An overview of a typical membrane protein purification and preparation for Mass spectrometry
Reference: Mass spectrometry of intact membrane protein complexes. Nat Protoc. 2013 Apr;8(4):639-51. doi: 10.1038/nprot.2013.024. Epub 2013 Mar 7.
Reference: Mass spectrometry of intact membrane protein complexes. Nat Protoc. 2013 Apr;8(4):639-51. doi: 10.1038/nprot.2013.024. Epub 2013 Mar 7.
Antibodies are the main contributor of body’s immune system which are proteins in nature and mainly secreted by plasma cells. Antibodies are the main component of the humoral immune response. Antibodies are members of immunoglobulin family. They constitute 20% of the plasma protein. Different population of antibodies are present in different parts of the body. They are host proteins produced in response to foreign molecules known as antigens. When foreign molecules like virus and bacteria invade body’s immune system, antigens or special molecules of the pathogen get recognized by the antibodies and elicit immune response. This antigen-antibody binding is required for the neutralization and clearance of the pathogen from body. This is the body’s self-defence mechanism against foreign bodies.
Antibodies are produced in special white blood cells, B-lymphocyte. B- Lymphocytes in the body have cell surface receptors for foreign bodies or antigens. On attachment of these bodies, they differentiate to form lymphoid or plasma cells, which in turn produce millions of antibodies secreting out in blood circulation. Antibodies generally exists in two forms; a free circulating antibodies present in blood plasma and a bound form attached to B-cell surface. Science has paved way for the understanding of antigen-antibody interaction and their characteristics. Now scientist can manipulate these characteristics of antibody fragments for different usage.
There are many application of antibodies in diagnosis and therapy. The use of recombinant technology opens up the potential to create an infinite number of combinations between immunoglobulins. We can now manipulate these fragments to our advantage. As the antibody usage has increased, our understanding about these molecules has increased. Various methods of purification technique have been identified and used for commercial applications. All these applications require antibody in a purified state. The state of purity depends on the scale of application. The parameters for purification entirely depend on its intended application. The parameters can be physical such as size, charge, pI, stability. Purity can be a scale from microgram to a gram or any other weight measurement.
In humans and rodents, there are five immunoglobulin classes or isotypes, which differ in the primary structure, carbohydrate content, and antigenic properties of their heavy chains . By contrast, the light chain types are the same for all immunoglobulin classes. Each immunoglobulin molecule contains light chains of one of two types, either lambda (2) or kappa (x). The 2 and light chains have different primary structures and antigenic properties. They are usually free of carbohydrate components. The ratio of x/2 chains in human and swine immunoglobulins is about 60:40, whereas in mouse, rat and rabbit immunoglobulins it is about 95:5. Some other mammals such as dog, cat, and farm animals (ox, sheep, and horse) have mainly 2 chains and chicken immunoglobulins contain only 2 chains.
Antibodies or iunoglobulin are Y shaped and glycoprotein in nature consisting of one or more units. All immunoglobulins have a common structure with four polypeptide chains; two identical heavy (H) chains almost 50-70kD in molecular weight, each carrying covalently attached oligosaccharide groups; two identical, nonglycosylated light (L) chains of molecular weight 23kD. An inter-chain disulfide bond joins the heavy chain and the light chain together along with non covalent bonds. Different types of imunoglobulins have different number of interchain disulphide bridge. The heavy chains are also joined by disulfide bonds. The disulfide bonds are present in the flexible region of the heavy chain known as hinge region. In mammal, there are five different types of heavy chains are represented with the greek letter sympbol α, δ, ε, γ, and μ. Whereas, mammalian light chain only consists of two parts known as lambda (λ) and kappa (κ). All four polypeptide chain s contains constant (C) and variable (V) regions found at the carboxyl and amino terminal portions, respectively. In the tip part of the Y shaped antibody molecule, variable (V) regions are present.
This region is composed of 110-130 amino acids and shown great variance between different immunoglobulins and also specific for antigen binding. The variable region represents end part of both heavy and light chain. On the other hand the constant region ( C) is important for antigen destruction and shows less variation . All light chains ( L) have a single V region ,VL and a single constant region CL. On the other hand, Heavy chain has one variable region VH and contains 3 C region forming CH1, CH2 and CH3. The V regions combine to form two identical antigen binding sites. Immunoglobulins are divided into five major classes according to their H chain components: IgG, IgA, IgM, IgD, and IgE. The light chain molecules have k chains and l chains. Individual molecules have either one of the molecule. The variable region of the immunoglobulin can be further subdivided into two part called hypervariable (HV) and framework (FR). For a given position, HV region will exhibit high ratio of amino acid difference.
Three HV regions, HV1, HV2 and HV3 are exists between heavy and light chain. Whereas, FR regions have comparatively stable amino acid sequence and work to separate HV regions. The function of HV region is to directly contact the antigenic surface and thus called as complementarity determining regions, or CDRs. whereas, the FR part is useful for placing the HV region in position to be in contact with antigen. Depending on the heavy chain imunoglobulins are further divided into five major classes; IgG , IgA IgM IgD and IgE. In each of these class differs from each other by the presence of different heavy chain. IgG , IgA IgM IgD and IgE contains the heavy chain γ,α, μ, δ and ε respectively. Whereas for all the imunoglobulin class, the light chain is either κ or λ.
IgG is most widely found iunoglobulin in serum and expressed on the surface of B cells. IgG can be firther subdivided into IgG1, IgG2, IgG3 and IgG4. IgA is the second most commonly available immunoglobulin. They are mostly found in secretion such as mucous, tear or saliva and also in milk as secreted form. IgA is further classified to subclass IgA1 and IgA2. The third immunoglobulins which comes in the list of availability is IgG M which is expressed both in immature and mature B cells. It has a pentameric structure and also shows expression in fetus. IgD immunoglobulin works together with for the development of B cell. IgE on the other hand is least available immunoglobulin present in serum and are mostly involved in allergic reaction.
Drug | Company | Indication | Status |
ASO | |||
Eteplirsen (Exondys 51) | Sarepta | DMD | Approved (2016)a |
Nusinersen (Spinraza) | Ionis/Biogen | SMA | Approved (2016)a |
Inotersen (Tegsedi) | Ionis/Akcea/PTC | hATTR | Approved (2018)a |
Volanesorsen (Waylivra) | Ionis/Akcea/PTC | FCS | Approved (2019)b |
Golodirsen (Vyondys 53) | Sarepta | DMD | Approved (2019)a |
Viltolarsen | NS Pharma | DMD | NDA |
Casimersen (SRP-4045) | Sarepta | DMD | NDA |
TQJ230 (AKCEA-APO(a)-LRx) | Ionis/Akcea/Novartis | Hyperlipoproteinaemia with cardiovascular risk | Phase III |
Tofersen | Ionis/Biogen | SOD1-driven ALS | Phase III |
IONIS-HTTRx | Ionis/Roche | Huntington disease | Phase III |
Trabedersen (OT-101) | Mateon (Oncotelic) | Brain cancer | Phase III |
Volanesorsen | Ionis/Akcea | FPL | Phase III |
siRNA | |||
Patisiran (Onpattro) | Alnylam | hATTR | Approved (2018)a |
Givosiran (Givlaari) | Alnylam | AHP | Approved (2019)a |
Lumasiran | Alnylam | Hyperoxaluria | NDA |
Inclisiran | Alnylam/Novartis (The Medicines Company) | Dyslipidaemia / hypercholesterolaemia | NDA |
QR-110 | ProQR | Leber’s congenital amaurosis | Phase III |
Vutrisiran | Alnylam | ATTR/hATTR | Phase III |
QP-1002 | Quark | Renal disease/failure, Delayed graft function | Phase III |
Tivanisiran (SYL1001) | Sylentis | Dry eye | Phase III |
Fitusiran | Alnylam /Sanofi Genzyme | Haemophilia A and B | Phase III |
“RNA therapeutics have demonstrated most success in the treatment of rare diseases, especially neurological and hepatic diseases. Of the 21 late-stage RNA therapeutics, 18 have orphan status (Table 1). The most commercially successful drug to date has been nusinersen, which has $4.7 billion in sales up to the end of 2019 . The two currently approved siRNA drugs — patisiran (Onpattro; Alnylam) and givosiran (Givlaari; Alnylam) — target liver mRNAs for the treatment of hereditary transthyretin amyloidosis and acute hepatic porphyria, respectively. Patisiran achieved sales of more than $150 million in its first full year on the market in 2019, which are forecast to approximately double in 2020.”
Reference: RNA therapeutics on the rise, Nature review drug discovery, 27 APRIL 2020
Bioinformatics approaches play a critical role on analyzing multiple genomes to select the protective epitopes in silico. It is conceived that cocktails of defined epitopes or chimeric protein arrangements, including the target epitopes, may provide a rationale design capable to elicit convenient humoral or cellular immune responses. Here we presents a comprehensive compilation of the most advantageous online immunological software and searchable, in order to facilitate the design and development of vaccines. An outlook on how these tools are supporting vaccine development is presented.
Table 1. Comprehensive list of T cell epitope prediction servers.
Table 2. Predictive server for TAP binding epitopes and CTL
Server name | Link | Description | Predictive method |
---|---|---|---|
EpiJen | http://www.ddg-pharmfac.net/epijen/EpiJen/EpiJen.htm | Predictive server for TAP binding epitopes | Multi-step algorithm |
TAP Pred | http://www.imtech.res.in/raghava/tappred/ | Predictive server for TAP binding epitopes | SVM method |
WAPP | http://abi.inf.uni-tuebingen.de/Services/WAPP/information | Predictive server for TAP binding epitopes | SVM method |
CTLPred | http://www.imtech.res.in/raghava/ctlpred/ | Predictive server for CTL | SVM and ANN method |
NetCTLPan | http://www.cbs.dtu.dk/services/NetCTLpan/ | Predictive server for CTL | Multi-step algorithm |
Table 3. Comprehensive list of B cell epitope prediction servers.
Server name | Link | Type |
---|---|---|
Bcepred | http://www.imtech.res.in/raghava/bcepred/ | Prediction of continuous B-cell epitopes |
BepiPred | http://www.cbs.dtu.dk/services/BepiPred/ | Prediction of continuous B-cell epitopes |
ABCPred | http://www.imtech.res.in/raghava/abcpred/ | Prediction of continuous B-cell epitopes |
BEST | http://biomine.ece.ualberta.ca/BEST/ | Prediction of continuous B-cell epitopes |
EPCES | http://sysbio.unl.edu/services/EPCES/ | Prediction of discontinuous B-cell epitopes |
Discotope | http://www.cbs.dtu.dk/services/DiscoTope/ | Prediction of discontinuous B-cell epitopes |
BEPro (PEPITO) | http://pepito.proteomics.ics.uci.edu/ | Prediction of discontinuous B-cell epitopes |
SEPPA | http://lifecenter.sgst.cn/seppa/index.php | Prediction of discontinuous B-cell epitopes |
EpiSearch | http://curie.utmb.edu/episearch.html | Prediction of discontinuous B-cell epitopes |
MimoPro | http://informatics.nenu.edu.cn/MimoPro | Prediction of discontinuous B-cell epitopes |
MIMOX | http://immunet.cn/mimox/ | Prediction of discontinuous B-cell epitopes |
Pep-3D-Search | http://kyc.nenu.edu.cn/Pep3DSearch | Prediction of discontinuous B-cell epitopes |
Epitopia | http://epitopia.tau.ac.il/ | Prediction of continuous and discontinuous B-cell epitopes |
PepSurf | http://pepitope.tau.ac.il | Prediction of continuous and discontinuous B-cell epitopes |
ElliPro | http://tools.immuneepitope.org/tools/ElliPro/iedb_input | Prediction of continuous and discontinuous B-cell epitopes |
Reference: An overview of bioinformatics tools for epitope prediction: implications on vaccine development. J Biomed Inform. 2015 Feb;53:405-14. doi: 10.1016/j.jbi.2014.11.003. Epub 2014 Nov 10.