Advertisement

In Silico Design of Anticancer Peptides

  • Shailesh Kumar
  • Hui Li
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1647)

Abstract

In the past few years, small peptides having anticancer properties have emerged as a potential avenue for cancer therapy. Compared to current anti-cancer chemotherapeutic drugs (or small molecules), anticancer peptides (ACPs) have numerous advantageous properties, such as high specificity, low production cost, high tumor penetration, ease of synthesis and modification. However, in wet lab setups, identification and characterization of novel ACPs is a time-consuming and labor-intensive process. Therefore, in silico designing of anticancer peptides is beneficial, prior to their synthesis and characterization. This approach is less time consuming and more cost-effective. In this chapter, we discuss a web-based tool, AntiCP (http://crdd.osdd.net/raghava/anticp/), for designing ACPs.

Key words

Anti-cancer peptides Machine learning Support vector machine 

Notes

Acknowledgement

AntiCP server was developed by Raghava’s group (http://www.imtech.res.in/raghava/) at CSIR-IMTECH, India.

References

  1. 1.
    Siegel RL, Miller KD, Jemal A (2016) Cancer statistics, 2016. CA Cancer J Clin 66:7–30. doi: 10.3322/caac.21332 CrossRefPubMedGoogle Scholar
  2. 2.
    Mayne ST, Playdon MC, Rock CL (2016) Diet, nutrition, and cancer: past, present and future. Nat Rev Clin Oncol. doi: 10.1038/nrclinonc.2016.24
  3. 3.
    Wu D, Gao Y, Qi Y et al (2014) Peptide-based cancer therapy: opportunity and challenge. Cancer Lett 351:13–22. doi: 10.1016/j.canlet.2014.05.002 CrossRefPubMedGoogle Scholar
  4. 4.
    Peer D, Karp JM, Hong S et al (2007) Nanocarriers as an emerging platform for cancer therapy. Nat Nanotechnol 2:751–760. doi: 10.1038/nnano.2007.387 CrossRefPubMedGoogle Scholar
  5. 5.
    Amit D, Hochberg A (2010) Development of targeted therapy for bladder cancer mediated by a double promoter plasmid expressing diphtheria toxin under the control of H19 and IGF2-P4 regulatory sequences. J Transl Med 8:134. doi: 10.1186/1479-5876-8-134 CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Kang TH, Mao C-P, He L et al (2012) Tumor-targeted delivery of IL-2 by NKG2D leads to accumulation of antigen-specific CD8+ T cells in the tumor loci and enhanced anti-tumor effects. PLoS One 7:e35141. doi: 10.1371/journal.pone.0035141 CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Bidwell GL (2012) Peptides for cancer therapy: a drug-development opportunity and a drug-delivery challenge. Ther Deliv 3:609–621CrossRefPubMedGoogle Scholar
  8. 8.
    Thundimadathil J (2012) Cancer treatment using peptides: current therapies and future prospects. J Amino Acids 2012:967347. doi: 10.1155/2012/967347 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Vlieghe P, Lisowski V, Martinez J, Khrestchatisky M (2010) Synthetic therapeutic peptides: science and market. Drug Discov Today 15:40–56. doi: 10.1016/j.drudis.2009.10.009 CrossRefPubMedGoogle Scholar
  10. 10.
    Mader JS, Hoskin DW (2006) Cationic antimicrobial peptides as novel cytotoxic agents for cancer treatment. Expert Opin Investig Drugs 15:933–946. doi: 10.1517/13543784.15.8.933 CrossRefPubMedGoogle Scholar
  11. 11.
    Gaspar D, Veiga AS, Castanho MARB (2013) From antimicrobial to anticancer peptides. A review. Front Microbiol 4:294. doi: 10.3389/fmicb.2013.00294 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Chu H-L, Yip B-S, Chen K-H et al (2015) Novel antimicrobial peptides with high anticancer activity and selectivity. PLoS One 10:e0126390. doi: 10.1371/journal.pone.0126390 CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Okumura K, Itoh A, Isogai E et al (2004) C-terminal domain of human CAP18 antimicrobial peptide induces apoptosis in oral squamous cell carcinoma SAS-H1 cells. Cancer Lett 212:185–194. doi: 10.1016/j.canlet.2004.04.006 CrossRefPubMedGoogle Scholar
  14. 14.
    Risso A, Braidot E, Sordano MC et al (2002) BMAP-28, an antibiotic peptide of innate immunity, induces cell death through opening of the mitochondrial permeability transition pore. Mol Cell Biol 22:1926–1935CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Lehmann J, Retz M, Sidhu SS et al (2006) Antitumor activity of the antimicrobial peptide magainin II against bladder cancer cell lines. Eur Urol 50:141–147. doi: 10.1016/j.eururo.2005.12.043 CrossRefPubMedGoogle Scholar
  16. 16.
    Hui L, Leung K (2002) Chen HM The combined effects of antibacterial peptide cecropin A and anti-cancer agents on leukemia cells. Anticancer Res 22:2811–2816PubMedGoogle Scholar
  17. 17.
    Kim S, Kim SS, Bang YJ et al (2003) In vitro activities of native and designed peptide antibiotics against drug sensitive and resistant tumor cell lines. Peptides 24:945–953CrossRefPubMedGoogle Scholar
  18. 18.
    Ohtake T, Fujimoto Y, Ikuta K et al (1999) Proline-rich antimicrobial peptide, PR-39 gene transduction altered invasive activity and actin structure in human hepatocellular carcinoma cells. Br J Cancer 81:393–403. doi: 10.1038/sj.bjc.6690707 CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Fang X-Y, Chen W, Fan J-T et al (2013) Plant cyclopeptide RA-V kills human breast cancer cells by inducing mitochondria-mediated apoptosis through blocking PDK1-AKT interaction. Toxicol Appl Pharmacol 267:95–103. doi: 10.1016/j.taap.2012.12.010 CrossRefPubMedGoogle Scholar
  20. 20.
    Cao Q, Lin Z-B (2006) Ganoderma lucidum polysaccharides peptide inhibits the growth of vascular endothelial cell and the induction of VEGF in human lung cancer cell. Life Sci 78:1457–1463. doi: 10.1016/j.lfs.2005.07.017 CrossRefPubMedGoogle Scholar
  21. 21.
    Kim SE, Kim HH, Kim JY et al (2000) Anticancer activity of hydrophobic peptides from soy proteins. Biofactors 12:151–155CrossRefPubMedGoogle Scholar
  22. 22.
    Kozłowska K, Nowak J, Kwiatkowski B, Cichorek M (1999) ESR study of plasmatic membrane of the transplantable melanoma cells in relation to their biological properties. Exp Toxicol Pathol Off J 51:89–92. doi: 10.1016/S0940-2993(99)80074-8 CrossRefGoogle Scholar
  23. 23.
    Sok M, Sentjurc M, Schara M (1999) Membrane fluidity characteristics of human lung cancer. Cancer Lett 139:215–220CrossRefPubMedGoogle Scholar
  24. 24.
    Ellerby HM, Arap W, Ellerby LM et al (1999) Anti-cancer activity of targeted pro-apoptotic peptides. Nat Med 5:1032–1038. doi: 10.1038/12469 CrossRefPubMedGoogle Scholar
  25. 25.
    Hariharan S, Gustafson D, Holden S et al (2007) Assessment of the biological and pharmacological effects of the alpha nu beta3 and alpha nu beta5 integrin receptor antagonist, cilengitide (EMD 121974), in patients with advanced solid tumors. Ann Oncol 18:1400–1407. doi: 10.1093/annonc/mdm140 CrossRefPubMedGoogle Scholar
  26. 26.
    Gregorc V, De Braud FG, De Pas TM et al (2011) Phase I study of NGR-hTNF, a selective vascular targeting agent, in combination with cisplatin in refractory solid tumors. Clin Cancer Res 17:1964–1972. doi: 10.1158/1078-0432.CCR-10-1376 CrossRefPubMedGoogle Scholar
  27. 27.
    Khalili P, Arakelian A, Chen G et al (2006) A non-RGD-based integrin binding peptide (ATN-161) blocks breast cancer growth and metastasis in vivo. Mol Cancer Ther 5:2271–2280. doi: 10.1158/1535-7163.MCT-06-0100 CrossRefPubMedGoogle Scholar
  28. 28.
    Deplanque G, Madhusudan S, Jones PH et al (2004) Phase II trial of the antiangiogenic agent IM862 in metastatic renal cell carcinoma. Br J Cancer 91:1645–1650. doi: 10.1038/sj.bjc.6602126 CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Sharma A, Kapoor P, Gautam A et al (2013) Computational approach for designing tumor homing peptides. Sci Rep 3:1607. doi: 10.1038/srep01607 CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Gupta S, Kapoor P, Chaudhary K et al (2013) In silico approach for predicting toxicity of peptides and proteins. PLoS One 8:e73957. doi: 10.1371/journal.pone.0073957 CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Gautam A, Chaudhary K, Kumar R et al (2013) In silico approaches for designing highly effective cell penetrating peptides. J Transl Med 11:74. doi: 10.1186/1479-5876-11-74 CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Sharma A, Singla D, Rashid M, Raghava GPS (2014) Designing of peptides with desired half-life in intestine-like environment. BMC Bioinformatics 15:282. doi: 10.1186/1471-2105-15-282 CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Kumar R, Chaudhary K, Singh Chauhan J et al (2015) An in silico platform for predicting, screening and designing of antihypertensive peptides. Sci Rep 5:12512. doi: 10.1038/srep12512 CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Tyagi A, Kapoor P, Kumar R et al (2013) In silico models for designing and discovering novel anticancer peptides. Sci Rep 3:2984. doi: 10.1038/srep02984 CrossRefPubMedGoogle Scholar
  35. 35.
    Vijayakumar S, PTV L (2014) ACPP: a Web server for prediction and design of anti-cancer peptides. Int J Pept Res Ther 21:99–106. doi: 10.1007/s10989-014-9435-7 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Department of Pathology, School of MedicineUniversity of VirginiaCharlottesvilleUSA
  2. 2.Department of Biochemistry and Molecular Genetics, School of MedicineUniversity of VirginiaCharlottesvilleUSA

Personalised recommendations