Skip to main content
Log in

Computational insight to structural aspects of Crispine-DNA binding

  • Original Research
  • Published:
Structural Chemistry Aims and scope Submit manuscript

Abstract

Crispines are naturally occurring isoquinoline alkaloids with potent cytotoxic activity reported against SKOV3, KB and Hela human cancer cell lines. The structural details on the drug-receptor interactions that induce cytotoxic activity are important factors to be considered in drug development and repurposing studies. In the present study, cytotoxic mechanism of Crispine variants; Crispine A and Crispine B with double-stranded DNA has been investigated through computational techniques including molecular docking, molecular dynamics simulations, and quantum mechanical calculations. Analysis of the drug binding mode, conformational perturbations induced by the binding of the drug, receptor and ligand flexibility in dynamic solvent environment and energetics of the complex formation clearly suggests that Crispine B portrays partial intercalation stabilized by hydrophobic interactions and binds to DNA with better affinity than Crispine A, the latter prefers the minor groove even in the presence of an intercalation cavity in DNA. The presence of the pi-electrons system in Crispine B enhances the molecular planarity and aromaticity to provide enough stacking forces and supports partial intercalation. Both the variants show minimal changes in terms of structure but induce significant change in DNA conformation to support cytotoxic behavior.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Data availability

All data generated or analyzed during this study are included in this article and appended in the Supplementary Information.

References

  1. Shen YM, Lv PC, Chen W et al (2010) Synthesis and antiproliferative activity of indolizine derivatives incorporating a cyclopropylcarbonyl group against Hep-G2 cancer cell line. Eur J Med Chem 45:3184–3190. https://doi.org/10.1016/J.EJMECH.2010.02.056

    Article  CAS  PubMed  Google Scholar 

  2. Gundersen LL, Negussie AH, Rise F, Østby OB (2003) Antimycobacterial activity of 1-substituted indolizines. Arch Pharm (Weinheim) 336:191–195. https://doi.org/10.1002/ARDP.200390019

    Article  CAS  PubMed  Google Scholar 

  3. Hazra A, Mondal S, Maity A et al (2011) Amberlite-IRA-402 (OH) ion exchange resin mediated synthesis of indolizines, pyrrolo[1,2-a]quinolines and isoquinolines: antibacterial and antifungal evaluation of the products. Eur J Med Chem 46:2132–2140. https://doi.org/10.1016/J.EJMECH.2011.02.066

    Article  CAS  PubMed  Google Scholar 

  4. Amariucai-Mantu D, Antoci V, Sardaru MC et al (2022) Fused pyrrolo-pyridines and pyrrolo-(iso)quinoline as anticancer agents. Phys Sci Rev. https://doi.org/10.1515/PSR-2021-0030/XML

    Article  Google Scholar 

  5. Zhang Q, Tu G, Zhao Y, Cheng T (2002) Novel bioactive isoquinoline alkaloids from Carduus crispus. Tetrahedron 58:6795–6798. https://doi.org/10.1016/S0040-4020(02)00792-5

    Article  CAS  Google Scholar 

  6. Xie W-D, Li P-L, Jia Z-J (2005) A new flavone glycoside and other constituents from Carduus crispus. Pharmazie 60:233–236

    CAS  PubMed  Google Scholar 

  7. Strekowski L, Wilson B (2007) Noncovalent interactions with DNA: an overview. Mutat Res 623:3–13. https://doi.org/10.1016/J.MRFMMM.2007.03.008

    Article  CAS  PubMed  Google Scholar 

  8. Gurova K (2009) New hopes from old drugs: revisiting DNA-binding small molecules as anticancer agents. Future Oncol 5:1685. https://doi.org/10.2217/FON.09.127

    Article  CAS  PubMed  Google Scholar 

  9. Martinez R, Chacon-Garcia L (2005) The search of DNA-intercalators as antitumoral drugs: what it worked and what did not work. Curr Med Chem 12:127–151. https://doi.org/10.2174/0929867053363414

    Article  CAS  PubMed  Google Scholar 

  10. Islam MM, Chakraborty M, Pandya P et al (2013) Binding of DNA with Rhodamine B: spectroscopic and molecular modeling studies. Dye Pigm 99:412–422. https://doi.org/10.1016/J.DYEPIG.2013.05.028

    Article  CAS  Google Scholar 

  11. Islam MM, Pandya P, Chowdhury SR et al (2008) Binding of DNA-binding alkaloids berberine and palmatine to tRNA and comparison to ethidium: spectroscopic and molecular modeling studies. J Mol Struct 891:498–507. https://doi.org/10.1016/J.MOLSTRUC.2008.04.043

    Article  CAS  Google Scholar 

  12. Pandya P, Agarwal LK, Gupta N, Pal S (2014) Molecular recognition pattern of cytotoxic alkaloid vinblastine with multiple targets. J Mol Graph Model 54:1–9. https://doi.org/10.1016/J.JMGM.2014.09.001

    Article  CAS  PubMed  Google Scholar 

  13. Islam MM, Pandya P, Kumar S, Kumar GS (2009) RNA targeting through binding of small molecules: studies on t-RNA binding by the cytotoxic protoberberine alkaloidcoralyne. Mol Biosyst 5:244–254. https://doi.org/10.1039/B816480K

    Article  CAS  PubMed  Google Scholar 

  14. Mohammad M, Al Rasid Gazi H, Pandav K et al (2021) Evidence for dual site binding of Nile Blue A toward DNA: spectroscopic, thermodynamic, and molecular modeling studies. ACS Omega 6:2613–2625. https://doi.org/10.1021/ACSOMEGA.0C04775

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. BIOVIA, Dassault Systèmes (2019) Discovery Studio Client, v20.1.0.19295. San Diego: Dassault Systèmes

  16. Drew HR, Wing RM, Takano T et al (1981) Structure of a B-DNA dodecamer: conformation and dynamics. Proc Natl Acad Sci U S A 78:2179–2183. https://doi.org/10.1073/PNAS.78.4.2179

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Canals A, Purciolas M, Aymamí J, Coll M (2005) The anticancer agent ellipticine unwinds DNA by intercalative binding in an orientation parallel to base pairs. Acta Crystallogr Sect D Biol Crystallogr 61:1009–1012. https://doi.org/10.1107/S0907444905015404

    Article  CAS  Google Scholar 

  18. Hanwell MD, Curtis DE, Lonie DC et al (2012) Avogadro: an advanced semantic chemical editor, visualization, and analysis platform. J Cheminform 4:1–17. https://doi.org/10.1186/1758-2946-4-17/FIGURES/14

    Article  Google Scholar 

  19. Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455–461. https://doi.org/10.1002/JCC.21334

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Phillips JC, Hardy DJ, Maia JDC et al (2020) Scalable molecular dynamics on CPU and GPU architectures with NAMD. J Chem Phys. https://doi.org/10.1063/5.0014475

    Article  PubMed  PubMed Central  Google Scholar 

  21. Gopi P, Gurnani M, Singh S et al (2022) Structural aspects of SARS-CoV-2 mutations: Implications to plausible infectivity with ACE-2 using computational modeling approach. J Biomol Struct Dyn 1–16. https://doi.org/10.1080/07391102.2022.2108901

  22. Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Graph 14:33–38. https://doi.org/10.1016/0263-7855(96)00018-5

    Article  CAS  PubMed  Google Scholar 

  23. Jo S, Kim T, Iyer VG, Im W (2008) CHARMM-GUI: a web-based graphical user interface for CHARMM. J Comput Chem 29:1859–1865. https://doi.org/10.1002/JCC.20945

    Article  CAS  PubMed  Google Scholar 

  24. Lee J, Cheng X, Swails JM et al (2016) CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. J Chem Theory Comput 12:405–413. https://doi.org/10.1021/ACS.JCTC.5B00935/SUPPL_FILE/CT5B00935_SI_001.PDF

    Article  CAS  PubMed  Google Scholar 

  25. Zheng G, Lu XJ, Olson WK (2009) Web 3DNA—a web server for the analysis, reconstruction, and visualization of three-dimensional nucleic-acid structures. Nucleic Acids Res 37:W240–W246. https://doi.org/10.1093/NAR/GKP358

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Liu H, Hou T (2016) CaFE: a tool for binding affinity prediction using end-point free energy methods. Bioinformatics 32:2216–2218. https://doi.org/10.1093/BIOINFORMATICS/BTW215

    Article  CAS  PubMed  Google Scholar 

  27. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Montgomery  JA Jr, Vreven T, Kudin KN, Burant JC, Millam JM, Iyengar SS, Tomasi J, Barone V, Mennucci B, Cossi M, Scalmani G, Rega N, Petersson GA, Nakatsuji H, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Klene M, Li X, Knox JE, Hratchian HP, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Ayala PY, Morokuma K, Voth GA, Salvador P, Dannenberg JJ, Zakrzewski VG, Dapprich S, Daniels AD, Strain MC, Farkas O, Malick DK, Rabuck AD, Raghavachari K, Foresman JB, Ortiz JV, Cui Q, Baboul AG, Clifford S, Cioslowski J, Stefanov BB, Liu G, Liashenko A, Piskorz P, Komaromi I, Martin RL, Fox DJ, Keith T, Al-Laham MA, Peng CY, Nanayakkara A, Challacombe M, Gill PMW, Johnson B, Chen W, Wong MW, Gonzalez C, Pople JA (2004) Gaussian 03, Revision C.02, Gaussian, Inc., Wallingford CT

Download references

Funding

Present work was conducted partially on the facilities provided by research grant (ISRM/12(06)/2017) from Indian Council of Medical Research to P.P and Senior Research Fellowship (CSIR, New Delhi) to L.K.A.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed equally to the concept, design, and analysis of this study. L.K.A. and P.G. performed the experiments. P.P. and N.G. supervised the work and finalized the manuscript. All authors gave inputs for the rational contents and approved final version of the manuscript.

Corresponding authors

Correspondence to Prateek Pandya or Neelima Gupta.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 302 KB)

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Agarwal, L.K., Gopi, P., Pandya, P. et al. Computational insight to structural aspects of Crispine-DNA binding. Struct Chem 34, 837–848 (2023). https://doi.org/10.1007/s11224-022-02034-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11224-022-02034-7

Keywords

Navigation