European Journal of Chemistry

QSAR study of benzofuran and indole derivatives to predict new compounds as histone lysine methyl transferase inhibitors

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Kaushik Sarkar
Sraboni Ghosh
Rajesh Kumar Das

Abstract

Initiation and progression of several diseases by post-translational histone modifications are considered a worldwide problem. Enhancer of Zeste Homologue 2 (EZH2), which belongs to the histone-lysine N-methyl transferase (HKMT) family, has been emphasised as a promising target for cancer therapy. It is a major challenge for the scientific community to find novel approaches to treating this disease. In this study, a series of 51 derivatives of the benzofuran and indole families, previously experimentally evaluated against HKMT, was used to develop the best model with promising anticancer activity. The multiple linear regression (MLR) method, implemented in QSARINS software, was used with a genetic algorithm for variable selection. According to QSARINS, the model with two descriptors (minHBint4 and Wlambdal.unity) was found to be the best and its parameters fit well, and its validation was well established. The applicability domain was also validated for this model. Furthermore, its robustness (R2 = 0.9328), stability (Q2LOO = 0.9212, Q2LMO = 0.9187), and good predictive power (R2ext = 0.929) were also verified. Hence, this model was assumed to have predictive HKMT anticancer activity for designing active compounds. Molecular docking was also performed to identify binding interactions, and new molecules with better predicted biological activity (pIC50) were designed. The binding energy of the three designed compounds demonstrated higher binding activity at the target receptor, followed by complex stability, determined by a 100 ns molecular dynamics simulation and binding free energy calculation. Density functional theory (DFT) and pharmacokinetic analyses also confirmed their drug-like properties. Finally, it can be declared that the proposed tools allow rapid and economical identification of potential anti-HKMT drugs (anticancer drugs) for further development.


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Sarkar, K.; Ghosh, S.; Das, R. K. QSAR Study of Benzofuran and Indole Derivatives to Predict New Compounds As Histone Lysine Methyl Transferase Inhibitors. Eur. J. Chem. 2023, 14, 231-245.

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References

[1]. Verma, S. K.; Tian, X.; LaFrance, L. V.; Duquenne, C.; Suarez, D. P.; Newlander, K. A.; Romeril, S. P.; Burgess, J. L.; Grant, S. W.; Brackley, J. A.; Graves, A. P.; Scherzer, D. A.; Shu, A.; Thompson, C.; Ott, H. M.; Van Aller, G. S.; Machutta, C. A.; Diaz, E.; Jiang, Y.; Johnson, N. W.; Knight, S. D.; Kruger, R. G.; McCabe, M. T.; Dhanak, D.; Tummino, P. J.; Creasy, C. L.; Miller, W. H. Identification of potent, selective, cell-active inhibitors of the histone lysine methyltransferase EZH2. ACS Med. Chem. Lett. 2012, 3, 1091-1096.
https://doi.org/10.1021/ml3003346

[2]. Son, M. J.; Kim, W. K.; Park, A.; Oh, K.-J.; Kim, J.-H.; Han, B. S.; Kim, I. C.; Chi, S.-W.; Park, S. G.; Lee, S. C.; Bae, K.-H. Set7/9, a methyltransferase, regulates the thermogenic program during brown adipocyte differentiation through the modulation of p53 acetylation. Mol. Cell. Endocrinol. 2016, 431, 46-53.
https://doi.org/10.1016/j.mce.2016.04.022

[3]. Batista, I. de A. A.; Helguero, L. A. Biological processes and signal transduction pathways regulated by the protein methyltransferase SETD7 and their significance in cancer. Signal Transduct. Target. Ther. 2018, 3, 19.
https://doi.org/10.1038/s41392-018-0017-6

[4]. Pradhan, S.; Chin, H. G.; Estève, P.-O.; Jacobsen, S. E. SET7/9 mediated methylation of non-histone proteins in mammalian cells. Epigenetics 2009, 4, 383-387.
https://doi.org/10.4161/epi.4.6.9450

[5]. Peterson, C. L.; Laniel, M.-A. Histones and histone modifications. Curr. Biol. 2004, 14, R546-51.
https://doi.org/10.1016/j.cub.2004.07.007

[6]. Biggar, K. K.; Li, S. S.-C. Non-histone protein methylation as a regulator of cellular signalling and function. Nat. Rev. Mol. Cell Biol. 2015, 16, 5-17.
https://doi.org/10.1038/nrm3915

[7]. Hahm, J. Y.; Kim, J.-Y.; Park, J. W.; Kang, J.-Y.; Kim, K.-B.; Kim, S.-R.; Cho, H.; Seo, S.-B. Methylation of UHRF1 by SET7 is essential for DNA double-strand break repair. Nucleic Acids Res. 2019, 47, 184-196.
https://doi.org/10.1093/nar/gky975

[8]. Song, Y.; Zhang, J.; Tian, T.; Fu, X.; Wang, W.; Li, S.; Shi, T.; Suo, A.; Ruan, Z.; Guo, H.; Yao, Y. SET7/9 inhibits oncogenic activities through regulation of Gli-1 expression in breast cancer. Tumour Biol. 2016, 37, 9311-9322.
https://doi.org/10.1007/s13277-016-4822-7

[9]. Takemoto, Y.; Ito, A.; Niwa, H.; Okamura, M.; Fujiwara, T.; Hirano, T.; Handa, N.; Umehara, T.; Sonoda, T.; Ogawa, K.; Tariq, M.; Nishino, N.; Dan, S.; Kagechika, H.; Yamori, T.; Yokoyama, S.; Yoshida, M. Identification of cyproheptadine as an inhibitor of SET domain containing lysine methyltransferase 7/9 (Set7/9) that regulates estrogen-dependent transcription. J. Med. Chem. 2016, 59, 3650-3660.
https://doi.org/10.1021/acs.jmedchem.5b01732

[10]. Fujiwara, T.; Ohira, K.; Urushibara, K.; Ito, A.; Yoshida, M.; Kanai, M.; Tanatani, A.; Kagechika, H.; Hirano, T. Steric structure-activity relationship of cyproheptadine derivatives as inhibitors of histone methyltransferase Set7/9. Bioorg. Med. Chem. 2016, 24, 4318-4323.
https://doi.org/10.1016/j.bmc.2016.07.024

[11]. Feoli, A.; Viviano, M.; Cipriano, A.; Milite, C.; Castellano, S.; Sbardella, G. Lysine methyltransferase inhibitors: where we are now. RSC Chem. Biol. 2022, 3, 359-406.
https://doi.org/10.1039/D1CB00196E

[12]. Chang, C.-J.; Hung, M.-C. The role of EZH2 in tumour progression. Br. J. Cancer 2012, 106, 243-247.
https://doi.org/10.1038/bjc.2011.551

[13]. Woo, J.; Kim, H.-Y.; Byun, B. J.; Chae, C.-H.; Lee, J. Y.; Ryu, S. Y.; Park, W.-K.; Cho, H.; Choi, G. Biological evaluation of tanshindiols as EZH2 histone methyltransferase inhibitors. Bioorg. Med. Chem. Lett. 2014, 24, 2486-2492.
https://doi.org/10.1016/j.bmcl.2014.04.010

[14]. Nasveschuk, C. G.; Gagnon, A.; Garapaty-Rao, S.; Balasubramanian, S.; Campbell, R.; Lee, C.; Zhao, F.; Bergeron, L.; Cummings, R.; Trojer, P.; Audia, J. E.; Albrecht, B. K.; Harmange, J.-C. P. Discovery and optimization of tetramethylpiperidinyl benzamides as inhibitors of EZH2. ACS Med. Chem. Lett. 2014, 5, 378-383.
https://doi.org/10.1021/ml400494b

[15]. Bradley, W. D.; Arora, S.; Busby, J.; Balasubramanian, S.; Gehling, V. S.; Nasveschuk, C. G.; Vaswani, R. G.; Yuan, C.-C.; Hatton, C.; Zhao, F.; Williamson, K. E.; Iyer, P.; Méndez, J.; Campbell, R.; Cantone, N.; Garapaty-Rao, S.; Audia, J. E.; Cook, A. S.; Dakin, L. A.; Albrecht, B. K.; Harmange, J.-C.; Daniels, D. L.; Cummings, R. T.; Bryant, B. M.; Normant, E.; Trojer, P. EZH2 inhibitor efficacy in non-Hodgkin's lymphoma does not require suppression of H3K27 monomethylation. Chem. Biol. 2014, 21, 1463-1475.
https://doi.org/10.1016/j.chembiol.2014.09.017

[16]. Siddiqui, S. K.; SahayaSheela, V. J.; Kolluru, S.; Pandian, G. N.; Santhoshkumar, T. R.; Dan, V. M.; Ramana, C. V. Discovery of 3-(benzofuran-2-ylmethyl)-1H-indole derivatives as potential autophagy inducers in cervical cancer cells. Bioorg. Med. Chem. Lett. 2020, 30, 127431.
https://doi.org/10.1016/j.bmcl.2020.127431

[17]. Al-Akra, L.; Bae, D.-H.; Leck, L. Y. W.; Richardson, D. R.; Jansson, P. J. The biochemical and molecular mechanisms involved in the role of tumor micro-environment stress in development of drug resistance. Biochim. Biophys. Acta Gen. Subj. 2019, 1863, 1390-1397.
https://doi.org/10.1016/j.bbagen.2019.06.007

[18]. Mu, L.-M.; Ju, R.-J.; Liu, R.; Bu, Y.-Z.; Zhang, J.-Y.; Li, X.-Q.; Zeng, F.; Lu, W.-L. Dual-functional drug liposomes in treatment of resistant cancers. Adv. Drug Deliv. Rev. 2017, 115, 46-56.
https://doi.org/10.1016/j.addr.2017.04.006

[19]. Jia, Y.; Wen, X.; Gong, Y.; Wang, X. Current scenario of indole derivatives with potential anti-drug-resistant cancer activity. Eur. J. Med. Chem. 2020, 200, 112359.
https://doi.org/10.1016/j.ejmech.2020.112359

[20]. Napiórkowska, M.; Cieślak, M.; Kaźmierczak-Barańska, J.; Królewska-Golińska, K.; Nawrot, B. Synthesis of new derivatives of benzofuran as potential anticancer agents. Molecules 2019, 24, 1529.
https://doi.org/10.3390/molecules24081529

[21]. Yap, C. W. PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints. J. Comput. Chem. 2011, 32, 1466-1474.
https://doi.org/10.1002/jcc.21707

[22]. Hanwell, M. D.; Curtis, D. E.; Lonie, D. C.; Vandermeersch, T.; Zurek, E.; Hutchison, G. R. Avogadro: an advanced semantic chemical editor, visualization, and analysis platform. J. Cheminform. 2012, 4, 17.
https://doi.org/10.1186/1758-2946-4-17

[23]. Gramatica, P.; Chirico, N.; Papa, E.; Cassani, S.; Kovarich, S. QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. J. Comput. Chem. 2013, 34, 2121-2132.
https://doi.org/10.1002/jcc.23361

[24]. Cañizares-Carmenate, Y.; Campos Delgado, L. E.; Torrens, F.; Castillo-Garit, J. A. Thorough evaluation of OECD principles in modelling of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine derivatives using QSARINS. SAR QSAR Environ. Res. 2020, 31, 741-759.
https://doi.org/10.1080/1062936X.2020.1810116

[25]. Morris, G. M.; Huey, R.; Lindstrom, W.; Sanner, M. F.; Belew, R. K.; Goodsell, D. S.; Olson, A. J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem. 2009, 30, 2785-2791.
https://doi.org/10.1002/jcc.21256

[26]. Trott, O.; Olson, A. J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. 2010, 31, 455-461.
https://doi.org/10.1002/jcc.21334

[27]. Lee, S.; Tran, A.; Allsopp, M.; Lim, J. B.; Hénin, J.; Klauda, J. B. CHARMM36 united atom chain model for lipids and surfactants. J. Phys. Chem. B 2014, 118, 547-556.
https://doi.org/10.1021/jp410344g

[28]. Boonstra, S.; Onck, P. R.; Giessen, E. van der CHARMM TIP3P water model suppresses peptide folding by solvating the unfolded state. J. Phys. Chem. B 2016, 120, 3692-3698.
https://doi.org/10.1021/acs.jpcb.6b01316

[29]. Vanommeslaeghe, K.; Hatcher, E.; Acharya, C.; Kundu, S.; Zhong, S.; Shim, J.; Darian, E.; Guvench, O.; Lopes, P.; Vorobyov, I.; Mackerell, A. D., Jr CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J. Comput. Chem. 2009, 31, 671-690.
https://doi.org/10.1002/jcc.21367

[30]. Vanommeslaeghe, K.; MacKerell, A. D., Jr Automation of the CHARMM General Force Field (CGenFF) I: bond perception and atom typing. J. Chem. Inf. Model. 2012, 52, 3144-3154.
https://doi.org/10.1021/ci300363c

[31]. Kumari, R.; Kumar, R.; Open Source Drug Discovery Consortium; Lynn, A. g_mmpbsa--a GROMACS tool for high-throughput MM-PBSA calculations. J. Chem. Inf. Model. 2014, 54, 1951-1962.
https://doi.org/10.1021/ci500020m

[32]. Baker, N. A.; Sept, D.; Joseph, S.; Holst, M. J.; McCammon, J. A. Electrostatics of nanosystems: application to microtubules and the ribosome. Proc. Natl. Acad. Sci. U. S. A. 2001, 98, 10037-10041.
https://doi.org/10.1073/pnas.181342398

[33]. Molecular properties prediction - Osiris property explorer. https://www.organic-chemistry.org/prog/peo/ (accessed February 9, 2023).

[34]. Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Montgomery, J. A.; Vreven, T.; Kudin, K. N.; Burant, J. C.; Millam, J. M.; Iyengar, S. S.; Tomasi, J.; Barone, V.; Mennucci, B.; Cossi, M.; Scalmani, G.; Rega, N.; Petersson, G. A.; Nakatsuji, H.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Klene, M.; Li, X.; Knox, J. E.; Hratchian, H. P.; Cross, J. B.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Ayala, P. Y.; Morokuma, K.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Zakrzewski, V. G.; Dapprich, S.; Daniels, A. D.; Strain, M. C.; Farkas, O.; Malick, D. K.; Rabuck, A. D.; Raghavachari, K; Foresman, J. B.; Ortiz, J. V.; Cui, Q.; Baboul, A. G.; Clifford, S.; Cioslowski, J.; Stefanov, B. B.; Liu, G.; Liashenko, A.; Piskorz, P.; Komaromi, I.; Martin, R. L.; Fox, D. J.; Keith, T.; Al-Laham, M. A.; Peng, C. Y.; Nanayakkara, A.; Challacombe, M.; Gill, P. M. W.; Johnson, B.; Chen, W.; Wong, M. W.; Gonzalez, C.; Pople, J. A. Gaussian, Inc. , Wallingford CT, 2016.

[35]. Dennington, R.; Keith, T. A.; Millam, J. M. GaussView, Version 6, Semichem Inc.; Shawnee Mission, KS, 2016.

[36]. Tirado-Rives, J.; Jorgensen, W. L. Performance of B3LYP density functional methods for a large set of organic molecules. J. Chem. Theory Comput. 2008, 4, 297-306.
https://doi.org/10.1021/ct700248k

[37]. Abdulfatai, U.; Uzairu, A.; Uba, S. Molecular docking and QSAR analysis of a few Gama amino butyric acid aminotransferase inhibitors. Egypt. J. Basic Appl. Sci. 2018, 5, 41-53.
https://doi.org/10.1016/j.ejbas.2018.01.003

[38]. Subramani, A. K.; Sivaperuman, A.; Natarajan, R.; Bhandare, R. R.; Shaik, A. B. QSAR and molecular docking studies of pyrimidine-coumarin-triazole conjugates as prospective anti-breast cancer agents. Molecules 2022, 27, 1845.
https://doi.org/10.3390/molecules27061845

[39]. Sarkar, K.; Das, R. K. Repurposing of existing pharmaceutical drugs against monkey-pox virus: An in silico study. Anal. Chem. Lett. 2022, 12, 655-670.
https://doi.org/10.1080/22297928.2022.2157224

[40]. Sharma, B.; Bhattacherjee, D.; Zyryanov, G. V.; Purohit, R. An insight from computational approach to explore novel, high-affinity phosphodiesterase 10A inhibitors for neurological disorders. J. Biomol. Struct. Dyn. 2022, 1-13.
https://doi.org/10.1080/07391102.2022.2141895

[41]. Al-Ostoot, F. H.; Geetha, D. V.; Mohammed, Y. H. E.; Akhileshwari, P.; Sridhar, M. A.; Khanum, S. A. Design-based synthesis, molecular docking analysis of an anti-inflammatory drug, and geometrical optimization and interaction energy studies of an indole acetamide derivative. J. Mol. Struct. 2020, 1202, 127244.
https://doi.org/10.1016/j.molstruc.2019.127244

Supporting Agencies

University Grants Commission, New Delhi, for the project F.30-515/2020(BSR), 12.02.2020, F.D. Diary No. 9719, 23.01.2020 and University Grants Commission, for the NET-JRF fellowship, India.
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