The Potency of Alkaloid Derivates as Anti-Breast Cancer Candidates: In Silico Study

Sedin Renadi, Anindita Tri Kusuma Pratita, Richa Mardianingrum, Ruswanto Ruswanto


Breast cancer is the most frequent malignancy in women worldwide. One of the target receptors for the treatment of breast cancer are estrogen, progesterone, and HER2 receptors. An alternative treatment using natural ingredients has been developed, one of which is alkaloid compounds. This study aims to determine the activity of alkaloid compounds as anti-breast cancer agents through an in-silico method. Virtual screening (AutoDock Vina), molecular docking (AutoDock Tools), molecular dynamics (Desmond), scanning Lipinski's rule of five, as well as pharmacokinetic and toxicity parameters, were performed. The results of virtual screening, molecular docking, and molecular dynamics show that the compounds daurisoline, solasodine, and sambutoxin have stable interactions with the HER2 receptor, with the lowest values of RMSD (Root Mean Square Deviation) and RMSF (Root Mean Square Fluctuation) compared to other compounds. Based on the results of the study conducted, it was shown that daurisoline, solasodine, and sambutoxin were predicted to be used as anti-HER2 candidates for the treatment of breast cancer.


alkaloids; molecular dynamics; breast cancer; molecular docking; virtual screening


Carugo, O., Djinovic Carugo, K. (2013). Half a century of Ramachandran plots. Acta Crystallographica Section D: Biological Crystallography, 69(8), 1333–1341.

Colovos, C., Yeates, T. O. (1993). Verification of protein structures: Patterns of nonbonded atomic interactions. Protein Science, 2(9), 1511–1519.

Devarajan, P. V., Dandekar, P., D’Souza, A. A. (2019). Targeted Intracellular Drug Delivery by Receptor Mediated Endocytosis (39 ed.). Springer.

Dey, P., Kundu, A., Chakraborty, H. J., Kar, B., Choi, W. S., Lee, B. M., Bhakta, T., Atanasov, A. G., Kim, H. S. (2019). Therapeutic value of steroidal alkaloids in cancer: Current trends and future perspectives. International Journal of Cancer, 145(7), 1731–1744.

Dubach, V. R. A., Guskov, A. (2020). The Resolution in X-ray Crystallography and Single-Particle Cryogenic Electron Microscopy. Crystals, 10(580), 1–13.

Dutta, B., Banerjee, A., Chakraborty, P., Bandopadhyay, R. (2018). In silico studies on bacterial xylanase enzyme: Structural and functional insight. Journal of Genetic Engineering and Biotechnology, 16(2), 749–756.

Florová, P., Sklenovský, P., Banáš, P., Otyepka, M. (2010). Explicit water models affect the specific solvation and dynamics of unfolded peptides while the conformational behavior and flexibility of folded peptides remain intact. Journal of Chemical Theory and Computation, 6(11), 3569–3579.

Forli, S., Huey, R., Pique, M. E., Sanner, M. F., Goodsell, D. S., Olson, A. J. (2016). Computational protein–ligand docking and virtual drug screening with the AutoDock suite. nature protocols, 11(5), 905–919.

Halgren, T. A. (1999). MMFF VII. Characterization of MMFF94, MMFF94s, and other widely available force fields for conformational energies and for intermolecular-interaction energies and geometries. Journal of Computational Chemistry, 20(7), 730–748.<730::AID-JCC8>3.0.CO;2-T

Hollingsworth, S. A., Dror, R. O. (2018). Molecular Dynamics Simulation for All. Neuron, 99(6), 1129–1143.

Huang, K., Chen, Q., Deng, L., Zou, Q., Min, S. (2022). Daurisoline Inhibiting Tumor Angiogenesis and Epithelial-Mesenchymal Transition in Bladder Cancer by Mediating HAKAI Protein Stability. Iranian Journal of Pharmaceutical Research, 21(1), 1–14.

Islam, M. K., Barman, A. C., Qais, N. (2020). Anti-Cancer Constituents from Plants : A Brief Review. J. Pharm, 19(1), 83–96.

Jayaram, B., Singh, T., Mukherjee, G., Mathur, A., Shekhar, S., Shekhar, V. (2012). Sanjeevini: a freely accessible web-server for target directed lead molecule discovery. BMC bioinformatics, 13 Suppl 1(Suppl 17).

Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., Klein, M. L. (1983). Comparison of simple potential functions for simulating liquid water. The Journal of Chemical Physics, 79(2), 926–935.

Kar, S., Leszczynski, J. (2020). Open access in silico tools to predict the ADMET profiling of drug candidates. Expert Opinion on Drug Discovery, 15(12), 1473–1487.

Laskowski, R. A., Hutchinson, E. G., Michie, A. D., Wallace, A. C., Jones, M. L., Thornton, J. M. (1997). PDBsum: A Web-based database of summaries and analyses of all PDB structures. Trends in Biochemical Sciences, 22(12), 488–490.

Laskowski, R. A., Jabłońska, J., Pravda, L., Vařeková, R. S., Thornton, J. M. (2018). PDBsum: Structural summaries of PDB entries. Protein Science, 27(1), 129–134.

Li, L.-N., Wang, L., Cheng, Y.-N., Cao, Z.-Q., Zhang, X.-K., Guo, X.-L. (2018). Discovery and Characterization of 4-Hydroxy-2-pyridone Derivative Sambutoxin as a Potent and Promising Anticancer Drug Candidate: Activity and Molecular Mechanism. Molecular Pharmaceutics, 15(11), 4898–4911.

Lipinski, C. A. (2004). Lead- and drug-like compounds: The rule-of-five revolution. Drug Discovery Today: Technologies, 1(4), 337–341.

Lu, H., Yin, D., Ye, Y., Luo, H., Geng, L., Li, H. (2009). Correlation Between Protein Sequence Similarity and X-Ray Diffraction Quality in the Protein Data Bank. 50–55.

Mardianingrum, R., Endah, S. R. N., Suhardiana, E., Ruswanto, R., Siswandono, S. (2021). Docking and molecular dynamic study of isoniazid derivatives as anti-tuberculosis drug candidate. Chemical Data Collections, 32, 100647.

Mario, D., Lobo, F., Amesty, Á., Vald, C., Canerina-amaro, A., Mesa-herrera, F., Soler, K., Boto, A., Mar, R., Est, A., Lahoz, F. (2021). FLTX2 : A Novel Tamoxifen Derivative Endowed with Antiestrogenic , Fluorescent , and Photosensitizer Properties.

Maximov, P. Y., Abderrahman, B., Fanning, S. W., Sengupta, S., Fan, P., Curpan, R. F., Rincon, D. M. Q., Greenland, J. A., Rajan, S. S., Greene, G. L., Jordan, V. C. (2018). Endoxifen, 4-Hydroxytamoxifen and an Estrogenic Derivative Modulate Estrogen Receptor Complex Mediated Apoptosis in Breast Cancer. Molecular Pharmacology, 94(2), 812–822.

Pires, D. E. V., Blundell, T. L., Ascher, D. B. (2015). pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. Journal of Medicinal Chemistry, 58(9), 4066–4072.

Pollastri, M. P. (2010). Overview on the rule of five. Current Protocols in Pharmacology, SUPPL. 49, 1–8.

Qing, Z.-X., Huang, J.-L., Yang, X.-Y., Liu, J.-H., Cao, H.-L., Xiang, F., Cheng, P., Zeng, J.-G. (2017). Anticancer and Reversing Multidrug Resistance Activities of Natural Isoquinoline Alkaloids and their Structure-activity Relationship. Current Medicinal Chemistry, 25(38), 5088–5114.

Rampogu, S., Balasubramaniyam, T., Lee, J. (2022). Biomedicine & Pharmacotherapy Phytotherapeutic applications of alkaloids in treating breast cancer. Biomedicine & Pharmacotherapy, 155(September), 113760.

Raval, K., Ganatra, T. (2022). Basics , types and applications of molecular docking : A review Basics , types and applications of molecular docking : A review. March.

Research, D. E. S. (2019). Desmond Molecular Dynamics System (No. 2019–2). Maestro-Desmond Interoperability Tools, Schrödinger.

Ruswanto, Aprillia, A. Y., Hapid, P. A. (2022). Monograf Telaah Analisis Bioinformatika Turunan Alkaloid Sebagai Kandidat Terapi SARS-CoV-2. Global Aksara Pers.

Ruswanto, R., Mardianingrum, R., Yanuar, A. (2022). Computational Studies of Thiourea Derivatives as Anticancer Candidates through Inhibition of Sirtuin-1 (SIRT1). Jurnal Kimia Sains dan Aplikasi, 25(3), 87–96.

Ruswanto, R., Miftah, A. M., Tjahjono, D. H., Siswandono. (2021). In silico study of 1-benzoyl-3-methylthiourea derivatives activity as epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor candidates. Chemical Data Collections, 34(36), 100741.

Selick, H. E., Beresford, A. P., Tarbit, M. H. (2002). The emerging importance of predictive ADME simulation in drug discovery. Drug Discovery Today, 7(2), 109–116.

Su, J., Sun, T., Wang, Y., Shen, Y. (2022). Conformational Dynamics of Glucagon-like Peptide-2 with Different Electric Field. Polymers, 14(2722).

Sunani, Andani, M., Kamaludin, A., Stannia, N., Helmi, P., Mei, K., Guspira, Y., Sabetta, O., Aulifa, D. (2022). In Silico Study of Compounds in Bawang Dayak ( Eleutherine palmifolia ( L ) Merr .) Bulbs on Alpha Estrogen Receptors. Indonesian Journal of Cancer Chemoprevention, June, 83–93.

Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., Bray, F. (2021). Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians, 71(3), 209–249.

Tam, B., Sinha, S., Wang, S. M. (2020). Combining Ramachandran plot and molecular dynamics simulation for structural-based variant classification: Using TP53 variants as model. Computational and Structural Biotechnology Journal, 18, 4033–4039.

Tilaoui, M., Ait Mouse, H., Zyad, A. (2021). Update and New Insights on Future Cancer Drug Candidates From Plant-Based Alkaloids. Frontiers in Pharmacology, 12(December), 1–19.

Tran, N. T., Jakovlić, I., Wang, W.-M. (2015). In silico characterisation, homology modelling and structure-based functional annotation of blunt snout bream (Megalobrama amblycephala) Hsp70 and Hsc70 proteins. Journal of Animal Science and Technology, 57(1), 1–9.

Trott, O., Olson, A. J. (2009). AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading. Journal of computational chemistry, 31(2), 174–182.

Wallner, B. (2006). Identification of correct regions in protein models using structural, alignment, and consensus information. Protein Science, 15(4), 900–913.

Wang, D., Zhang, W., Zhang, X., Li, M., Wu, Q., Li, X., Zhao, L., Yuan, Q., Yu, Y., Lu, J., Zhao, J., Dong, Z., Liu, K., Jiang, Y. (2023). Daurisoline suppresses esophageal squamous cell carcinoma growth in vitro and in vivo by targeting MEK1/2 kinase. Molecular Carcinogenesis, December 2022.

Wilding, B., Scharn, D., Böse, D., Baum, A., Santoro, V., Chetta, P., Schnitzer, R., Botesteanu, D. A., Reiser, C., Kornigg, S., Knesl, P., Hörmann, A., Köferle, A., Corcokovic, M., Lieb, S., Scholz, G., Bruchhaus, J., Spina, M., Balla, J., … Neumüller, R. A. (2022). Discovery of potent and selective HER2 inhibitors with efficacy against HER2 exon 20 insertion-driven tumors, which preserve wild-type EGFR signaling. Nature Cancer, 3(7), 821–836.

Wiltgen, M. (2018). Algorithms for structure comparison and analysis: Homology modelling of proteins. In Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics (Vol. 1–3). Elsevier Ltd.

Wu, M. Y., Wang, S. F., Cai, C. Z., Tan, J. Q., Li, M., Lu, J. J., Chen, X. P., Wang, Y. T., Zheng, W., Lu, J. H. (2017). Natural autophagy blockers, dauricine (DAC) and daurisoline (DAS), sensitize cancer cells to camptothecin-induced toxicity. Oncotarget, 8(44), 77673–77684.

Yang, C., Xia, A. J., Du, C. H., Hu, M. X., Gong, Y. L., Tian, R., Jiang, X., Xie, Y. M. (2022). Discovery of highly potent and selective 7-ethyl-10-hydroxycamptothecin-glucose conjugates as potential anti-colorectal cancer agents. Frontiers in Pharmacology, 13(November), 1–12.

Zhang, Z., Olland, A. M., Zhu, Y., Cohen, J., Berrodin, T., Chippari, S., Appavu, C., Li, S., Wilhem, J., Chopra, R., Fensome, A., Zhang, P., Wrobel, J., Unwalla, R. J., Lyttle, C. R., Winneker, R. C. (2005). Molecular and pharmacological properties of a potent and selective novel nonsteroidal progesterone receptor agonist tanaproget. The Journal of Biological Chemistry, 280(31), 28468–28475.

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DOI: 10.15408/jkv.v9i1.31481


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