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Lomitapide as a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study

Year 2024, Volume: 10 Issue: 1, 8 - 14, 15.03.2024
https://doi.org/10.30934/kusbed.1347829

Abstract

Objective: Estrogen receptor (ER) inhibitors have significant therapeutic potential for hormone-dependent cancers and related disorders. Tamoxifen, a well-known selective estrogen receptor modulator, has been widely used as adjuvant therapy for estrogen receptor-positive breast cancer. However, tamoxifen may exhibit a tendency to develop resistance with prolonged usage and particularly elevate the risk of uterine cancer. Therefore, there is a need for the discovery and development of new ER modulators or inhibitors. In this study, we identified potential estrogen receptor inhibitors through computational drug repositioning.

Methods: A set of 2048 compounds, encompassing FDA-approved drugs and active metabolites, were subjected to molecular docking, molecular dynamics simulations, and free energy calculations to evaluate their interaction with estrogen receptor α (ERα).

Results: Among the compounds evaluated, conivaptan, atogepant, and lomitapide exhibited the highest affinities for ERα. Lomitapide displayed a superior docking score (-12 kcal/mol) compared to the established ER inhibitor, tamoxifen (-10 kcal/mol). Further investigation using molecular dynamics simulations and free energy calculations disclosed lomitapide's heightened binding affinity of -380.727 kJ/mol, surpassing tamoxifen's binding affinity of -352.029 kJ/mol.

Conclusion: This comprehensive computational exploration underscores lomitapide's potential as a compelling candidate with an envisaged stronger estrogen receptor affinity than the acknowledged standard, tamoxifen. To validate lomitapide's promise as a novel ER inhibitor, essential in vitro and in vivo studies are suggested. These investigations will provide essential insights into lomitapide's reposition in addressing the challenges tied to hormone-dependent cancers and associated maladies.

References

  • Hall JM, Couse JF, Korach KS. The Multifaceted Mechanisms of Estradiol and Estrogen Receptor Signaling. J Biol Chem. 2001;276(40). doi:10.1074/jbc.R100029200
  • Srinivasan S, Nawaz Z. Molecular biology of estrogen receptor action. In: Hormones, Brain and Behavior Online.; 2009. doi:10.1016/B978-008088783-8.00035-8
  • Patel HK, Bihani T. Selective estrogen receptor modulators (SERMs) and selective estrogen receptor degraders (SERDs) in cancer treatment. Pharmacol Ther. 2018;186:1-24. doi:10.1016/j.pharmthera.2017.12.012
  • Shagufta, Ahmad I. Tamoxifen a pioneering drug: An update on the therapeutic potential of tamoxifen derivatives. Eur J Med Chem. 2018;143:515-531. doi:10.1016/j.ejmech.2017.11.056
  • Visvanathan K, Fabian CJ, Bantug E, et al. Use of Endocrine Therapy for Breast Cancer Risk Reduction: ASCO Clinical Practice Guideline Update. J Clin Oncol. 2019;37(33):3152-3165. doi:10.1200/JCO.19.01472
  • Dar H, Johansson A, Nordenskjöld A, et al. Assessment of 25-Year Survival of Women with Estrogen Receptor-Positive/ ERBB2 -Negative Breast Cancer Treated with and without Tamoxifen Therapy: A Secondary Analysis of Data from the Stockholm Tamoxifen Randomized Clinical Trial. JAMA Netw Open. 2021;4(6). doi:10.1001/jamanetworkopen.2021.14904
  • Rosso R, D’Alonzo M, Bounous VE, et al. Adherence to Adjuvant Endocrine Therapy in Breast Cancer Patients. Curr Oncol. 2023;30(2). doi:10.3390/curroncol30020112
  • Xu X, Chlebowski RT, Shi J, Barac A, Haque R. Aromatase inhibitor and tamoxifen use and the risk of venous thromboembolism in breast cancer survivors. Breast Cancer Res Treat. 2019;174(3). doi:10.1007/s10549-018-05086-8
  • Zhang K, Jiang K, Hong R, et al. Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer. PeerJ. 2020;8. doi:10.7717/peerj.10468
  • Webb B, Sali A. Comparative protein structure modeling using MODELLER. Curr Protoc Bioinforma. 2016;54(1):5-6.
  • Pettersen EF, Goddard TD, Huang CC, et al. UCSF Chimera--A visualization system for exploratory research and analysis. J Comput Chem. 2004;25(13):1605-1612. doi:10.1002/jcc.20084
  • Douguet D. Data sets representative of the structures and experimental properties of FDA-approved drugs. ACS Med Chem Lett. 2018;9(3):204-209.
  • Samdani A, Vetrivel U. POAP: A GNU parallel based multithreaded pipeline of open babel and AutoDock suite for boosted high throughput virtual screening. Comput Biol Chem. 2018;74:39-48.
  • Alhossary A, Handoko SD, Mu Y, Kwoh C-K. Fast, accurate, and reliable molecular docking with QuickVina 2. Bioinformatics. 2015;31(13):2214-2216.
  • Huey R, Morris GM, Forli S. Using AutoDock 4 and AutoDock vina with AutoDockTools: a tutorial. Scripps Res Inst Mol Graph Lab. 2012;10550(92037):1000.
  • Goddard TD, Huang CC, Meng EC, et al. UCSF ChimeraX: Meeting modern challenges in visualization and analysis. Protein Sci. 2018;27(1):14-25.
  • Bell EW, Zhang Y. DockRMSD: an open-source tool for atom mapping and RMSD calculation of symmetric molecules through graph isomorphism. J Cheminform. 2019;11(1):1-9.
  • Sousa da Silva AW, Vranken WF. ACPYPE-Antechamber python parser interface. BMC Res Notes. 2012;5:1-8.
  • Jakalian A, Jack DB, Bayly CI. Fast, efficient generation of high‐quality atomic charges. AM1‐BCC model: II. Parameterization and validation. J Comput Chem. 2002;23(16):1623-1641.
  • Abraham MJ, Murtola T, Schulz R, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1:19-25.
  • Lindorff‐Larsen K, Piana S, Palmo K, et al. Improved side‐chain torsion potentials for the Amber ff99SB protein force field. Proteins Struct Funct Bioinforma. 2010;78(8):1950-1958.
  • Hess B, Bekker H, Berendsen HJC, Fraaije JGEM. LINCS: A linear constraint solver for molecular simulations. J Comput Chem. 1997;18(12):1463-1472.
  • Berendsen HJC, Postma JPM van, Van Gunsteren WF, DiNola A, Haak JR. Molecular dynamics with coupling to an external bath. J Chem Phys. 1984;81(8):3684-3690.
  • Martoňák R, Laio A, Parrinello M. Predicting Crystal Structures: The Parrinello-Rahman Method Revisited. Phys Rev Lett. 2003;90(7):4. doi:10.1103/PhysRevLett.90.075503
  • Kumari R, Kumar R, Consortium OSDD, Lynn A. g_mmpbsa A GROMACS tool for high-throughput MM-PBSA calculations. J Chem Inf Model. 2014;54(7):1951-1962.
  • Yu K, Huang ZY, Xu XL, Li J, Fu XW, Deng SL. Estrogen Receptor Function: Impact on the Human Endometrium. Front Endocrinol (Lausanne). 2022;13. doi:10.3389/fendo.2022.827724
  • Min J, Nwachukwu JC, Min CK, et al. Dual-mechanism estrogen receptor inhibitors. Proc Natl Acad Sci U S A. 2021;118(35). doi:10.1073/pnas.2101657118
  • Stefanutti C. Lomitapide–a Microsomal Triglyceride Transfer Protein Inhibitor for Homozygous Familial Hypercholesterolemia. Curr Atheroscler Rep. 2020;22(8). doi:10.1007/s11883-020-00858-4
  • Sen P, Kandasamy T, Ghosh SS. Multi-targeting TACE/ADAM17 and gamma-secretase of notch signalling pathway in TNBC via drug repurposing approach using Lomitapide. Cell Signal. 2023;102. doi:10.1016/j.cellsig.2022.110529
  • Lee B, Park SJ, Lee S, et al. Lomitapide, a cholesterol-lowering drug, is an anticancer agent that induces autophagic cell death via inhibiting mTOR. Cell Death Dis. 2022;13(7):603. doi:10.1038/s41419-022-05039-6
  • Wang Y, Zhang S, He H, et al. Repositioning Lomitapide to block ZDHHC5-dependant palmitoylation on SSTR5 leads to anti-proliferation effect in preclinical pancreatic cancer models. Cell Death Discov. 2023;9(1). doi:10.1038/s41420-023-01359-4
  • Zuo Q, Liao L, Yao ZT, et al. Targeting PP2A with lomitapide suppresses colorectal tumorigenesis through the activation of AMPK/Beclin1-mediated autophagy. Cancer Lett. 2021;521. doi:10.1016/j.canlet.2021.09.010
  • TilakVijay J, Babu KV, Uma A. Virtual screening of novel compounds as potential ER-alpha inhibitors. Bioinformation. 2019;15(5):321. doi:10.6026/97320630015321
  • Li-Ng M, Verbalis JG. Conivaptan: Evidence supporting its therapeutic use in hyponatremia. Core Evid. 2009;4. doi:10.2147/ce.s5997
  • Raftopoulos H. Diagnosis and management of hyponatremia in cancer patients. Support Care Cancer. 2007;15(12):1341-1347. doi:10.1007/S00520-007-0309-9/FIGURES/2
  • Ferraldeschi R, Sharifi N, Auchus RJ, Attard G. Molecular pathways: inhibiting steroid biosynthesis in prostate cancer. Clin cancer Res. 2013;19(13):3353-3359.
  • Dou D, Ji Y, Zheng J, et al. A New Role for Conivaptan in Ulcerative Colitis in Mice: Inhibiting Differentiation of CD4+ T Cells into Th1 Cells. Dig Dis Sci. Published online 2022:1-10.
  • Deeks ED. Atogepant: First Approval. Drugs. 2022;82(1):65-70. doi:10.1007/S40265-021-01644-5
  • Ankrom W, Xu J, Vallee M, et al. Atogepant Has No Clinically Relevant Effects on the Pharmacokinetics of an Ethinyl Estradiol/Levonorgestrel Oral Contraceptive in Healthy Female Participants. J Clin Pharmacol. 2020;60(9):1157-1165. doi:10.1002/jcph.1610
  • Berberich AJ, Hegele RA. Lomitapide for the treatment of hypercholesterolemia. Expert Opin Pharmacother. 2017;18(12):1261-1268.
  • Khan MI, Waguespack SG, Ahmed I. Recent advances in the management of hyponatremia in cancer patients. J Cancer Metastasis Treat. 2019;5:71.
Year 2024, Volume: 10 Issue: 1, 8 - 14, 15.03.2024
https://doi.org/10.30934/kusbed.1347829

Abstract

References

  • Hall JM, Couse JF, Korach KS. The Multifaceted Mechanisms of Estradiol and Estrogen Receptor Signaling. J Biol Chem. 2001;276(40). doi:10.1074/jbc.R100029200
  • Srinivasan S, Nawaz Z. Molecular biology of estrogen receptor action. In: Hormones, Brain and Behavior Online.; 2009. doi:10.1016/B978-008088783-8.00035-8
  • Patel HK, Bihani T. Selective estrogen receptor modulators (SERMs) and selective estrogen receptor degraders (SERDs) in cancer treatment. Pharmacol Ther. 2018;186:1-24. doi:10.1016/j.pharmthera.2017.12.012
  • Shagufta, Ahmad I. Tamoxifen a pioneering drug: An update on the therapeutic potential of tamoxifen derivatives. Eur J Med Chem. 2018;143:515-531. doi:10.1016/j.ejmech.2017.11.056
  • Visvanathan K, Fabian CJ, Bantug E, et al. Use of Endocrine Therapy for Breast Cancer Risk Reduction: ASCO Clinical Practice Guideline Update. J Clin Oncol. 2019;37(33):3152-3165. doi:10.1200/JCO.19.01472
  • Dar H, Johansson A, Nordenskjöld A, et al. Assessment of 25-Year Survival of Women with Estrogen Receptor-Positive/ ERBB2 -Negative Breast Cancer Treated with and without Tamoxifen Therapy: A Secondary Analysis of Data from the Stockholm Tamoxifen Randomized Clinical Trial. JAMA Netw Open. 2021;4(6). doi:10.1001/jamanetworkopen.2021.14904
  • Rosso R, D’Alonzo M, Bounous VE, et al. Adherence to Adjuvant Endocrine Therapy in Breast Cancer Patients. Curr Oncol. 2023;30(2). doi:10.3390/curroncol30020112
  • Xu X, Chlebowski RT, Shi J, Barac A, Haque R. Aromatase inhibitor and tamoxifen use and the risk of venous thromboembolism in breast cancer survivors. Breast Cancer Res Treat. 2019;174(3). doi:10.1007/s10549-018-05086-8
  • Zhang K, Jiang K, Hong R, et al. Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer. PeerJ. 2020;8. doi:10.7717/peerj.10468
  • Webb B, Sali A. Comparative protein structure modeling using MODELLER. Curr Protoc Bioinforma. 2016;54(1):5-6.
  • Pettersen EF, Goddard TD, Huang CC, et al. UCSF Chimera--A visualization system for exploratory research and analysis. J Comput Chem. 2004;25(13):1605-1612. doi:10.1002/jcc.20084
  • Douguet D. Data sets representative of the structures and experimental properties of FDA-approved drugs. ACS Med Chem Lett. 2018;9(3):204-209.
  • Samdani A, Vetrivel U. POAP: A GNU parallel based multithreaded pipeline of open babel and AutoDock suite for boosted high throughput virtual screening. Comput Biol Chem. 2018;74:39-48.
  • Alhossary A, Handoko SD, Mu Y, Kwoh C-K. Fast, accurate, and reliable molecular docking with QuickVina 2. Bioinformatics. 2015;31(13):2214-2216.
  • Huey R, Morris GM, Forli S. Using AutoDock 4 and AutoDock vina with AutoDockTools: a tutorial. Scripps Res Inst Mol Graph Lab. 2012;10550(92037):1000.
  • Goddard TD, Huang CC, Meng EC, et al. UCSF ChimeraX: Meeting modern challenges in visualization and analysis. Protein Sci. 2018;27(1):14-25.
  • Bell EW, Zhang Y. DockRMSD: an open-source tool for atom mapping and RMSD calculation of symmetric molecules through graph isomorphism. J Cheminform. 2019;11(1):1-9.
  • Sousa da Silva AW, Vranken WF. ACPYPE-Antechamber python parser interface. BMC Res Notes. 2012;5:1-8.
  • Jakalian A, Jack DB, Bayly CI. Fast, efficient generation of high‐quality atomic charges. AM1‐BCC model: II. Parameterization and validation. J Comput Chem. 2002;23(16):1623-1641.
  • Abraham MJ, Murtola T, Schulz R, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1:19-25.
  • Lindorff‐Larsen K, Piana S, Palmo K, et al. Improved side‐chain torsion potentials for the Amber ff99SB protein force field. Proteins Struct Funct Bioinforma. 2010;78(8):1950-1958.
  • Hess B, Bekker H, Berendsen HJC, Fraaije JGEM. LINCS: A linear constraint solver for molecular simulations. J Comput Chem. 1997;18(12):1463-1472.
  • Berendsen HJC, Postma JPM van, Van Gunsteren WF, DiNola A, Haak JR. Molecular dynamics with coupling to an external bath. J Chem Phys. 1984;81(8):3684-3690.
  • Martoňák R, Laio A, Parrinello M. Predicting Crystal Structures: The Parrinello-Rahman Method Revisited. Phys Rev Lett. 2003;90(7):4. doi:10.1103/PhysRevLett.90.075503
  • Kumari R, Kumar R, Consortium OSDD, Lynn A. g_mmpbsa A GROMACS tool for high-throughput MM-PBSA calculations. J Chem Inf Model. 2014;54(7):1951-1962.
  • Yu K, Huang ZY, Xu XL, Li J, Fu XW, Deng SL. Estrogen Receptor Function: Impact on the Human Endometrium. Front Endocrinol (Lausanne). 2022;13. doi:10.3389/fendo.2022.827724
  • Min J, Nwachukwu JC, Min CK, et al. Dual-mechanism estrogen receptor inhibitors. Proc Natl Acad Sci U S A. 2021;118(35). doi:10.1073/pnas.2101657118
  • Stefanutti C. Lomitapide–a Microsomal Triglyceride Transfer Protein Inhibitor for Homozygous Familial Hypercholesterolemia. Curr Atheroscler Rep. 2020;22(8). doi:10.1007/s11883-020-00858-4
  • Sen P, Kandasamy T, Ghosh SS. Multi-targeting TACE/ADAM17 and gamma-secretase of notch signalling pathway in TNBC via drug repurposing approach using Lomitapide. Cell Signal. 2023;102. doi:10.1016/j.cellsig.2022.110529
  • Lee B, Park SJ, Lee S, et al. Lomitapide, a cholesterol-lowering drug, is an anticancer agent that induces autophagic cell death via inhibiting mTOR. Cell Death Dis. 2022;13(7):603. doi:10.1038/s41419-022-05039-6
  • Wang Y, Zhang S, He H, et al. Repositioning Lomitapide to block ZDHHC5-dependant palmitoylation on SSTR5 leads to anti-proliferation effect in preclinical pancreatic cancer models. Cell Death Discov. 2023;9(1). doi:10.1038/s41420-023-01359-4
  • Zuo Q, Liao L, Yao ZT, et al. Targeting PP2A with lomitapide suppresses colorectal tumorigenesis through the activation of AMPK/Beclin1-mediated autophagy. Cancer Lett. 2021;521. doi:10.1016/j.canlet.2021.09.010
  • TilakVijay J, Babu KV, Uma A. Virtual screening of novel compounds as potential ER-alpha inhibitors. Bioinformation. 2019;15(5):321. doi:10.6026/97320630015321
  • Li-Ng M, Verbalis JG. Conivaptan: Evidence supporting its therapeutic use in hyponatremia. Core Evid. 2009;4. doi:10.2147/ce.s5997
  • Raftopoulos H. Diagnosis and management of hyponatremia in cancer patients. Support Care Cancer. 2007;15(12):1341-1347. doi:10.1007/S00520-007-0309-9/FIGURES/2
  • Ferraldeschi R, Sharifi N, Auchus RJ, Attard G. Molecular pathways: inhibiting steroid biosynthesis in prostate cancer. Clin cancer Res. 2013;19(13):3353-3359.
  • Dou D, Ji Y, Zheng J, et al. A New Role for Conivaptan in Ulcerative Colitis in Mice: Inhibiting Differentiation of CD4+ T Cells into Th1 Cells. Dig Dis Sci. Published online 2022:1-10.
  • Deeks ED. Atogepant: First Approval. Drugs. 2022;82(1):65-70. doi:10.1007/S40265-021-01644-5
  • Ankrom W, Xu J, Vallee M, et al. Atogepant Has No Clinically Relevant Effects on the Pharmacokinetics of an Ethinyl Estradiol/Levonorgestrel Oral Contraceptive in Healthy Female Participants. J Clin Pharmacol. 2020;60(9):1157-1165. doi:10.1002/jcph.1610
  • Berberich AJ, Hegele RA. Lomitapide for the treatment of hypercholesterolemia. Expert Opin Pharmacother. 2017;18(12):1261-1268.
  • Khan MI, Waguespack SG, Ahmed I. Recent advances in the management of hyponatremia in cancer patients. J Cancer Metastasis Treat. 2019;5:71.
There are 41 citations in total.

Details

Primary Language English
Subjects Bioinformatics and Computational Biology (Other)
Journal Section Original Article / Medical Sciences
Authors

Zekeriya Düzgün 0000-0001-6420-6292

Funda Demırtaş Korkmaz 0000-0003-3978-9427

Publication Date March 15, 2024
Submission Date August 22, 2023
Acceptance Date October 18, 2023
Published in Issue Year 2024 Volume: 10 Issue: 1

Cite

APA Düzgün, Z., & Demırtaş Korkmaz, F. (2024). Lomitapide as a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi, 10(1), 8-14. https://doi.org/10.30934/kusbed.1347829
AMA Düzgün Z, Demırtaş Korkmaz F. Lomitapide as a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study. KOU Sag Bil Derg. March 2024;10(1):8-14. doi:10.30934/kusbed.1347829
Chicago Düzgün, Zekeriya, and Funda Demırtaş Korkmaz. “Lomitapide As a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study”. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi 10, no. 1 (March 2024): 8-14. https://doi.org/10.30934/kusbed.1347829.
EndNote Düzgün Z, Demırtaş Korkmaz F (March 1, 2024) Lomitapide as a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi 10 1 8–14.
IEEE Z. Düzgün and F. Demırtaş Korkmaz, “Lomitapide as a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study”, KOU Sag Bil Derg, vol. 10, no. 1, pp. 8–14, 2024, doi: 10.30934/kusbed.1347829.
ISNAD Düzgün, Zekeriya - Demırtaş Korkmaz, Funda. “Lomitapide As a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study”. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi 10/1 (March 2024), 8-14. https://doi.org/10.30934/kusbed.1347829.
JAMA Düzgün Z, Demırtaş Korkmaz F. Lomitapide as a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study. KOU Sag Bil Derg. 2024;10:8–14.
MLA Düzgün, Zekeriya and Funda Demırtaş Korkmaz. “Lomitapide As a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study”. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi, vol. 10, no. 1, 2024, pp. 8-14, doi:10.30934/kusbed.1347829.
Vancouver Düzgün Z, Demırtaş Korkmaz F. Lomitapide as a Potential Estrogen Receptor Inhibitor: A Computational Drug Repurposing Study. KOU Sag Bil Derg. 2024;10(1):8-14.