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Current Proteomics

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ISSN (Print): 1570-1646
ISSN (Online): 1875-6247

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Research Article

Developing Multi-epitope Antigen Construct from Immunodominant Proteins for Serological Diagnosis of Chlamydia trachomatis: An In Silico Approach

Author(s): Farideh Ghalamfarsa, Amir Savardashtaki, Cambyz Irajie, Amir Emami, Navid Nezafat* and Younes Ghasemi*

Volume 20, Issue 2, 2023

Published on: 27 October, 2023

Page: [91 - 106] Pages: 16

DOI: 10.2174/0115701646244648231014153217

Price: $65

Abstract

Background: Chlamydiasis is a widespread bacterial infection in the world. Serological tests are expensive, and in addition, intrinsic antigens can cause cross-reactions and make the diagnosis process difficult. Multi-epitope protein antigens are novel and potential diagnostic markers that have the capability of more accurate and cheaper diagnosis. Therefore, in this study, the main goal is to design a new protein vaccine, including multiple epitopes of B cells with dominant immunity from three proteins named MOMP, ompA and Pgp3D from C. trachomatis.

Methods: The amino acid sequences were obtained from the UniProt database. The areas with the highest antigenicity were identified using the EMBOSS server. Linear B cell epitopes were determined using BCPRED, ABCpred, and Bepipred servers. Epitopes with the highest antigenicity were connected using the EAAAK linker.

Results: Two epitopes from MOMP, two from ompA, and one from Pgp3D were selected. These epitopes were connected to each other with the EAAAK linker. Three residues (0.592), 16 residues (0.76), 36 residues (0.578), and 37 residues (0.734) were obtained from the prediction of the spatial structure of the B cell multiple epitopes designed with ElliPro. Model 1 of RaptorX was selected as the best structure. In this model, the ERRAT quality, ProSA-web z-score, and Verify3D were 83.1169, - 5.17 and 84.62% with PASS score, respectively. Moreover, the Ramachandran plot showed that 86.093% of the amino acid residues were located in the favored region. To achieve the highest level of protein expression, the designed multi-epitope reverse-translated with the Genscript server and was cloned in E. coli. The highest level of expression was achieved, and a CAI score of 0.91 was reported. The gene GC content was 51.98%, and the contribution of low-frequency codons was 0%.

Conclusion: The results confirmed that the designed construct could identify C. trachomatis with high sensitivity and specificity in serum samples of patients with chlamydiasis. However, further experimental studies are needed for final confirmation.

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[1]
Nguyen, B.D.; Valdivia, R.H. Virulence determinants in the obligate intracellular pathogen Chlamydia trachomatis revealed by forward genetic approaches. Proc. Natl. Acad. Sci., 2012, 109(4), 1263-1268.
[http://dx.doi.org/10.1073/pnas.1117884109] [PMID: 22232666]
[2]
Shimano, S.; Mariya, T.; Saito, T. Increased cervical Chlamydia trachomatis and syphilis infections in Japanese females of reproductive age in the late 2010s: Possible cause. J. Infect. Chemother., 2021, 27(10), 1529-1532.
[http://dx.doi.org/10.1016/j.jiac.2021.05.015] [PMID: 34078564]
[3]
Borges, V.; Cordeiro, D.; Salas, A.I.; Lodhia, Z.; Correia, C.; Isidro, J.; Fernandes, C.; Rodrigues, A.M.; Azevedo, J.; Alves, J.; Roxo, J.; Rocha, M.; Côrte-Real, R.; Vieira, L.; Borrego, M.J.; Gomes, J.P. Chlamydia trachomatis: when the virulence-associated genome backbone imports a prevalence-associated major antigen signature. Microb. Genom., 2019, 5(11), e000313.
[http://dx.doi.org/10.1099/mgen.0.000313] [PMID: 31697227]
[4]
Aslam, S.; Ahmad, S.; Noor, F.; Ashfaq, U.A.; Shahid, F.; Rehman, A. Tahir ul Qamar, M.; Alatawi, E.A.; Alshabrmi, F.M.; Allemailem, K.S. Designing a multi-epitope vaccine against Chlamydia trachomatis by employing integrated core proteomics, immuno-informatics and in silico approaches. Biology, 2021, 10(10), 997.
[http://dx.doi.org/10.3390/biology10100997] [PMID: 34681096]
[5]
Deluca, G.D.; Basiletti, J.; Schelover, E.; Vásquez, N.D.; Alonso, J.M.; Marín, H.M.; Lucero, R.H.; Picconi, M.A. Chlamydia trachomatis as a probable cofactor in human papillomavirus infection in aboriginal women from northeastern Argentina. Braz. J. Infect. Dis., 2011, 15(6), 567-572.
[http://dx.doi.org/10.1590/S1413-86702011000600011] [PMID: 22218516]
[6]
Shiragannavar, S.; Madagi, S.; Hosakeri, J.; Barot, V. In silico vaccine design against Chlamydia trachomatis infection. Netw. Model. Anal. Health Inform. Bioinform., 2020, 9(1), 39.
[http://dx.doi.org/10.1007/s13721-020-00243-w] [PMID: 32537381]
[7]
Byrne, G.I. Chlamydia trachomatis strains and virulence: Rethinking links to infection prevalence and disease severity. J. Infect. Dis., 2010, 201(S2), 126-133.
[http://dx.doi.org/10.1086/652398] [PMID: 20470049]
[8]
Mylonas, I. Female genital Chlamydia trachomatis infection: Where are we heading? Arch. Gynecol. Obstet., 2012, 285(5), 1271-1285.
[http://dx.doi.org/10.1007/s00404-012-2240-7] [PMID: 22350326]
[9]
Banoo, S.; Bell, D.; Bossuyt, P.; Herring, A.; Mabey, D.; Poole, F.; Smith, P.G.; Sriram, N.; Wongsrichanalai, C.; Linke, R.; O’Brien, R.; Perkins, M.; Cunningham, J.; Matsoso, P.; Nathanson, C.M.; Olliaro, P.; Peeling, R.W.; Ramsay, A. Evaluation of diagnostic tests for infectious diseases: General principles. Nat. Rev. Microbiol., 2006, 4(S9), S21-S31.
[http://dx.doi.org/10.1038/nrmicro1523] [PMID: 17034069]
[10]
Akande, V.; Turner, C.; Horner, P.; Horne, A.; Pacey, A. Impact of Chlamydia trachomatis in the reproductive setting: British Fertility Society Guidelines for practice. Hum. Fertil., 2010, 13(3), 115-125.
[http://dx.doi.org/10.3109/14647273.2010.513893] [PMID: 20849196]
[11]
Rahimi, H.; Salehiabar, M.; Barsbay, M.; Ghaffarlou, M.; Kavetskyy, T.; Sharafi, A.; Davaran, S.; Chauhan, S.C.; Danafar, H.; Kaboli, S.; Nosrati, H.; Yallapu, M.M.; Conde, J. CRISPR systems for COVID-19 diagnosis. ACS Sens., 2021, 6(4), 1430-1445.
[http://dx.doi.org/10.1021/acssensors.0c02312] [PMID: 33502175]
[12]
Muvunyi, C.; Claeys, L.; De Sutter, T.; De Sutter, P.; Temmerman, M.; Van Renterghem, L.; Claeys, G.; Padalko, E. Comparison of four serological assays for the diagnosis of Chlamydia trachomatis in subfertile women. J. Infect. Dev. Ctries., 2011, 6(5), 396-402.
[http://dx.doi.org/10.3855/jidc.1740] [PMID: 22610705]
[13]
Puolakkainen, M. Laboratory diagnosis of persistent human chlamydial infection. Front. Cell. Infect. Microbiol., 2013, 3, 99.
[http://dx.doi.org/10.3389/fcimb.2013.00099] [PMID: 24381934]
[14]
Rahman, K.S. Discovery of human-specific immunodominant Chlamydia trachomatis B cell epitopes. MSphere, 2018, 3(4), e00246-e00218.
[http://dx.doi.org/10.1128/mSphere.00246-18]
[15]
Rahman, K.S.; Kaltenboeck, B. Multi-peptide ELISAs overcome cross-reactivity and inadequate sensitivity of conventional Chlamydia pneumoniae serology. Sci. Rep., 2019, 9(1), 15078.
[http://dx.doi.org/10.1038/s41598-019-51501-5] [PMID: 31636331]
[16]
Hunt, I. From gene to protein: A review of new and enabling technologies for multi-parallel protein expression. Protein Expr. Purif., 2005, 40(1), 1-22.
[http://dx.doi.org/10.1016/j.pep.2004.10.018] [PMID: 15721767]
[17]
Baud, D.; Regan, L.; Greub, G. Comparison of five commercial serological tests for the detection of anti-Chlamydia trachomatis antibodies. Eur. J. Clin. Microbiol. Infect. Dis., 2010, 29(6), 669-675.
[http://dx.doi.org/10.1007/s10096-010-0912-4] [PMID: 20349260]
[18]
Forsbach-Birk, V.; Simnacher, U.; Pfrepper, K.I.; Soutschek, E.; Kiselev, A.O.; Lampe, M.F.; Meyer, T.; Straube, E.; Essig, A. Identification and evaluation of a combination of chlamydial antigens to support the diagnosis of severe and invasive Chlamydia trachomatis infections. Clin. Microbiol. Infect., 2010, 16(8), 1237-1244.
[http://dx.doi.org/10.1111/j.1469-0691.2009.03041.x] [PMID: 19723133]
[19]
Bas, S.; Muzzin, P.; Vischer, T.L. Chlamydia trachomatis serology: Diagnostic value of outer membrane protein 2 compared with that of other antigens. J. Clin. Microbiol., 2001, 39(11), 4082-4085.
[http://dx.doi.org/10.1128/JCM.39.11.4082-4085.2001] [PMID: 11682533]
[20]
Betsou, F.; Sueur, J.M.; Orfila, J. Serological investigation of Chlamydia trachomatis heat shock protein 10. Infect. Immun., 1999, 67(10), 5243-5246.
[http://dx.doi.org/10.1128/IAI.67.10.5243-5246.1999] [PMID: 10496901]
[21]
den Hartog, J.E.; Land, J.A.; Stassen, F.R.M.; Kessels, A.G.H.; Bruggeman, C.A. Serological markers of persistent C. trachomatis infections in women with tubal factor subfertility. Hum. Reprod., 2005, 20(4), 986-990.
[http://dx.doi.org/10.1093/humrep/deh710] [PMID: 15640255]
[22]
Igietseme, J.U.; Murdin, A. Induction of protective immunity against Chlamydia trachomatis genital infection by a vaccine based on major outer membrane protein-lipophilic immune response-stimulating complexes. Infect. Immun., 2000, 68(12), 6798-6806.
[http://dx.doi.org/10.1128/IAI.68.12.6798-6806.2000] [PMID: 11083798]
[23]
Nunes, A.; Borrego, M.J.; Nunes, B.; Florindo, C.; Gomes, J.P. Evolutionary dynamics of ompA, the gene encoding the Chlamydia trachomatis key antigen. J. Bacteriol., 2009, 191(23), 7182-7192.
[http://dx.doi.org/10.1128/JB.00895-09] [PMID: 19783629]
[24]
Wills, G.S.; Horner, P.J.; Reynolds, R.; Johnson, A.M.; Muir, D.A.; Brown, D.W.; Winston, A.; Broadbent, A.J.; Parker, D.; McClure, M.O. Pgp3 antibody enzyme-linked immunosorbent assay, a sensitive and specific assay for seroepidemiological analysis of Chlamydia trachomatis infection. Clin. Vaccine Immunol., 2009, 16(6), 835-843.
[http://dx.doi.org/10.1128/CVI.00021-09] [PMID: 19357314]
[25]
Siegl, C. Degradation of Tumour Suppressor p53 during Chlamydia trachomatis Infections; Universität Würzburg, 2014.
[26]
Brunham, R.; Yang, C.; Maclean, I.; Kimani, J.; Maitha, G.; Plummer, F. Chlamydia trachomatis from individuals in a sexually transmitted disease core group exhibit frequent sequence variation in the major outer membrane protein (omp1) gene. J. Clin. Invest., 1994, 94(1), 458-463.
[http://dx.doi.org/10.1172/JCI117347] [PMID: 8040290]
[27]
Goodall, J.C.; Beacock-Sharp, H.; Deane, K.H.O.; Gaston, J.S.H. Recognition of the 60 kilodalton cysteine-rich outer membrane protein OMP2 by CD4+ T cells from humans infected with Chlamydia trachomatis. Clin. Exp. Immunol., 2002, 126(3), 488-493.
[http://dx.doi.org/10.1046/j.1365-2249.2001.01709.x] [PMID: 11737067]
[28]
Confer, A.W.; Ayalew, S. The OmpA family of proteins: Roles in bacterial pathogenesis and immunity. Vet. Microbiol., 2013, 163(3-4), 207-222.
[http://dx.doi.org/10.1016/j.vetmic.2012.08.019] [PMID: 22986056]
[29]
Peeling, R.W.; Wang, S.P.; Grayston, J.T.; Blasi, F.; Boman, J.; Clad, A.; Freidank, H.; Gaydos, C.A.; Gnarpe, J.; Hagiwara, T.; Jones, R.B.; Orfila, J.; Persson, K.; Puolakkainen, M.; Saikku, P.; Schachter, J. Chlamydia pneumoniae serology: Interlaboratory variation in microimmunofluorescence assay results. J. Infect. Dis., 2000, 181(S3), S426-S429.
[http://dx.doi.org/10.1086/315603] [PMID: 10839729]
[30]
Comanducci, M.; Ricci, S.; Cevenini, R.; Ratti, G. Diversity of the Chlamydia trachomatis common plasmid in biovars with different pathogenicity. Plasmid, 1990, 23(2), 149-154.
[http://dx.doi.org/10.1016/0147-619X(90)90034-A] [PMID: 2194229]
[31]
Liu, Y.; Huang, Y.; Yang, Z.; Sun, Y.; Gong, S.; Hou, S.; Chen, C.; Li, Z.; Liu, Q.; Wu, Y.; Baseman, J.; Zhong, G. Plasmid-encoded Pgp3 is a major virulence factor for Chlamydia muridarum to induce hydrosalpinx in mice. Infect. Immun., 2014, 82(12), 5327-5335.
[http://dx.doi.org/10.1128/IAI.02576-14] [PMID: 25287930]
[32]
Woodhall, S.C.; Wills, G.S.; Horner, P.J.; Craig, R.; Mindell, J.S.; Murphy, G.; McClure, M.O.; Soldan, K.; Nardone, A.; Johnson, A.M. Chlamydia trachomatis Pgp3 antibody population Seroprevalence before and during an era of widespread opportunistic chlamydia screening in England (1994-2012). PLoS One, 2017, 12(1), e0152810.
[http://dx.doi.org/10.1371/journal.pone.0152810] [PMID: 28129328]
[33]
Myers, G.S.A.; Mathews, S.A.; Eppinger, M.; Mitchell, C.; O’Brien, K.K.; White, O.R.; Benahmed, F.; Brunham, R.C.; Read, T.D.; Ravel, J.; Bavoil, P.M.; Timms, P. Evidence that human Chlamydia pneumoniae was zoonotically acquired. J. Bacteriol., 2009, 191(23), 7225-7233.
[http://dx.doi.org/10.1128/JB.00746-09] [PMID: 19749045]
[34]
Baxevanis, A.D.; Bader, G.D.; Wishart, D.S. Bioinformatics; John Wiley & Sons, 2020.
[35]
Ranjbar, M.M.; Ebrahimi, M.M.; Shahsavandi, S.; Farhadi, T.; Mirjalili, A.; Tebianian, M.; Motedayen, M.H. Novel applications of immuno-bioinformatics in vaccine and bio-product developments at research institutes. Arch. Razi Inst., 2019, 74(3), 219-233.
[PMID: 31592587]
[36]
Fereig, R.M.; Metwally, S.; El-Alfy, E.S.; Abdelbaky, H.H.; Shanab, O.; Omar, M.A.; Alsayeqh, A.F. High relatedness of bioinformatic data and realistic experimental works on the potentials of Fasciola hepatica and F. gigantica cathepsin L1 as a diagnostic and vaccine antigen. Front. Public Health, 2022, 10, 1054502.
[http://dx.doi.org/10.3389/fpubh.2022.1054502] [PMID: 36568750]
[37]
Jimenez-Vasquez, V.; Calvay-Sanchez, K.D.; Zarate-Sulca, Y.; Mendoza-Mujica, G. In-silico identification of linear B-cell epitopes in specific proteins of Bartonella bacilliformis for the serological diagnosis of Carrion’s disease. PLoS Negl. Trop. Dis., 2023, 17(5), e0011321.
[http://dx.doi.org/10.1371/journal.pntd.0011321] [PMID: 37228134]
[38]
Yao, B. SVMTriP: A method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity. PLoS One, 2012, 7(9), e45152.
[http://dx.doi.org/10.1371/journal.pone.0045152]
[39]
Singh, H.; Ansari, H.R.; Raghava, G.P.S. Improved method for linear B-cell epitope prediction using antigen’s primary sequence. PLoS One, 2013, 8(5), e62216.
[http://dx.doi.org/10.1371/journal.pone.0062216] [PMID: 23667458]
[40]
Jespersen, M.C.; Peters, B.; Nielsen, M.; Marcatili, P. BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res., 2017, 45(W1), W24-W29.
[http://dx.doi.org/10.1093/nar/gkx346] [PMID: 28472356]
[41]
Saha, S.; Raghava, G.P.S. BcePred: Prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties. International conference on artificial immune systems, 2004.
[http://dx.doi.org/10.1007/978-3-540-30220-9_16]
[42]
EL-Manzalawy. Y.; Dobbs, D.; Honavar, V. Predicting linear B‐cell epitopes using string kernels. J. Mol. Recognit., 2008, 21(4), 243-255.
[http://dx.doi.org/10.1002/jmr.893]
[43]
Saha, S.; Raghava, G.P.S. Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins, 2006, 65(1), 40-48.
[http://dx.doi.org/10.1002/prot.21078] [PMID: 16894596]
[44]
Mehrpour, K.; Mirzaei, S.A.; Savardashtaki, A.; Nezafat, N.; Ghasemi, Y. Designing an HCV diagnostic kit for common genotypes of the virus in Iran based on conserved regions of core, NS3-protease, NS4A/B, and NS5A/B antigens: An in silico approach. Biologia, 2021, 76(1), 281-296.
[http://dx.doi.org/10.2478/s11756-020-00566-z]
[45]
Haste Andersen, P.; Nielsen, M.; Lund, O. Prediction of residues in discontinuous B-cell epitopes using protein 3D structures. Protein Sci., 2006, 15(11), 2558-2567.
[http://dx.doi.org/10.1110/ps.062405906] [PMID: 17001032]
[46]
Dorosti, H.; Eslami, M.; Negahdaripour, M.; Ghoshoon, M.B.; Gholami, A.; Heidari, R.; Dehshahri, A.; Erfani, N.; Nezafat, N.; Ghasemi, Y. Vaccinomics approach for developing multi-epitope peptide pneumococcal vaccine. J. Biomol. Struct. Dyn., 2019, 37(13), 3524-3535.
[http://dx.doi.org/10.1080/07391102.2018.1519460] [PMID: 30634893]
[47]
Galanis, K.A.; Nastou, K.C.; Papandreou, N.C.; Petichakis, G.N.; Pigis, D.G.; Iconomidou, V.A. Linear B-cell epitope prediction for in silico vaccine design: A performance review of methods available via command-line interface. Int. J. Mol. Sci., 2021, 22(6), 3210.
[http://dx.doi.org/10.3390/ijms22063210] [PMID: 33809918]
[48]
Dehghani, B.; Hashempour, T.; Hasanshahi, Z. Using immunoinformatics and structural approaches to design a novel HHV8 vaccine. Int. J. Pept. Res. Ther., 2020, 26(1), 321-331.
[http://dx.doi.org/10.1007/s10989-019-09839-x] [PMID: 32435167]
[49]
Adhikari, U.K.; Tayebi, M. Epitope-specific anti-PrP antibody toxicity: A comparative in-silico study of human and mouse prion proteins. Prion, 2021, 15(1), 155-176.
[http://dx.doi.org/10.1080/19336896.2021.1964326] [PMID: 34632945]
[50]
Ko, J.; Park, H.; Heo, L.; Seok, C. GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Res., 2012, 40(W1), W294-W297.
[http://dx.doi.org/10.1093/nar/gks493] [PMID: 22649060]
[51]
Abriata, L.A.; Dal Peraro, M. State-of-the-art web services for de novo protein structure prediction. Brief. Bioinform., 2021, 22(3), bbaa139.
[http://dx.doi.org/10.1093/bib/bbaa139] [PMID: 34020540]
[52]
Källberg, M. RaptorX server: A resource for template-based protein structure modeling. Protein structure prediction; Springer, 2014, pp. 17-27.
[http://dx.doi.org/10.1007/978-1-4939-0366-5_2]
[53]
Peng, J.; Xu, J. Raptorx: Exploiting structure information for protein alignment by statistical inference. Proteins, 2011, 79(S10), 161-171.
[http://dx.doi.org/10.1002/prot.23175] [PMID: 21987485]
[54]
Hegedűs, T. AlphaFold2 transmembrane protein structure prediction shines. bioRxiv, 2021.
[55]
Millán, C.; Keegan, R.M.; Pereira, J.; Sammito, M.D.; Simpkin, A.J.; McCoy, A.J.; Lupas, A.N.; Hartmann, M.D.; Rigden, D.J.; Read, R.J. Assessing the utility of CASP14 models for molecular replacement. Proteins, 2021, 89(12), 1752-1769.
[http://dx.doi.org/10.1002/prot.26214] [PMID: 34387010]
[56]
Wiederstein, M.; Sippl, M.J. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res., 2007, 35(S2), W407-W410.
[http://dx.doi.org/10.1093/nar/gkm290] [PMID: 17517781]
[57]
Ji, Y.Y.; Li, Y.Q. The role of secondary structure in protein structure selection. Eur. Phys. J. E, 2010, 32(1), 103-107.
[http://dx.doi.org/10.1140/epje/i2010-10591-5] [PMID: 20524028]
[58]
Santra, D.; Banerjee, A.; Maiti, S. Better binding informatics of delta variants (B.1.617.2) with ACE2 than wild, D614G or N501Y CoV-2 is fully blocked by 84 amino-acid cut of wild spike. Informatics in Medicine Unlocked, 2022, 29, 100900.
[http://dx.doi.org/10.1016/j.imu.2022.100900]
[59]
Kumar, S. Mobashar, HUTF; Khurshid, A. Computational analysis of protein-protein interactions in motile t-cell. Methods Mol. Biol., 2019, 1930, 149-156.
[http://dx.doi.org/10.1007/978-1-4939-9036-8_18]
[60]
Goyal, M.; Chauhan, S.; Kumar, P. In silico analysis, structural modeling and phylogenetic analysis of EPSP synthase of Phaseolus vulgaris. Agric. Sci. Dig., 2017, 37(3), 185-190.
[http://dx.doi.org/10.18805/asd.v37i03.8986]
[61]
Tuli, H.S. in silico evaluation of harmane & palmarin as α-Glucosidase inhibitors: Hope for the discovery of anti-hyperglycemic compounds. Int. J. Pharm. Res., 2020, 12, 1331-1336.
[62]
Alom, M.W.; Shehab, M.N.; Sujon, K.M.; Akter, F.; Exploring, E. NS3, and NS5 proteins to design a novel multi-epitope vaccine candidate against West Nile Virus: An in-silico approach. Informatics in Medicine Unlocked, 2021, 25, 100644.
[http://dx.doi.org/10.1016/j.imu.2021.100644]
[63]
Puigbò, P.; Guzmán, E.; Romeu, A.; Garcia-Vallvé, S. OPTIMIZER: a web server for optimizing the codon usage of DNA sequences. Nucleic Acids Res., 2007, 35(S2), W126-W131.
[http://dx.doi.org/10.1093/nar/gkm219] [PMID: 17439967]
[64]
Haridhasapavalan, K.K.; Sundaravadivelu, P.K.; Thummer, R.P. Codon optimization, cloning, expression, purification, and secondary structure determination of human ETS2 transcription factor. Mol. Biotechnol., 2020, 62(10), 485-494.
[http://dx.doi.org/10.1007/s12033-020-00266-8] [PMID: 32808171]
[65]
Eisenstein, M. Artificial intelligence powers protein-folding predictions. Nature, 2021, 599(7886), 706-708.
[http://dx.doi.org/10.1038/d41586-021-03499-y]
[66]
Pak, M.A.; Markhieva, K.A.; Novikova, M.S.; Petrov, D.S.; Vorobyev, I.S.; Maksimova, E.S.; Kondrashov, F.A.; Ivankov, D.N. Using AlphaFold to predict the impact of single mutations on protein stability and function. PLoS One, 2023, 18(3), e0282689.
[http://dx.doi.org/10.1371/journal.pone.0282689] [PMID: 36928239]
[67]
Gonzales, G.F.; Muñoz, G.; Sánchez, R.; Henkel, R.; Gallegos-Avila, G.; Díaz-Gutierrez, O.; Vigil, P.; Vásquez, F.; Kortebani, G.; Mazzolli, A.; Bustos-Obregón, E. Update on the impact of Chlamydia trachomatis infection on male fertility. Andrologia, 2004, 36(1), 1-23.
[http://dx.doi.org/10.1046/j.0303-4569.2003.00594.x] [PMID: 14871260]
[68]
Peng, L.; Chen, J.L.; Wang, D. Progress and perspectives in point of care testing for urogenital chlamydia trachomatis infection: A review. Med. Sci. Monit., 2020, 26, e920873-e1.
[http://dx.doi.org/10.12659/MSM.920873] [PMID: 32298243]
[69]
Galdino, A.S.; José, C.S.; Marilen, Q.S. A novel structurally stable multiepitope protein for detection of HCV. Hepat. Res. Treat., 2016, 2016, 6592143.
[http://dx.doi.org/10.1155/2016/6592143]
[70]
Thomasini, R.L.; Souza, H.G.A.; Bruna-Romero, O.; Totola, A.H.; Gonçales, N.S.L.; Lima, C.X.; Teixeira, M.M. Evaluation of a recombinant multiepitope antigen for diagnosis of hepatitis C virus: A lower cost alternative for antigen production. J. Clin. Lab. Anal., 2018, 32(6), e22410.
[http://dx.doi.org/10.1002/jcla.22410] [PMID: 29453831]
[71]
de Haro-Cruz, M.J.; Guadarrama-Macedo, S.I.; López-Hurtado, M.; Escobedo-Guerra, M.R.; Guerra-Infante, F.M. Obtaining an ELISA test based on a recombinant protein of Chlamydia trachomatis. Int. Microbiol., 2019, 22(4), 471-478.
[http://dx.doi.org/10.1007/s10123-019-00074-4] [PMID: 30976995]
[72]
Frikha-Gargouri, O.; Gdoura, R.; Znazen, A.; Gargouri, B.; Gargouri, J.; Rebai, A.; Hammami, A. Evaluation of an in silico predicted specific and immunogenic antigen from the OmcB protein for the serodiagnosis of Chlamydia trachomatis infections. BMC Microbiol., 2008, 8(1), 217.
[http://dx.doi.org/10.1186/1471-2180-8-217] [PMID: 19077181]
[73]
Kaur, H.; Dize, L.; Munoz, B.; Gaydos, C.; West, S.K. Evaluation of the reproducibility of a serological test for antibodies to Chlamydia trachomatis pgp3: A potential surveillance tool for trachoma programs. J. Microbiol. Methods, 2018, 147, 56-58.
[http://dx.doi.org/10.1016/j.mimet.2018.02.017] [PMID: 29501689]
[74]
Rahman, K.S.; Kaltenboeck, B. Multi-peptide ELISAS overcome cross-reactivity and inadequate sensitivity of chlamydia trachomatis and C. pneumoniae serology; BMJ Publishing Group Ltd., 2019, p. 855.
[75]
Rahman, K.S. Comprehensive molecular serology of human Chlamydia trachomatis infections by peptide enzyme-linked immunosorbent assays. MSphere, 2018, 3(4)
[http://dx.doi.org/10.1128/mSphere.00253-18]
[76]
Mehmood, M.A.; Sehar, U.; Ahmad, N. Use of bioinformatics tools in different spheres of life sciences. J. Data Mining Genomics Proteomics, 2014, 5(2), 1.
[77]
Huang, W.L.; Tsai, M.J.; Hsu, K.T.; Wang, J.R.; Chen, Y.H.; Ho, S.Y. Prediction of linear B-cell epitopes of hepatitis C virus for vaccine development. BMC Med. Genomics, 2015, 8(S4), S3.
[http://dx.doi.org/10.1186/1755-8794-8-S4-S3] [PMID: 26680271]
[78]
Vakili, B.; Eslami, M.; Hatam, G.R.; Zare, B.; Erfani, N.; Nezafat, N.; Ghasemi, Y. Immunoinformatics-aided design of a potential multi-epitope peptide vaccine against Leishmania infantum. Int. J. Biol. Macromol., 2018, 120(Pt A), 1127-1139.
[http://dx.doi.org/10.1016/j.ijbiomac.2018.08.125] [PMID: 30172806]
[79]
Söllner, J.; Mayer, B. Machine learning approaches for prediction of linear B-cell epitopes on proteins. J. Mol. Recognit., 2006, 19(3), 200-208.
[http://dx.doi.org/10.1002/jmr.771] [PMID: 16598694]
[80]
Rahman, K.S. Mixed Chlamydia trachomatis peptide antigens provide a specific and sensitive single-well colorimetric enzyme-linked immunosorbent assay for detection of human anti-C. trachomatis antibodies. MSphere, 2018, 3(6)
[81]
Li, Z.; Chen, C.; Chen, D.; Wu, Y.; Zhong, Y.; Zhong, G. Characterization of fifty putative inclusion membrane proteins encoded in the Chlamydia trachomatis genome. Infect. Immun., 2008, 76(6), 2746-2757.
[http://dx.doi.org/10.1128/IAI.00010-08] [PMID: 18391011]
[82]
Wang, J.; Zhang, Y.; Lu, C.; Lei, L.; Yu, P.; Zhong, G. A genome-wide profiling of the humoral immune response to Chlamydia trachomatis infection reveals vaccine candidate antigens expressed in humans. J. Immunol., 2010, 185(3), 1670-1680.
[http://dx.doi.org/10.4049/jimmunol.1001240] [PMID: 20581152]
[83]
Reddy Chichili, V.P.; Kumar, V.; Sivaraman, J. Linkers in the structural biology of protein–protein interactions. Protein Sci., 2013, 22(2), 153-167.
[http://dx.doi.org/10.1002/pro.2206] [PMID: 23225024]
[84]
Lee, M.; Bang, K.; Kwon, H.; Cho, S. Enhanced antibacterial activity of an attacin-coleoptericin hybrid protein fused with a helical linker. Mol. Biol. Rep., 2013, 40(6), 3953-3960.
[http://dx.doi.org/10.1007/s11033-012-2472-4] [PMID: 23271135]
[85]
Chen, X.; Zaro, J.; Shen, W.C. Fusion protein linkers: Effects on production, bioactivity, and pharmacokinetics. In: Fusion protein technologies for biopharmaceuticals: applications and challenges; , 2013; p. 57-73.
[http://dx.doi.org/10.1002/9781118354599.ch4]
[86]
Phan, I.Q.; Subramanian, S.; Kim, D.; Murphy, M.; Pettie, D.; Carter, L.; Anishchenko, I.; Barrett, L.K.; Craig, J.; Tillery, L.; Shek, R.; Harrington, W.E.; Koelle, D.M.; Wald, A.; Veesler, D.; King, N.; Boonyaratanakornkit, J.; Isoherranen, N.; Greninger, A.L.; Jerome, K.R.; Chu, H.; Staker, B.; Stewart, L.; Myler, P.J.; Van Voorhis, W.C. In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19. Sci. Rep., 2021, 11(1), 4290.
[http://dx.doi.org/10.1038/s41598-021-83730-y] [PMID: 33619344]
[87]
Versiani, A.F.; Rocha, R.P.; Mendes, T.A.O.; Pereira, G.C.; Coelho dos Reis, J.G.A.; Bartholomeu, D.C.; da Fonseca, F.G. Identification of B-cell epitopes with potential to serologicaly discrimnate Dengue from Zika infections. Viruses, 2019, 11(11), 1079.
[http://dx.doi.org/10.3390/v11111079] [PMID: 31752352]
[88]
Dipti, C.A.; Jain, S.K.; Navin, K. A novel recombinant multiepitope protein as a hepatitis C diagnostic intermediate of high sensitivity and specificity. Protein Expr. Purif., 2006, 47(1), 319-328.
[http://dx.doi.org/10.1016/j.pep.2005.12.012] [PMID: 16504539]

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