Evaluation of SERMs as potential molecular inhibitors of PD-L1 in cancer immunotherapy

Cenk Serhan Özverel; Emine Erdag; Ahmet Özer Şehirli

Evaluation of SERMs as potential molecular inhibitors of PD-L1 in cancer immunotherapy

Abstract

Since the development of immune checkpoint drugs targeting PD-1 and PD-L1, cancer immunotherapy has advanced significantly. However, there are drawbacks to using monoclonal antibodies for this purpose, such as their high manufacturing costs and potential immunological side effects. Small molecule inhibitors, such as Selective Estrogen Receptor Modulators (SERMs) could offer a potential alternative for cancer immunotherapy targeting PD-L1. This study aimed to evaluate the binding energies and interactions of 17 selected SERMs with the PD-L1 protein using molecular docking, Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) calculations, and umbrella sampling methods, in comparison to benchmark PD-L1 inhibitors. Raloxifene emerged as the top-performing compound, demonstrating superior binding affinities (-85.80 ± 1.20 kJ/mol, MM/PBSA; -84.90 ± 1.10 kJ/mol, umbrella sampling) compared to the BMS series of known PD-L1 inhibitors and other SERMs. Interaction analyses highlighted significant stabilizing interactions between raloxifene and key PD-L1 residues. Other SERMs, such as lasofoxifene and ormeloxifene, also demonstrated competitive binding affinities, reinforcing the versatility of SERMs as potential PD-L1 inhibitors. This preliminary study underscored the promise of SERMs as effective and accessible alternatives in cancer immunotherapy. However, further experimental validation is warranted to establish their efficacy in preclinical and clinical settings in the future.

Keywords

Supporting Institution

Not Applicable

Project Number

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Ethical Statement

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Thanks

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References

[1] Abaza A, Sid Idris F, Anis Shaikh H, Vahora I, Moparthi KP, Al Rushaidi MT, Muddam MR, Obajeun OA, Jaramillo AP, Khan S. Programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1) immunotherapy: a promising breakthrough in cancer therapeutics. Cureus. 2023; 15: e44582. https://doi.org/10.7759/cureus.44582.
[2] Shiravand Y, Khodadadi F, Kashani SMA, Hosseini-Fard SR, Hosseini S, Sadeghirad H, Ladwa R, O'Byrne K, Kulasinghe A. Immune checkpoint inhibitors in cancer therapy. Curr Oncol. 2022; 29: 3044–3060. https://doi.org/10.3390/curroncol29050247.
[3] Dong Y, Sun Q, Zhang X. PD-1 and its ligands are important immune checkpoints in cancer. Oncotarget. 2017; 8: 2171–2186. https://doi.org/10.18632/oncotarget.13895.
[4] Mizuno R, Sugiura D, Shimizu K, Maruhashi T, Watada M, Okazaki IM, Okazaki T. PD-1 primarily targets TCR signal in the inhibition of functional T cell activation. Front Immunol. 2019; 10: 630. https://doi.org/10.3389/fimmu.2019.00630.
[5] Chen RY, Zhu YY, Shen YY, Xu QY, Tang HY, Cui NX, Jiang L, Dai XM, Chen WQ, Lin Q, Li XZ. The role of PD-1 signaling in health and immune-related diseases. Front Immunol. 2023; 14: 1163633. https://doi.org/10.3389/fimmu.2023.1163633.
[6] Javed SA, Najmi A, Ahsan W, Zoghebi K. Targeting PD-1/PD-L1 immune checkpoint inhibition for cancer immunotherapy: success and challenges. Front Immunol. 2024; 15: 1383456. https://doi.org/10.3389/fimmu.2024.1383456.
[7] Yin S, Chen Z, Chen D, Yan D. Strategies targeting PD-L1 expression and associated opportunities for cancer combination therapy. Theranostics. 2023; 13: 1520–1544. https://doi.org/10.7150/thno.80091.
[8] Skalniak L, Zak KM, Guzik K, Magiera K, Musielak B, Pachota M, Szelazek B, Kocik J, Grudnik P, Tomala M, Krzanik S, Pyrc K, Dömling A, Dubin G, Holak TA. Small-molecule inhibitors of PD-1/PD-L1 immune checkpoint alleviate the PD-L1-induced exhaustion of T-cells. Oncotarget. 2017; 8: 72167–72181. https://doi.org/10.18632/oncotarget.20050.

[9] Chen FF, Li Z, Ma D, Yu Q. Small-molecule PD-L1 inhibitor BMS1166 abrogates the function of PD-L1 by blocking its ER export. Oncoimmunology. 2020; 9: 1831153. https://doi.org/10.1080/2162402X.2020.1831153.
[10] Pickar JH, Boucher M, Morgenstern D. Tissue selective estrogen complex (TSEC): a review. Menopause. 2018; 25: 1033–1045. https://doi.org/10.1097/GME.0000000000001095.
[11] An KC. Selective estrogen receptor modulators. Asian Spine J. 2016; 10: 787–791. https://doi.org/10.4184/asj.2016.10.4.787.
[12] Abramenko N, Vellieux F, Veselá K, Kejík Z, Hajduch J, Masařík M, Babula P, Hoskovec D, Pacák K, Martásek P, Smetana K Jr, Jakubek M. Investigation of the potential effects of estrogen receptor modulators on immune checkpoint molecules. Sci Rep. 2024; 14: 3043. https://doi.org/10.1038/s41598-024-51804-2.
[13] Chopra C, Yodun T, Singh H, Singh B, Singh SK, Goutam U. Raloxifene, a SERM targets PD-L1: an in-silico study. Am J Transl Res. 2023; 15: 5206–5215. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10492081/.
[14] Swaby RF, Sharma CG, Jordan VC. SERMs for the treatment and prevention of breast cancer. Rev Endocr Metab Disord. 2007; 8: 229–239. https://doi.org/10.1007/s11154-007-9034-4
[15] Nath A, Sitruk-Ware R. Pharmacology and clinical applications of selective estrogen receptor modulators. Climacteric. 2009;12:188-205. https://doi.org/10.1080/13697130802657896
[16] Wolber G, Langer T. LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J Chem Inf Model. 2005; 45: 160–169. https://doi.org/10.1021/ci049885e.
[17] Sliwoski G, Kothiwale S, Meiler J, Lowe EW Jr. Computational methods in drug discovery. Pharmacol Rev. 2013; 66: 334–395. https://doi.org/10.1124/pr.112.007336.
[18] Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem. 2009; 30: 2785–2791. https://doi.org/10.1002/jcc.21256.
[19] Erdag E, Haskologlu IC, Mercan M, Abacioglu N, Sehirli AO. An in silico investigation: can melatonin serve as an adjuvant in NR1D1-linked chronotherapy for amyotrophic lateral sclerosis? Chronobiol Int. 2023; 40: 1395–1403. https://doi.org/10.1080/07420528.2023.2265476.
[20] Erdag E, Ersalici I, Ozverel CS. Friend or foe: association of Euphorbia spp. with Epstein–Barr virus and Burkitt’s lymphoma, an in silico approach. Future Virol. 2023; 18: 583–594. https://doi.org/10.2217/fvl-2023-0011.
[21] Jaillet L, Artemova S, Redon S. IM-UFF: extending the universal force field for interactive molecular modeling. J Mol Graph Model. 2017; 77: 350–362. https://doi.org/10.1016/j.jmgm.2017.08.023.
[22] Binkowski TA, Naghibzadeh S, Liang J. CASTp: computed atlas of surface topography of proteins. Nucleic Acids Res. 2003; 31: 3352–3355. https://doi.org/10.1093/nar/gkg512.
[23] Kohnke B, Kutzner C, Grubmüller H. A GPU-accelerated fast multipole method for GROMACS: performance and accuracy. J Chem Theory Comput. 2020; 16: 6938–6949. https://doi.org/10.1021/acs.jctc.0c00744.
[24] Vrahatis MN, Androulakis GS, Lambrinos JN, Magoulas GD. A class of gradient unconstrained minimization algorithms with adaptive stepsize. J Comput Appl Math. 2000; 114: 367–386. https://doi.org/10.1016/S0377-0427(00)00439-4.
[25] Ke Q, Gong X, Liao S, Duan C, Li L. Effects of thermostats/barostats on physical properties of liquids by molecular dynamics simulations. J Mol Liq. 2022; 365: 120116. https://doi.org/10.1016/j.molliq.2022.120116.
[26] Saito H, Nagao H, Nishikawa K, Kinugawa K. Molecular collective dynamics in solid para-hydrogen and ortho-deuterium: the Parrinello–Rahman-type path integral centroid molecular dynamics approach. J Chem Phys. 2003; 119: 953–963. https://doi.org/10.1063/1.1578512.
[27] You W, Tang Z, Chang CA. Potential mean force from umbrella sampling simulations: what can we learn and what is missed? J Chem Theory Comput. 2019; 15: 2433–2443. https://doi.org/10.1021/acs.jctc.8b01142.
[28] Ciura P, Smardz P, Spodzieja M, Sieradzan AK, Krupa P. Multilayered computational framework for designing peptide inhibitors of HVEM-LIGHT interaction. J Phys Chem B. 2024; 128: 6770–6785. https://doi.org/10.1021/acs.jpcb.4c02255.
[29] Homeyer N, Gohlke H. Free energy calculations by the molecular mechanics Poisson-Boltzmann surface area method. Mol Inform. 2012; 31: 114–122. https://doi.org/10.1002/minf.201100135.
[30] Namsoy E, Sadikoglu IS, Ozverel CS, Erdag E. Computational analysis of 3D printing: selecting the better among newly released materials. Eur J Oral Sci. 2024; 132: e12987. https://doi.org/10.1111/eos.12987.
[31] Budyak IL, Zhuravleva A, Gierasch LM. The role of aromatic-aromatic interactions in strand-strand stabilization of β-sheets. J Mol Biol. 2013; 425: 3522–3535. https://doi.org/10.1016/j.jmb.2013.06.030.
[32] Maximov PY, Lee TM, Jordan VC. The discovery and development of selective estrogen receptor modulators (SERMs) for clinical practice. Curr Clin Pharmacol. 2013; 8: 135–155. https://doi.org/10.2174/1574884711308020006.
[33] Jordan VC. Selective estrogen receptor modulation: concept and consequences in cancer. Cancer Cell. 2004; 5: 207–213. https://doi.org/10.1016/s1535-6108(04)00059-5.
[34] Zhang F, Wang SS. Narrative review on advancing breast cancer treatment: harnessing the power of PD-1/PD-L1 inhibitors for improved patient outcomes. Transl Breast Cancer Res. 2023; 5: 2. https://doi.org/10.21037/tbcr-23-23.
[35] Muszak D, Surmiak E, Plewka J, Magiera-Mularz K, Kocik-Krol J, Musielak B, Sala D, Kitel R, Stec M, Weglarczyk K, Siedlar M, Dömling A, Skalniak L, Holak TA. Terphenyl-based small-molecule inhibitors of programmed cell death-1/programmed death-ligand 1 protein-protein interaction. J Med Chem. 2021; 64: 11614–11636. https://doi.org/10.1021/acs.jmedchem.1c00957.
[36] Surmiak E, Magiera-Mularz K, Musielak B, Muszak D, Kocik-Krol J, Kitel R, Plewka J, Holak TA, Skalniak L. PD-L1 inhibitors: different classes, activities, and mechanisms of action. Int J Mol Sci. 2021; 22: 11797. https://doi.org/10.3390/ijms222111797.
[37] Ostrowska N, Feig A, Trylska M. Modeling crowded environment in molecular simulations. Front Mol Biosci. 2019; 6: 86. https://doi.org/10.3389/fmolb.2019.00086.
[38] Shrestha R, Garrett-Thomson SC, Liu W, Almo SC, Fiser A. Redesigning HVEM interface for selective binding to LIGHT, BTLA, and CD160. Structure. 2020; 28: 1197–1205.e2. https://doi.org/10.1016/j.str.2020.07.013.

Details

Primary Language

English

Subjects

Basic Pharmacology

Journal Section

Research Article

Authors

Cenk Serhan Özverel
0000-0001-9932-4774
Türkiye

Emine Erdag ^*
Türkiye

Ahmet Özer Şehirli
0000-0002-5175-9290
Kuzey Kıbrıs Türk Cumhuriyeti

Publication Date

August 3, 2026

Submission Date

September 24, 2025

Acceptance Date

June 30, 2026

Published in Issue

Year 2026 Volume: 30 Number: 4

IZ

https://izlik.org/JA33ZF94ZS

Cite

RIS / Bibtex

APA

Özverel, C. S., Erdag, E., & Şehirli, A. Ö. (2026). Evaluation of SERMs as potential molecular inhibitors of PD-L1 in cancer immunotherapy. Journal of Research in Pharmacy, 30(4), 1157-1169. https://izlik.org/JA33ZF94ZS

AMA

1.Özverel CS, Erdag E, Şehirli AÖ. Evaluation of SERMs as potential molecular inhibitors of PD-L1 in cancer immunotherapy. J. Res. Pharm. 2026;30(4):1157-1169. https://izlik.org/JA33ZF94ZS

Chicago

Özverel, Cenk Serhan, Emine Erdag, and Ahmet Özer Şehirli. 2026. “Evaluation of SERMs As Potential Molecular Inhibitors of PD-L1 in Cancer Immunotherapy”. Journal of Research in Pharmacy 30 (4): 1157-69. https://izlik.org/JA33ZF94ZS.

EndNote

Özverel CS, Erdag E, Şehirli AÖ (August 1, 2026) Evaluation of SERMs as potential molecular inhibitors of PD-L1 in cancer immunotherapy. Journal of Research in Pharmacy 30 4 1157–1169.

IEEE

[1]C. S. Özverel, E. Erdag, and A. Ö. Şehirli, “Evaluation of SERMs as potential molecular inhibitors of PD-L1 in cancer immunotherapy”, J. Res. Pharm., vol. 30, no. 4, pp. 1157–1169, Aug. 2026, [Online]. Available: https://izlik.org/JA33ZF94ZS

ISNAD

Özverel, Cenk Serhan - Erdag, Emine - Şehirli, Ahmet Özer. “Evaluation of SERMs As Potential Molecular Inhibitors of PD-L1 in Cancer Immunotherapy”. Journal of Research in Pharmacy 30/4 (August 1, 2026): 1157-1169. https://izlik.org/JA33ZF94ZS.

JAMA

1.Özverel CS, Erdag E, Şehirli AÖ. Evaluation of SERMs as potential molecular inhibitors of PD-L1 in cancer immunotherapy. J. Res. Pharm. 2026;30:1157–1169.

MLA

Özverel, Cenk Serhan, et al. “Evaluation of SERMs As Potential Molecular Inhibitors of PD-L1 in Cancer Immunotherapy”. Journal of Research in Pharmacy, vol. 30, no. 4, Aug. 2026, pp. 1157-69, https://izlik.org/JA33ZF94ZS.

Vancouver

1.Cenk Serhan Özverel, Emine Erdag, Ahmet Özer Şehirli. Evaluation of SERMs as potential molecular inhibitors of PD-L1 in cancer immunotherapy. J. Res. Pharm. [Internet]. 2026 Aug. 1;30(4):1157-69. Available from: https://izlik.org/JA33ZF94ZS