Summary: CD4, extracellular
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|CD4, Cluster of differentiation 4, extracellular|
structure of t-cell surface glycoprotein cd4, monoclinic crystal form
In molecular biology, CD4 (cluster of differentiation 4) is a glycoprotein found on the surface of immune cells such as T helper cells, monocytes, macrophages, and dendritic cells. It was discovered in the late 1970s and was originally known as leu-3 and T4 (after the OKT4 monoclonal antibody that reacted with it) before being named CD4 in 1984. In humans, the CD4 protein is encoded by the CD4 gene.
CD4+ T helper cells are white blood cells that are an essential part of the human immune system. They are often referred to as CD4 cells, T-helper cells or T4 cells. They are called helper cells because one of their main roles is to send signals to other types of immune cells, including CD8 killer cells, which then destroy the infectious particle. If CD4 cells become depleted, for example in untreated HIV infection, or following immune suppression prior to a transplant, the body is left vulnerable to a wide range of infections that it would otherwise have been able to fight.
Like many cell surface receptors/markers, CD4 is a member of the immunoglobulin superfamily.
It has four immunoglobulin domains (D1 to D4) that are exposed on the extracellular surface of the cell:
- D1 and D3 resemble immunoglobulin variable (IgV) domains.
- D2 and D4 resemble immunoglobulin constant (IgC) domains.
CD4 uses its D1 domain to interact with the β2-domain of MHC class II molecules. T cells expressing CD4 molecules (and not CD8) on their surface, therefore, are specific for antigens presented by MHC II and not by MHC class I (they are MHC class II-restricted). MHC class I contains Beta-2 microglobulin.
CD4 is a co-receptor that assists the T cell receptor (TCR) in communicating with an antigen-presenting cell. Using its intracellular domain, CD4 amplifies the signal generated by the TCR by recruiting an enzyme, the tyrosine kinase Lck, which is essential for activating many molecular components of the signaling cascade of an activated T cell. Various types of T helper cells are thereby produced. CD4 also interacts directly with MHC class II molecules on the surface of the antigen-presenting cell using its extracellular domain. The extracellular domain adopts an immunoglobulin-like beta-sandwich with seven strands in 2 beta sheets, in a Greek key topology.
During antigen presentation, both the TCR complex and CD4 are recruited to bind to different regions of the MHCII molecule (α1/β1 and β2, respectively) . Close proximity between the TCR complex and CD4 in this situation means the Lck kinase bound to the cytoplasmic tail of CD4 is able to tyrosine-phosphorylate the Immunoreceptor tyrosine activation motifs (ITAM) present on the cytoplasmic domains of CD3. Phosphorylated ITAM motifs on CD3 recruits and activates SH2 domain-containing protein tyrosine kinases (PTK) such as Zap70 to further mediate downstream signal transduction via tyrosine phosphorylation, leading to transcription factor activation including NF-κB and consequent T cell activation.
HIV-1 uses CD4 to gain entry into host T-cells and achieves this through its viral envelope protein known as gp120. The binding to CD4 creates a shift in the conformation of gp120 allowing HIV-1 to bind to a co-receptor expressed on the host cell. These co-receptors are chemokine receptors CCR5 or CXCR4. Following a structural change in another viral protein (gp41), HIV inserts a fusion peptide into the host cell that allows the outer membrane of the virus to fuse with the cell membrane.
HIV infection leads to a progressive reduction in the number of T cells expressing CD4. Medical professionals refer to the CD4 count to decide when to begin treatment during HIV infection. A CD4 count measures the number of T cells expressing CD4. While CD4 counts are not a direct HIV test—e.g. they do not check the presence of viral DNA, or specific antibodies against HIV—they are used to assess the immune system of a patient.
National Institute of Health guidelines recommend treatment of any HIV-positive individuals, regardless of CD4 count Normal blood values are usually expressed as the number of cells per microliter (or cubic millimeter, mm3) of blood, with normal values for CD4 cells being 500-1200 cells/mm3. Patients often undergo treatments when the CD4 counts reach a level of 350 cells per microliter in Europe but usually around 500cpm in the US; people with less than 200 cells per microliter are at high risk of contracting AIDS defined illnesses. Medical professionals also refer to CD4 tests to determine efficacy of treatment.
Viral load testing provides more information about the efficacy for therapy than CD4 counts. For the first 2 years of HIV therapy, CD4 counts may be done every 3-6 months. If a patient's viral load becomes undetectable after 2 years then CD4 counts might not be needed if they are consistently above 500 cells/mm3. If the count remains at 300-500 cells/mm3, then the tests can be done annually. It is not necessary to schedule CD4 counts with viral load tests and the two should be done independently when each is indicated.
CD4 continues to be expressed in most neoplasms derived from T helper cells. It is therefore possible to use CD4 immunohistochemistry on tissue biopsy samples to identify most forms of peripheral T cell lymphoma and related malignant conditions. The antigen has also been associated with a number of autoimmune diseases such as vitiligo and type I diabetes mellitus.
T-cells play a large part in autoinflammatory diseases. When testing a drug's efficacy or studying diseases, it is helpful to quantify the amount of T-cells. on fresh-frozen tissue with CD4+, CD8+, and CD3+ T-cell markers (which stain different markers on a T-cell - giving different results).
- Bernard A, Boumsell L, Hill C (1984). "Joint Report of the First International Workshop on Human Leucocyte Differentiation Antigens by the Investigators of the Participating Laboratories". In Bernard A, Boumsell L, Dausset J, Milstein C, Schlossman SF. Leucocyte typing: human leucocyte differentiation antigens detected by monoclonal antibodies: specification, classification, nomenclature. Berlin: Springer. pp. 45–48. doi:10.1007/978-3-642-68857-7_3. ISBN 0-387-12056-4.
Report on the first international references workshop sponsored by INSERM, WHO and IUIS
- Isobe M, Huebner K, Maddon PJ, Littman DR, Axel R, Croce CM (June 1986). "The gene encoding the T-cell surface protein T4 is located on human chromosome 12". Proc. Natl. Acad. Sci. U.S.A. 83 (12): 4399–402. doi:10.1073/pnas.83.12.4399. PMC 323740. PMID 3086883.
- Ansari-Lari MA, Muzny DM, Lu J, Lu F, Lilley CE, Spanos S, Malley T, Gibbs RA (April 1996). "A gene-rich cluster between the CD4 and triosephosphate isomerase genes at human chromosome 12p13". Genome Res. 6 (4): 314–26. doi:10.1101/gr.6.4.314. PMID 8723724.
- Brady RL, Dodson EJ, Dodson GG, Lange G, Davis SJ, Williams AF, Barclay AN (May 1993). "Crystal structure of domains 3 and 4 of rat CD4: relation to the NH2-terminal domains". Science 260 (5110): 979–83. doi:10.1126/science.8493535. PMID 8493535.
- Zeitlmann L, Sirim P, Kremmer E, Kolanus W (Mar 2001). "Cloning of ACP33 as a novel intracellular ligand of CD4". J. Biol. Chem. 276 (12): 9123–32. doi:10.1074/jbc.M009270200. PMID 11113139.
- Rudd CE, Trevillyan JM, Dasgupta JD, Wong LL, Schlossman SF (September 2010). "Pillars article: the CD4 receptor is complexed in detergent lysates to a protein-tyrosine kinase (pp58) from human T lymphocytes. 1988". J. Immunol. 185 (5): 2645–9. PMC 3791413. PMID 20724730.
- Rudd CE, Trevillyan JM, Dasgupta JD, Wong LL, Schlossman SF (July 1988). "The CD4 receptor is complexed in detergent lysates to a protein-tyrosine kinase (pp58) from human T lymphocytes". Proc. Natl. Acad. Sci. U.S.A. 85 (14): 5190–4. doi:10.1073/pnas.85.14.5190. PMC 281714. PMID 2455897.
- Barber EK, Dasgupta JD, Schlossman SF, Trevillyan JM, Rudd CE (May 1989). "The CD4 and CD8 antigens are coupled to a protein-tyrosine kinase (p56lck) that phosphorylates the CD3 complex". Proc. Natl. Acad. Sci. U.S.A. 86 (9): 3277–81. doi:10.1073/pnas.86.9.3277. PMC 287114. PMID 2470098.
- Hawash IY, Hu XE, Adal A, Cassady JM, Geahlen RL, Harrison ML (April 2002). "The oxygen-substituted palmitic acid analogue, 13-oxypalmitic acid, inhibits Lck localization to lipid rafts and T cell signaling". Biochim. Biophys. Acta 1589 (2): 140–50. doi:10.1016/S0167-4889(02)00165-9. PMID 12007789.
- Foti M, Phelouzat MA, Holm A, Rasmusson BJ, Carpentier JL (February 2002). "p56Lck anchors CD4 to distinct microdomains on microvilli". Proc. Natl. Acad. Sci. U.S.A. 99 (4): 2008–13. doi:10.1073/pnas.042689099. PMC 122310. PMID 11854499.
- Gorska MM, Stafford SJ, Cen O, Sur S, Alam R (February 2004). "Unc119, a Novel Activator of Lck/Fyn, Is Essential for T Cell Activation". J. Exp. Med. 199 (3): 369–79. doi:10.1084/jem.20030589 (inactive 2015-10-29). PMC 2211793. PMID 14757743.
- Kwong PD, Wyatt R, Robinson J, Sweet RW, Sodroski J, Hendrickson WA (June 1998). "Structure of an HIV gp120 envelope glycoprotein in complex with the CD4 receptor and a neutralizing human antibody". Nature 393 (6686): 648–59. doi:10.1038/31405. PMID 9641677.
- "Guidelines for the Use of Antiretroviral Agents in HIV-1-Infected Adults and Adolescents" (PDF). AIDSinfo. U.S. Department of Health & Human Services. 2013-02-13.
- Bofill M, Janossy G, Lee CA, MacDonald-Burns D, Phillips AN, Sabin C, Timms A, Johnson MA, Kernoff PB (May 1992). "Laboratory control values for CD4 and CD8 T lymphocytes. Implications for HIV-1 diagnosis". Clin. Exp. Immunol. 88 (2): 243–52. doi:10.1111/j.1365-2249.1992.tb03068.x. PMC 1554313. PMID 1349272.
- HIV Medicine Association (February 2016), "Five Things Physicians and Patients Should Question", Choosing Wisely: an initiative of the ABIM Foundation (HIV Medicine Association), retrieved 9 May 2016
- Kumarasen Cooper; Anthony S-Y. Leong (2003). Manual of diagnostic antibodies for immunohistology. London: Greenwich Medical Media. p. 65. ISBN 1-84110-100-1.
- Zamani M, Tabatabaiefar MA, Mosayyebi S, Mashaghi A, Mansouri P (July 2010). "Possible association of the CD4 gene polymorphism with vitiligo in an Iranian population". Clin. Exp. Dermatol. 35 (5): 521–4. doi:10.1111/j.1365-2230.2009.03667.x. PMID 19843086.
- Ciccarelli F, De Martinis M, Ginaldi L (2014). "An update on autoinflammatory diseases". Curr. Med. Chem. 21 (3): 261–9. doi:10.2174/09298673113206660303. PMC 3905709. PMID 24164192.
- "550280 - BD Biosciences". BD Biosciences. Becton Dickinson.
- Miceli MC, Parnes JR (1993). "Role of CD4 and CD8 in T cell activation and differentiation". Adv. Immunol. Advances in Immunology 53: 59–122. doi:10.1016/S0065-2776(08)60498-8. ISBN 978-0-12-022453-1. PMID 8512039.
- Geyer M, Fackler OT, Peterlin BM (2001). "Structure–function relationships in HIV-1 Nef". EMBO Rep. 2 (7): 580–5. doi:10.1093/embo-reports/kve141. PMC 1083955. PMID 11463741.
- Greenway AL, Holloway G, McPhee DA, Ellis P, Cornall A, Lidman M (2004). "HIV-1 Nef control of cell signalling molecules: multiple strategies to promote virus replication". J. Biosci. 28 (3): 323–35. doi:10.1007/BF02970151. PMID 12734410.
- Bénichou S, Benmerah A (2003). "[The HIV nef and the Kaposi-sarcoma-associated virus K3/K5 proteins: "parasites"of the endocytosis pathway]". Med Sci (Paris) 19 (1): 100–6. doi:10.1051/medsci/2003191100. PMID 12836198.
- Leavitt SA, SchOn A, Klein JC, Manjappara U, Chaiken IM, Freire E (2004). "Interactions of HIV-1 proteins gp120 and Nef with cellular partners define a novel allosteric paradigm". Curr. Protein Pept. Sci. 5 (1): 1–8. doi:10.2174/1389203043486955. PMID 14965316.
- Tolstrup M, Ostergaard L, Laursen AL, Pedersen SF, Duch M (2004). "HIV/SIV escape from immune surveillance: focus on Nef". Curr. HIV Res. 2 (2): 141–51. doi:10.2174/1570162043484924. PMID 15078178.
- Hout DR, Mulcahy ER, Pacyniak E, Gomez LM, Gomez ML, Stephens EB (2005). "Vpu: a multifunctional protein that enhances the pathogenesis of human immunodeficiency virus type 1". Curr. HIV Res. 2 (3): 255–70. doi:10.2174/1570162043351246. PMID 15279589.
- Joseph AM, Kumar M, Mitra D (2005). "Nef: "necessary and enforcing factor" in HIV infection". Curr. HIV Res. 3 (1): 87–94. doi:10.2174/1570162052773013. PMID 15638726.
- Anderson JL, Hope TJ (2005). "HIV accessory proteins and surviving the host cell". Current HIV/AIDS reports 1 (1): 47–53. doi:10.1007/s11904-004-0007-x. PMID 16091223.
- Li L, Li HS, Pauza CD, Bukrinsky M, Zhao RY (2006). "Roles of HIV-1 auxiliary proteins in viral pathogenesis and host-pathogen interactions". Cell Res. 15 (11–12): 923–34. doi:10.1038/sj.cr.7290370. PMID 16354571.
- Stove V, Verhasselt B (2006). "Modelling thymic HIV-1 Nef effects". Curr. HIV Res. 4 (1): 57–64. doi:10.2174/157016206775197583. PMID 16454711.
- CD1 Antigen at the US National Library of Medicine Medical Subject Headings (MeSH)
- Mouse CD Antigen Chart
- Human CD Antigen Chart
- *Human Immunodeficiency Virus Glycoprotein 120
This tab holds the annotation information that is stored in the Pfam database. As we move to using Wikipedia as our main source of annotation, the contents of this tab will be gradually replaced by the Wikipedia tab.
CD4, extracellular Provide feedback
Members of this family adopt an immunoglobulin-like beta-sandwich, with seven strands in 2 beta sheets, in a Greek key topology. They are predominantly found in the extracellular portion of CD4 proteins, where they enable interaction with major histocompatibility complex class II antigens .
Brady RL, Dodson EJ, Dodson GG, Lange G, Davis SJ, Williams AF, Barclay AN; , Science. 1993;260:979-983.: Crystal structure of domains 3 and 4 of rat CD4: relation to the NH2-terminal domains. PUBMED:8493535 EPMC:8493535
External database links
This tab holds annotation information from the InterPro database.
InterPro entry IPR015274
This domain adopts an immunoglobulin-like beta-sandwich with seven strands in 2 beta sheets, in a Greek key topology. It is predominantly found in the extracellular portion of CD4 proteins, where it enables interaction with major histocompatibility complex class II antigens [PUBMED:8493535].
Below is a listing of the unique domain organisations or architectures in which this domain is found. More...
The graphic that is shown by default represents the longest sequence with a given architecture. Each row contains the following information:
- the number of sequences which exhibit this architecture
a textual description of the architecture, e.g. Gla, EGF x 2, Trypsin.
This example describes an architecture with one
Gladomain, followed by two consecutive
EGFdomains, and finally a single
- a link to the page in the Pfam site showing information about the sequence that the graphic describes
- the UniProt description of the protein sequence
- the number of residues in the sequence
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Note that you can see the family page for a particular domain by clicking on the graphic. You can also choose to see all sequences which have a given architecture by clicking on the Show link in each row.
Finally, because some families can be found in a very large number of architectures, we load only the first fifty architectures by default. If you want to see more architectures, click the button at the bottom of the page to load the next set.
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We store a range of different sequence alignments for families. As well as the seed alignment from which the family is built, we provide the full alignment, generated by searching the sequence database (reference proteomes) using the family HMM. We also generate alignments using four representative proteomes (RP) sets, the UniProtKB sequence database, the NCBI sequence database, and our metagenomics sequence database. More...
There are various ways to view or download the sequence alignments that we store. We provide several sequence viewers and a plain-text Stockholm-format file for download.
We make a range of alignments for each Pfam-A family:
- the curated alignment from which the HMM for the family is built
- the alignment generated by searching the sequence database using the HMM
- Representative Proteomes (RPs) at 15%, 35%, 55% and 75% co-membership thresholds
- alignment generated by searching the UniProtKB sequence database using the family HMM
- alignment generated by searching the NCBI sequence database using the family HMM
- alignment generated by searching the metagenomics sequence database using the family HMM
You can see the alignments as HTML or in three different sequence viewers:
- a Java applet developed at the University of Dundee. You will need Java installed before running jalview
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You can download (or view in your browser) a text representation of a Pfam alignment in various formats:
You can also change the order in which sequences are listed in the alignment, change how insertions are represented, alter the characters that are used to represent gaps in sequences and, finally, choose whether to download the alignment or to view it in your browser directly.
You may find that large alignments cause problems for the viewers and the reformatting tool, so we also provide all alignments in Stockholm format. You can download either the plain text alignment, or a gzipped version of it.
We make a range of alignments for each Pfam-A family. You can see a description of each above. You can view these alignments in various ways but please note that some types of alignment are never generated while others may not be available for all families, most commonly because the alignments are too large to handle.
1Cannot generate PP/Heatmap alignments for seeds; no PP data available
Key: available, not generated, — not available.
Format an alignment
We make all of our alignments available in Stockholm format. You can download them here as raw, plain text files or as gzip-compressed files.
You can also download a FASTA format file containing the full-length sequences for all sequences in the full alignment.
HMM logos is one way of visualising profile HMMs. Logos provide a quick overview of the properties of an HMM in a graphical form. You can see a more detailed description of HMM logos and find out how you can interpret them here. More...
If you find these logos useful in your own work, please consider citing the following article:
This page displays the phylogenetic tree for this family's seed alignment. We use FastTree to calculate neighbour join trees with a local bootstrap based on 100 resamples (shown next to the tree nodes). FastTree calculates approximately-maximum-likelihood phylogenetic trees from our seed alignment.
Note: You can also download the data file for the tree.
Curation and family details
This section shows the detailed information about the Pfam family. You can see the definitions of many of the terms in this section in the glossary and a fuller explanation of the scoring system that we use in the scores section of the help pages.
|Number in seed:||20|
|Number in full:||53|
|Average length of the domain:||105.00 aa|
|Average identity of full alignment:||58 %|
|Average coverage of the sequence by the domain:||23.42 %|
|HMM build commands:||
build method: hmmbuild -o /dev/null HMM SEED
search method: hmmsearch -Z 11927849 -E 1000 --cpu 4 HMM pfamseq
|Family (HMM) version:||7|
|Download:||download the raw HMM for this family|
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This visualisation provides a simple graphical representation of the distribution of this family across species. You can find the original interactive tree in the More....
This chart is a modified "sunburst" visualisation of the species tree for this family. It shows each node in the tree as a separate arc, arranged radially with the superkingdoms at the centre and the species arrayed around the outermost ring.
How the sunburst is generated
The tree is built by considering the taxonomic lineage of each sequence that has a match to this family. For each node in the resulting tree, we draw an arc in the sunburst. The radius of the arc, its distance from the root node at the centre of the sunburst, shows the taxonomic level ("superkingdom", "kingdom", etc). The length of the arc represents either the number of sequences represented at a given level, or the number of species that are found beneath the node in the tree. The weighting scheme can be changed using the sunburst controls.
In order to reduce the complexity of the representation, we reduce the number of taxonomic levels that we show. We consider only the following eight major taxonomic levels:
Colouring and labels
Segments of the tree are coloured approximately according to their superkingdom. For example, archeal branches are coloured with shades of orange, eukaryotes in shades of purple, etc. The colour assignments are shown under the sunburst controls. Where space allows, the name of the taxonomic level will be written on the arc itself.
As you move your mouse across the sunburst, the current node will be highlighted. In the top section of the controls panel we show a summary of the lineage of the currently highlighed node. If you pause over an arc, a tooltip will be shown, giving the name of the taxonomic level in the title and a summary of the number of sequences and species below that node in the tree.
Anomalies in the taxonomy tree
There are some situations that the sunburst tree cannot easily handle and for which we have work-arounds in place.
Missing taxonomic levels
Some species in the taxonomic tree may not have one or more of the main eight levels that we display. For example, Bos taurus is not assigned an order in the NCBI taxonomic tree. In such cases we mark the omitted level with, for example, "No order", in both the tooltip and the lineage summary.
Unmapped species names
The tree is built by looking at each sequence in the full alignment for the family. We take the name of the species given by UniProt and try to map that to the full taxonomic tree from NCBI. In some cases, the name chosen by UniProt does not map to any node in the NCBI tree, perhaps because the chosen name is listed as a synonym or a misspelling in the NCBI taxonomy.
So that these nodes are not simply omitted from the sunburst tree, we group them together in a separate branch (or segment of the sunburst tree). Since we cannot determine the lineage for these unmapped species, we show all levels between the superkingdom and the species as "uncategorised".
Since we reduce the species tree to only the eight main taxonomic levels, sequences that are mapped to the sub-species level in the tree would not normally be shown. Rather than leave out these species, we map them instead to their parent species. So, for example, for sequences belonging to one of the Vibrio cholerae sub-species in the NCBI taxonomy, we show them instead as belonging to the species Vibrio cholerae.
Too many species/sequences
For large species trees, you may see blank regions in the outer layers of the sunburst. These occur when there are large numbers of arcs to be drawn in a small space. If an arc is less than approximately one pixel wide, it will not be drawn and the space will be left blank. You may still be able to get some information about the species in that region by moving your mouse across the area, but since each arc will be very small, it will be difficult to accurately locate a particular species.
The tree shows the occurrence of this domain across different species. More...
We show the species tree in one of two ways. For smaller trees we try to show an interactive representation, which allows you to select specific nodes in the tree and view them as an alignment or as a set of Pfam domain graphics.
Unfortunately we have found that there are problems viewing the interactive tree when the it becomes larger than a certain limit. Furthermore, we have found that Internet Explorer can become unresponsive when viewing some trees, regardless of their size. We therefore show a text representation of the species tree when the size is above a certain limit or if you are using Internet Explorer to view the site.
If you are using IE you can still load the interactive tree by clicking the "Generate interactive tree" button, but please be aware of the potential problems that the interactive species tree can cause.
For all of the domain matches in a full alignment, we count the number that are found on all sequences in the alignment. This total is shown in the purple box.
We also count the number of unique sequences on which each domain is found, which is shown in green. Note that a domain may appear multiple times on the same sequence, leading to the difference between these two numbers.
Finally, we group sequences from the same organism according to the NCBI code that is assigned by UniProt, allowing us to count the number of distinct sequences on which the domain is found. This value is shown in the pink boxes.
We use the NCBI species tree to group organisms according to their taxonomy and this forms the structure of the displayed tree. Note that in some cases the trees are too large (have too many nodes) to allow us to build an interactive tree, but in most cases you can still view the tree in a plain text, non-interactive representation. Those species which are represented in the seed alignment for this domain are highlighted.
You can use the tree controls to manipulate how the interactive tree is displayed:
- show/hide the summary boxes
- highlight species that are represented in the seed alignment
- expand/collapse the tree or expand it to a given depth
- select a sub-tree or a set of species within the tree and view them graphically or as an alignment
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Please note: for large trees this can take some time. While the tree is loading, you can safely switch away from this tab but if you browse away from the family page entirely, the tree will not be loaded.
There are 3 interactions for this family. More...
We determine these interactions using iPfam, which considers the interactions between residues in three-dimensional protein structures and maps those interactions back to Pfam families. You can find more information about the iPfam algorithm in the journal article that accompanies the website.
For those sequences which have a structure in the Protein DataBank, we use the mapping between UniProt, PDB and Pfam coordinate systems from the PDBe group, to allow us to map Pfam domains onto UniProt sequences and three-dimensional protein structures. The table below shows the structures on which the CD4-extracel domain has been found. There are 15 instances of this domain found in the PDB. Note that there may be multiple copies of the domain in a single PDB structure, since many structures contain multiple copies of the same protein seqence.
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