10.1038/srep10517
Zaware, N., & Zhou, M. M. (2019). Bromodomain biology and drug discovery. Nature Structural and Molecular Biology, 26(10), 870–879. https://doi.org/10.1038/S41594-019-0309-8/
Zhao, J., Cao, Y., & Zhang, L. (2020). Exploring the computational methods for protein-ligand binding site prediction. Computational and Structural Biotechnology Journal, 18, 417. https://doi.org/10.1016/J.CSBJ.2020.02.008