Therapeutic Path to Triple Knockout: Investigating the Pan-inhibitory Mechanisms of AKT, CDK9, and TNKS2 by a Novel 2-phenylquinazolinone Derivative in Cancer Therapy- An In-silico Investigation Therapy


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Background:Blocking the oncogenic Wnt//β-catenin pathway has of late been investigated as a viable therapeutic approach in the treatment of cancer. This involves the multi-targeting of certain members of the tankyrase-kinase family; Tankyrase 2 (TNKS2), Protein Kinase B (AKT), and Cyclin- Dependent Kinase 9 (CDK9), which propagate the oncogenic Wnt/β-catenin signalling pathway.

Methods:During a recent investigation, the pharmacological activity of 2-(4-aminophenyl)-7-chloro- 3H-quinazolin-4-one was repurposed to serve as a ‘triple-target’ inhibitor of TNKS2, AKT and CDK9. Yet, the molecular mechanism that surrounds its multi-targeting activity remains unanswered. As such, this study aims to explore the pan-inhibitory mechanism of 2-(4-aminophenyl)-7-chloro-3H-quinazolin- 4-one towards AKT, CDK9, and TNKS2, using in silico techniques.

Results:Results revealed favourable binding affinities of -34.17 kcal/mol, -28.74 kcal/mol, and -27.30 kcal/mol for 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one towards TNKS2, CDK9, and AKT, respectively. Pan-inhibitory binding of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one is illustrated by close interaction with specific residues on tankyrase-kinase. Structurally, 2-(4-aminophenyl)-7-chloro- 3H-quinazolin-4-one had an impact on the flexibility, solvent-accessible surface area, and stability of all three proteins, which was illustrated by numerous modifications observed in the unbound as well as the bound states of the structures, which evidenced the disruption of their biological function. Prediction of the pharmacokinetics and physicochemical properties of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4- one further established its inhibitory potential, evidenced by the favourable absorption, metabolism, excretion, and minimal toxicity properties.

Conclusion:The following structural insights provide a starting point for understanding the paninhibitory activity of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one. Determining the criticality of the interactions that exist between the pyrimidine ring and catalytic residues could offer insight into the structure-based design of innovative tankyrase-kinase inhibitors with enhanced therapeutic effects.

Об авторах

Xylia Peters

Department of Pharmaceutical Science, University of KwaZulu-Natal

Email: info@benthamscience.net

Ghazi Elamin

Department of Pharmaceutical Science,, University of KwaZulu-Natal

Email: info@benthamscience.net

Aimen Aljoundi

Department of Pharmaceutical Science, University of KwaZulu-Natal

Email: info@benthamscience.net

Mohamed Alahmdi

Department of Pharmaceutical Science, University of Tabuk

Email: info@benthamscience.net

Nader Abo-Dya

Department of Pharmaceutical Science, Tabuk University

Email: info@benthamscience.net

Peter Sidhom

Department of Pharmacy,, Tanta University

Email: info@benthamscience.net

Ahmed Tawfeek

Chemistry Department, College of Science,, King Saud University

Email: info@benthamscience.net

Mahmoud Ibrahim

Department of Pharmaceutical Science,, University of KwaZulu-Natal

Email: info@benthamscience.net

Opeyemi Soremekun

Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London

Email: info@benthamscience.net

Mahmoud Soliman

Department of Pharmaceutical Science, University of KwaZulu-Natal

Автор, ответственный за переписку.
Email: info@benthamscience.net

Список литературы

  1. Mandal, R.; Becker, S.; Strebhardt, K. Targeting CDK9 for anti-cancer therapeutics Internet. Cancers. Multidisciplinary Digital Publishing Institute, 2021, 13, 2181. Available From: https://www.mdpi.com/2072-6694/13/9/2181/htm accessed on 2022 May 19
  2. Boffo, S; Damato, A; Alfano, L; Giordano, A. CDK9 inhibitors in acute myeloid leukemia. J. Exp. Clin. Cancer Res. BioMed Central Ltd, 2018, 37 doi: 10.1186/s13046-018-0704-8
  3. Anshabo, A.T.; Bantie, L.; Diab, S.; Lenjisa, J.; Kebede, A.; Long, Y.; Heinemann, G.; Karanjia, J.; Noll, B.; Basnet, S.K.C.; Li, M.; Milne, R.; Albrecht, H.; Wang, S. An orally bioavailable and highly efficacious inhibitor of cdk9/flt3 for the treatment of acute myeloid leukemia. Cancers, 2022, 14(5), 1113. Available From: https://www.mdpi.com/2072-6694/14/5/1113 doi: 10.3390/cancers14051113 PMID: 35267421
  4. Li, L.; Han, C.; Yu, X.; Shen, J.; Cao, Y. Targeting AraC-resistant acute myeloid leukemia by dual inhibition of CDK9 and Bcl-2: A systematic review and meta-analysis. J. Healthc. Eng., 2022. Available From: https://www.hindawi.com/journals/jhe/2022/2842066/ accessed on 2022 May 17 doi: 10.1155/2022/2842066
  5. Anshabo, A.T.; Milne, R.; Wang, S.; Albrecht, H. CDK9: A comprehensive review of its biology, and its role as a potential target for anti-cancer agents. Frontiers in Oncology. Frontiers Media S.A., 2021; Vol. 11, .
  6. Martorana, F.; Motta, G.; Pavone, G.; Motta, L.; Stella, S.; Vitale, S.R. AKT inhibitors: New weapons in the fight against breast cancer? Frontiers in Pharmacology. Frontiers Media S.A., 2021; Vol. 12, p. 546.
  7. Manning, B.D.; Cantley, L.C. AKT/PKB signaling: Navigating downstream. Cell, 2007, 129(7), 1261-1274. Available From: https://www.sciencedirect.com/science/article/pii/S0092867407007751 doi: 10.1016/j.cell.2007.06.009 PMID: 17604717
  8. Nicholson, K.M.; Anderson, N.G. The protein kinase B/Akt signalling pathway in human malignancy. Cellular Signalling Pergamon, 2002, 381-395. Available From: https://www.sciencedirect.com/science/article/pii/S0898656801002716
  9. Hemmings, B.A. Akt signaling: Linking membrane events to life and death decisions. Science, 1997, 275(5300), 628-630. doi: 10.1126/science.275.5300.628 PMID: 9019819
  10. Yu, L.; Wei, J.; Liu, P. Attacking the PI3K/Akt/mTOR signaling pathway for targeted therapeutic treatment in human cancer. Seminars in Cancer Biology, 2021. Available From: https://www.sciencedirect.com/science/article/pii/S1044579X21001887 accessed on 2022 May 16
  11. Xie, X.; Shu, R.; Yu, C.; Fu, Z.; Li, Z. Mammalian AKT, the emerging roles on mitochondrial function in diseases. Aging Dis., 2022, 13(1), 157-174. Available From: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782557/ doi: 10.14336/AD.2021.0729 PMID: 35111368
  12. Lin, K.; Lin, J.; Wu, W.I.; Ballard, J.; Lee, B.B.; Gloor, S.L.; Vigers, G.P.A.; Morales, T.H.; Friedman, L.S.; Skelton, N.; Brandhuber, B.J. An ATP-site on-off switch that restricts phosphatase accessibility of Akt. Sci. Signal., 2012, 5(223), ra37. doi: 10.1126/scisignal.2002618 PMID: 22569334
  13. Altomare, D.A.; Testa, J.R. Perturbations of the AKT signaling pathway in human cancer. Oncogene, 2005, 24(50), 7455-7464. Available From: https://www.nature.com/articles/1209085 doi: 10.1038/sj.onc.1209085 PMID: 16288292
  14. Stambolic, V.; Woodgett, J.R. Functional distinctions of protein kinase B/Akt isoforms defined by their influence on cell migration. Trends Cell Biol., 2006, 16(9), 461-466. Available From: https://www.sciencedirect.com/science/article/pii/S0962892406001735 doi: 10.1016/j.tcb.2006.07.001 PMID: 16870447
  15. Whiteman, E.L.; Cho, H.; Birnbaum, M.J. Role of Akt/protein kinase B in metabolism. Trends Endocrinol. Metab., 2002, 13(10), 444-451. Available From: https://www.sciencedirect.com/science/article/pii/S1043276002006628 doi: 10.1016/S1043-2760(02)00662-8 PMID: 12431841
  16. Khezri, M.R.; Varzandeh, R.; Ghasemnejad-Berenji, M. The probable role and therapeutic potential of the PI3K/AKT signaling pathway in SARS-CoV-2 induced coagulopathy. Cellular and Molecular Biology Letters. BioMed Central Ltd, 2022; Vol. 27, .
  17. Brognard, J.; Clark, A.S.; Ni, Y.; Dennis, P.A. Akt/protein kinase B is constitutively active in non-small cell lung cancer cells and promotes cellular survival and resistance to chemotherapy and radiation. Cancer Res., 2001, 61(10), 3986-3997. Available From: https://cancerres.aacrjournals.org/content/61/10/3986.short Internet. PMID: 11358816
  18. Hemmings, B.A.; Restuccia, D.F. PI3K-PKB/Akt pathway. Cold Spring Harb. Perspect. Biol., 2012, 4(9), a011189. Available From: https://cshperspectives.cshlp.org/content/4/9/a011189.short doi: 10.1101/cshperspect.a011189 PMID: 22952397
  19. Pal, S.K.; Reckamp, K.; Yu, H.; Figlin, R.A. Akt inhibitors in clinical development for the treatment of cancer. Expert Opin. Investig. Drugs, 2010, 19(11), 1355-1366. doi: 10.1517/13543784.2010.520701 PMID: 20846000
  20. Guo, T.; Liu, D.F.; Peng, S.H.; Abid, H. CDK9 is up-regulated and associated with prognosis in patients with papillary thyroid carcinom. Medicine (United States, 2022, 101(5), E28309. Available From: https://www.ncbi.nlm.nih.gov/pmc/articles/pmc8812708/ accessed on 2022 May 19
  21. Olson, C.M.; Jiang, B.; Erb, M.A.; Liang, Y.; Doctor, Z.M.; Zhang, Z.; Zhang, T.; Kwiatkowski, N.; Boukhali, M.; Green, J.L.; Haas, W.; Nomanbhoy, T.; Fischer, E.S.; Young, R.A.; Bradner, J.E.; Winter, G.E.; Gray, N.S. Pharmacological perturbation of CDK9 using selective CDK9 inhibition or degradation. Nat. Chem. Biol., 2018, 14(2), 163-170. Available From: https://www.nature.com/articles/nchembio.2538 doi: 10.1038/nchembio.2538 PMID: 29251720
  22. Morales, F.; Giordano, A. Overview of CDK9 as a target in cancer research. Cell Cycle. Taylor and Francis Inc, 2016, 15, 519-27. Available From: https://www.tandfonline.com/doi/abs/10.1080/15384101.2016.1138186 accessed on 2022 May 19
  23. Egloff, S. CDK9 keeps RNA polymerase II on track. Cellular and Molecular Life Sciences. Springer Science and Business Media Deutschland GmbH, 2021; 78, pp. 5543-5567.
  24. Hochegger, H.; Takeda, S.; Hunt, T. Cyclin-dependent kinases and cell-cycle transitions: Does one fit all? Nat. Rev. Mol. Cell Biol., 2008, 9(11), 910-916. Available From: https://www.nature.com/articles/nrm2510 doi: 10.1038/nrm2510 PMID: 18813291
  25. Borowczak, J.; Szczerbowski, K.; Ahmadi, N.; Szylberg, Ł. CDK9 inhibitors in multiple myeloma: A review of progress and perspectives. Med. Oncol., 2022, 39(4), 39. Available From: https://link.springer.com/article/10.1007/s12032-021-01636-1 doi: 10.1007/s12032-021-01636-1 PMID: 35092513
  26. Malumbres, M. Cyclin-dependent kinases. Genome Biol., 2014, 15(6), 122. doi: 10.1186/gb4184 PMID: 25180339
  27. Shore, S.M.; Byers, S.A.; Dent, P.; Price, D.H. Characterization of Cdk955 and differential regulation of two Cdk9 isoforms. Gene, 2005, 350(1), 51-58. Available From: https://www.sciencedirect.com/science/article/pii/S0378111905000430 doi: 10.1016/j.gene.2005.01.015 PMID: 15780980
  28. Liu, H.; Herrmann, C.H. Differential localization and expression of the Cdk9 42k and 55k isoforms. J. Cell. Physiol., 2005, 203(1), 251-260. doi: 10.1002/jcp.20224 PMID: 15452830
  29. Baumli, S.; Lolli, G.; Lowe, E.D.; Troiani, S.; Rusconi, L.; Bullock, A.N.; Debreczeni, J.É.; Knapp, S.; Johnson, L.N. The structure of P-TEFb (CDK9/cyclin T1), its complex with flavopiridol and regulation by phosphorylation. EMBO J., 2008, 27(13), 1907-1918. doi: 10.1038/emboj.2008.121 PMID: 18566585
  30. Borowczak, J.; Szczerbowski, K.; Maniewski, M.; Zdrenka, M.; Słupski, P.; Antosik, P.; Kołodziejska, S.; Sekielska-Domanowska, M.; Dubiel, M.; Bodnar, M.; Szylberg, Ł. The prognostic role of cdk9 in bladder cancer. Cancers, 2022, 14(6), 1492. Available From: https://www.mdpi.com/2072-6694/14/6/1492 doi: 10.3390/cancers14061492 PMID: 35326643
  31. Beauchamp, E.M.; Abedin, S.M.; Radecki, S.G.; Fischietti, M.; Arslan, ADi.; Blyth, GT. Identification and targeting of novel CDK9 complexes in acute myeloid leukemia. Blood, 2019. Available From: https://ashpublications.org/blood/article-abstract/133/11/1171/260506 accessed on 2022 May 17
  32. Fiskus, W.; Manshouri, T.; Birdwell, C.; Mill, C.P.; Masarova, L.; Bose, P. Efficacy of CDK9 inhibition in therapy of post-myeloproliferative neoplasm (MPN) secondary (s) AML cells. Blood Cancer Journal, 2022, 12 Available From: https://www.nature.com/articles/s41408-022-00618-4 accessed on 2022 May 19
  33. Abudureheman, T.; Xia, J.; Li, M.H.; Zhou, H.; Zheng, W.W.; Zhou, N.; Shi, R.Y.; Zhu, J.M.; Yang, L.T.; Chen, L.; Zheng, L.; Xue, K.; Qing, K.; Duan, C.W. CDK7 Inhibitor thz1 induces the cell apoptosis of b-cell acute lymphocytic leukemia by perturbing cellular metabolism. Front. Oncol., 2021, 11, 663360. doi: 10.3389/fonc.2021.663360 PMID: 33889549
  34. Ferri, M.; Liscio, P.; Carotti, A.; Asciutti, S.; Sardella, R.; Macchiarulo, A.; Camaioni, E. Targeting Wnt-driven cancers: Discovery of novel tankyrase inhibitors. Eur. J. Med. Chem., 2017, 142, 506-522. Available From: https://www.sciencedirect.com/science/article/pii/S0223523417307444 doi: 10.1016/j.ejmech.2017.09.030 PMID: 29107427
  35. Verma, A.; Kumar, A.; Chugh, A.; Kumar, S.; Kumar, P. Tankyrase inhibitors: Emerging and promising therapeutics for cancer treatment. Medicinal Chemistry Research, 2020, 30(1), 50-73. Available From: https://link.springer.com/article/10.1007/s00044-020-02657-7 accessed on 2021 Aug 19
  36. Peters, X.Q.; Malinga, T.H.; Agoni, C.; Olotu, F.A.; Soliman, M.E.S. Zoning in on tankyrases: A brief review on the past, present and prospective studies. Anticancer. Agents Med. Chem., 2020, 19(16), 1920-1934. doi: 10.2174/1871520619666191019114321 PMID: 31648650
  37. Shirai, F.; Tsumura, T.; Yashiroda, Y.; Yuki, H.; Niwa, H.; Sato, S.; Chikada, T.; Koda, Y.; Washizuka, K.; Yoshimoto, N.; Abe, M.; Onuki, T.; Mazaki, Y.; Hirama, C.; Fukami, T.; Watanabe, H.; Honma, T.; Umehara, T.; Shirouzu, M.; Okue, M.; Kano, Y.; Watanabe, T.; Kitamura, K.; Shitara, E.; Muramatsu, Y.; Yoshida, H.; Mizutani, A.; Seimiya, H.; Yoshida, M.; Koyama, H. Discovery of novel spiroindoline derivatives as selective tankyrase inhibitors. J. Med. Chem., 2019, 62(7), 3407-3427. doi: 10.1021/acs.jmedchem.8b01888 PMID: 30883102
  38. Mygland, L.; Brinch, S.A.; Strand, M.F.; Olsen, P.A.; Aizenshtadt, A.; Lund, K.; Solberg, N.T.; Lycke, M.; Thorvaldsen, T.E.; Espada, S.; Misaghian, D.; Page, C.M.; Agafonov, O.; Nygård, S.; Chi, N.W.; Lin, E.; Tan, J.; Yu, Y.; Costa, M.; Krauss, S.; Waaler, J. Identification of response signatures for tankyrase inhibitor treatment in tumor cell lines. iScience, 2021, 24(7), 102807. Available From: https://www.sciencedirect.com/science/article/pii/S2589004221007756 doi: 10.1016/j.isci.2021.102807 PMID: 34337362
  39. Peters, X.Q.; Agoni, C.; Soliman, M.E.S. Unravelling the structural mechanism of action of 5-methyl-5-4-(4-oxo-3h-quinazolin-2-yl)phenylimidazolidine-2,4-dione in dual-targeting tankyrase 1 and 2: A novel avenue in cancer therapy. Cell Biochemistry and Biophysics, 2022, 1-14. Available From: https://link.springer.com/article/10.1007/s12013-022-01076-2 accessed on 2022 Jun 6
  40. Haikarainen, T.; Krauss, S.; Lehtio, L. Tankyrases: Structure, function and therapeutic implications in cancer. Curr. Pharm. Des., 2014, 20(41), 6472-6488. doi: 10.2174/1381612820666140630101525 PMID: 24975604
  41. Mariotti, L.; Templeton, C.M.; Ranes, M.; Paracuellos, P.; Cronin, N.; Beuron, F.; Morris, E.; Guettler, S. Tankyrase requires SAM domain-dependent polymerization to support Wnt-β-catenin signaling. Mol. Cell, 2016, 63(3), 498-513. doi: 10.1016/j.molcel.2016.06.019 PMID: 27494558
  42. Lehtiö, L.; Collins, R.; van den Berg, S.; Johansson, A.; Dahlgren, L.G.; Hammarström, M.; Helleday, T.; Holmberg-Schiavone, L.; Karlberg, T.; Weigelt, J. Zinc binding catalytic domain of human tankyrase 1. J. Mol. Biol., 2008, 379(1), 136-145. doi: 10.1016/j.jmb.2008.03.058 PMID: 18436240
  43. Haikarainen, T.; Koivunen, J.; Narwal, M.; Venkannagari, H.; Obaji, E.; Joensuu, P.; Pihlajaniemi, T.; Lehtiö, L. para-Substituted 2-phenyl-3,4-dihydroquinazolin-4-ones as potent and selective tankyrase inhibitors. ChemMedChem, 2013, 8(12), 1978-1985. doi: 10.1002/cmdc.201300337 PMID: 24130191
  44. De Rycker, M.; Price, C.M. Tankyrase polymerization is controlled by its sterile alpha motif and poly(ADP-ribose) polymerase domains. Mol. Cell. Biol., 2004, 24(22), 9802-9812. doi: 10.1128/MCB.24.22.9802-9812.2004 PMID: 15509784
  45. Zamudio-Martinez, E; Herrera-Campos, AB; Muñoz, A; Rodríguez-Vargas, JM; Oliver, FJ Tankyrases as modulators of pro-tumoral functions: molecular insights and therapeutic opportunities. J. Exp. Clin. Cancer Res. BioMed Central Ltd, 2021, 1-15. doi: 10.1186/s13046-021-01950-6
  46. Villegas, I.; Sanchez-Fidalgo, S.; Sánchez-Fidalgo, S.; Alarcon de la Lastra, C.; Villegas, I.; Sanchez-Fidalgo, S. Poly(ADP-ribose) polymerase inhibitors: New pharmacological functions and potential clinical implications. Curr. Pharm. Des., 2007, 13(9), 933-962. doi: 10.2174/138161207780414241 PMID: 17430191
  47. Menon, M.; Elliott, R.; Bowers, L.; Balan, N.; Rafiq, R.; Costa-Cabral, S.; Munkonge, F.; Trinidade, I.; Porter, R.; Campbell, A.D.; Johnson, E.R.; Esdar, C.; Buchstaller, H.P.; Leuthner, B.; Rohdich, F.; Schneider, R.; Sansom, O.; Wienke, D.; Ashworth, A.; Lord, C.J. A novel tankyrase inhibitor, MSC2504877, enhances the effects of clinical CDK4/6 inhibitors. Sci. Rep., 2019, 9(1), 201. doi: 10.1038/s41598-018-36447-4 PMID: 30655555
  48. Park, H.W.; Guan, K.L. Regulation of the Hippo pathway and implications for anticancer drug development. Trends Pharmacol. Sci., 2013, 34(10), 581-589. doi: 10.1016/j.tips.2013.08.006 PMID: 24051213
  49. Wang 2015. Tankyrase inhibitors target YAP by stabilizing angiomotin family proteins. Physiol. Behav., 2018, 176(5), 139-148.
  50. Kierulf-Vieira, K.S.; Sandberg, C.J.; Waaler, J.; Lund, K.; Skaga, E.; Saberniak, B.M.; Panagopoulos, I.; Brandal, P.; Krauss, S.; Langmoen, I.A.; Vik-Mo, E.O. A small-molecule tankyrase inhibitor reduces glioma stem cell proliferation and sphere formation. Cancers, 2020, 12(6), 1630. doi: 10.3390/cancers12061630 PMID: 32575464
  51. Nkizinkiko, Y.; Desantis, J.; Koivunen, J.; Haikarainen, T.; Murthy, S.; Sancineto, L.; Massari, S.; Ianni, F.; Obaji, E.; Loza, M.I.; Pihlajaniemi, T.; Brea, J.; Tabarrini, O.; Lehtiö, L. 2-Phenylquinazolinones as dual-activity tankyrase-kinase inhibitors. Sci. Rep., 2018, 8(1), 1680. doi: 10.1038/s41598-018-19872-3 PMID: 29374194
  52. Hanahan, D.; Weinberg, R.A. Hallmarks of cancer: The next generation.Cell Press, 2011, pp. 646-674.
  53. Fares, J.; Fares, M.Y.; Khachfe, H.H.; Salhab, H.A.; Fares, Y. Molecular principles of metastasis: A hallmark of cancer revisited. Signal Transduction and Targeted Therapy, 2020, 5 Available From: https://www.nature.com/articles/s41392-020-0134-x accessed on 2022 May 16
  54. Yard, B.D.; Adams, D.J.; Chie, E.K.; Tamayo, P.; Battaglia, J.S.; Gopal, P.; Rogacki, K.; Pearson, B.E.; Phillips, J.; Raymond, D.P.; Pennell, N.A.; Almeida, F.; Cheah, J.H.; Clemons, P.A.; Shamji, A.; Peacock, C.D.; Schreiber, S.L.; Hammerman, P.S.; Abazeed, M.E. A genetic basis for the variation in the vulnerability of cancer to DNA damage. Nat. Commun., 2016, 7(1), 11428. Available From: https://www.nature.com/articles/ncomms11428 doi: 10.1038/ncomms11428 PMID: 27109210
  55. Schaue, D.; McBride, W.H. Opportunities and challenges of radiotherapy for treating cancer. Nat. Rev. Clin. Oncol., 2015, 12(9), 527-540. Available From: https://www.nature.com/articles/nrclinonc.2015.120 doi: 10.1038/nrclinonc.2015.120 PMID: 26122185
  56. Lawrence, T.S.; Haffty, B.G.; Harris, J.R. Milestones in the use of combined-modality radiation therapy and chemotherapy. J. Clin. Oncol., 2014, 32(12), 1173-1179. doi: 10.1200/JCO.2014.55.2281 PMID: 24663053
  57. Burley, S.K.; Berman, H.M.; Christie, C.; Duarte, J.M.; Feng, Z.; Westbrook, J.; Young, J.; Zardecki, C. RCSB Protein Data Bank: Sustaining a living digital data resource that enables breakthroughs in scientific research and biomedical education. Protein Sci., 2018, 27(1), 316-330. Available From: https://onlinelibrary.wiley.com/doi/full/10.1002/pro.3331 doi: 10.1002/pro.3331 PMID: 29067736
  58. Berman, H.M.; Battistuz, T.; Bhat, T.N.; Bluhm, W.F.; Bourne, P.E.; Burkhardt, K. TheProtein Data Bank, 2002, 58(6-1), 899-907. Internet Available From: https://www.onlinelibrary.wiley.com/doi/abs/10.1107/S0907444902003451
  59. Kusumaningrum, S.; Budianto, E.; Kosela, S.; Sumaryono, W.; Juniarti, F. The molecular docking of 1,4-naphthoquinone derivatives as inhibitors of Polo-like kinase 1 using Molegro Virtual Docker. J. Appl. Pharm. Sci., 2014, 4(11), 47-53. Available From: http://www.academia.edu/download/54300101/The_molecular_docking_of_14-naphthoquino20170831-2707-1eyf3nf.pdf Internet.
  60. Pettersen, E.F.; Goddard, T.D.; Huang, C.C.; Couch, G.S.; Greenblatt, D.M.; Meng, E.C.; Ferrin, T.E. UCSF Chimera?A visualization system for exploratory research and analysis. J. Comput. Chem., 2004, 25(13), 1605-1612. Available From: https://pubmed.ncbi.nlm.nih.gov/15264254/ doi: 10.1002/jcc.20084 PMID: 15264254
  61. Eswar, N.; Webb, B.; Marti-Renom, M.A.; Madhusudhan, M.S.; Eramian, D.; Shen, M.Y.; Pieper, U.; Sali, A. Comparative protein structure modeling using Modeller. Curr. Protoc. Bioinformatics, 2006, Chapter 5(1), 6. PMID: 18428767
  62. Cherinka, B.; Andrews, B.H.; Sánchez-Gallego, J.; Brownstein, J.; Argudo-Fernández, M.; Blanton, M.; Bundy, K.; Jones, A.; Masters, K.; Law, D.R.; Rowlands, K.; Weijmans, A-M.; Westfall, K.; Yan, R. Marvin: A tool kit for streamlined access and visualization of the SDSS-IV manga data set. Astron. J., 2019, 158(2), 74. Available From: https://ui.adsabs.harvard.edu/abs/2019AJ....158...74C/abstract Internet. doi: 10.3847/1538-3881/ab2634
  63. ChemAxon. Marvin ⋅ ChemAxon. 2020. Available From: https://chemaxon.com/products/marvin accessed on 2022 Mar 22
  64. Hanwell, M.D.; Curtis, D.E.; Lonie, D.C.; Vandermeersch, T.; Zurek, E.; Hutchison, G.R. Avogadro: An advanced semantic chemical editor, visualization, and analysis platform. J. Cheminform., 2012, 4(1), 17. doi: 10.1186/1758-2946-4-17 PMID: 22889332
  65. Salifu, E.Y.; Issahaku, A.R.; Agoni, C.; Ibrahim, M.A.A.; Manimbulu, N.; Soliman, M.E.S. Prioritizing the catalytic gatekeepers through pan- inhibitory mechanism of entrectinib against ALK, ROS1 and TRKA tyrosine kinases. Cell Biochem. Biophys., 2022, 80(1), 11-21. doi: 10.1007/s12013-021-01052-2 PMID: 35040089
  66. Trott, O; Olson, AJ AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem., 2009.
  67. Eberhardt, J.; Santos-Martins, D.; Tillack, A.F.; Forli, S. Autodock vina 1.2.0: New docking methods, expanded force field, and python bindings. J. Chem. Inf. Model., 2021, 61(8), 3891-3898. doi: 10.1021/acs.jcim.1c00203 PMID: 34278794
  68. Case, D.A.; Ben-Shalom, I.Y.; Brozell, S.R.; Cerutti, D.S.; Cheatham, T.E., III; Cruzeiro, V.W.D. Amber. University of California: San Francisco, 2018; p. 1. Internet Available From: http://ambermd.org/
  69. Salomon-Ferrer, R.; Case, D.A.; Walker, R.C. An overview of the Amber biomolecular simulation package. Wiley Interdiscip. Rev. Comput. Mol. Sci., 2013, 3(2), 198-210. Available From: https://onlinelibrary.wiley.com/doi/pdf/10.1002/wcms.1121 Internet. doi: 10.1002/wcms.1121
  70. Ponder, J.W.; Case, D.A. Force fields for protein simulations Elsevier., 2003. Available From: https://www.sciencedirect.com/science/article/pii/S006532330366002X accessed on 2020 Mar 31
  71. Wang, J.; Wolf, R.M.; Caldwell, J.W.; Kollman, P.A.; Case, D.A. Development and testing of a general amber force field. J. Comput. Chem., 2004, 25(9), 1157-1174. doi: 10.1002/jcc.20035 PMID: 15116359
  72. Grest, G.S.; Kremer, K. Molecular dynamics simulation for polymers in the presence of a heat bath. Phys. Rev. A Gen. Phys., 1986, 33(5), 3628-3631. doi: 10.1103/PhysRevA.33.3628 PMID: 9897103
  73. Berendsen, H.J.C.; Postma, J.P.M.; van Gunsteren, W.F.; DiNola, A.; Haak, J.R. Molecular dynamics with coupling to an external bath. J. Chem. Phys., 1984, 81(8), 3684-3690. Available From: http://aip.scitation.org/doi/10.1063/1.448118 Internet. doi: 10.1063/1.448118
  74. Omolabi, K.F.; Agoni, C.; Olotu, F.A.; Soliman, M.E.S. ‘Finding the needle in the haystack’- will natural products fit for purpose in the treatment of cryptosporidiosis? – A theoretical perspective. Mol. Simul., 2021, 47(8), 636-649. doi: 10.1080/08927022.2021.1895435
  75. Roe, D.R.; Cheatham, T.E., III PTRAJ and CPPTRAJ: Software for processing and analysis of molecular synamics trajectory data. J. Chem. Theory Comput., 2013, 9(7), 3084-3095. doi: 10.1021/ct400341p PMID: 26583988
  76. Seifert, E. OriginPro 9.1: Scientific data analysis and graphing software - Software review. J. Chem. Inf. Model. American Chemical Society, 2014, 54, 1552.
  77. Hess, B.; Bekker, H.; Berendsen, H.J.C.; Fraaije, J.G.E.M. LINCS: A linear constraint solver for molecular simulations. Comput Chem. John Wiley & Sons, Inc, 1997. Available From: https://onlinelibrary.wiley.com/doi/abs/10.1002/(SICI)1096-987X(199709)18:12%3C1463:AID-JCC4%3E3.0.CO;2-H accessed on 2020 Mar 31
  78. BIOVIA DS. Discovery Studio 2016 Client. San Diego: Dassault Systèmes. 2016. Available From: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=D.+S.+BIOVIA%2C+ accessed on 2022 Mar 23
  79. Massova, I.; Kollman, P.A. Combined molecular mechanical and continuum solvent approach (MM- PBSA/GBSA) to predict ligand binding. Vol. 18. Perspect. Drug Discov. Des., 2000, 18(1), 113-135. doi: 10.1023/A:1008763014207
  80. Genheden, S.; Kuhn, O.; Mikulskis, P.; Hoffmann, D.; Ryde, U. The normal-mode entropy in the MM/GBSA method: effect of system truncation, buffer region, and dielectric constant. J. Chem. Inf. Model., 2012, 52(8), 2079-2088. doi: 10.1021/ci3001919 PMID: 22817270
  81. Onufriev, A.; Bashford, D.; Case, D.A. Modification of the generalized born model suitable for macromolecules. J. Phys. Chem. B, 2000, 104(15), 3712-3720. Available From: https://pubs.acs.org/doi/abs/10.1021/jp994072s Internet. doi: 10.1021/jp994072s
  82. Ylilauri, M.; Pentikäinen, O.T. MMGBSA as a tool to understand the binding affinities of filamin-peptide interactions. J. Chem. Inf. Model., 2013, 53(10), 2626-2633. doi: 10.1021/ci4002475 PMID: 23988151
  83. Kollman, P.A.; Massova, I.; Reyes, C.; Kuhn, B.; Huo, S.; Chong, L.; Lee, M.; Lee, T.; Duan, Y.; Wang, W.; Donini, O.; Cieplak, P.; Srinivasan, J.; Case, D.A.; Cheatham, T.E., III Calculating structures and free energies of complex molecules: Combining molecular mechanics and continuum models. Acc. Chem. Res., 2000, 33(12), 889-897. doi: 10.1021/ar000033j PMID: 11123888
  84. Hou, T.; Wang, J.; Li, Y.; Wang, W. Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. J. Chem. Inf. Model., 2011, 51(1), 69-82. doi: 10.1021/ci100275a PMID: 21117705
  85. Homeyer, N.; Gohlke, H. Free energy calculations by the molecular mechanics poisson−boltzmann surface area method. Mol. Inform., 2012, 31(2), 114-122. Available From: https://onlinelibrary.wiley.com/doi/abs/10.1002/minf.201100135 doi: 10.1002/minf.201100135 PMID: 27476956
  86. Sitkoff, D.; Sharp, K.A.; Honig, B. Accurate calculation of hydration free energies using macroscopic solvent models. J. Phys. Chem., 1994, 98(7), 1978-1988. doi: 10.1021/j100058a043
  87. Webborn, P.J.H. The role of pharmacokinetic studies in drug discovery: Where are we now, how did we get here and where are we going? Future Medicinal Chemistry. Future Science, 2014; Vol. 6, pp. 1233-1235.
  88. Daina, A.; Michielin, O.; Zoete, V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep., 2017, 7(1), 42717. doi: 10.1038/srep42717 PMID: 28256516
  89. Daina, A.; Zoete, V. A BOILED-Egg to predict gastrointestinal absorption and brain penetration of small molecules. ChemMedChem, 2016, 11(11), 1117-1121. Available From: https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cmdc.201600182 doi: 10.1002/cmdc.201600182 PMID: 27218427
  90. Elamin, G.; Aljoundi, A.; Alahmdi, M.I.; Abo-Dya, N.E.; Soliman, M.E.S. Battling BTK mutants with noncovalent inhibitors that overcome Cys481 and Thr474 mutations in Waldenström macroglobulinemia therapy: Structural mechanistic insights on the role of fenebrutinib. J. Mol. Model., 2022, 28(11), 355. Available From: https://link.springer.com/article/10.1007/s00894-022-05345-y doi: 10.1007/s00894-022-05345-y PMID: 36222928
  91. Ahmed, S.S.S.J.; Ramakrishnan, V. Systems biological approach of molecular descriptors connectivity: Optimal descriptors for oral bioavailability prediction. PLoS One, 2012, 7(7), e40654. doi: 10.1371/journal.pone.0040654 PMID: 22815781
  92. Mukherjee, J.; Gupta, M.N. Increasing importance of protein flexibility in designing biocatalytic processes. Biotechnol. Rep., 2015, 6, 119-123. Available From: https://www.sciencedirect.com/science/article/pii/S2215017X1500020X doi: 10.1016/j.btre.2015.04.001 PMID: 28626705
  93. Xie, Y.; An, J.; Yang, G.; Wu, G.; Zhang, Y.; Cui, L.; Feng, Y. Enhanced enzyme kinetic stability by increasing rigidity within the active site. J. Biol. Chem., 2014, 289(11), 7994-8006. Available From: https://www.jbc.org/article/S0021-9258(20)44301-7/abstract doi: 10.1074/jbc.M113.536045 PMID: 24448805
  94. Celej, M.S.; Montich, G.G.; Fidelio, G.D. Protein stability induced by ligand binding correlates with changes in protein flexibility. Protein Sci., 2003, 12(7), 1496-1506. Available From: https://onlinelibrary.wiley.com/doi/abs/10.1110/ps.0240003 doi: 10.1110/ps.0240003 PMID: 12824495
  95. Liu, K.; Watanabe, E.; Kokubo, H. Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations. J. Comput. Aided Mol. Des., 2017, 31(2), 201-211. doi: 10.1007/s10822-016-0005-2 PMID: 28074360
  96. Agoni, C.; Salifu, E.Y.; Munsamy, G.; Olotu, F.A.; Soliman, M. CF 3 ‐Pyridinyl substitution on antimalarial therapeutics: probing differential ligand binding and dynamical inhibitory effects of a novel triazolopyrimidine‐based inhibitor on Plasmodium falciparum dihydroorotate dehydrogenase. Chem. Biodivers., 2019, 16(12), e1900365. doi: 10.1002/cbdv.201900365 PMID: 31589372
  97. Luque, I.; Freire, E.; Saecker, R.M.; Record, M.T. Structural stability of binding sites: Consequences for binding affinity and allosteric effects. Proteins, 2000, 41(S4)(Suppl. 4), 63-71. Available From: https://onlinelibrary.wiley.com/doi/abs/10.1002/1097-0134(2000)41:4+%3C63:AID-PROT60%3E3.0.CO;2-6 doi: 10.1002/1097-0134(2000)41:4+3.0.CO;2-6 PMID: 11013401
  98. Brüschweiler, R. Efficient RMSD measures for the comparison of two molecular ensembles. Proteins, 2003, 50(1), 26-34. doi: 10.1002/prot.10250 PMID: 12471596
  99. Pitera, J.W. Expected distributions of root-mean-square positional deviations in proteins. J. Phys. Chem. B, 2014, 118(24), 6526-6530. Available From: https://pubs.acs.org/doi/abs/10.1021/jp412776d doi: 10.1021/jp412776d PMID: 24655018
  100. Kumar, CV; Swetha, RG; Anbarasu, A; Ramaiah, S Computational analysis reveals the association of threonine 118 methionine mutation in PMP22 resulting in CMT-1A. Advances in Bioinformatics, 2014. doi: 10.1155/2014/502618
  101. Teilum, K.; Olsen, J.G.; Kragelund, B.B. Functional aspects of protein flexibility. Cell. Mol. Life Sci., 2009, 66(14), 2231-2247. Available From: https://link.springer.com/article/10.1007/s00018-009-0014-6 doi: 10.1007/s00018-009-0014-6 PMID: 19308324
  102. Gromiha, M.; Ahmad, S. Role of solvent accessibility in structure based drug design. Curr. Computeraided Drug Des., 2005, 1(3), 223-235. Available From: https://www.ingentaconnect.com/content/ben/cad/2005/00000001/00000003/art00001 Internet. doi: 10.2174/1573409054367664

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