Antisoma Application: A Fully Integrated V-Like Antibodies Platform

Louis Papageorgiou; Dimitrios Vlachakis; Louis Papageorgiou; Dimitrios Vlachakis

doi:10.3934/medsci.2017.4.382

AIMS Medical Science

2017, Volume 4, Issue 4: 382-394. doi: 10.3934/medsci.2017.4.382

Previous Article Next Article

Research article Special Issues

Antisoma Application: A Fully Integrated V-Like Antibodies Platform

Louis Papageorgiou ^1,2,
Dimitrios Vlachakis ^{1
,
,}

1.
Computational Biology & Medicine Group, Biomedical Research Foundation, Academy of Athens, Soranou Efessiou 4, Athens 11527, Greece
2.
Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, University Campus, Athens, 15784, Greece

Received: 20 April 2017 Accepted: 31 August 2017 Published: 11 October 2017

Antibodies, also called immunoglobulins, are large Y-shaped proteins which are produced and used by the immune system in order to identify and neutralize foreign substances called antigens. The study and research of antibodies is a critical issue in science and has led in remarkable results with medical applications such as diseases diagnosis, therapies and antibodies related drugs. Due to the importance of antibodies, a comprehensive database of full length protein sequences or crystal structures of immunoglobulin (IG) and T cell receptor (TR) V-like protein sequences from human and other vertebrate species has been created. In this article, we study in detail the unique numbering system for immunoglobulins of IMGT, we correlate the database antibody entries and we provide a more in detailed approach into the data. Finally, due to the deviation of the expected from the real data, a user friendly application has been created. This powerful and flexible tool manipulates the antibodies V-like protein sequences with the approach described below and gives the opportunity to the user to extract and study the results and its physicochemical properties. The need for new therapeutic targets and the development of more potent drugs is enormous, despite the efforts and the investments all these years for the development of novel next generation drugs, the discovery and the characterization of new therapeutic targets using immunoglobulins or antibodies. The final outcome from this project will support the development of novel therapies. Antisoma can be freely downloaded from http://www.dimvl.com/antisoma.
- antisoma application,
- antibodies/immunoglobulins database,
- V-like antibodies,
- antibodies numbering system,
- complementarity-determining regions,
- fragment region,
- physicochemical properties
Citation: Louis Papageorgiou, Dimitrios Vlachakis. Antisoma Application: A Fully Integrated V-Like Antibodies Platform[J]. AIMS Medical Science, 2017, 4(4): 382-394. doi: 10.3934/medsci.2017.4.382

Related Papers:

Abstract

Antibodies, also called immunoglobulins, are large Y-shaped proteins which are produced and used by the immune system in order to identify and neutralize foreign substances called antigens. The study and research of antibodies is a critical issue in science and has led in remarkable results with medical applications such as diseases diagnosis, therapies and antibodies related drugs. Due to the importance of antibodies, a comprehensive database of full length protein sequences or crystal structures of immunoglobulin (IG) and T cell receptor (TR) V-like protein sequences from human and other vertebrate species has been created. In this article, we study in detail the unique numbering system for immunoglobulins of IMGT, we correlate the database antibody entries and we provide a more in detailed approach into the data. Finally, due to the deviation of the expected from the real data, a user friendly application has been created. This powerful and flexible tool manipulates the antibodies V-like protein sequences with the approach described below and gives the opportunity to the user to extract and study the results and its physicochemical properties. The need for new therapeutic targets and the development of more potent drugs is enormous, despite the efforts and the investments all these years for the development of novel next generation drugs, the discovery and the characterization of new therapeutic targets using immunoglobulins or antibodies. The final outcome from this project will support the development of novel therapies. Antisoma can be freely downloaded from http://www.dimvl.com/antisoma.

References

[1]	Llewelyn MB, Hawkins RE, Russell SJ (1992) Discovery of antibodies. BMJ 305: 1269-1272. doi: 10.1136/bmj.305.6864.1269
[2]	Silverstein AM (1999) Paul Ehrlich's passion: the origins of his receptor immunology. Cell Immunol 194: 213-221. doi: 10.1006/cimm.1999.1505
[3]	Kabat EA, Furth J (1940) Chemical and Immunological Studies on the Agent Producing Leukosis and Sarcoma of Fowls. J Exp Med 71: 55-70. doi: 10.1084/jem.71.1.55
[4]	Ribatti D (2015) Edelman's view on the discovery of antibodies. Immunol Lett 164: 72-75. doi: 10.1016/j.imlet.2015.02.005
[5]	Liu JK (2014) The history of monoclonal antibody development - Progress, remaining challenges and future innovations. Ann Med Surg (Lond. 3): 113-116.
[6]	Scott AM, Wolchok JD, Old LJ (2012) Antibody therapy of cancer. Nat Rev Cancer 12: 278-287. doi: 10.1038/nrc3236
[7]	Novotný J, Bruccoleri R, Newell J, et al. (1983) Molecular anatomy of the antibody binding site. J Biol Chem 258: 14433-14437.
[8]	Coleclough C (1983) Chance, necessity and antibody gene dynamics. Nature 303: 23-26. doi: 10.1038/303023a0
[9]	Chothia C, Novotný J, Bruccoleri R, et al. (1985) Domain association in immunoglobulin molecules. The packing of variable domains. J Mol Biol 186: 651-663.
[10]	Maltezos A, Platis D, Vlachakis D, et al. (2014) Design, synthesis and application of benzyl-sulfonate biomimetic affinity adsorbents for monoclonal antibody purification from transgenic corn. J Mol Recognit 27: 19-31. doi: 10.1002/jmr.2327
[11]	Chothia C, Lesk AM, Tramontano A, et al.(1989) Conformations of immunoglobulin hypervariable regions. Nature 342: 877-883.
[12]	Kovtun YV, Goldmacher VS (2007) Cell killing by antibody-drug conjugates. Cancer Lett 255: 232-240. doi: 10.1016/j.canlet.2007.04.010
[13]	Sela-Culang I, Kunik V, Ofran Y (2013) The structural basis of antibody-antigen recognition. Front Immunol 4: 302.
[14]	Shirai H, Prades C, Vita R, et al. (2014) Antibody informatics for drug discovery. Biochim Biophys Acta 1844: 2002-2015. doi: 10.1016/j.bbapap.2014.07.006
[15]	Winter G. Milstein C (1991) Man-made antibodies. Nature 349: 293-299. doi: 10.1038/349293a0
[16]	Fajardo-Ramirez OR, Ascacio-Martinez JA, Licea-Navarro AF, et al. (2015) Technological Evolution in the Development of Therapeutic Antibodies. Rev Invest Clin 67: 158-169.
[17]	Wang J, Bu D, Zhu X (2007) Immunoglobulin variable region gene analysis to the autoantibody-secreting B cells from tumors in association with paraneoplastic autoimmune multiorgan syndrome. Int J Dermatol 46: 1146-1154. doi: 10.1111/j.1365-4632.2007.03267.x
[18]	Peters C, Brown S (2015) Antibody-drug conjugates as novel anti-cancer chemotherapeutics. Biosci Rep 35: e00225. doi: 10.1042/BSR20150089
[19]	Zhang N, Deng H, Fan X, et al. (2015) Dysfunctional antibodies in the tumor microenvironment associate with impaired anticancer immunity. Clin Cancer Res 21: 5380-5390. doi: 10.1158/1078-0432.CCR-15-1057
[20]	Campa MJ, Gottlin EB, Bushey RT, et al. (2015) Complement Factor H Antibodies from Lung Cancer Patients Induce Complement Dependent Lysis of Tumor Cells, Suggesting a Novel Immunotherapeutic Strategy. Cancer Immunol Res 3: 1325-1332. doi: 10.1158/2326-6066.CIR-15-0122
[21]	Zitvogel L, Kroemer G (2015) Cancer: Antibodies regulate antitumour immunity. Nature 521: 35-37. doi: 10.1038/nature14388
[22]	Papageorgiou L, Cuong NT, Vlachakis D (2016) Antibodies as stratagems against cancer. Mol Biosyst 12: 2047-2055. doi: 10.1039/C5MB00699F
[23]	Kumar S, King L E, Clark T H, et al. (2015) Antibody-drug conjugates nonclinical support: from early to late nonclinical bioanalysis using ligand-binding assays. Bioanalysis 7: 1605-1617. doi: 10.4155/bio.15.107
[24]	Gorovits B (2015) Bioanalysis of antibody-drug conjugates. Bioanalysis 7: 1559-1560. doi: 10.4155/bio.15.106
[25]	Merten H, Brandl F, Plückthun A, et al. (2015) Antibody-Drug Conjugates for Tumor Targeting-Novel Conjugation Chemistries and the Promise of non-IgG Binding Proteins. Bioconjug Chem 26: 2176-2185. doi: 10.1021/acs.bioconjchem.5b00260
[26]	Hamilton GS (2015) Antibody-drug conjugates for cancer therapy: The technological and regulatory challenges of developing drug-biologic hybrids. Biologicals 43: 318-332. doi: 10.1016/j.biologicals.2015.05.006
[27]	Johnson G, Wu TT (2000) Kabat database and its applications: 30 years after the first variability plot. Nucleic Acids Res 28: 214-218. doi: 10.1093/nar/28.1.214
[28]	Abhinandan KR, Martin AC (2008) Analysis and improvements to Kabat and structurally correct numbering of antibody variable domains. Mol Immunol 45: 3832-3839. doi: 10.1016/j.molimm.2008.05.022
[29]	Lefranc MP (2014) Immunoinformatics of the V, C, and G domains: IMGT(R) definitive system for IG, TR and IgSF, MH, and MhSF. Methods Mol Biol 1184: 59-107. doi: 10.1007/978-1-4939-1115-8_4
[30]	Lefranc MP (2014) Antibody Informatics: IMGT, the International ImMunoGeneTics Information System. Microbiol Spectr: 363-379.
[31]	Lefranc MP (2011) IMGT unique numbering for the variable (V), constant (C), and groove (G) domains of IG, TR, MH, IgSF, and MhSF. Cold Spring Harb Protoc 2011: 633-642.
[32]	Lefranc MP, Giudicelli V, Duroux P, et al. (2014) IMGT®, the international ImMunoGeneTics information system® 25 years on. Nucleic Acids Res 43: D413-D422.
[33]	Lefranc MP, Pommié C, Ruiz M, et al. (2003) IMGT unique numbering for immunoglobulin and T cell receptor variable domains and Ig superfamily V-like domains. Dev Comp Immunol 27: 55-77. doi: 10.1016/S0145-305X(02)00039-3
[34]	Lefranc MP (2014) Immunoglobulins: 25 years of immunoinformatics and IMGT-ONTOLOGY. Biomolecules 4: 1102-1139. doi: 10.3390/biom4041102
[35]	Alamyar E, Giudicelli V, Duroux P, et al. (2014) Antibody V and C domain sequence, structure, and interaction analysis with special reference to IMGT(R). Methods Mol Biol 1131: 337-381. doi: 10.1007/978-1-62703-992-5_21
[36]	Tinberg CE, Khare SD, Dou J, et al. (2013) Computational design of ligand-binding proteins with high affinity and selectivity. Nature 501: 212-216. doi: 10.1038/nature12443
[37]	Benson DA, Cavanaugh M, Clark K, et al. (2017) GenBank. Nucleic Acids Res 45: D37-D42. doi: 10.1093/nar/gkw1070
[38]	Apweiler R, Bairoch A, Wu CH, et al. (2017) UniProt: the universal protein knowledgebase. Nucleic Acids Res 45: D158-D169. doi: 10.1093/nar/gkw1099
[39]	Giudicelli V, Duroux P, Ginestoux C, et al. (2006) IMGT/LIGM-DB, the IMGT comprehensive database of immunoglobulin and T cell receptor nucleotide sequences. Nucleic Acids Res 34: D781-D784. doi: 10.1093/nar/gkj088
[40]	Sobie EA (2011) An introduction to MATLAB. Sci Signal 4: tr7.

Reader Comments

Your name:*

Email:*
© 2017 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)