145
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Computer-aided drug discovery of c-Abl kinase inhibitors from plant compounds against chronic myeloid leukemia

, ORCID Icon, , , , , , , , & ORCID Icon show all
Received 21 Aug 2023, Accepted 06 Mar 2024, Published online: 22 Mar 2024

References

  • Abbas, Z., & Rehman, S. (2018). An overview of cancer treatment modalities. InTech. https://doi.org/10.5772/intechopen.76558
  • Acharya, P. C., Shetty, S., Fernandes, C., Suares, D., Maheshwari, R., & Tekade, R. K. (2018). Preformulation in drug research and pharmaceutical product development. In R. K. Tekade (Ed.), Dosage Form Design Considerations. (pp. 1–55). Academic Press.
  • Aldewachi, H., Al-Zidan, R. N., Conner, M. T., & Salman, M. M. (2021). High-throughput screening platforms in the discovery of novel drugs for neurodegenerative diseases. Bioengineering, 8(2), 30. https://doi.org/10.3390/bioengineering8020030
  • Alpay, K., Farshchian, M., Tuomela, J., Sandholm, J., Aittokallio, K., Siljamäki, E., Kallio, M., Kähäri, V. M., & Hietanen, S. (2014). Inhibition of c-Abl kinase activity renders cancer cells highly sensitive to mitoxantrone. PloS One, 9(8), e105526. https://doi.org/10.1371/journal.pone.0105526
  • Alshehri, M. M., Danazumi, A. U., Kanan, M., Bello, R. O., Alghazwni, M. K., Alshehri, M., Alshlali, O. M., Umar, H. I., Alshlali, O. M., Isiyaku, H., & Repurposing, U. (2024). Repurposing the inhibitors of MMP-9 and SGLT-2 against ubiquitin specific protease 30 in Parkinson ’ s disease : Computational modelling studies. Journal of Biomolecular Structure & Dynamics, 42(3), 1307–1318. https://doi.org/10.1080/07391102.2023.2208223
  • Arber, D. A., Orazi, A., Hasserjian, R., Thiele, J., Borowitz, M. J., Le Beau, M. M., Bloomfield, C. D., Cazzola, M., & Vardiman, J. W. (2016). The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood, 127(20), 2391–2405. https://doi.org/10.1182/blood-2016-03-643544
  • Astalakshmi, D., T, G., K B, G. S., M, N., M R, H. H. S., S, G., Latha, D., & Kumar, D. (2022). Over view on molecular docking: A powerful approach for structure based drug discovery. International Journal of Pharmaceutical Sciences Review and Research, 77(2), 146–157. https://doi.org/10.47583/ijpsrr.2022.v77i02.029
  • Aung, T. N., Qu, Z., Kortschak, R. D., & Adelson, D. L. (2017). Understanding the effectiveness of natural compound mixtures in cancer through their molecular mode of action. International Journal of Molecular Sciences, 18(3), 656. https://doi.org/10.3390/ijms18030656
  • Ayuba, A. M., & Umar, U. (2021). Modeling vitexin and isovitexin flavones as corrosion inhibitors for aluminium metal. Karbala International Journal of Modern Science, 7(3), 206–205. https://doi.org/10.33640/2405-609X.3119
  • Aziz, M., Ejaz, S. A., Zargar, S., Akhtar, N., Aborode, A. T., A Wani, T., Batiha, G. E.-S., Siddique, F., Alqarni, M., & Akintola, A. A. (2022). Deep learning and structure-based virtual screening for drug discovery against NEK7: A novel target for the treatment of cancer. Molecules (Basel, Switzerland), 27(13), 4098. https://doi.org/10.3390/molecules27134098
  • Banks, W. A. (2009). Characteristics of compounds that cross the blood-brain barrier. BMC Neurology, 9 Suppl 1(SUPPL. 1), S3. https://doi.org/10.1186/1471-2377-9-S1-S3
  • Barclay, P. L., & Zhang, D. Z. (2021). Periodic boundary conditions for arbitrary deformations in molecular dynamics simulations. Journal of Computational Physics, 435, 110238. https://doi.org/10.1016/j.jcp.2021.110238
  • Bello, R. O., Okunlola, S. T., Kumar, N., Victor, O., Jimoh, T. O., Abdulsalam, Z. N., Kehinde, I. O., & Umar, H. I. (2023). An integrative computational approach for the identification of dual inhibitors of isocitrate dehydrogenase 1 and 2 from phytocompounds of Phyllantus amarus. Journal of Biomolecular Structure and Dynamics. https://doi.org/10.1080/07391102.2023.2245494
  • Bendjeddou, A., Abbaz, T., Gouasmia, A., & Villemin, D. (2016). Molecular Structure, HOMO-LUMO, MEP and Fukui function analysis of some TTF-donor substituted molecules using DFT (B3LYP) calculations. International Research Journal of Pure and Applied Chemistry, 12(1), 1–9. https://doi.org/10.9734/IRJPAC/2016/27066
  • Bergström, C. A. S., & Larsson, P. (2018). Computational prediction of drug solubility in water-based systems: Qualitative and quantitative approaches used in the current drug discovery and development setting. International Journal of Pharmaceutics, 540(1-2), 185–193. https://doi.org/10.1016/j.ijpharm.2018.01.044
  • Boral, N., Ghosh, P., Goswami, A., & Bhattacharyya, M. (2022). Accountable prediction of drug ADMET Properties with molecular descriptors. BioRxiv, 2, 1–11.
  • Borges, C. D S., Ferreira, A. F., Almeida, V. H., Gomes, F. G., Berzoti-Coelho, M. G., Cacemiro, M. D C., Nunes, N. S., Figueiredo-Pontes, L. L., Simões, B. P., Castro, F. A., & Monteiro, R. Q. (2018). Crosstalk between BCR-ABL and protease-activated receptor 1 (PAR1) suggests a novel target in chronic myeloid leukemia. Experimental Hematology, 66(Im), 50–62. https://doi.org/10.1016/j.exphem.2018.07.008
  • Bors, L., & Erdö, F. (2019). Overcoming the blood-brain barrier. Challenges and tricks for CNS drug delivery. Scientia Pharmaceutica, 87(1), 6. https://doi.org/10.3390/scipharm87010006
  • Cai, J., Liu, H., Chen, Y., Yu, J., Gao, J., Jiang, H., Zhai, X., Ju, X., Wu, X., Wang, N., Tian, X., Liang, C., Fang, Y., Zhou, F., Li, H., Sun, L., Yang, L., Guo, J., Liu, A., … Pui, C.-H. (2023). Effect of the tyrosine kinase inhibitors on the growth in children with Philadelphia chromosome – positive acute lymphoblastic leukemia: A case-control study. The Lancet Regional Health. Western Pacific, 38, 100818. https://doi.org/10.1016/j.lanwpc.2023.100818
  • Cai, C., Tang, W., Qiao, C., Bao, B., Xie, P., Zhao, S., & Liu, H. (2022). A reaction density functional theory study of solvent effect in the nucleophilic addition reactions in aqueous solution. Green Energy & Environment, 7(4), 782–791. https://doi.org/10.1016/j.gee.2020.11.028
  • Cavasotto, C. N., Aucar, M. G., & Adler, N. S. (2019). Computational chemistry in drug lead discovery and design. International Journal of Quantum Chemistry, 119(2), 1–19. https://doi.org/10.1002/qua.25678
  • Chow, S.-C. (2014). Bioavailability and bioequivalence in drug development. Interdisciplinary Sciences: Computational Life Sciences, 6(4), 304–320. https://doi.org/10.1002/wics.1310.Bioavailability
  • Ciftci, H. I., Ozturk, S. E., Ali, T. F. S., Radwan, M. O., Tateishi, H., Koga, R., Ocak, Z., Can, M., Otsuka, M., & Fujita, M. (2018). The first pentacyclic triterpenoid gypsogenin derivative exhibiting anti-ABL1 kinase and anti-chronic myelogenous leukemia activities. Biological & Pharmaceutical Bulletin, 41(4), 570–574. https://doi.org/10.1248/bpb.b17-00902
  • Cruz-Vicente, P., Passarinha, L. A., Silvestre, S., & Gallardo, E. (2021). Recent developments in new therapeutic agents against Alzheimer and Parkinson’s diseases: In-silico approaches. Molecules (Basel, Switzerland), 26(8), 2193. https://doi.org/10.3390/molecules26082193
  • 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), 42717. https://doi.org/10.1038/srep42717
  • Danazumi, A. U., & Umar, H. I. (2023). You must be flexible enough to be trained, Mr. Dynamics simulator. Molecular Diversity, 0123456789, 5–7. https://doi.org/10.1007/s11030-023-10689-5
  • Dar, A. M., & Mir, S. (2017). Molecular docking: Approaches, types, applications and basic challenges. Journal of Analytical & Bioanalytical Techniques, 08(02), 1–10. https://doi.org/10.4172/2155-9872.1000356
  • de Oliveira, V. M., Estácio, S. P., da Silva Mendes, F. R., Campos, O. S., Marinho, M. M., & Marinho, E. S. (2020). Characterization of rotenoid stemonal by semiempirical methods and molecular docking. SN Applied Sciences, 2(4), 1–8. https://doi.org/10.1007/s42452-020-2346-7
  • do Carmo, A. L., Bettanin, F., Oliveira Almeida, M., Pantaleão, S. Q., Rodrigues, T., Homem-de-Mello, P., & Honorio, K. M. (2020). Competition between phenothiazines and BH3 peptide for the binding site of the antiapoptotic BCL-2 protein. Frontiers in Chemistry, 8(April), 235. https://doi.org/10.3389/fchem.2020.00235
  • Druker, B. J., Guilhot, F., O'Brien, S. G., Gathmann, I., Kantarjian, H., Gattermann, N., Deininger, M. W. N., Silver, R. T., Goldman, J. M., Stone, R. M., Cervantes, F., Hochhaus, A., Powell, B. L., Gabrilove, J. L., Rousselot, P., Reiffers, J., Cornelissen, J. J., Hughes, T., Agis, H., … Larson, R. A. (2006). Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia. The New England Journal of Medicine, 355(23), 2408–2417. https://doi.org/10.1056/NEJMoa062867
  • Du, X., Li, Y., Xia, Y. L., Ai, S. M., Liang, J., Sang, P., Ji, X. L., & Liu, S. Q. (2016). Insights into protein–ligand interactions: Mechanisms, models, and methods. International Journal of Molecular Sciences, 17(2), 144. https://doi.org/10.3390/ijms17020144
  • Du, Z., & Lovly, C. M. (2018). Mechanisms of receptor tyrosine kinase activation in cancer. Molecular Cancer, 17(1), 58. https://doi.org/10.1186/s12943-018-0782-4
  • Dumnicka, P., Góra-tybor, J., Sacha, T., Prejzner, W., Wasilewska, E., Kłoczko, J., Niesiob, J., Wasilewska, J., Ciepłuch, H., Makowska, W., Kopera, M., Wichary, R., Kroll-balcerzak, R., Swiniarska, M., Paczkowska, E., Biernat, M., Joks, M., Oller, M., Kasza, R., … Grzybowska-izydorczyk, O. (2022). The outcomes of ponatinib therapy in patients with chronic myeloid leukemia resistant or intolerant to previous tyrosine kinase inhibitors, treated in Poland within the donation program. Clinical Lymphoma, Myeloma and Leukemia, 22(6), 405–415. https://doi.org/10.1016/j.clml.2021.11.012
  • Ece, A. (2023). Computer‑aided drug design. BMC Chemistry, 17(1), 26. https://doi.org/10.1186/s13065-023-00939-w
  • Ejaz, S. A., Aziz, M., Zafar, Z., Akhtar, N., & Ogaly, H. A. (2023). Revisiting the inhibitory potential of protein kinase inhibitors against NEK7 protein via comprehensive computational investigations. Scientific Reports, 13(1), 4304. https://doi.org/10.1038/s41598-023-31499-7
  • Fadler, R. E., & Flood, A. H. (2022). Rigidity and flexibility in rotaxanes and their relatives; On being stubborn and easy-going. Frontiers in Chemistry, 10(April), 856173. https://doi.org/10.3389/fchem.2022.856173
  • Flores-Holguín, N., Frau, J., & Glossman-Mitnik, D. (2021). In silico pharmacokinetics, ADMET study and conceptual DFT analysis of two plant cyclopeptides isolated from Rosaceae as a computational peptidology approach. Frontiers in Chemistry, 9(August), 708364. https://doi.org/10.3389/fchem.2021.708364
  • Guan, L., Yang, H., Cai, Y., Sun, L., Di, P., Li, W., Liu, G., & Tang, Y. (2019). ADMET-score - A comprehensive scoring function for evaluation of chemical drug-likeness. MedChemComm, 10(1), 148–157. https://doi.org/10.1039/C8MD00472B
  • Guengerich, F. P. (2022). Inhibition of cytochrome P450 enzymes by drugs - Molecular basis and practical applications. Biomolecules & Therapeutics, 30(1), 1–18. https://doi.org/10.4062/biomolther.2021.102
  • Harder, E., Damm, W., Maple, J., Wu, C., Reboul, M., Xiang, J. Y., Wang, L., Lupyan, D., Dahlgren, M. K., Knight, J. L., Kaus, J. W., Cerutti, D. S., Krilov, G., Jorgensen, W. L., Abel, R., & Friesner, R. A. (2016). OPLS3: A force field providing broad coverage of drug-like small molecules and proteins. Journal of Chemical Theory and Computation, 12(1), 281–296. https://doi.org/10.1021/acs.jctc.5b00864
  • Hartmann, T., & Schmitt, J. (2004). Lipophilicity - Beyond octanol/water: A short comparison of modern technologies. Drug Discovery Today. Technologies, 1(4), 431–439. https://doi.org/10.1016/j.ddtec.2004.10.006
  • He, B., Wang, Q., Liu, X., Lu, Z., Han, J., Pan, C., Carter, B. Z., Liu, Q., Xu, N., & Zhou, H. (2020). A novel HDAC inhibitor chidamide combined with imatinib synergistically targets tyrosine kinase inhibitor resistant chronic myeloid leukemia cells. Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie, 129(June), 110390. https://doi.org/10.1016/j.biopha.2020.110390
  • Helms, H. C. C., Kristensen, M., Saaby, L., Fricker, G., & Brodin, B. (2022). Drug delivery strategies to overcome the blood–brain barrier (BBB). Handbook of Experimental Pharmacology, 273(9), 151–183. https://doi.org/10.1007/164_2020_403
  • Hochhaus, A., Baccarani, M., Deininger, M., Apperley, J. F., Lipton, J. H., Goldberg, S. L., Corm, S., Shah, N. P., Cervantes, F., Silver, R. T., Niederwieser, D., Stone, R. M., Dombret, H., Larson, R. A., Roy, L., Hughes, T., Müller, M. C., Ezzeddine, R., Countouriotis, A. M., & Kantarjian, H. M. (2008). Dasatinib induces durable cytogenetic responses in patients with chronic myelogenous leukemia in chronic phase with resistance or intolerance to imatinib. Leukemia, 22(6), 1200–1206. https://doi.org/10.1038/leu.2008.84
  • Hochhaus, A., Baccarani, M., Silver, R. T., Schiffer, C., Apperley, J. F., Cervantes, F., Clark, R. E., Cortes, J. E., Deininger, M. W., Guilhot, F., Hjorth-Hansen, H., Hughes, T. P., Janssen, J. J. W. M., Kantarjian, H. M., Kim, D. W., Larson, R. A., Lipton, J. H., Mahon, F. X., Mayer, J., … Hehlmann, R. (2020). European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia, 34(4), 966–984. https://doi.org/10.1038/s41375-020-0776-2
  • Hollingsworth, S. A., & Dror, R. O. (2018). Molecular dynamics simulation for all. Neuron, 99(6), 1129–1143. https://doi.org/10.1016/j.neuron.2018.08.011
  • Hoover, W. G. (1985). Canonical dynamics: Equilibrium phase-space distributions. Physical Review. A, General Physics, 31(3), 1695–1697. https://doi.org/10.1103/physreva.31.1695
  • Hospital, A., Goñi, J. R., Orozco, M., & Gelpí, J. L. (2015). Molecular dynamics simulations: Advances and applications. Advances and Applications in Bioinformatics and Chemistry: AABC, 8(1), 37–47. https://doi.org/10.2147/AABC.S70333
  • Hou, T., Wang, J., Zhang, W., & Xu, X. (2007). ADME evaluation in drug discovery. Can oral biavailability in humans be effectively predicted by simple molecular property-based rules? Journal of Chemical Information and Modeling, 47(2), 460–463. https://doi.org/10.1021/ci6003515
  • Hughes, J. P., Rees, S. S., Kalindjian, S. B., & Philpott, K. L. (2011). Principles of early drug discovery. British Journal of Pharmacology, 162(6), 1239–1249. https://doi.org/10.1111/j.1476-5381.2010.01127.x
  • Isabel, A., Pin, C., Villaverde, L., Martín, S., Milena, M., & Castro, S. (2023). The needs and medication experience of patients with chronic myeloid leukemia treated with tyrosine kinase inhibitors: A systematic review. Farmacia Hospitalaria, 47, 785–792. https://doi.org/10.1016/j.farma.2023.02.002
  • Ishiki, H. M., Maria, J., Filho, B., Silva, M. S., Scotti, M. T., & Scotti, L. (2018). Computer-aided drug design applied to Parkinson targets. Current Neuropharmacology, 16(6), 865–880. https://doi.org/10.2174/1570159X15666171128145423
  • Jia, C. Y., Li, J. Y., Hao, G. F., & Yang, G. F. (2020). A drug-likeness toolbox facilitates ADMET study in drug discovery. Drug Discovery Today, 25(1), 248–258. https://doi.org/10.1016/j.drudis.2019.10.014
  • Kaiser, T. M., Dentmon, Z. W., Dalloul, C. E., Sharma, S. K., & Liotta, D. C. (2020). Accelerated discovery of novel ponatinib analogs with improved properties for the treatment of Parkinson’s disease. ACS Medicinal Chemistry Letters, 11(4), 491–496. https://doi.org/10.1021/acsmedchemlett.9b00612
  • Kantarjian, H. M., Giles, F. J., Bhalla, K. N., Pinilla-Ibarz, J., Larson, R. A., Gattermann, N., Ottmann, O. G., Hochhaus, A., Radich, J. P., Saglio, G., Hughes, T. P., Martinelli, G., Kim, D. W., Shou, Y., Gallagher, N. J., Blakesley, R., Baccarani, M., Cortes, J., & Le Coutre, P. D. (2011). Nilotinib is effective in patients with chronic myeloid leukemia in chronic phase after imatinib resistance or intolerance: 24-month follow-up results. Blood, 117(4), 1141–1145. https://doi.org/10.1182/blood-2010-03-277152
  • Kantarjian, H., Giles, F., Wunderle, L., Bhalla, K., O'Brien, S., Wassmann, B., Tanaka, C., Manley, P., Rae, P., Mietlowski, W., Bochinski, K., Hochhaus, A., Griffin, J. D., Hoelzer, D., Albitar, M., Dugan, M., Cortes, J., Alland, L., & Ottmann, O. G. (2006). Nilotinib in imatinib-resistant CML and Philadelphia chromosome-positive ALL. The New England Journal of Medicine, 354(24), 2542–2551. https://doi.org/10.1056/NEJMoa055104
  • Kantarjian, H., Pasquini, R., Lévy, V., Jootar, S., Holowiecki, J., Hamerschlak, N., Hughes, T., Bleickardt, E., Dejardin, D., Cortes, J., & Shah, N. P. (2009). Dasatinib or high-dose imatinib for chronic-phase chronic myeloid leukemia resistant to imatinib at a dose of 400 to 600 milligrams daily: Two-year follow-up of a randomized phase 2 study (START-R). Cancer, 115(18), 4136–4147. https://doi.org/10.1002/cncr.24504
  • 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. https://doi.org/10.1080/17460441.2020.1798926
  • Kenny, P. W. (2022). Hydrogen bond donors in drug design. Journal of Medicinal Chemistry, 65(21), 14261–14275. https://doi.org/10.1021/acs.jmedchem.2c01147
  • Khan, T., Ali, M., Khan, A., Nisar, P., Jan, S. A., Afridi, S., & Shinwari, Z. K. (2020). Anticancer plants: A review of the active phytochemicals, applications in animal models, and regulatory aspects. Biomolecules, 10(1), 1–30. https://doi.org/10.3390/biom10010047
  • Khazdair, M. R., Kianmehr, M., & Anaeigoudari, A. (2021). Effects of medicinal plants and flavonoids on Parkinson’s disease: A review on basic and clinical evidences. Tabriz University of Medical Sciences, 11(2), 224–232. https://doi.org/10.34172/apb.2021.026
  • Kotsampasakou, E., Montanari, F., & Ecker, G. F. (2017). Predicting drug-induced liver injury: The importance of data curation. Toxicology, 389, 139–145. https://doi.org/10.1016/j.tox.2017.06.003
  • Kulkarni, A. M., Rampogu, S., & Lee, K. W. (2021). Computer-aided drug discovery identifies alkaloid inhibitors of Parkinson’s disease associated protein, prolyl oligopeptidase. Evidence-Based Complementary and Alternative Medicine: ECAM, 2021, 6687572–6687510. https://doi.org/10.1155/2021/6687572
  • Kumar, A., & Higdon, J. J. L. (2011). Particle mesh Ewald Stokesian dynamics simulations for suspensions of non-spherical particles. Journal of Fluid Mechanics, 675, 297–335. https://doi.org/10.1017/jfm.2011.18
  • Li, Y., Meng, Q., Yang, M., Liu, D., Hou, X., Tang, L., Wang, X., Lyu, Y., Chen, X., Liu, K., Yu, A. M., Zuo, Z., & Bi, H. (2019). Current trends in drug metabolism and pharmacokinetics. Acta Pharmaceutica Sinica. B, 9(6), 1113–1144. https://doi.org/10.1016/j.apsb.2019.10.001
  • Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23(1-3), 3–25. https://doi.org/10.1016/S0169-409X(96)00423-1
  • Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 46(1-3), 3–26. https://doi.org/10.1016/j.addr.2012.09.019
  • Liu, Y., Jang, H., Zhang, M., Tsai, C., Maloney, R., & Nussinov, R. (2022). The structural basis of BCR-ABL recruitment of GRB2 in chronic myelogenous leukemia. Biophysical Journal, 121(12), 2251–2265. https://doi.org/10.1016/j.bpj.2022.05.030
  • Mahul-Mellier, A.-L., Fauvet, B., Gysbers, A., Dikiy, I., Oueslati, A., Georgeon, S., Lamontanara, A. J., Bisquertt, A., Eliezer, D., Masliah, E., Halliday, G., Hantschel, O., & Lashuel, H. A. & Hilal. (2014). c-Abl phosphorylates alpha-synuclein and regulates its degradation, implication for alpha-synuclein clearance and contribution to the pathogenesis of Parkinson’s disease. Human Molecular Genetics, 23(11), 2858–2879. https://doi.org/10.1093/hmg/ddt674
  • Mishra, C. B., Pandey, P., Sharma, R. D., Malik, M. Z., Mongre, R. K., Lynn, A. M., Prasad, R., Jeon, R., & Prakash, A. (2021). Identifying the natural polyphenol catechin as a multi-targeted agent against SARS-CoV-2 for the plausible therapy of COVID-19: An integrated computational approach. Briefings in Bioinformatics, 22(2), 1346–1360. https://doi.org/10.1093/bib/bbaa378
  • Mukhtar, M., Saleem, M., Nazir, M., Riaz, N., Shafiq, N., Saleem, H., Tauseef, S., Khan, S., Ehsan Mazhar, M., Bakhsh Tareen, R., Mahmood, M. H., Ur, R., Tousif, M. I., & Ojha, S. C. (2023). Identification of pyrrolizidine alkaloids and flavonoid glycosides through HR-LCMS/MS analysis, biological screening, DFT and molecular docking studies on Heliotropium dasycarpum Ledeb. Arabian Journal of Chemistry, 16(5), 104655. https://doi.org/10.1016/j.arabjc.2023.104655
  • Natarajan, A., Thangarajan, R., & Kesavan, S. (2019). Repurposing drugs by in silico methods to target BCR kinase domain in chronic myeloid leukemia. Asian Pacific Journal of Cancer Prevention: APJCP, 20(11), 3399–3406. https://doi.org/10.31557/APJCP.2019.20.11.3399
  • Orio, M., Pantazis, D. A., & Neese, F. (2009). Density functional theory. Photosynthesis Research, 102(2-3), 443–453. https://doi.org/10.1007/s11120-009-9404-8
  • Patel, C. N., Kumar, S. P., Pandya, H. A., & Rawal, R. M. (2021). Identification of potential inhibitors of coronavirus hemagglutinin-esterase using molecular docking, molecular dynamics simulation and binding free energy calculation. Molecular Diversity, 25(1), 421–433. https://doi.org/10.1007/s11030-020-10135-w
  • Peverati, R., & Truhlar, D. G. (2014). Quest for a universal density functional: The accuracy of density functionals across a broad spectrum of databases in chemistry and physics. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 372(2011), 20120476. https://doi.org/10.1098/rsta.2012.0476
  • Pophali, P. A., & Patnaik, M. M. (2016). The role of new tyrosine kinase inhibitors in chronic myeloid leukemia. Cancer Journal (Sudbury, Mass.), 22(1), 40–50. https://doi.org/10.1097/PPO.0000000000000165
  • Quy, P. T., My, T. T. A., Bui, T. Q., Loan, H. T. P., Van Anh, T. T., Triet, N. T., Quang, D. T., & Nhung, N. T. A. (2021). Molecular docking prediction of carvone and trans-geraniol inhibitability towards SARS-CoV-2. Vietnam Journal of Chemistry, 59(4), 457–466. https://doi.org/10.1002/vjch.202000175
  • Rabiei, Z., Solati, K., & Amini-Khoei, H. (2019). Phytotherapy in treatment of Parkinson’s disease: A review. Pharmaceutical Biology, 57(1), 355–362. https://doi.org/10.1080/13880209.2019.1618344
  • Rahman, J., Tareq, A. M., Hossain, M. M., Sakib, S. A., Islam, M. N., Ali, M. H., Neshar Uddin, A. B. M., Hoque, M., Nasrin, M. S., Emran, T. B., Capasso, R., Ali Reza, A. S. M., & Simal-Gandara, J. (2020). Biological evaluation, DFT calculations and molecular docking studies on the antidepressant and cytotoxicity activities of Cycas pectinata Buch.-Ham. compounds. Pharmaceuticals (Basel, Switzerland), 13(9), 232. https://doi.org/10.3390/ph13090232
  • Ren, Y., De Blanco, E. J. C., Fuchs, J. R., Soejarto, D. D., Burdette, J. E., Swanson, S. M., & Kinghorn, A. D. (2019). Potential anticancer agents characterized from selected tropical plants. Journal of Natural Products, 82(3), 657–679. https://doi.org/10.1021/acs.jnatprod.9b00018
  • Rossari, F., Minutolo, F., & Orciuolo, E. (2018). Past, present, and future of BCR-Abl inhibitors: From chemical development to clinical efficacy. Journal of Hematology & Oncology, 11(1), 84. https://doi.org/10.1186/s13045-018-0624-2
  • Sadatmadani, S. F., Malakoutikhah, Z., Mohaghegh, F., Peikar, M., & Saboktakin, M. (2022). Nilotinib-induced elephantine psoriasis in a patient with chronic myeloid leukemia: A rare case report and literature review. Current Therapeutic Research, Clinical and Experimental, 96, 100676. https://doi.org/10.1016/j.curtheres.2022.100676
  • Sajvani, K. T., Gajjar, A. K., & Savjani, J. K. (2012). Drug solubility: Importance and enhancement techniques. ISRN Pharmaceutics, 199727, 1–10. https://doi.org/10.3390/cancers15010268
  • Saleem, U., Bibi, S., Shah, M. A., Ahmad, B., Saleem, A., Chauhdary, Z., Anwar, F., Javaid, N., Hira, S., Akhtar, M. F., Shah, G. M., Khan, M. S., Muhammad, H., & Qasim, M. (2021). Anti-Parkinson’s evaluation of Brassica juncea leaf extract and underlying mechanism of its phytochemicals. Frontiers in Bioscience-Landmark, 26(October), 1031–1051. https://doi.org/10.52586/5007
  • Salehi, B., Vlaisavljevic, S., Adetunji, C. O., Adetunji, J. B., Kregiel, D., Antolak, H., Pawlikowska, E., Uprety, Y., Mileski, K. S., Devkota, H. P., Sharifi-Rad, J., Das, G., Patra, J. K., Jugran, A. K., Segura-Carretero, A., & Contreras, M. D M. (2019). Plants of the genus Vitis: Phenolic compounds, anticancer properties and clinical relevance. Trends in Food Science & Technology, 91(July), 362–379. https://doi.org/10.1016/j.tifs.2019.07.042
  • Salman, M. M., Al-Obaidi, Z., Kitchen, P., Loreto, A., Bill, R. M., & Wade-Martins, R. (2021). Advances in applying computer-aided drug design for neurodegenerative diseases. International Journal of Molecular Science, 22, 1–22. https://doi.org/10.1021/jm990129n
  • Sarkar, U., & Chattaraj, P. K. (2021). Conceptual DFT based electronic structure principles in a dynamical context. Journal of the Indian Chemical Society, 98(7), 100098. https://doi.org/10.1016/j.jics.2021.100098
  • Schiffer, C. A. (2018). Diagnosis and treatment of chronic myeloid leukemia. Neoplastic Diseases of the Blood, 90(10), 49–68. https://doi.org/10.1007/978-3-319-64263-5_5
  • Schlauderer, F., Lammens, K., Nagel, D., Vincendeau, M., Eitelhuber, A. C., Verhelst, S. H. L., Kling, D., Chrusciel, A., Ruland, J., Krappmann, D., & Hopfner, K. P. (2013). Structural analysis of phenothiazine derivatives as allosteric inhibitors of the MALT1 paracaspase. Angewandte Chemie (International ed. in English), 52(39), 10384–10387. https://doi.org/10.1002/anie.201304290
  • Shah, N. P., Kantarjian, H. M., Kim, D. W., Réa, D., Dorlhiac-Llacer, P. E., Milone, J. H., Vela-Ojeda, J., Silver, R. T., Khoury, H. J., Charbonnier, A., Khoroshko, N., Paquette, R. L., Deininger, M., Collins, R. H., Otero, I., Hughes, T., Bleickardt, E., Strauss, L., Francis, S., & Hochhaus, A. (2008). Intermittent target inhibition with dasatinib 100 mg once daily preserves efficacy and improves tolerability in imatinib-resistant and -intolerant chronic-phase chronic myeloid leukemia. Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 26(19), 3204–3212. https://doi.org/10.1200/JCO.2007.14.9260
  • Sharma, A., Gupta, N., Orfali, R., Kumar, V., Patel, C. N., Peng, J., & Perveen, S. (2022). Evaluation of the antifungal, antioxidant, and anti-diabetic potential of the essential oil of Curcuma longa leaves from the North-Western Himalayas by in vitro and in silico analysis. Molecules (Basel, Switzerland), 27(22), 7664. https://doi.org/10.3390/molecules27227664
  • Sharma, O., Srivastava, S., Sharma, M., & Malik, R. (2023). Discovery of a new dihydropyrimidinone derivative as a potential haspin kinase inhibitor: Structure-guided insights, in-vitro and molecular dynamics-based validation. ChemistrySelect, 8(35), 1–13. https://doi.org/10.1002/slct.202301233
  • Shivanika, C., Deepak Kumar, S., Ragunathan, V., Tiwari, P., Sumitha, A., & Brindha Devi, P. (2022). Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease. Journal of Biomolecular Structure & Dynamics, 40(2), 585–611. https://doi.org/10.1080/07391102.2020.1815584
  • Smith, D. A., Beaumont, K., Maurer, T. S., & Di, L. (2018). Relevance of half-life in drug design. Journal of Medicinal Chemistry, 61(10), 4273–4282. https://doi.org/10.1021/acs.jmedchem.7b00969
  • Soars, M. G., McGinnity, D. F., Grime, K., & Riley, R. J. (2007). The pivotal role of hepatocytes in drug discovery. Chemico-Biological Interactions, 168(1), 2–15. https://doi.org/10.1016/j.cbi.2006.11.002
  • Sohlenius-Sternbeck, A. K., & Terelius, Y. (2022). Evaluation of ADMET predictor in early discovery drug metabolism and pharmacokinetics project work. Drug Metabolism and Disposition: The Biological Fate of Chemicals, 50(2), 95–104. https://doi.org/10.1124/dmd.121.000552
  • Solo-Aben, O. M. H., Alanko, I., Bhadane, R., Bonvin, A. M. J. J., Honorato, R. V., Hussain, S., Juffer, A. H., Kabedev, A., Lahtela-Kakkomen, M., Larsen, A. S., Lescrinier, E., Marimuthu, P., Mina, M. U., Mustafa, G., Nunes-Alves, A., Panisar, T., Saadabadi, A., Singaravelu, K., & Vanmeert, M. (2021). Molecular dynamics simulations in drug discovery and pharmaceutical development. Processes, 9(71), 1–60. https://doi.org/10.1007/978-3-030-36260-7_10
  • Stella, S., Gottardi, E. M., Favout, V., Gonzalez, E. B., Errichiello, S., Vitale, S. R., Fava, C., Luciano, L., Stagno, F., Grimaldi, F., Pironi, L., Simarro, C. S., Vigneri, P., & Izzo, B. (2019). The Q-LAMP method represents a valid and rapid alternative for the detection of the BCR-ABL1 rearrangement in Philadelphia-positive leukemias. International Journal of Molecular Sciences, 20(24), 6106. https://doi.org/10.3390/ijms20246106
  • Sun, L., Yang, H., Li, J., Wang, T., Li, W., Liu, G., & Tang, Y. (2018). In silico prediction of compounds binding to human plasma proteins by QSAR models. ChemMedChem. 13(6), 572–581. https://doi.org/10.1002/cmdc.201700582
  • 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. https://doi.org/10.3322/caac.21660
  • Tian, H., Ketkar, R., & Tao, P. (2022). ADMETboost: A web server for accurate ADMET prediction. Journal of Molecular Modeling, 28(12), 408. https://doi.org/10.1007/s00894-022-05373-8
  • Tibbitts, J., Canter, D., Graff, R., Smith, A., & Khawli, L. A. (2016). Key factors influencing ADME properties of therapeutic proteins: A need for ADME characterization in drug discovery and development. mAbs, 8(2), 229–245. https://doi.org/10.1080/19420862.2015.1115937
  • Torres, P. H. M., Sodero, A. C. R., Jofily, P., & Silva, F. P. Jr, (2019). Key topics in molecular docking for drug design. International Journal of Molecular Sciences, 20(18), 4574. https://doi.org/10.3390/ijms20184574
  • Tran, Q. H., Nguyen, Q. T., Vo, N. Q. H., Mai, T. T., Tran, T. T. N., Tran, T. D., Le, M. T., Trinh, D. T. T., & Minh Thai, K. (2022). Structure-based 3D-pharmacophore modeling to discover novel interleukin 6 inhibitors: An in silico screening, molecular dynamics simulations and binding free energy calculations. PloS One, 17(4), e0266632. https://doi.org/10.1371/journal.pone.0266632
  • van Mourik, T., Bühl, M., & Gaigeot, M. P. (2014). Density functional theory across chemistry, physics and biology. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 372(2011), 20120488. https://doi.org/10.1098/rsta.2012.0488
  • Veber, D. F., Johnson, S. R., Cheng, H., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular properties that influence the oral bioavailability of drug candidates. Journal of Medicinal Chemistry, 45(12), 2615–2623. https://doi.org/10.1021/jm020017n
  • Vlasiou, M. C., & Pafti, K. S. (2021). Screening possible drug molecules for COVID-19. The example of vanadium (III/IV/V) complex molecules with computational chemistry and molecular docking. Computational Toxicology (Amsterdam, Netherlands), 18(January), 100157. https://doi.org/10.1016/j.comtox.2021.100157
  • Wang, J. B., Cao, D. S., Zhu, M. F., Yun, Y. H., Xiao, N., & Liang, Y. Z. (2015). In silico evaluation of logD7.4 and comparison with other prediction methods. Journal of Chemometrics, 29(7), 389–398. https://doi.org/10.1002/cem.2718
  • Wang, R., Zheng, Q. X., Wang, W., Feng, L., Li, H. J., & Huai, Q. Y. (2017). Design and synthesis of new anticancer glycyrrhetinic acids and oleanolic acids. Biological & Pharmaceutical Bulletin, 40(5), 703–710. https://doi.org/10.1248/bpb.b17-00016
  • Weisberg, E., Manley, P. W., Breitenstein, W., Brüggen, J., Cowan-Jacob, S. W., Ray, A., Huntly, B., Fabbro, D., Fendrich, G., Hall-Meyers, E., Kung, A. L., Mestan, J., Daley, G. Q., Callahan, L., Catley, L., Cavazza, C., Azam, M., Neuberg, D., Wright, R. D., Gilliland, D. G., & Griffin, J. D. (2005). Characterization of AMN107, a selective inhibitor of native and mutant BCR-Abl. Cancer Cell, 7(2), 129–141. https://doi.org/10.1016/j.ccr.2005.01.007
  • Wicker, J. G. P., & Cooper, R. I. (2016). Beyond rotatable bond counts: Capturing 3D conformational flexibility in a single descriptor. Journal of Chemical Information and Modeling, 56(12), 2347–2352. https://doi.org/10.1021/acs.jcim.6b00565
  • Williams, J., Siramshetty, V., Nguyễn, Ð.-T., Padilha, E. C., Kabir, M., Yu, K.-R., Wang, A. Q., Zhao, T., Itkin, M., Shinn, P., Mathé, E. A., Xu, X., & Shah, P. (2022). Using in vitro ADME data for lead compound selection: An emphasis on PAMPA pH 5 permeability and oral bioavailability. Bioorganic & Medicinal Chemistry, 56(56), 116588. https://doi.org/10.1016/j.bmc.2021.116588.Using
  • World Health Organization (WHO). (2023, November 12). WHO reveals leading causes of death and disability worldwide: 2000-2019. Retrieved from https://www.who.int/news/item/09-12-2020-who-reveals-leading-causes-of-death-and-disability-worldwide-2000-2019
  • Wu, F., Zhou, Y., Li, L., Shen, X., Chen, G., Wang, X., Liang, X., Tan, M., & Huang, Z. (2020). Computational approaches in preclinical studies on drug discovery and development. Frontiers in Chemistry, 8(September), 726. https://doi.org/10.3389/fchem.2020.00726
  • Yuan, M., Zhang, G., Bai, W., Han, X., Li, C., & Bian, S. (2022). The role of bioactive compounds in natural products extracted from plants in cancer treatment and their mechanisms related to anticancer effects. Oxidative Medicine and Cellular Longevity, 2022, 1429869. https://doi.org/10.1155/2022/1429869
  • Zarrouk, A., Assouag, M., Zarrok, H., Oudda, H., Bentiss, F., Touzani, R., Hammouti, B., Bouachrine, M., & August, J. (2015). Theoretical study of a new group of corrosion inhibitors. Research Journal of Pharmaceutical, Biological and Chemical Sciences, 6(4), 1874–1882. https://doi.org/10.1021/jp052188k
  • Zhang, H., Mu, Y., Wang, F., Song, L., Sun, J., Liu, Y., & Sun, J. (2018). Synthesis of gypsogenin derivatives with capabilities to arrest cell cycle and induce apoptosis in human cancer cells. Royal Society Open Science, 5(1), 171510. https://doi.org/10.1098/rsos.171510
  • Zhang, Y., Wu, J., Jin, W., Shen, M., Yin, S., Lai, X., Ma, H., Jiang, M., Sun, D., & Yan, J. (2022). Nonreceptor tyrosine kinase c-Abl-mediated PHB2 phosphorylation aggravates mitophagy disorder in Parkinson’s disease model. Oxidative Medicine and Cellular Longevity, 2022, 9233749. https://doi.org/10.1155/2022/9233749

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.