90
Views
0
CrossRef citations to date
0
Altmetric
Research Article

2,4,6-Trimethoxy chalcone derivatives: an integrated study for redesigning novel chemical entities as anticancer agents through QSAR, molecular docking, ADMET prediction, and computational simulation

, , , , , , & show all
Received 11 Aug 2023, Accepted 18 Jan 2024, Published online: 07 Feb 2024

References

  • Abdullahi, M., Uzairu, A., Shallangwa, G. A., Mamza, P. A., & Ibrahim, M. T. (2022). In-silicomodeling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions. Heliyon, 8(8), e10101. https://doi.org/10.1016/j.heliyon.2022.e10101
  • Arthur, D. E., Soliman, M. E. S., Adeniji, S. E., Adedirin, O., & Peter, F. (2022). QSAR and molecular docking study of gonadotropin-releasing hormone receptor inhibitors. Scientific African, 17, e01291. https://doi.org/10.1016/j.sciaf.2022.e01291
  • Asgaonkar, K. D., Patil, S. M., Chitre, T. S., Ghegade, V. N., Jadhav, S. R., Sande, S. S., & Kulkarni, A. S. (2019). Comparative docking studies: A drug design tool for some pyrazine- thiazolidinone based derivatives for anti-HIV activity. Current Computer-Aided Drug Design, 15(3), 252–258. https://doi.org/10.2174/1573409915666181219125944
  • Asgaonkar, K. D., Patil, S. M., Chitre, T. S., Wani, S. D., & Singh, M. T. (2022). QSAR tool for optimization of nitrobenzamide pharmacophore for antitubercular activity. Bulletin of the Karaganda University, 105(1), 60–68. https://doi.org/10.31489/2022Ch1/60-68
  • Baiocchi, R. A., Flynn, J. M., Jones, J. A., Blum, K. A., Hofmeister, C. C., Poon, J., Small, K., Statkevich, P., Grever, M. R., Bannerji, R., & Byrd, J. C. (2010). Early evidence of anti-lymphoma activity of the cyclin dependent kinase inhibitor dinaciclib (SCH 727965) in heavily pre-treated low grade lymphoma and diffuse large cell lymphoma patients. Blood, 116(21), 3966–3966. https://doi.org/10.1182/blood.V116.21.3966.3966
  • Broustas, C. G., & Lieberman, H. B. (2014). DNA damage response genes and the development of cancer metastasis. Radiation Research, 181(2), 111–130. https://doi.org/10.1667/RR13515.1
  • Cañizares-Carmenate, Y., Mena-Ulecia, K., Perera-Sardiña, Y., Torrens, F., & Castillo-Garit, J. A. (2019). An approach to identify new antihypertensive agents using Thermolysin as model: In silico study based on QSARINS and docking. Arabian Journal of Chemistry, 12(8), 4861–4877. https://doi.org/10.1016/j.arabjc.2016.10.003
  • Chen, Y., Zheng, Y., Fong, P., Mao, S., & Wang, Q. (2020). The application of the MM/GBSA method in the binding pose prediction of FGFR inhibitors. Physical Chemistry Chemical Physics: PCCP, 22(17), 9656–9663. https://doi.org/10.1039/D0CP00831A
  • Chitre, T. S., Asgaonkar, K. D., Miniyar, P. B., Dharme, A. B., Arkile, M. A., Yeware, A., Sarkar, D., Khedkar, V. M., & Jha, P. C. (2016). Synthesis and docking studies of pyrazine–thiazolidinone hybrid scaffold targeting dormant tuberculosis. Bioorganic & Medicinal Chemistry Letters, 26(9), 2224–2228. https://doi.org/10.1016/j.bmcl.2016.03.055
  • Chitre, T. S., Asgaonkar, K. D., Patil, S. M., Kumar, S., Khedkar, V. M., & Garud, D. R. (2017). QSAR, docking studies of 1,3-thiazinan-3-yl isonicotinamide derivatives for antitubercular activity. Computational Biology and Chemistry, 68, 211–218. https://doi.org/10.1016/j.compbiolchem.2017.03.015
  • Chitre, T. S., Asgaonkar, K. D., Vikhe, A. B., Patil, S. M., Garud, D. R., Khedkar, V. M., Sarkar, D., Nawale, L. U., & Yeware, A. (2021). In silico studies, synthesis and antitubercular activity of some novel quinoline—azitidinone derivatives. Current Computer-Aided Drug Design, 17(1), 134–143. https://doi.org/10.2174/1573409916666200129095952
  • Chitre, T. S., Hirode, P. V., Lokwani, D. K., Bhatambrekar, A. L., Hajare, S. G., Thorat, S. B., Priya, D., Pradhan, K. B., Asgaonkar, K. D., & Jain, S. P. (2023). In-silico studies of 2-aminothiazole derivatives as anticancer agents by QSAR, molecular docking, MD simulation and MM-GBSA approaches. Journal of Biomolecular Structure & Dynamics, 41(10), 1–19. https://doi.org/10.1080/07391102.2023.2262594
  • Chitre, T. S., Kathiravan, M. K., Bothara, K. G., Bhandari, S. V., & Jalnapurkar, R. R. (2011). Pharmacophore optimization and design of competitive inhibitors of thymidine monophosphate kinase through molecular modeling studies: Pharmacophore optimization and design of competitive inhibitors. Chemical Biology & Drug Design, 78(5), 826–834. https://doi.org/10.1111/j.1747-0285.2011.01200.x
  • Chitre, T. S., Patil, S. M., Sujalegaonkar, A. G., & Asgaonkar, K. D. (2021). Designing of Thiazolidin-4-one pharmacophore using QSAR studies for Anti-HIV activity. Indian Journal of Pharmaceutical Education and Research, 55(2), 581–589. https://doi.org/10.5530/ijper.55.2.97
  • Chitre, T. S., Patil, S. M., Sujalegaonkar, A. G., Asgaonkar, K. D., Khedkar, V. M., Garud, D. R., Jha, P. C., Gaikwad, S. Y., Kulkarni, S. S., Choudhari, A., & Sarkar, D. (2019). Non nucleoside reverse transcriptase inhibitors, molecular docking studies and antitubercular activity of thiazolidin-4-one derivatives. Current Computer-Aided Drug Design, 15(5), 433–444. https://doi.org/10.2174/1573409915666181221102903
  • Chitre, T., Parse, S., Asgaonkar, K., Khedekar, V., Jadhav, S., & Pradhan, K. (2023). QSAR and molecular docking studies of 5-benzylideno-2-adamantylthiazol[3,2-b][1,2,4]triazol-6(5H)ones derivatives as antimicrobial activity. Indian Journal of Pharmaceutical Education and Research, 57(1), 194–201. https://doi.org/10.5530/001954641712
  • Costa, A. S., Martins, J. P. A., & De Melo, E. B. (2022). SMILES-based 2D-QSAR and similarity search for identification of potential new scaffolds for development of SARS-CoV-2 MPRO inhibitors. Structural Chemistry, 33(5), 1691–1706. https://doi.org/10.1007/s11224-022-02008-9
  • Cui, W., Aouidate, A., Wang, S., Yu, Q., Li, Y., & Yuan, S. (2020). Discovering anti-cancer drugs via computational methods. Frontiers in Pharmacology, 11, 733. https://doi.org/10.3389/fphar.2020.00733
  • Cvetnić, M., Novak Stankov, M., Kovačić, M., Ukić, Š., Bolanča, T., Kušić, H., Rasulev, B., Dionysiou, D. D., & Lončarić Božić, A. (2019). Key structural features promoting radical driven degradation of emerging contaminants in water. Environment International, 124, 38–48. https://doi.org/10.1016/j.envint.2018.12.043
  • De, P., & Roy, K. (2021). QSAR and QSAAR modeling of nitroimidazole sulfonamide radiosensitizers: Application of small dataset modeling. Structural Chemistry, 32(2), 631–642. https://doi.org/10.1007/s11224-021-01734-w
  • Ding, L., Cao, J., Lin, W., Chen, H., Xiong, X., Ao, H., Yu, M., Lin, J., & Cui, Q. (2020). The roles of cyclin-dependent kinases in cell-cycle progression and therapeutic strategies in human breast cancer. International Journal of Molecular Sciences, 21(6), 1960. https://doi.org/10.3390/ijms21061960
  • Dutta, D., Guha, R., Wild, D., & Chen, T. (2007). Ensemble feature selection: Consistent descriptor subsets for multiple QSAR models. Journal of Chemical Information and Modeling, 47(3), 989–997. https://doi.org/10.1021/ci600563w
  • Farghaly, T. A., Masaret, G. S., Muhammad, Z. A., & Harras, M. F. (2020). Discovery of thiazole-based-chalcones and 4-hetarylthiazoles as potent anticancer agents: Synthesis, docking study and anticancer activity. Bioorganic Chemistry, 98, 103761. https://doi.org/10.1016/j.bioorg.2020.103761
  • Flynn, J. M., Johnson, A. J., Andritsos, L., Blum, K. A., Jones, J. A., Wiley, E. A., Hu, W., Hessler, J., Smith, L. L., Lucas, D. M., Small, K., Statkevich, P., Grever, M. R., Bannerji, R., & Byrd, J. C. (2009). The cyclin dependent kinase inhibitor SCH 727965 demonstrates promising pre-clinical and early clinical activity in chronic lymphocytic leukemia. Blood, 114(22), 886–886. https://doi.org/10.1182/blood.V114.22.886.886
  • Genheden, S., & Ryde, U. (2015). The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opinion on Drug Discovery, 10(5), 449–461. https://doi.org/10.1517/17460441.2015.1032936
  • Gooch, A., Sizochenko, N., Rasulev, B., Gorb, L., & Leszczynski, J. (2017). In vivo toxicity of nitroaromatics: A comprehensive quantitative structure–activity relationship study. Environmental Toxicology and Chemistry, 36(8), 2227–2233. https://doi.org/10.1002/etc.3761
  • Gramatica, P. (2007). Principles of QSAR models validation: Internal and external. QSAR & Combinatorial Science, 26(5), 694–701. https://doi.org/10.1002/qsar.200610151
  • Gramatica, P., Chirico, N., Papa, E., Cassani, S., & Kovarich, S. (2013). QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. Journal of Computational Chemistry, 34(24), 2121–2132. https://doi.org/10.1002/jcc.23361
  • Greenwood, J. R., Calkins, D., Sullivan, A. P., & Shelley, J. C. (2010). Towards the comprehensive, rapid, and accurate prediction of the favorable tautomeric states of drug-like molecules in aqueous solution. Journal of Computer-Aided Molecular Design, 24(6-7), 591–604. https://doi.org/10.1007/s10822-010-9349-1
  • Hanwell, M. D., Curtis, D. E., Lonie, D. C., Vandermeersch, T., Zurek, E., & Hutchison, G. R. (2012). Avogadro: An advanced semantic chemical editor, visualization, and analysis platform. Journal of Cheminformatics, 4(1), 17. https://doi.org/10.1186/1758-2946-4-17
  • Hassanpour, S. H., & Dehghani, M. (2017). Review of cancer from perspective of molecular. Journal of Cancer Research and Practice, 4(4), 127–129. https://doi.org/10.1016/j.jcrpr.2017.07.001
  • Hughes, T. P., Mauro, M. J., Cortes, J. E., Minami, H., Rea, D., DeAngelo, D. J., Breccia, M., Goh, Y.-T., Talpaz, M., Hochhaus, A., Le Coutre, P., Ottmann, O., Heinrich, M. C., Steegmann, J. L., Deininger, M. W. N., Janssen, J. J. W. M., Mahon, F.-X., Minami, Y., Yeung, D., … Kim, D.-W. (2019). Asciminib in chronic myeloid leukemia after ABL kinase inhibitor failure. The New England Journal of Medicine, 381(24), 2315–2326. https://doi.org/10.1056/NEJMoa1902328\
  • Kasmi, R., Hadaji, E., Chedadi, O., El Aissouq, A., Bouachrine, M., & Ouammou, A. (2020). 2D-QSAR and docking study of a series of coumarin derivatives as inhibitors of CDK (anticancer activity) with an application of the molecular docking method. Heliyon, 6(8), e04514. https://doi.org/10.1016/j.heliyon.2020.e04514
  • Kiralj, R., & Ferreira, M. M. C. (2009). Basic validation procedures for regression models in QSAR and QSPR studies: Theory and application. Journal of the Brazilian Chemical Society, 20(4), 770–787. https://doi.org/10.1590/S0103-50532009000400021
  • Kumar, B., Singh, S., Skvortsova, I., & Kumar, V. (2017). Promising targets in anti-cancer drug development: Recent updates. Current Medicinal Chemistry, 24(42), 4729–4752. https://doi.org/10.2174/0929867324666170331123648
  • Li, T., Li, W., Yang, X., Chen, G., Jin, X., Chen, W., & Ye, L. (2023). Design, Synthesis, anticancer evaluation and in silico studies of 2, 4, 6-trimethoxychalcone derivatives. Saudi Pharmaceutical Journal, 31(1), 65–84. https://doi.org/10.1016/j.jsps.2022.11.006
  • Liu, W., He, M., Li, Y., Peng, Z., & Wang, G. (2022). A review on synthetic chalcone derivatives as tubulin polymerisation inhibitors. Journal of Enzyme Inhibition and Medicinal Chemistry, 37(1), 9–38. https://doi.org/10.1080/14756366.2021.1976772
  • Łukasik, P., Załuski, M., & Gutowska, I. (2021). Cyclin-dependent kinases (CDK) and their role in diseases development–review. International Journal of Molecular Sciences, 22(6), 2935. https://doi.org/10.3390/ijms22062935
  • Madhavi Sastry, G., Adzhigirey, M., Day, T., Annabhimoju, R., & Sherman, W. (2013). Protein and ligand preparation: Parameters, protocols, and influence on virtual screening enrichments. Journal of Computer-Aided Molecular Design, 27(3), 221–234. https://doi.org/10.1007/s10822-013-9644-8
  • Moshinsky, D. J., Bellamacina, C. R., Boisvert, D. C., Huang, P., Hui, T., Jancarik, J., Kim, S.-H., & Rice, A. G. (2003). SU9516: Biochemical analysis of cdk inhibition and crystal structure in complex with cdk2. Biochemical and Biophysical Research Communications, 310(3), 1026–1031. https://doi.org/10.1016/j.bbrc.2003.09.114
  • Navarro-Retamal, C., & Caballero, J. (2016). Flavonoids as CDK1 Inhibitors: Insights in Their Binding Orientations and Structure-Activity Relationship. PLOS One, 11(8), e0161111. https://doi.org/10.1371/journal.pone.0161111
  • O'Boyle, N. M., Banck, M., James, C. A., Morley, C., Vandermeersch, T., & Hutchison, G. R. (2011). Open Babel: An open chemical toolbox. Journal of Cheminformatics, 3(1), 33. https://doi.org/10.1186/1758-2946-3-33
  • Orlikova, B., Tasdemir, D., Golais, F., Dicato, M., & Diederich, M. (2011). Dietary chalcones with chemopreventive and chemotherapeutic potential. Genes & Nutrition, 6(2), 125–147. https://doi.org/10.1016/j.ejphar.2017.12.053
  • Otto, T., & Sicinski, P. (2017). Cell cycle proteins as promising targets in cancer therapy. Nature Reviews. Cancer, 17(2), 93–115. https://doi.org/10.1038/nrc.2016.138
  • Patil, S., Asgaonkar, K., Chitre, T., Bhat, V., Ethape, S., Sujalegaonkar, A., & Bhalekar, S. (2017). 2D and 3D QSAR of benzimidazole analogues as novel HIV-1 non nucleoside reverse transcriptase inhibitors. Indian Journal of Pharmaceutical Education and Research, 51(2 suppl), s122–s128. https://doi.org/10.5530/ijper.51.2s.58
  • Priya, D., & Kathiravan, M. K. (2021). Molecular insights into benzene sulphonamide substituted diarylpyrazoles as cyclooxygenase-2 inhibitor and its structural modifications. Journal of Biomolecular Structure & Dynamics, 39(14), 5093–5104. https://doi.org/10.1080/07391102.2020.1785329
  • Pucci, C., Martinelli, C., & Ciofani, G. (2019). Innovative approaches for cancer treatment: Current perspectives and new challenges. Ecancermedicalscience, 13, 961. https://doi.org/10.3332/ecancer.2019.961
  • Raparti, V., Chitre, T., Bothara, K., Kumar, V., Dangre, S., Khachane, C., Gore, S., & Deshmane, B. (2009). Novel 4-(morpholin-4-yl)-N′-(arylidene)benzohydrazides: Synthesis, antimycobacterial activity and QSAR investigations. European Journal of Medicinal Chemistry, 44(10), 3954–3960. https://doi.org/10.1016/j.ejmech.2009.04.023
  • Sadeghian-Rizi, S., Sakhteman, A., & Hassanzadeh, F. (2016). A quantitative structure-activity relationship (QSAR) study of some diaryl urea derivatives of B-RAF inhibitors. Research in Pharmaceutical Sciences, 11(6), 445. https://doi.org/10.4103/1735-5362.194869
  • Sánchez-Martínez, C., Lallena, M. J., Sanfeliciano, S. G., & De Dios, A. (2019). Cyclin dependent kinase (CDK) inhibitors as anticancer drugs: Recent advances (2015–2019). Bioorganic & Medicinal Chemistry Letters, 29(20), 126637. https://doi.org/10.1016/j.bmcl.2019.126637
  • Schrodinger Release 2023-1. (2021). Protein Preparation Wizard. Epik.
  • Schrödinger Release. (2023). 1: LigPrep. Schrödinger, LLC.
  • Shapiro, G. I., & Harper, J. W. (1999). Anticancer drug targets: Cell cycle and checkpoint control. The Journal of Clinical Investigation, 104(12), 1645–1653. https://doi.org/10.1172/JCI9054
  • Shayanfar, S., & Shayanfar, A. (2022). Comparison of various methods for validity evaluation of QSAR models. BMC Chemistry, 16(1), 63. https://doi.org/10.1186/s13065-022-00856-4
  • Small-Molecule Drug Discovery Suite. (2023). QikProp, version 5.0. Schrödinger, LLC.
  • Srimathi, R., & Kathiravan, M. K. (2021). Lead optimization of 4-(thio)-chromenone 6- O -sulfamate analogs using QSAR, molecular docking and DFT – a combined approach as steroidal sulfatase inhibitors. Journal of Receptor and Signal Transduction Research, 41(2), 123–137. https://doi.org/10.1080/10799893.2020.1794004
  • Su, B., Su, J., He, H., Wu, Y., Xia, H., Zeng, X., Dai, W., Ai, X., Ling, H., Jiang, H., & Su, Q. (2015). Identification of potential targets for diallyl disulfide in human gastric cancer MGC-803 cells using proteomics approaches. Oncology Reports, 33(5), 2484–2494. https://doi.org/10.3892/or.2015.3859
  • Su, Z., Yu, B., Deng, Z., & Sun, H. (2020). Isoliquiritigenin inhibits the survival of diffuse large B-cell lymphoma cells by regulating Akt/mTOR signaling pathway. Tropical Journal of Pharmaceutical Research, 19(8), 1619–1623. https://doi.org/10.4314/tjpr.v19i8.8
  • Subramani, A. K., Sivaperuman, A., Natarajan, R., Bhandare, R. R., & Shaik, A. B. (2022). QSAR and molecular docking studies of pyrimidine-coumarin-triazole conjugates as prospective anti-breast cancer agents. Molecules, 27(6), 1845. https://doi.org/10.3390/molecules27061845
  • Talatam, A., Reddy, P. K., Motohashi, N., Vanam, A., & Gollapudi, R. (2023). Targeting overexpressed cyclin dependent kinase 1 (CDK1) in human cancers: Kamalachalcone A emerged as potential inhibitor of CDK1 kinase through in silico docking study. Oncogen, 6(1), 25. https://doi.org/10.35702/onc.10025
  • Thakur, A., Kumar, A., Sharma, V., & Mehta, V. (2022). PIC50: An open source tool for interconversion of pIC50 values and IC 50 for efficient data representation and analysis [Preprint]. Bioinformatics. https://doi.org/10.1101/2022.10.15.512366
  • Tropsha, A. (2010). Best practices for QSAR model development, validation, and exploitation. Molecular Informatics, 29(6–7), 476–488. https://doi.org/10.1002/minf.201000061
  • Uchiyama, H., Sowa, Y., Wakada, M., Yogosawa, M., Nakanishi, R., Horinaka, M., Shimazaki, C., Taniwaki, M., & Sakai, T. (2010). Cyclin-dependent kinase inhibitors enhance sensitivity to methotrexate in human T-cell leukemia Jurkat cells. Blood, 116(21), 3976–3976. https://doi.org/10.1182/blood.V116.21.3976.3976
  • Vijayakumar, S., Manogar, P., Prabhu, S., & Sanjeev Kumar Singh, R. A. (2018). Novel ligand-based docking; molecular dynamic simulations; and absorption, distribution, metabolism, and excretion approach to analyzing potential acetylcholinesterase inhibitors for Alzheimer’s disease. Journal of Pharmaceutical Analysis, 8(6), 413–420. https://doi.org/10.1016/j.jpha.2017.07.006
  • WHO. (2020). Cancer country profiles. https://www.who.int/health-topics/cancer#tab=tab_1
  • Wijnen, R., Pecoraro, C., Carbone, D., Fiuji, H., Avan, A., Peters, G. J., Giovannetti, E., & Diana, P. (2021). Cyclin dependent kinase-1 (CDK-1) inhibition as a novel therapeutic strategy against pancreatic ductal adenocarcinoma (PDAC). Cancers, 13(17), 4389. https://doi.org/10.3390/cancers13174389
  • Wu, W., Liu, F., Su, A., Gong, Y., Zhao, W., Liu, Y., Ye, H., & Zhu, J. (2018). The effect and mechanism of millepachine-disrupted spindle assembly in tumor cells. Anti-Cancer Drugs, 29(5), 449–456. https://doi.org/10.1097/CAD.0000000000000618
  • Wu, W., Ye, H., Wan, L., Han, X., Wang, G., Hu, J., Tang, M., Duan, X., Fan, Y., He, S., Huang, L., Pei, H., Wang, X., Li, X., Xie, C., Zhang, R., Yuan, Z., Mao, Y., Wei, Y., & Chen, L. (2013). Millepachine, a novel chalcone, induces G 2/M arrest by inhibiting CDK1 activity and causing apoptosis via ROS-mitochondrial apoptotic pathway in human hepatocarcinoma cells in vitro and in vivo. Carcinogenesis, 34(7), 1636–1643. https://doi.org/10.1093/carcin/bgt087
  • Yan, P., Lai, Q., Li, M., Jin, X., Wie, G., Chen, W., & Ye, L. (2021). New anticancer agents: Design, synthesis, biological activity, and molecular docking of bicyclic phloroglucinol derivatives. ChemistrySelect, 6(7), 1453–1457. https://doi.org/10.1002/slct.202004442

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.