Cover Image

Prediction of Leishmania Major Key Proteins via Topological Analysis of Protein-Protein Interaction Network

Nasrin Amiri Dashatan, Mostafa Rezaie Tavirani, Hakimeh Zali, Mehdi Koushki, Nayebali Ahmadi

Background: Although leishmaniasis is regarded as a public health problem, no effective vaccine or decisive treatment has been introduced for this disease. Therefore, representing novel therapeutic proteins is essential. Protein-protein Interaction network analysis is a suitable tool to discover novel drug targets for leishmania major. To this aim, gene and protein expression data is used for instructing protein network and the key proteins are highlighted.

Materials and Methods: In this computational and bioinformatics study, the protein/gene expression data related to leishmania major were studied, and 252 candidate proteins were extracted. Then, the protein networks of these proteins were explored and visualized by using String database and Cytoscape software. Finally, clustering and gene ontology were performed by MCODE and PANTHER databases, respectively.

Results:  Based on gene ontology analysis, most of the leishmania major proteins were located in cell compartments and membrane. Catalytic activity and binding were regarded as the relevant molecular functions and metabolic and cellular processes were the significant biological process. In this network analysis, UB-EP52, EF-2, chaperonin, Hsp70.4, Hsp60, tubulin alpha and beta chain, and ENOL and LACK were introduced as hub-bottleneck proteins. Based on clustering analysis, Lmjf.32.3270, ENOL and Lmjf.13.0290 were determined as seed proteins in each cluster.

Conclusion: The results indicated that hub proteins play a significant role in pathogenesis and life cycle of leishmania major. Further studies of hubs will provide a better understanding of leishmaniasis mechanisms. Finally, these key hub proteins could be a suitable and helpful potential for drug targets and treating leishmaniasis by considering their validation. [GMJ.2018;7:e1129]

Protein Interaction Networks; Leishmaniasis; Leishmania Major; Gene Ontology; Centrality Analysis

Alvar J, Velez ID, Bern C, Herrero M, Desjeux P, Cano J, et al. Leishmaniasis worldwide and global estimates of its incidence. PloS one. 2012;7(5):e35671.

Ahmadi N, Modiri M, Mamdohi S. First survey of cutaneous leishmaniasis in Borujerd county, western Islamic Republic of Iran. East Mediterr Health J. 2013;19(10):847-53.

Kumar A, Misra P, Sisodia B, Shasany AK, Sundar S, Dube A. Proteomic analyses of membrane enriched proteins of Leishmania donovani Indian clinical isolate by mass spectrometry. Int Parasitol. 2015;64(4):36-42.

Rezende AM, Folador EL, Resende DdM, Ruiz JC. Computational prediction of protein-protein interactions in Leishmania predicted proteomes. PloS one. 2012;7(12):e51304.

Dai Y-F, Zhao X-M. A survey on the computational approaches to identify drug targets in the postgenomic era. Biomed Res Int. 2015;2015: 239654.

Keyvani H, Ahmadi NA, Ranjbar MM, Kachooei SA, Ghorban K, Dadmanesh M. Immunoinformatics Study of gp120 of Human Immunodeficiency Virus Type 1 Subtype CRF35_AD Isolated from Iranian Patients. Arch Clin Infect Dis. 2016;11(4): e36270.

Rezaei-Tavirani M, Rezaei-Taviran S, Mansouri M, Rostami-Nejad M, Rezaei-Tavirani M. Protein-Protein Interaction Network Analysis for a Biomarker Panel Related to Human Esophageal Adenocarcinoma. Asian Pac J Cancer Prev. 2017;18(12):3357-63.

Vaseghi Maghvan P, Rezaei-Tavirani M, Zali H, Nikzamir A, Abdi S, Khodadoostan M, et al. Network analysis of common genes related to esophageal, gastric, and colon cancers. Gastroenterol Hepatol Bed Bench. 2017;10(4):295-302.

Segura-Cabrera A, García-Pérez CA, Rodríguez-Pérez MA, Guo X, Rivera G, Bocanegra-García V. Analysis of protein interaction networks to prioritize drug targets of neglected-diseases pathogens. JMCDD. InTech; 2012.

Jeong H, Mason SP, Barabási A-L, Oltvai ZN. Lethality and centrality in protein networks. Nature. 2001;411(6833):41-2.

Walker J, Gongora R, Vasquez J-J, Drummelsmith J, Burchmore R, Roy G, et al. Discovery of factors linked to antimony resistance in Leishmania panamensis through differential proteome analysis. Mol Biochem Parasitol. 2012;183(2):166-76.

Alizadeh R, Hooshyar H, Bandehpor M, Arbabi M, Kazemi F, Talari A, et al. Detection of drug resistance gene in cutaneous leishmaniasis by PCR in some endemic areas of iran. Iran Red Crescent Med J. 2011;13(12):863-7.

Atan NAD, Yekta RF, Nejad MR, Nikzamir A. Pathway and Network Analysis in Primary Open Angle Glaucoma. J Paramed Sci. 2014;5(3):92-101.

Safari-Alighiarloo N, Rezaei-Tavirani M, Taghizadeh M, Tabatabaei SM, Namaki S. Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis. PeerJ. 2016;4:e2775.

Safaei A, Rezaei Tavirani M, Arefi Oskouei A, Zamanian Azodi M, Mohebbi SR, Nikzamir AR. Protein-protein interaction network analysis of cirrhosis liver disease. Gastroenterol Hepatol Bed Bench. 2016;9(2):114-23.

Florez AF, Park D, Bhak J, Kim BC, Kuchinsky A, Morris JH, et al. Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection. BMC Bioinformatics. 2010;11:484.

Bhattacharyya M, Chakrabarti S. Identification of important interacting proteins (IIPs) in Plasmodium falciparum using large-scale interaction network analysis and in-silico knock-out studies. Malar J. 2015;14:70.

Drummelsmith J, Brochu V, Girard I, Messier N, Ouellette M. Proteome mapping of the protozoan parasite Leishmania and application to the study of drug targets and resistance mechanisms. Mol Cell Proteomics. 2003;2(3):146-55.

Hajjaran H, Bazargani MM, Mohebali M, Burchmore R, Salekdeh GH, Kazemi-Rad E, et al. Comparison of the Proteome Profiling of Iranian isolates of Leishmania tropica, L. major and L. infantum by Two-Dimensional Electrophoresis (2-DE) and Mass-spectrometry. Iran J Parasitol. 2015;10(4):530-40.

Mojtahedi Z, Clos J, Kamali-Sarvestani E. Leishmania major: identification of developmentally regulated proteins in procyclic and metacyclic promastigotes. Exp Parasitol. 2008;119(3):422-9.

Dillon LA, Okrah K, Hughitt VK, Suresh R, Li Y, Fernandes MC et al. Transcriptomic profiling of gene expression and RNA processing during Leishmania major differentiation. Nucleic acids Res. 2015;43(14):6799-813.

Leifso K, Cohen-Freue G, Dogra N, Murray A, McMaster WR. Genomic and proteomic expression analysis of Leishmania promastigote and amastigote life stages: the Leishmania genome is constitutively expressed. Mol Biochem Parasitol. 2007;152(1):35-46.

Mi H, Muruganujan A, Thomas PD. PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees. Nucleic acids Res. 2012;41(D1):D377-D86.

Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P et al. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic acids Res. 2010;39(suppl_1):D561-D8.

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498-504.

Albert R. Scale-free networks in cell biology. J Cell Sci. 2005;118(21):4947-57.

Ficenec D, Osborne M, Pradines J, Richards D, Felciano R, Cho RJ et al. Computational knowledge integration in biopharmaceutical research. Brief Bioinform. 2003;4(3):260-78.

Gursoy A, Keskin O, Nussinov R. Topological properties of protein interaction networks from a structural perspective. Biochem Soc Trans; 2008;36(Pt 6):1398-403.

Gupta SK, Sisodia BS, Sinha S, Hajela K, Naik S, Shasany AK et al. Proteomic approach for identification and characterization of novel immunostimulatory proteins from soluble antigens of Leishmania donovani promastigotes. Proteomics. 2007;7(5):816-23.

Requena JM, Montalvo AM, Fraga J. Molecular chaperones of Leishmania: central players in many stress-related and-unrelated physiological processes. Biomed Res Int. 2015;2015:301326.

Vonlaufen N, Kanzok SM, Wek RC, Sullivan Jr WJ. Stress response pathways in protozoan parasites. Cell Microbiol. 2008;10(12):2387-99.

Rosenzweig D, Smith D, Opperdoes F, Stern S, Olafson RW, Zilberstein D. Retooling Leishmania metabolism: from sand fly gut to human macrophage. T The FASEB J. 2008;22(2):590-602.

Zamora-Veyl FB, Kroemer M, Zander D, Clos J. Stage-specific expression of the mitochondrial co-chaperonin of Leishmania donovani, CPN10. Kinetoplastid Biol Dis. 2005;4(1):3.

Soto M, Ramírez L, Pineda MA, González VM, Entringer PF, de Oliveira CI et al. Searching genes encoding Leishmania antigens for diagnosis and protection. Scholarly Res Exch. 2009;2009:173039.

Hombach A, Ommen G, Chrobak M, Clos J. The Hsp90–Sti1 interaction is critical for Leishmania donovani proliferation in both life cycle stages. Cell Microbiol. 2013;15(4):585-600.

Avilán L, Gualdrón-López M, Quiñones W, González-González L, Hannaert V, Michels PA et al. Enolase: a key player in the metabolism and a probable virulence factor of trypanosomatid parasites—perspectives for its use as a therapeutic target. Enzyme Res. 2011;2011:932549.

Launois P, Pingel S, Himmelrich H, Locksley R, Louis J. Different epitopes of the LACK protein are recognized by Vβ4 Vα8 CD4+ T cells in H-2 b and H-2 d mice susceptible to Leishmania major. Microbes Infect. 2007;9(11):1260-6.

Kelly BL, Stetson DB, Locksley RM. Leishmania major LACK antigen is required for efficient vertebrate parasitization. J Exp Med. 2003;198(11):1689-98.

Havens CG, Bryant N, Asher L, Lamoreaux L, Perfetto S, Brendle JJ et al. Cellular effects of leishmanial tubulin inhibitors on L. donovani. Mol Biochem Parasitol. 2000;110(2):223-36.


  • There are currently no refbacks.