2022 Volume 13 Issue 2

Structure-based Multi-targeted Molecular Docking and Molecular Dynamic Simulation Analysis to Identify Potential Inhibitors against Ovarian Cancer


Bandar Hamad Aloufi*


Ovarian Cancer (OC) is among the most prevalent cancers in females. OC is one of the deadliest and worst prognosis diseases. Currently, there are no approved OC screening tests or early detection methods. Hence, new screening, prevention, and early detection strategies are still highly demanded. Plant compounds have recently become increasingly important in developing new, effective, and affordable anti-cancer drugs. To investigate the protein-ligand interaction, molecular docking was used with the Molecular Operating Environment (MOE) tool to find the best inhibitor for the target proteins. Compound spatial affinity for the active sites of the NY-ESO-1, RUNX3, and UBE2Q1 proteins was calculated using molecular docking. ADMET analysis was used to determine the drug-likeness of the selected compounds, while MD simulation and MMGBSA/MMPBSA experiments were used to further understand the binding behaviors. Pre-clinical tests can help confirm the validity of our in silico studies and determine whether the compound can be used as an anti-cancer drug to treat OC.

Keywords: Ovarian cancer, Anti-cancer drugs, NY-ESO-1, RUNX3, UBE2Q1



Abdelrheem, D. A., Rahman, A. A., Elsayed, K. N., Abd El-Mageed, H. R., Mohamed, H. S., & Ahmed, S. A. (2021). Isolation, characterization, in vitro anticancer activity, dft calculations, molecular docking, bioactivity score, drug-likeness and admet studies of eight phytoconstituents from brown alga sargassum platycarpum. Journal of Molecular Structure1225, 129245.

Alhumaydhi, F. A., Rauf, A., Rashid, U., Bawazeer, S., Khan, K., Mubarak, M. S., Aljohani, A. S., Khan, H., El-Saber Batiha, G., El-Esawi, M. A., et al. (2021). In Vivo and In Silico Studies of Flavonoids Isolated from Pistacia integerrima as Potential Antidiarrheal Agents. ACS Omega6(24), 15617-15624.

Auner, V., Sehouli, J., Oskay-Oezcelik, G., Horvat, R., Speiser, P., & Zeillinger, R. (2010). ABC transporter gene expression in benign and malignant ovarian tissue. Gynecologic Oncology117(2), 198-201.

Awasthi, M., Singh, S., Pandey, V. P., & Dwivedi, U. N. (2015). Molecular docking and 3D-QSAR-based virtual screening of flavonoids as potential aromatase inhibitors against estrogen-dependent breast cancer. Journal of Biomolecular Structure and Dynamics33(4), 804-819.

Barua, A., Kesavan, K., & Jayanthi, S. (2018). Molecular Docking Studies of Plant Compounds to Identify Efficient Inhibitors for Ovarian Cancer. Research Journal of Pharmacy and Technology11(9), 3811-3815.

Bittrich, S., Rose, Y., Segura, J., Lowe, R., Westbrook, J. D., Duarte, J. M., & Burley, S. K. (2022). RCSB Protein Data Bank: improved annotation, search and visualization of membrane protein structures archived in the PDB. Bioinformatics38(5), 1452-1454.

Bray, F., Ferlay, J., Soerjomataram, I., Siegel, R. L., Torre, L. A., & Jemal, A. (2018). Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians, 68(6), 394-424.

Cheng, F., Li, W., Zhou, Y., Shen, J., Wu, Z., Liu, G., Lee, P. W., & Tang, Y. (2012). admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties. ACS Publications.

Danilova, A., Misyurin, V., Novik, A., Girdyuk, D., Avdonkina, N., Nekhaeva, T., Emelyanova, N., Pipia, N., Misyurin, A., & Baldueva, I. (2020). Cancer/testis antigens expression during cultivation of melanoma and soft tissue sarcoma cells. Clinical Sarcoma Research10(1), 1-14.

Das, P., Majumder, R., Mandal, M., & Basak, P. (2021). In-Silico approach for identification of effective and stable inhibitors for COVID-19 main protease (Mpro) from flavonoid based phytochemical constituents of Calendula officinalis. Journal of Biomolecular Structure and Dynamics39(16), 6265-6280.

de Vries, S. J., & Bonvin, A. M. (2011). CPORT: a consensus interface predictor and its performance in prediction-driven docking with HADDOCK. PloS one6(3), e17695.

Devi, K. P., Rajavel, T., Habtemariam, S., Nabavi, S. F., & Nabavi, S. M. (2015). Molecular mechanisms underlying anticancer effects of myricetin. Life Sciences142, 19-25.

Ghilardi, C., Moreira Barbosa, C., Brunelli, L., Ostano, P., Panini, N., Lupi, M., Anastasia, A., Fiordaliso, F., Salio, M., Formenti, L., et al. (2022). PGC1α/β expression predicts therapeutic response to oxidative phosphorylation inhibition in ovarian canceroxphos inhibition as therapeutic option in ovarian cancer. Cancer Research.

Gogoi, B., Gogoi, D., Silla, Y., Kakoti, B. B., & Bhau, B. S. (2017). Network pharmacology-based virtual screening of natural products from Clerodendrum species for identification of novel anti-cancer therapeutics. Molecular BioSystems13(2), 406-416.

Gupta, S., Afaq, F., & Mukhtar, H. (2001). Selective growth-inhibitory, cell-cycle deregulatory and apoptotic response of apigenin in normal versus human prostate carcinoma cells. Biochemical and Biophysical Research Communications287(4), 914-920.

Haque, A., Baig, G. A., Alshawli, A. S., Sait, K. H. W., Hafeez, B. B., Tripathi, M. K., Alghamdi, B. S., Mohammed Ali, H. S., & Rasool, M. (2022). Interaction Analysis of MRP1 with Anticancer Drugs Used in Ovarian Cancer: In Silico Approach. Life12(3), 383.

Henriksen, J. R., Donskov, F., Waldstrøm, M., Jakobsen, A., Hjortkjaer, M., Petersen, C. B., & Dahl Steffensen, K. (2020). Favorable prognostic impact of Natural Killer cells and T cells in high-grade serous ovarian carcinoma. Acta Oncologica59(6), 652-659.

Ikot, A. N., Okorie, U. S., Osobonye, G., Amadi, P. O., Edet, C. O., Sithole, M. J., Rampho, G. J., & Sever, R. (2020). Superstatistics of Schrödinger equation with pseudo-harmonic potential in external magnetic and Aharanov-Bohm fields. Heliyon6(4), e03738.

Irwin, J. J., & Shoichet, B. K. (2005). ZINC− a free database of commercially available compounds for virtual screening. Journal of chemical Information and Modeling45(1), 177-182.

Kabir, M., Nantasenamat, C., Kanthawong, S., Charoenkwan, P., & Shoombuatong, W. (2022). Large-scale comparative review and assessment of computational methods for phage virion proteins identification. EXCLI Journal21, 11-29.

Kbirou, A., Sayah, M., Sounni, F., Zamd, M., Benghanem, M. G., Dakir, M., Debbagh, A., & Aboutaib, R. (2022). Obstructive oligo-anuria revealing pelvic gynecological cancers, analysis of a series of 102 cases. Annals of Medicine and Surgery75, 103332.

Khalifa, I., Zhu, W., Mohammed, H. H. H., Dutta, K., & Li, C. (2020). Tannins inhibit SARS‐CoV‐2 through binding with catalytic dyad residues of 3CLpro: An in silico approach with 19 structural different hydrolysable tannins. Journal of Food Biochemistry44(10), e13432.

Kim, S., Thiessen, P. A., Bolton, E. E., Chen, J., Fu, G., Gindulyte, A., Han, L., He, J., He, S., Shoemaker, B. A., et al. (2016). PubChem substance and compound databases. Nucleic Acids Research44(D1), D1202-D1213.

Kumar, A., Rathi, E., & Kini, S. G. (2019). E-pharmacophore modelling, virtual screening, molecular dynamics simulations and in-silico ADME analysis for identification of potential E6 inhibitors against cervical cancer. Journal of Molecular Structure1189, 299-306.

Ledermann, J. A., Raja, F. A., Fotopoulou, C., Gonzalez-Martin, A., Colombo, N., & Sessa, C. (2013). Newly diagnosed and relapsed epithelial ovarian carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Annals of Oncology24, vi24-vi32.

Li, Y., Zhang, S., Bao, Z., Sun, N., & Lin, S. (2022). Explore the activation mechanism of alcalase activity with pulsed electric field treatment: Effects on enzyme activity, spatial conformation, molecular dynamics simulation and molecular docking parameters. Innovative Food Science & Emerging Technologies, 102918.

Manchanda, R. (2022). Special Issue “Gynaecological Cancers Risk: Breast Cancer, Ovarian Cancer and Endometrial Cancer”. Cancers14(2), 319.

Mishra, A., & Singh, A. (2022). Discovery of Histone Deacetylase Inhibitor Using Molecular Modeling and Free Energy Calculations. ACS Omega.

Mohammed, I. (2021). Virtual screening of Microalgal compounds as potential inhibitors of Type 2 Human Transmembrane serine protease (TMPRSS2). arXiv preprint arXiv:2108.13764.

Mumtaz, A., Ashfaq, U. A., ul Qamar, M. T., Anwar, F., Gulzar, F., Ali, M. A., Saari, N., & Pervez, M. T. (2017). MPD3: a useful medicinal plants database for drug designing. Natural Product Research31(11), 1228-1236.

Opo, F. A., Rahman, M. M., Ahammad, F., Ahmed, I., Bhuiyan, M. A., & Asiri, A. M. (2021). Structure based pharmacophore modeling, virtual screening, molecular docking and ADMET approaches for identification of natural anti-cancer agents targeting XIAP protein. Scientific Reports11(1), 1-17.

Pahwa, R., Chhabra, J., Kumar, R., & Narang, R. (2022). Melphalan: Recent insights on synthetic, analytical and medicinal aspects. European Journal of Medicinal Chemistry, 114494.

Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera—a visualization system for exploratory research and analysis. Journal of Computational Chemistry25(13), 1605-1612.

Pettersen, E. F., Goddard, T. D., Huang, C. C., Meng, E. C., Couch, G. S., Croll, T. I., Morris, J. H., & Ferrin, T. E. (2021). UCSF ChimeraX: Structure visualization for researchers, educators, and developers. Protein Science30(1), 70-82.

Podvinec, M., Lim, S. P., Schmidt, T., Scarsi, M., Wen, D., Sonntag, L. S., Sanschagrin, P., Shenkin, P. S., & Schwede, T. (2010). Novel inhibitors of dengue virus methyltransferase: discovery by in vitro-driven virtual screening on a desktop computer grid. Journal of Medicinal Chemistry53(4), 1483-1495.

Rehan, M., & Bajouh, O. S. (2019). Virtual screening of naphthoquinone analogs for potent inhibitors against the cancer‐signaling PI3K/AKT/mTOR pathway. Journal of Cellular Biochemistry120(2), 1328-1339.

Release, S. (2017). 3: Desmond molecular dynamics system, DE Shaw research, New York, NY, 2017. Maestro-Desmond Interoperability Tools, Schrödinger, New York, NY.

Roy, P., Sur, S., Das, S., & Wui, W. T. (2022). Phytochemical-conjugated bio-safe gold nanoparticles in breast cancer: a comprehensive update. Breast Cancer, 1-17.

Siegel, R. L., Miller, K. D., & Jemal, A. (2016). Cancer statistics, 2016. CA: a cancer journal for clinicians66(1), 7-30.

Tavsan, Z., & Kayali, H. A. (2019). Flavonoids showed anticancer effects on the ovarian cancer cells: Involvement of reactive oxygen species, apoptosis, cell cycle and invasion. Biomedicine & Pharmacotherapy116, 109004.

Thomas, R., Al-Khadairi, G., Roelands, J., Hendrickx, W., Dermime, S., Bedognetti, D., & Decock, J. (2018). NY-ESO-1 based immunotherapy of cancer: current perspectives. Frontiers in Immunology9, 947.

Topno, R., Singh, I., Kumar, M., & Agarwal, P. (2021). Integrated bioinformatic analysis identifies UBE2Q1 as a potential prognostic marker for high grade serous ovarian cancer. BMC Cancer21(1), 1-13.

Torre, L. A., Trabert, B., DeSantis, C. E., Miller, K. D., Samimi, G., Runowicz, C. D., Gaudet, M. M., Jemal, A.., & Siegel, R. L. (2018). Ovarian cancer statistics, 2018. CA: a Cancer Journal for Clinicians68(4), 284-296.

Vilar, S., Cozza, G., & Moro, S. (2008). Medicinal chemistry and the molecular operating environment (MOE): application of QSAR and molecular docking to drug discovery. Current Topics in Medicinal Chemistry8(18), 1555-1572.

Wang, L., Chen, L., Yu, M., Xu, L. H., Cheng, B., Lin, Y. S., Gu, Q., He, X. H., & Xu, J. (2016). Discovering new mTOR inhibitors for cancer treatment through virtual screening methods and in vitro assays. Scientific Reports6(1), 1-13.

Wang, Y. T., Yang, Z. X., Piao, Z. H., Xu, X. J., Yu, J. H., & Zhang, Y. H. (2021). Prediction of flavor and retention index for compounds in beer depending on molecular structure using a machine learning method. RSC Advances11(58), 36942-36950.

Yousefi, H., Yuan, J., Keshavarz-Fathi, M., Murphy, J. F., & Rezaei, N. (2017). Immunotherapy of cancers comes of age. Expert Review of Clinical Immunology13(10), 1001-1015.

Yousuf, Z., Iman, K., Iftikhar, N., & Mirza, M. U. (2017). Structure-based virtual screening and molecular docking for the identification of potential multi-targeted inhibitors against breast cancer. Breast Cancer: Targets and Therapy9, 447.

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This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. Keywords include, Biochemical Research: Endo/exocytosis, Trafficking, Membrane Biology, Cell Migration, Cell-Matrix Organelle Biogenesis, Cytoskeleton Proteolysis, Cell Death, Cell Cycle, Cancer, Cell Growth/Death, Differentiation, Drug Targets, Gene Therapy, Models of Disease, Proteomics, Stem Cells, Bioenergetics, Mitochondria, Free Radicals, Redox Signaling, Ion Transport/Channels, Oxidative