Skip to main content
SpringerLink
Log in

Molecular modeling of four Dermaseptin-related peptides of the gliding tree frog Agalychnis spurrelli

  • Original Paper
  • Published:
Journal of Molecular Modeling Aims and scope Submit manuscript

Abstract

In this research, we present a preliminary computational study of four Dermaseptin-related peptides from the skin exudate of the gliding tree frog Agalychnis spurrelli. Experimentally, the amino acid sequence of these peptides was elucidated through molecular cloning and tandem mass spectrometry and synthetic peptides were assayed against E. coli, S. aureus, and C. albicans to determine their antimicrobial properties. With the sequences on hand, a computational study of the structures was carried out, obtaining their physicochemical properties, secondary structure, and their similarity to other known peptides. A molecular docking study of these peptides was also performed against cell membrane and several enzymes are known to be vital for the organisms. Results showed that Dermaseptin-related peptides are α-helical cationic peptides with an isoelectric point above 9.70 and a positive charge of physiological pH. Introducing theses peptides in a database, it was determined that their identity compared with known peptides range from 36 to 82% meaning these four Dermaseptins are novel peptides. This preliminary study of molecular docking suggests the mechanism of action of this peptide is not given by the inhibition of essential enzymatic pathways, but by cell lysis.

Graphical abstract

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Conlon JM (2012) The potential of frog skin antimicrobial peptides for development into therapeutically valuable anti-infective agents, Chapter 3 In Small Wonders. Peptides for Disease Control; ACS Symposium Series; American Chemical Society, Washington

    Google Scholar 

  2. Lacombe C, Piesse C, Sagan S, Combadière C, Rosenstein Y, Auvynet C (2015) Pachymodulin, a new functional formyl peptide receptor 2 peptidic ligand isolated from frog skin has Janus-like immunomodulatory capacities. J Med Chem 58:1089–1099. https://doi.org/10.1021/jm501018q

    Article  CAS  PubMed  Google Scholar 

  3. Holthausen D, Lee S, Kumar V, Bouvier N, Krammer F, Ellebedy A, Wrammert J, Lowen A, George S, Pillai M, Jacob J (2017) An amphibian host defense peptide is virucidal for human H1 hemagglutinin-bearing influenza viruses. Immunity 46:587–595. https://doi.org/10.1016/j.immuni.2017.03.018

    Article  CAS  PubMed  Google Scholar 

  4. Scorciapino M, Manzo G, Rinaldi A, Sanna R, Casu M, Pantic J, Lukic M, Conlon J (2013) Conformational analysis of the frog skin peptide, plasticin-L1 and its effects on the production of proinflammatory cytokines by macrophages. Biochemistry 52(41):7231–7241. https://doi.org/10.1021/bi4008287

    Article  CAS  PubMed  Google Scholar 

  5. Manzo G, Casu M, Rinaldi M, Montaldo N, Luganini A, Gribaudo G, Scorciapino M (2014) Folded structure and insertion depth of the frog-skin antimicrobial peptide esculentin-1b (1–18) in the presence of differently charged membrane-mimicking micelles. J Nat Prod 77(11):2410–2417. https://doi.org/10.1021/np5004406

    Article  CAS  PubMed  Google Scholar 

  6. Samgina T, Vorontsov E, Gorshkov V, Hakalehto E, Hanninen O, Zubarev R, Lebedevl A (2012) Composition and antimicrobial activity of the skin peptidome of Russian Brown Frog Rana temporaria. J Proteome Res 11(12):6213–6222. https://doi.org/10.1021/pr300890m

    Article  CAS  PubMed  Google Scholar 

  7. Marani M, Dourado F, Quelemes P, Rodrigues A, Gomes M, Alves E, Costa L, Rodrigues A, Barroso E, Eaton P, Figueiró J, Bentes R, Delerue-Matos C, Leite J (2015) Characterization and biological activities of ocellatin peptides from the skin secretion of the frog Leptodactylus pustulatus. J Nat Prod 78(7):1495–1504. https://doi.org/10.1021/np500907t

    Article  CAS  PubMed  Google Scholar 

  8. Stutz K, Muller A, Hiss J, Schneider P, Blatter M, Pfeiffer B, Posselt G, Kanfer G, Kornmann B, Wrede P, Altmann K, Wessler S, Schneider G (2017) Peptide-membrane interaction between targeting and lysis. ACS Chem Biol 12(9):2254–2259. https://doi.org/10.1021/acschembio.7b00504

    Article  CAS  PubMed  Google Scholar 

  9. Ortega-Andrade HM (2008) Agalychnis spurrelli Boulenger (Anura: Hylidae): variación, distribución y sinonimia. Papéis Avulsos de Zoologia 48:103–1117

    Article  Google Scholar 

  10. Duellman WE (2001) Hylid Frogs of Middle America. Society for the Study of Amphibians and Reptiles, Ithaca

    Google Scholar 

  11. Gray AR (1997) Observations on the biology of Agalychnis spurrelli from the Caribbean lowlands of Costa Rica. Observaciones sobre la biología de Agalychnis spurrelli de las tierras bajas del caribe de Costa Rica. Journal of the International Herpetological Society 22:61–70

    Google Scholar 

  12. MECN (2010) Serie Herpetofauna del Ecuador: El Choco Esmeraldeño. Monografía. Museo Ecuatoriano de Ciencias Naturales. Quito-Ecuador 5:1–232

    Google Scholar 

  13. Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, Bairoch A (2005) Protein Identification and Analysis Tools on the ExPASy Server. In: En Walker J (ed) The Proteomics Protocols Handbook. Springer, London

    Google Scholar 

  14. Innovagen (2015) Peptide property calculator, Innovagen AB, https://pepcalc.com/

  15. Bio-Synthesis. (2018). Peptide Property Calculator, Bio-Synthesis Inc. https://www.biosyn.com/peptidepropertycalculatorlanding.aspx

  16. Drozdetskiy A, Cole C, Procter J, Barton GJ (2015) JPred4: a protein secondary structure prediction server. Nucleic Acids Res 43:389–394

    Article  Google Scholar 

  17. Jones DT (1999) Protein secondary structure prediction based on position-specific scoring matrices. J Mol Biol 292:195–202

    Article  CAS  Google Scholar 

  18. The PyMOL Molecular Graphics System (2017) Version 2.0 Schrödinger, LLC. https://pymol.org/2/support.html?#citing

  19. ChembioDraw (2009) PerkinElmer Informatics. http://informatics.perkinelmer.com/Support/KnowledgeBase/details/Default?TechNote=3411

  20. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Fox DJ (2009) Gaussian 09. Revision A.01. Gaussian, Inc, Wallingford https://doi.org/111\

    Google Scholar 

  21. Berman H, Westbrook J, Feng Z, Gilliland G, Bhat T, Weissig H, Shindyalov I, Bourne P (2000) The Protein Data Bank. Nucleic Acids Res 28(1):235–242

    Article  CAS  Google Scholar 

  22. 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(2):455–461

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Gill SC, von Hippel PH (1989) Calculation of protein extinction coefficients from amino acid sequence data. Anal Biochem 182(2):319–326

    Article  CAS  Google Scholar 

  24. Cuesta S, Arias J, Gallegos F, Proaño C, Blasco-Zúñiga A, Rivera M, Meneses L (2019) Molecular modeling of Dermaseptine SP2 extracted from Agalychnis spurrelli. InfoANALÍTICA 7(1):41–56. https://doi.org/10.26807/ia.v7i1.95

    Article  Google Scholar 

  25. Guruprasad K, Reddy BVB, Pandit MW (1990) Correlation between stability of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Eng 4:155–161

    Article  CAS  Google Scholar 

  26. Li RF, Lu ZF, Sun YN, Chen SH, Yi YJ, Zhang HR, Yang SY, Yu GH, Huang L, Li CN (2016) Molecular design, structural analysis and antifungal activity of derivatives of peptide CGA-N46. Interdisciplinary sciences, computational life sciences 8(3):319–326

    Article  Google Scholar 

  27. Fieser TM, Tainer JA, Geysen HM, Houghten RA, Lerner RA (1987) Influence of protein flexibility and peptide conformation on reactivity of monoclonal anti-peptide antibodies with a protein alpha-helix. Proc Natl Acad Sci U S A 84(23):8568–8572

    Article  CAS  Google Scholar 

  28. Karplus PA, Schulz GE (1985) Prediction of chain flexibility in proteins: a tool for the selection of peptide antigens. Naturwissenschaften 72:212–213

    Article  CAS  Google Scholar 

  29. Huang F, Nau WM (2003) A conformational flexibility scale for amino acids in peptides. Angew Chem Int Ed Eng 42(20):2269–2272

    Article  CAS  Google Scholar 

  30. Melchiorri P, Negri L (2009) Amphibian peptides, Encyclopedia of Neuroscience. Elsevier Academic Press, San Diego

    Google Scholar 

  31. Park MS, Gao C, Stern HA (2011) Estimating binding affinities by docking/scoring methods using variable protonation states. Proteins 79(1):304–314. https://doi.org/10.1002/prot.22883

    Article  CAS  PubMed  Google Scholar 

  32. Pantsar T, Poso A (2018) Binding affinity via docking: fact and fiction. Molecules 23(8):1899

    Article  Google Scholar 

  33. Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A, Grant JR, Sajed T, Johnson D, Li C, Sayeeda Z, Assempour N, Iynkkaran I, Liu Y, Maciejewski A, Gale N, Wilson A, Chin L, Cummings R, Le D, Pon A, Knox C, Wilson M (2017) DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res 46:1074–1082

    Article  Google Scholar 

  34. Wang G (2014) Human antimicrobial peptides and proteins. Pharmaceuticals 7(5):545–594

    Article  CAS  Google Scholar 

  35. Bechinger B, Gorr SU (2017) Antimicrobial peptides: mechanisms of action and resistance. J Dent Res 96(3):254–260

    Article  CAS  Google Scholar 

Download references

Acknowledgments

CPB obtained the peptides sequences in Queen’s University Belfast funded by the Natural drug discovery group and the Ecuadorian Secretariat of Science and Technology (SENESCYT) through a scholarship. Collection and rearing of frogs in Ecuador were done under permits of the Ecuadorian Ministerio de Ambiente (MAE): 001-13 IC-FAU-DNB/MA, 003-11 IC-FAU-DNB/MA, 005-15 IC-FAU-DNB/MA (Issued to the Centro Jambatu). This research is part of the project “Conservation of Ecuadorian amphibian diversity and sustainable use of its genetic resources”, which involves MAE, Ikiam-Universidad Regional Amazónica, Queen’s University Belfast, and Centro Jambatu, and help of the Global Environmental Facility (GEF) and “Programa de las Naciones Unidas para el Desarrollo” (PNUD).

Funding

This research was funded by two research grants to L.M and M.R. of the Dirección General Académica of the Pontificia Universidad Católica del Ecuador, projects: QINV0035-IINV529010100 and QIV0046-IINV529010100.

Author information

Authors and Affiliations

  1. Laboratorios LIFE, Av. De la Prensa y Juan Galarza, Quito, Ecuador

    Sebastián Cuesta

  2. Laboratorio de Química Computacional, Escuela de Ciencias Químicas, Pontificia Universidad Católica del Ecuador, Av. 12 de Octubre 1076 y Roca, Apartado 17-01-2184, Quito, Ecuador

    Felipe Gallegos, Josefa Arias, Fernanda Pilaquinga & Lorena Meneses

  3. Laboratorio de Investigación en Citogenética y Biomoléculas de Anfibios-LICBA, Centro de Investigación para la Salud en América Latina-CISeAL, Facultad de Ciencias Exactas y Naturales, Pontificia Universidad Católica del Ecuador, Av. 12 de octubre 1076 y Roca, Apartado 17-01-2184, Quito, Ecuador

    Ailín Blasco-Zúñiga & Miryan Rivera

  4. Laboratorio de Biología Molecular y Bioquímica, Universidad Regional Amazónica Ikiam, Km 7 vía Muyuna, Tena, Ecuador

    Carolina Proaño-Bolaños

Authors
  1. Sebastián Cuesta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Felipe Gallegos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Josefa Arias
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fernanda Pilaquinga
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ailín Blasco-Zúñiga
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Carolina Proaño-Bolaños
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Miryan Rivera
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Lorena Meneses
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lorena Meneses.

Additional information

Publisher’s note

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

This paper belongs to Topical Collection QUITEL 2018 (44th Congress of Theoretical Chemists of Latin Expression)

Electronic supplementary material

ESM 1

(DOCX 14 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cuesta, S., Gallegos, F., Arias, J. et al. Molecular modeling of four Dermaseptin-related peptides of the gliding tree frog Agalychnis spurrelli. J Mol Model 25, 260 (2019). https://doi.org/10.1007/s00894-019-4141-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00894-019-4141-1

Keywords

Search

Navigation