European Journal of Chemistry

QSAR and docking studies of pyrazole analogs as antiproliferative against human colorectal adenocarcinoma cell line HT-29

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Hiba Hashim Mahgoub Mohamed
Amna Bint Wahab Elrashid Mohammed Hussien
Ahmed Elsadig Mohammed Saeed

Abstract

In-silico quantitative structure-activity relationship (QSAR) study was performed to develop a model on a series of novel pyrazole derivatives containing acetamide moiety which exhibited considerable antiproliferative activity against human colorectal adenocarcinoma cell line HT-29. The model obtained has a correlation coefficient (r) of 0.9693, squared correlation coefficient (r2) of 0.9395 and a leave-one-out (LOO) cross-validation coefficient (Q2) value of 0.8744. The predictive power of the developed model was confirmed by the external validation which has an r2 value of 0.9488. These parameters confirm the stability and robustness of the model to predict the activity of a new designed set of 3,5-dimethyl-pyrazole derivatives (22-36), results indicated that the compounds 26, 31, 35, and 36 showed the strongest antiproliferative activity with (IC50 = 0.182, 0.172, 0.166 and 0.024 μM, respectively) against human colorectal adenocarcinoma cell line HT-29 compared to the reference vemurafenib with (IC50 = 1.52 μM). Molecular docking was performed on the new designed compounds with the human colorectal adenocarcinoma cell line 5JRQ protein. The docking results showed that compounds 26, 31, 35, and 36 have docking affinity of -8.528, -5.932, 23.017 and 18.432 kcal/mol, respectively.


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Mohamed, H. H. M.; Hussien, A. B. W. E. M.; Saeed, A. E. M. QSAR and Docking Studies of Pyrazole Analogs As Antiproliferative Against Human Colorectal Adenocarcinoma Cell Line HT-29. Eur. J. Chem. 2022, 13, 319-326.

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References

[1]. El Bali, M.; Bakkach, J.; Bennani Mechita, M. Colorectal cancer: From genetic landscape to targeted therapy. J. Oncol. 2021, 2021, 9918116.
https://doi.org/10.1155/2021/9918116

[2]. Sawicki, T.; Ruszkowska, M.; Danielewicz, A.; Niedźwiedzka, E.; Arłukowicz, T.; Przybyłowicz, K. E. A review of colorectal cancer in terms of epidemiology, risk factors, development, symptoms and diagnosis. Cancers (Basel) 2021, 13.
https://doi.org/10.3390/cancers13092025

[3]. Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R. L.; Torre, L. A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018, 68, 394-424.
https://doi.org/10.3322/caac.21492

[4]. Picard, E.; Verschoor, C. P.; Ma, G. W.; Pawelec, G. Relationships between immune landscapes, genetic subtypes and responses to immunotherapy in colorectal cancer. Front. Immunol. 2020, 11, 369.
https://doi.org/10.2307/j.ctv160bt82.12

[5]. You, Y. N.; Lee, L. D.; Deschner, B. W.; Shibata, D. Colorectal cancer in the adolescent and young adult population. JCO Oncol Pract 2020, 16, 19-27.
https://doi.org/10.1200/JOP.19.00153

[6]. Testa, U.; Pelosi, E.; Castelli, G. Colorectal cancer: genetic ab-normalities, tumor progression, tumor heterogeneity, clonal evolution and tumor-initiating cells. Med. Sci. (Basel) 2018, 6.
https://doi.org/10.3390/medsci6020031

[7]. Loke, Y. L.; Chew, M. T.; Ngeow, Y. F.; Lim, W. W. D.; Peh, S. C. Colon carcinogenesis: The interplay between diet and gut Microbiota. Front. Cell. Infect. Microbiol. 2020, 10, 603086.
https://doi.org/10.3389/fcimb.2020.603086

[8]. Vernia, F.; Longo, S.; Stefanelli, G.; Viscido, A.; Latella, G. Dietary factors modulating colorectal carcinogenesis. Nutrients 2021, 13, 143.
https://doi.org/10.3390/nu13010143

[9]. Barnes, J. L.; Zubair, M.; John, K.; Poirier, M. C.; Martin, F. L. Carcinogens and DNA damage. Biochem. Soc. Trans. 2018, 46, 1213-1224.
https://doi.org/10.1042/BST20180519

[10]. Basu, A. K. DNA damage, Mutagenesis and cancer. Int. J. Mol. Sci. 2018, 19.
https://doi.org/10.3390/ijms19040970

[11]. Mármol, I.; Sánchez-de-Diego, C.; Pradilla Dieste, A.; Cerrada, E.; Rodriguez Yoldi, M. J. Colorectal carcinoma: A general overview and future perspectives in colorectal cancer. Int. J. Mol. Sci. 2017, 18, 197.
https://doi.org/10.3390/ijms18010197

[12]. Naim, M. J.; Alam, O.; Nawaz, F.; Alam, M. J.; Alam, P. Current status of pyrazole and its biological activities. J. Pharm. Bioallied Sci. 2016, 8, 2-17.
https://doi.org/10.4103/0975-7406.171694

[13]. Alsayari, A.; Asiri, Y. I.; Muhsinah, A. B.; Hassan, M. Z. Anticolon cancer properties of pyrazole derivatives acting through xanthine oxidase inhibition. J. Oncol. 2021, 2021, 5691982.
https://doi.org/10.1155/2021/5691982

[14]. Aziz, H.; Zahoor, A. F.; Ahmad, S. Pyrazole bearing molecules as bioactive scaffolds: A review. J. Chil. Chem. Soc. 2020, 65, 4746-4753.
https://doi.org/10.4067/S0717-97072020000104746

[15]. Karrouchi, K.; Radi, S.; Ramli, Y.; Taoufik, J.; Mabkhot, Y. N.; Al-Aizari, F. A.; Ansar, M. Synthesis and pharmacological activities of pyrazole derivatives: A review. Molecules 2018, 23, 134.
https://doi.org/10.3390/molecules23010134

[16]. Halder, A. K.; Moura, A. S.; Cordeiro, M. N. D. S. QSAR modelling: a therapeutic patent review 2010-present. Expert Opin. Ther. Pat. 2018, 28, 467-476.
https://doi.org/10.1080/13543776.2018.1475560

[17]. Kausar, S.; Falcao, A. O. An automated framework for QSAR model building. J. Cheminform. 2018, 10, 1.
https://doi.org/10.1186/s13321-017-0256-5

[18]. Muhammad, U.; Uzairu, A.; Ebuka Arthur, D. Review on: quantitative structure activity relationship (QSAR) modeling. J. Anal. Pharm. Res. 2018, 7, 240-242.
https://doi.org/10.15406/japlr.2018.07.00232

[19]. Wang, C.-R.; Wang, Z.-F.; Shi, L.; Wang, Z.-C.; Zhu, H.-L. Design, synthesis, and biological evaluation of pyrazole derivatives containing acetamide bond as potential BRAF V600E inhibitors. Bioorg. Med. Chem. Lett. 2018, 28, 2382-2390.
https://doi.org/10.1016/j.bmcl.2018.06.028

[20]. ACD/ChemSketch, version 14.01, Advanced Chemistry Development, Inc. (ACD/Labs), Toronto, ON, Canada, www.acdlabs.com (accessed June 2, 2022).

[21]. Molecular Operating Environment (MOE), 2009.10 Chemical Computing Group ULC, 1010 Sherbooke St. West, Suite #910, Montreal, QC, Canada, H3A 2R7, 2022.

[22]. Berman, H. M.; Henrick, K.; Nakamura, H. Announcing the worldwide Protein Data Bank Nature Structural Biology 10 (12): 980, 2003, https://www.rcsb.org/structure/5JRQ (accessed June 2, 2022).
https://doi.org/10.1038/nsb1203-980

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