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Research Article

Pharmacokinetics and drug-likeness of anti-cancer traditional Chinese medicine: molecular docking and molecular dynamics simulation study

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Pages 3295-3306 | Received 23 Sep 2022, Accepted 03 May 2023, Published online: 06 Jun 2023

References

  • Akbarzadeh Khiavi, M., Safary, A., Barar, J., Ajoolabady, A., Somi, M. m. m H., & Omidi, Y. (2020). Multifunctional nanomedicines for targeting epidermal growth factor receptor in colorectal cancer. Cellular and Molecular Life Sciences : CMLS, 77(6), 997–1019. https://doi.org/10.1007/s00018-019-03305-z
  • Alam, R., Biswas, S., Haque, F., Pathan, M. T., Imon, R. R., Talukder, M. E. K., Samad, A., Asseri, A. H., & Ahammad, F. (2022). A systematic analysis of ATPase cation transporting 13A2 (ATP13A2) transcriptional expression and prognostic value in human brain cancer. Biomedical Signal Processing and Control, 71, 103183. https://doi.org/10.1016/j.bspc.2021.103183
  • Aljahdali, M. O., Molla, M. H. R., & Ahammad, F. (2021). Compounds identified from marine mangrove plant (Avicennia Alba) as potential antiviral drug candidates against WDSV, an in-silico approach. Marine Drugs, 19(5), 253. https://doi.org/10.3390/md19050253
  • Anzali, S., Barnickel, G., Cezanne, B., Krug, M., Filimonov, D., & Poroikov, V. (2001). Discriminating between drugs and nondrugs by prediction of activity spectra for substances (PASS). Journal of Medicinal Chemistry, 44(15), 2432–2437. https://doi.org/10.1021/jm0010670
  • Asgharzadeh, M. R., Barar, J., Pourseif, M. M., Eskandani, M., Jafari Niya, M., Mashayekhi, M. R., & Omidi, Y. (2017). Molecular machineries of pH dysregulation in tumor microenvironment: Potential targets for cancer therapy. BioImpacts: BI, 7(2), 115–133. https://doi.org/10.15171/bi.2017.15
  • Baell, J. B., & Holloway, G. A. (2010). New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. Journal of Medicinal Chemistry, 53(7), 2719–2740. https://doi.org/10.1021/jm901137j
  • Berendsen, H., Grigera, J., & Straatsma, T. (1987). The missing term in effective pair potentials. The Journal of Physical Chemistry, 91(24), 6269–6271. https://doi.org/10.1021/j100308a038
  • Berman, H. M., Battistuz, T., Bhat, T. N., Bluhm, W. F., Bourne, P. E., Burkhardt, K., Feng, Z., Gilliland, G. L., Iype, L., Jain, S., Fagan, P., Marvin, J., Padilla, D., Ravichandran, V., Schneider, B., Thanki, N., Weissig, H., Westbrook, J. D., & Zardecki, C. (2002). The protein data bank. Acta Crystallographica. Section D, Biological Crystallography, 58(Pt 6 No 1), 899–907. https://doi.org/10.1107/s0907444902003451
  • Cai, C., Wu, Q., Hong, H., He, L., Liu, Z., Gu, Y., Zhang, S., Wang, Q., Fan, X., & Fang, J. (2021). In silico identification of natural products from Traditional Chinese Medicine for cancer immunotherapy. Scientific Reports, 11(1), 1–13. https://doi.org/10.1038/s41598-021-82857-2
  • Casey, S. C., et al. (2015). Cancer prevention and therapy through the modulation of the tumor microenvironment. Seminars in cancer biology. Elsevier.
  • Chen, C. Y.-C. (2011). TCM Database@ Taiwan: The world’s largest traditional Chinese medicine database for drug screening in silico. PloS One, 6(1), e15939. https://doi.org/10.1371/journal.pone.0015939
  • Cheng, F., et al. (2012). admetSAR: A comprehensive source and free tool for assessment of chemical ADMET properties. ACS Publications.
  • Choudhari, A. S., Mandave, P. C., Deshpande, M., Ranjekar, P., & Prakash, O. (2020). Phytochemicals in cancer treatment: From preclinical studies to clinical practice. Frontiers in Pharmacology, 10, 1614. https://doi.org/10.3389/fphar.2019.01614
  • Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7(1), 1–13. https://doi.org/10.1038/srep42717
  • Dobbelstein, M., & Moll, U. (2014). Targeting tumour-supportive cellular machineries in anticancer drug development. Nature Reviews. Drug Discovery, 13(3), 179–196. https://doi.org/10.1038/nrd4201
  • Fang, J., Cai, C., Wang, Q., Lin, P., Zhao, Z., & Cheng, F. (2017). Systems pharmacology‐based discovery of natural products for precision oncology through targeting cancer mutated genes. CPT: Pharmacometrics & Systems Pharmacology, 6(3), 177–187. https://doi.org/10.1002/psp4.12172
  • Fiser, A., Do, R. K., & Sali, A. (2000). Modeling of loops in protein structures. Protein Science: A Publication of the Protein Society, 9(9), 1753–1773. https://doi.org/10.1110/ps.9.9.1753
  • Globocan, U. (2020). New Global Cancer Data.
  • Hashemzadeh, S., Shahmorad, S., Rafii-Tabar, H., & Omidi, Y. (2020). Computational modeling to determine key regulators of hypoxia effects on the lactate production in the glycolysis pathway. Scientific Reports, 10(1), 1–8. https://doi.org/10.1038/s41598-020-66059-w
  • Huey, R., Morris, G. M., & Forli, S. (2012). Using AutoDock 4 and AutoDock vina with AutoDockTools: A tutorial. The Scripps Research Institute Molecular Graphics Laboratory, 10550, 92037.
  • Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD: Visual molecular dynamics. Journal of Molecular Graphics, 14(1), 33–38. https://doi.org/10.1016/0263-7855(96)00018-5
  • Jalal, K., Khan, K., Haleem, D. J., & Uddin, R. (2022). In silico study to identify new monoamine oxidase type a (MAO-A) selective inhibitors from natural source by virtual screening and molecular dynamics simulation. Journal of Molecular Structure, 1254, 132244. https://doi.org/10.1016/j.molstruc.2021.132244
  • Jiang, W. G., Sanders, A. J., Katoh, M., Ungefroren, H., Gieseler, F., Prince, M., Thompson, S. K., Zollo, M., Spano, D., Dhawan, P., Sliva, D., Subbarayan, P. R., Sarkar, M., Honoki, K., Fujii, H., Georgakilas, A. G., Amedei, A., Niccolai, E., Amin, A., … Santini, D. (2015). Tissue invasion and metastasis: Molecular, biological and clinical perspectives. Seminars in Cancer Biology, 35, S244–S275. in Elsevier. https://doi.org/10.1016/j.semcancer.2015.03.008
  • Kalimuthu, A. K., Panneerselvam, T., Pavadai, P., Pandian, S. R. K., Sundar, K., Murugesan, S., Ammunje, D. N., Kumar, S., Arunachalam, S., & Kunjiappan, S. (2021). Pharmacoinformatics-based investigation of bioactive compounds of Rasam (South Indian recipe) against human cancer. Scientific Reports, 11(1), 1–19. https://doi.org/10.1038/s41598-021-01008-9
  • Karim, M. A., Samad, A., Adhikari, U. K., Kader, M. A., Kabir, M. M., Islam, M. A., & Hasan, M. N. (2020). A multi-omics analysis of bone morphogenetic protein 5 (BMP5) mRNA expression and clinical prognostic outcomes in different cancers using bioinformatics approaches. Biomedicines, 8(2), 19. https://doi.org/10.3390/biomedicines8020019
  • Lagunin, A., Stepanchikova, A., Filimonov, D., & Poroikov, V. (2000). PASS: Prediction of activity spectra for biologically active substances. Bioinformatics (Oxford, England), 16(8), 747–748. https://doi.org/10.1093/bioinformatics/16.8.747
  • Lakhera, S., et al. (2022). A comprehensive exploration of pharmacological properties, bioactivities and inhibitory potentiality of luteolin from Tridax procumbens as anticancer drug by in-silico approach. Structural Chemistry, 1–17.
  • Lee, S., et al. (2003). The PreADME Approach: Web-based program for rapid prediction of physico-chemical, drug absorption and drug-like properties. EuroQSAR Designing Drugs Crop Protectants: Processes, Problems Solutions, 2003, 418–420.
  • Li, Z., & Xu, X. (2019). Post-translational modifications of the mini-chromosome maintenance proteins in DNA replication. Genes, 10(5), 331. https://doi.org/10.3390/genes10050331
  • Liang, Z., Li, W., Liu, J., Li, J., He, F., Jiang, Y., Yang, L., Li, P., Wang, B., Wang, Y., Ren, Y., Yang, J., Luo, Z., Vaziri, C., & Liu, P. (2017). Simvastatin suppresses the DNA replication licensing factor MCM7 and inhibits the growth of tamoxifen-resistant breast cancer cells. Scientific Reports, 7(1), 1–11. https://doi.org/10.1038/srep41776
  • Lima, L. R., Bastos, R. S., Ferreira, E. F. B., Leão, R. P., Araújo, P. H. F., Pita, S. S. d R., De Freitas, H. F., Espejo-Román, J. M., Dos Santos, E. L. V. S., Ramos, R. d S., Macêdo, W. J. C., & Santos, C. B. R. (2022). Identification of potential new Aedes aegypti Juvenile Hormone Inhibitors from N-Acyl piperidine derivatives: A bioinformatics approach. International Journal of Molecular Sciences, 23(17), 9927. https://doi.org/10.3390/ijms23179927
  • Mahmud, S., Uddin, M. A. R., Paul, G. K., Shimu, M. S. S., Islam, S., Rahman, E., Islam, A., Islam, M. S., Promi, M. M., Emran, T. B., & Saleh, M. A. (2021). Virtual screening and molecular dynamics simulation study of plant-derived compounds to identify potential inhibitors of main protease from SARS-CoV-2. Briefings in Bioinformatics, 22(2), 1402–1414. https://doi.org/10.1093/bib/bbaa428
  • Miyazawa‐Onami, M., Araki, H., & Tanaka, S. (2017). Pre‐initiation complex assembly functions as a molecular switch that splits the Mcm2‐7 double hexamer. EMBO Reports, 18(10), 1752–1761. https://doi.org/10.15252/embr.201744206
  • Müller-Kuhrt, L. (2003). Putting nature back into drug discovery. Nature Biotechnology, 21(6), 602–602. https://doi.org/10.1038/nbt0603-602
  • Nugent, M. (2014). MicroRNA function and dysregulation in bone tumors: The evidence to date. Cancer Management and Research, 6, 15–25. https://doi.org/10.2147/CMAR.S53928
  • O’Boyle, N. M. (2013). Journal of cheminformatics. Open Babel., 3(1), 33–2011.
  • Omidi, Y., & Barar, J. (2014). Targeting tumor microenvironment: Crossing tumor interstitial fluid by multifunctional nanomedicines. BioImpacts: BI, 4(2), 55.
  • Opo, F. A. D. M., 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 Reports, 11(1), 1–17. https://doi.org/10.1038/s41598-021-83626-x
  • Orzechowska, B., Chaber, R., Wiśniewska, A., Pajtasz-Piasecka, E., Jatczak, B., Siemieniec, I., Gulanowski, B., Chybicka, A., & Błach-Olszewska, Z. (2014). Baicalin from the extract of Scutellaria baicalensis affects the innate immunity and apoptosis in leukocytes of children with acute lymphocytic leukemia. International Immunopharmacology, 23(2), 558–567. https://doi.org/10.1016/j.intimp.2014.10.005
  • Parvizpour, S., Masoudi-Sobhanzadeh, Y., Pourseif, M. M., Barzegari, A., Razmara, J., & Omidi, Y. (2021). Pharmacoinformatics-based phytochemical screening for anticancer impacts of yellow sweet clover, Melilotus officinalis (Linn.) Pall. Computers in Biology and Medicine, 138, 104921. https://doi.org/10.1016/j.compbiomed.2021.104921
  • Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. n. i M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera—a visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084
  • Pokhrel, S., Bouback, T. A., Samad, A., Nur, S. M., Alam, R., Abdullah-Al-Mamun, M., Nain, Z., Imon, R. R., Talukder, M. E. K., Tareq, M. M. I., Hossen, M. S., Karpiński, T. M., Ahammad, F., Qadri, Ish. (2021). ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2. International Journal of Biological Macromolecules, 191, 1114–1125.
  • Pronk, S., Páll, S., Schulz, R., Larsson, P., Bjelkmar, P., Apostolov, R., Shirts, M. R., Smith, J. C., Kasson, P. M., van der Spoel, D., Hess, B., & Lindahl, E. (2013). GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics (Oxford, England), 29(7), 845–854. https://doi.org/10.1093/bioinformatics/btt055
  • Samad, A., Haque, F., Nain, Z., Alam, R., Al Noman, M. A., Rahman Molla, M. H., Hossen, M. S., Islam, M. R., Khan, M. I., & Ahammad, F. (2020). Computational assessment of MCM2 transcriptional expression and identification of the prognostic biomarker for human breast cancer. Heliyon, 6(10), e05087. https://doi.org/10.1016/j.heliyon.2020.e05087
  • Samad, A., Huq, M., & Rahman, M. (2022). Bioinformatics approaches identified dasatinib and bortezomib inhibit the activity of MCM7 protein as a potential treatment against human cancer. Scientific Reports, 12(1), 1–16. https://doi.org/10.1038/s41598-022-05621-0
  • Silva de Souza, A., Rivera, J. D., Almeida, V. M., Ge, P., de Souza, R. F., Farah, C. S., Ulrich, H., Marana, S. R., Salinas, R. K., & Guzzo, C. R. (2020). Molecular dynamics reveals complex compensatory effects of ionic strength on the severe acute respiratory syndrome coronavirus 2 spike/human angiotensin-converting enzyme 2 interaction. The Journal of Physical Chemistry Letters, 11(24), 10446–10453. https://doi.org/10.1021/acs.jpclett.0c02602
  • Silva, R. C., Freitas, H. F., Campos, J. M., Kimani, N. M., Silva, C. H. T. P., Borges, R. S., Pita, S. S. R., & Santos, C. B. R. (2021). Natural products-based drug design against SARS-CoV-2 Mpro 3CLpro. International Journal of Molecular Sciences, 22(21), 11739. https://doi.org/10.3390/ijms222111739
  • Stroet, M., Caron, B., Visscher, K. M., Geerke, D. P., Malde, A. K., & Mark, A. E. (2018). Automated topology builder version 3.0: Prediction of solvation free enthalpies in water and hexane. Journal of Chemical Theory and Computation, 14(11), 5834–5845. https://doi.org/10.1021/acs.jctc.8b00768
  • Sun, L., Chen, B., Jiang, R., Li, J., & Wang, B. (2017). Resveratrol inhibits lung cancer growth by suppressing M2-like polarization of tumor associated macrophages. Cellular Immunology, 311, 86–93. https://doi.org/10.1016/j.cellimm.2016.11.002
  • Tabassum, A., Samdani, M. N., Dhali, T. C., Alam, R., Ahammad, F., Samad, A., & Karpiński, T. M. (2021). Transporter associated with antigen processing 1 (TAP1) expression and prognostic analysis in breast, lung, liver, and ovarian cancer. Journal of Molecular Medicine (Berlin, Germany), 99(9), 1293–1309. https://doi.org/10.1007/s00109-021-02088-w
  • Trott, O., & Olson, A. J. (2010). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334
  • van der Spoel, D., van Maaren, P. J., Larsson, P., & Tîmneanu, N. (2006). Thermodynamics of hydrogen bonding in hydrophilic and hydrophobic media. The Journal of Physical Chemistry. B, 110(9), 4393–4398. https://doi.org/10.1021/jp0572535
  • Vassilev, A., & DePamphilis, M. L. (2017). Links between DNA replication, stem cells and cancer. Genes, 8(2), 45. https://doi.org/10.3390/genes8020045
  • Wichapong, K., et al. (2013). Identification of potential hit compounds for Dengue virus NS2B/NS3 protease inhibitors by combining virtual screening and binding free energy calculations. Tropical Biomedicine, 30(3), 388–408.
  • Zhong, L., et al. (2021). Small molecules in targeted cancer therapy: Advances, challenges, and future perspectives. Signal Transduction Targeted Therapy, 6(1), 201.
  • Zhou, H., Xiong, Y., Zhang, G., Liu, Z., Li, L., Hou, S., & Zhou, T. (2020). Elevated expression of minichromosome maintenance 3 indicates poor outcomes and promotes G1/S cell cycle progression, proliferation, migration and invasion in colorectal cancer. Bioscience Reports, 40(7) https://doi.org/10.1042/BSR20201503

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