Optimizing the binding of OGT and a peptidic substrate towards pseudo-substrate inhibitors via molecular dynamic simulations

Xinfang Qin, Jie Shi, Xia Li, Mingming Lu, Yating Zhu, Qiyuan Yang, Zhimeng Wu, Cheng Lu

Systems Microbiology and Biomanufacturing ›› 2023, Vol. 4 ›› Issue (1) : 165-174. DOI: 10.1007/s43393-023-00168-1
Original Article

Optimizing the binding of OGT and a peptidic substrate towards pseudo-substrate inhibitors via molecular dynamic simulations

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Abstract

Elevated O-GlcNAcylation has been shown to be closely correlated with the occurrence and development of cancer, and inhibiting O-GlcNAc transferase (OGT) activity was demonstrated as a potential tumor treatment strategy. However, the development of pharmacological OGT inhibitors still faces challenges, such as low affinity and poor selectivity. Considering to OGT preferences for the sequence of its peptidic substrates, we herein integrated molecular dynamics simulation approaches to give deep insights into the binding behaviors between OGT and its peptidic substrate ZO3S1, and discussed the unfavorable inter-residue contacts inside the binding pocket, especially between H509 of OGT and S15 of the peptide, upon temperature increase. Removing this unfavorable contact from the peptide (ZO3S1 with S15A mutation) was shown to be able to increase its interaction with OGT, which was manifested by the enhanced OGT activity against this peptide. The pseudo-substrate peptide (ZO3S1 with S13A and S15A mutations) inhibited the activity of purified OGT with an IC50 of 192.9 μM and it can also inhibit the total O-GlcNAcylation in cancer cell lines in a concentration-dependent manner. Our results provided useful models and basis for further rational optimization of selective OGT inhibitors based on the dynamic interactions of OGT and its peptidic substrates.

Keywords

OGT / O-GlcNAcylation / Peptidic substrates / Molecular dynamics simulation / Inhibitors

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Xinfang Qin, Jie Shi, Xia Li, Mingming Lu, Yating Zhu, Qiyuan Yang, Zhimeng Wu, Cheng Lu. Optimizing the binding of OGT and a peptidic substrate towards pseudo-substrate inhibitors via molecular dynamic simulations. Systems Microbiology and Biomanufacturing, 2023, 4(1): 165‒174 https://doi.org/10.1007/s43393-023-00168-1

References

[1]
Shi J, et al.. Peptide microarray analysis of the cross-talk between O-GlcNAcylation and tyrosine phosphorylation. FEBS Lett, 2017, 591(13): 1872-1883,
CrossRef Google scholar
[2]
Kakade PS, et al.. Functional implications of O-GlcNAcylation-dependent phosphorylation at a proximal site on keratin 18. J Biol Chem, 2016, 291(23): 12003-12013,
CrossRef Google scholar
[3]
Xie S, et al.. O-GlcNAcylation of protein kinase A catalytic subunits enhances its activity: a mechanism linked to learning and memory deficits in Alzheimer's disease. Aging Cell, 2016, 15(3): 455-464,
CrossRef Google scholar
[4]
Nie H, et al.. O-GlcNAcylation of PGK1 coordinates glycolysis and TCA cycle to promote tumor growth. Nat Commun, 2020, 11(1): 36,
CrossRef Google scholar
[5]
Myers SA, et al.. SOX2 O-GlcNAcylation alters its protein-protein interactions and genomic occupancy to modulate gene expression in pluripotent cells. Elife, 2016, 5,
CrossRef Google scholar
[6]
Masclef L, et al.. Cyclin D1 stability is partly controlled by O-GlcNAcylation. Front Endocrinol (Lausanne), 2019, 10: 106,
CrossRef Google scholar
[7]
Chen Y, et al.. O-GlcNAcylation enhances NUSAP1 stability and promotes bladder cancer aggressiveness. Onco Targets Ther, 2021, 14: 445-454,
CrossRef Google scholar
[8]
Inoue Y, et al.. Elevated O-GlcNAcylation stabilizes FOXM1 by its reduced degradation through GSK-3beta inactivation in a human gastric carcinoma cell line, MKN45 cells. Biochem Biophys Res Commun, 2018, 495(2): 1681-1687,
CrossRef Google scholar
[9]
Gu Y, et al.. O-GlcNAcylation is increased in prostate cancer tissues and enhances malignancy of prostate cancer cells. Mol Med Rep, 2014, 10(2): 897-904,
CrossRef Google scholar
[10]
Phueaouan T, et al.. Aberrant O-GlcNAc-modified proteins expressed in primary colorectal cancer. Oncol Rep, 2013, 30(6): 2929-2936,
CrossRef Google scholar
[11]
Champattanachai V, et al.. Proteomic analysis and abrogated expression of O-GlcNAcylated proteins associated with primary breast cancer. Proteomics, 2013, 13(14): 2088-2099,
CrossRef Google scholar
[12]
Efimova EV, et al.. O-GlcNAcylation enhances double-strand break repair, promotes cancer cell proliferation, and prevents therapy-induced senescence in irradiated tumors. Mol Cancer Res, 2019, 17(6): 1338-1350,
CrossRef Google scholar
[13]
Yu M, et al.. O-GlcNAcylation of ITGA5 facilitates the occurrence and development of colorectal cancer. Exp Cell Res, 2019, 382(2),
CrossRef Google scholar
[14]
Luanpitpong S, et al.. Hyper-O-GlcNAcylation induces cisplatin resistance via regulation of p53 and c-Myc in human lung carcinoma. Sci Rep, 2017, 7(1): 10607,
CrossRef Google scholar
[15]
Akella NM, et al.. O-GlcNAc transferase regulates cancer stem-like potential of breast cancer cells. Mol Cancer Res, 2020, 18(4): 585-598,
CrossRef Google scholar
[16]
Xu D, et al.. Increased expression of O-GlcNAc transferase (OGT) is a biomarker for poor prognosis and allows tumorigenesis and invasion in colon cancer. Int J Clin Exp Pathol, 2019, 12(4): 1305-1314
[17]
Barkovskaya A, et al.. O-GlcNAc transferase inhibition differentially affects breast cancer subtypes. Sci Rep, 2019, 9(1): 5670,
CrossRef Google scholar
[18]
Xia M, et al.. Inhibition of O-GlcNAc transferase sensitizes prostate cancer cells to docetaxel. Front Oncol, 2022, 12,
CrossRef Google scholar
[19]
Liu Y, et al.. Suppression of OGT by microRNA24 reduces FOXA1 stability and prevents breast cancer cells invasion. Biochem Biophys Res Commun, 2017, 487(3): 755-762,
CrossRef Google scholar
[20]
Trapannone R, Rafie K, van Aalten DM. O-GlcNAc transferase inhibitors: current tools and future challenges. Biochem Soc Trans, 2016, 44(1): 88-93,
CrossRef Google scholar
[21]
Alteen MG, Tan HY, Vocadlo DJ. Monitoring and modulating O-GlcNAcylation: assays and inhibitors of O-GlcNAc processing enzymes. Curr Opin Struct Biol, 2021, 68: 157-165,
CrossRef Google scholar
[22]
Martin SES, et al.. Structure-based evolution of low nanomolar O-GlcNAc transferase inhibitors. J Am Chem Soc, 2018, 140(42): 13542-13545,
CrossRef Google scholar
[23]
Ortiz-Meoz RF, et al.. A small molecule that inhibits OGT activity in cells. ACS Chem Biol, 2015, 10(6): 1392-1397,
CrossRef Google scholar
[24]
Rafie K, et al.. Thio-linked UDP-peptide conjugates as O-GlcNAc transferase inhibitors. Bioconjug Chem, 2018, 29(6): 1834-1840,
CrossRef Google scholar
[25]
Zhang H, et al.. Inhibition of O-GlcNAc transferase (OGT) by peptidic hybrids. Medchemcomm, 2018, 9(5): 883-887,
CrossRef Google scholar
[26]
Pathak S, et al.. The active site of O-GlcNAc transferase imposes constraints on substrate sequence. Nat Struct Mol Biol, 2015, 22(9): 744-750,
CrossRef Google scholar
[27]
Shi J, et al.. Activity based high-throughput screening for novel O-GlcNAc transferase substrates using a dynamic peptide microarray. PLoS ONE, 2016, 11(3),
CrossRef Google scholar
[28]
Pronk S, et al.. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics, 2013, 29(7): 845-854,
CrossRef Google scholar
[29]
Lindorff-Larsen K, et al.. Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins, 2010, 78(8): 1950-1958,
CrossRef Google scholar
[30]
Bussi G, Donadio D, Parrinello M. Canonical sampling through velocity rescaling. J Chem Phys, 2007, 126(1),
CrossRef Google scholar
[31]
Berendsen HJC, et al.. Molecular dynamics with coupling to an external bath. J Chem Phys, 1984, 81(8): 3684-3690,
CrossRef Google scholar
[32]
Darden T, York D, Pedersen L. Particle mesh Ewald: an N⋅log(N) method for Ewald sums in large systems. J Chem Phys, 1993, 98(12): 10089-10092,
CrossRef Google scholar
[33]
Ryckaert J-P, Ciccotti G, Berendsen HJC. Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J Comput Phys, 1977, 23(3): 327-341,
CrossRef Google scholar
[34]
Lu C, Stock G, Knecht V. Mechanisms for allosteric activation of protease DegS by ligand binding and oligomerization as revealed from molecular dynamics simulations. Proteins, 2016, 84(11): 1690-1705,
CrossRef Google scholar
[35]
Berezovska G, et al.. Accounting for the kinetics in order parameter analysis: lessons from theoretical models and a disordered peptide. J Chem Phys, 2012, 137(19),
CrossRef Google scholar
[36]
Rao F, Spichty M. Thermodynamics and kinetics of large-time-step molecular dynamics. J Comput Chem, 2012, 33(5): 475-483,
CrossRef Google scholar
[37]
Moglich A, Joder K, Kiefhaber T. End-to-end distance distributions and intrachain diffusion constants in unfolded polypeptide chains indicate intramolecular hydrogen bond formation. Proc Natl Acad Sci U S A, 2006, 103(33): 12394-12399,
CrossRef Google scholar
[38]
Bieri O, et al.. The speed limit for protein folding measured by triplet-triplet energy transfer. Proc Natl Acad Sci U S A, 1999, 96(17): 9597-9601,
CrossRef Google scholar
[39]
Lu C, Knecht V, Stock G. Long-range conformational response of a PDZ domain to ligand binding and release: a molecular dynamics study. J Chem Theory Comput, 2016, 12(2): 870-878,
CrossRef Google scholar
[40]
Lazarus MB, et al.. Structural snapshots of the reaction coordinate for O-GlcNAc transferase. Nat Chem Biol, 2012, 8(12): 966-968,
CrossRef Google scholar
[41]
Jorgensen WL, et al.. Comparison of simple potential functions for simulating liquid water. J Chem Phys, 1983, 79(2): 926-935,
CrossRef Google scholar

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