Summary: Fibroblast growth factor
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Fibroblast growth factor Edit Wikipedia article
|Fibroblast growth factor|
Crystal structure analysis of the FGF10-FGFR2b complex
Fibroblast growth factors, or FGFs, are a family of growth factors, with members involved in angiogenesis, wound healing, embryonic development and various endocrine signaling pathways. The FGFs are heparin-binding proteins and interactions with cell-surface-associated heparan sulfate proteoglycans have been shown to be essential for FGF signal transduction. FGFs are key players in the processes of proliferation and differentiation of wide variety of cells and tissues.
- Members FGF1 through FGF10 all bind fibroblast growth factor receptors (FGFRs). FGF1 is also known as acidic, and FGF2 is also known as basic fibroblast growth factor.
- Members FGF11, FGF12, FGF13, and FGF14, also known as FGF homologous factors 1-4 (FHF1-FHF4), have been shown to have distinct functional differences compared to the FGFs. Although these factors possess remarkably similar sequence homology, they do not bind FGFRs and are involved in intracellular processes unrelated to the FGFs. This group is also known as "iFGF".
- Human FGF18 is involved in cell development and morphogenesis in various tissues including cartilage.
- FGF15 through FGF23 were described later and functions are still being characterized. FGF15 is the mouse ortholog of human FGF19 (there is no human FGF15) and, where their functions are shared, they are often described as FGF15/19. In contrast to the local activity of the other FGFs, FGF15/19, FGF21 and FGF23 have systemic effects.
The mammalian fibroblast growth factor receptor family has 4 members, FGFR1, FGFR2, FGFR3, and FGFR4. The FGFRs consist of three extracellular immunoglobulin-type domains (D1-D3), a single-span trans-membrane domain and an intracellular split tyrosine kinase domain. FGFs interact with the D2 and D3 domains, with the D3 interactions primarily responsible for ligand-binding specificity (see below). Heparan sulfate binding is mediated through the D3 domain. A short stretch of acidic amino acids located between the D1 and D2 domains has auto-inhibitory functions. This 'acid box' motif interacts with the heparan sulfate binding site to prevent receptor activation in the absence of FGFs.
Alternate mRNA splicing gives rise to 'b' and 'c' variants of FGFRs 1, 2 and 3. Through this mechanism seven different signaling FGFR sub-types can be expressed at the cell surface. Each FGFR binds to a specific subset of the FGFs. Similarly most FGFs can bind to several different FGFR subtypes. FGF1 is sometimes referred to as the 'universal ligand' as it is capable of activating all 7 different FGFRs. In contrast, FGF7 (keratinocyte growth factor, KGF) binds only to FGFR2b (KGFR).
Fibroblast growth factor was found in pituitary extracts by Armelin in 1973 and then was also found in a cow brain extract by Gospodarowicz, et al., and tested in a bioassay that caused fibroblasts to proliferate (first published report in 1974).
They then further fractionated the extract using acidic and basic pH and isolated two slightly different forms that were named "acidic fibroblast growth factor" (FGF1) and "basic fibroblast growth factor" (FGF2). These proteins had a high degree of amino acid identity but were determined to be distinct mitogens. Human FGF2 occurs in low molecular weight (LMW) and high molecular weight (HMW) isoforms. LMW FGF2 is primarily cytoplasmic and functions in an autocrine manner, whereas HMW FGF2s are nuclear and exert activities through an intracrine mechanism.
Not long after FGF1 and FGF2 were isolated, another group isolated a pair of heparin-binding growth factors that they named HBGF-1 and HBGF-2, while a third group isolated a pair of growth factors that caused proliferation of cells in a bioassay containing blood vessel endothelium cells, which they called ECGF1 and ECGF2. These proteins were found to be identical to the acidic and basic FGFs described by Gospodarowicz, et al.
FGFs are multifunctional proteins with a wide variety of effects; they are most commonly mitogens but also have regulatory, morphological, and endocrine effects. They have been alternately referred to as "pluripotent" growth factors and as "promiscuous" growth factors due to their multiple actions on multiple cell types. Promiscuous refers to the biochemistry and pharmacology concept of how a variety of molecules can bind to and elicit a response from single receptor. In the case of FGF, four receptor subtypes can be activated by more than twenty different FGF ligands. Thus the functions of FGFs in developmental processes include mesoderm induction, antero-posterior patterning, limb development, neural induction and neural development, and in mature tissues/systems angiogenesis, keratinocyte organization, and wound healing processes.
FGFs secreted by hypoblasts during avian gastrulation play a role in stimulating a Wnt signaling pathway that is involved in the differential movement of Koller's sickle cells during formation of the primitive streak.
One important function of FGF1 and FGF2 is the promotion of endothelial cell proliferation and the physical organization of endothelial cells into tube-like structures. They thus promote angiogenesis, the growth of new blood vessels from the pre-existing vasculature. FGF1 and FGF2 are more potent angiogenic factors than vascular endothelial growth factor (VEGF) or platelet-derived growth factor (PDGF). FGF1 has been shown in clinical experimental studies to induce angiogenesis in the heart.
As well as stimulating blood vessel growth, FGFs are important players in wound healing. FGF1 and FGF2 stimulate angiogenesis and the proliferation of fibroblasts that give rise to granulation tissue, which fills up a wound space/cavity early in the wound-healing process. FGF7 and FGF10 (also known as Keratinocyte Growth Factors KGF and KGF2, respectively) stimulate the repair of injured skin and mucosal tissues by stimulating the proliferation, migration and differentiation of epithelial cells, and they have direct chemotactic effects on tissue remodeling.
During development of the central nervous system, FGFs play important roles in neurogenesis, axon growth, and differentiation. FGFs are also important for maintenance of the adult brain. Thus, FGFs are major determinants of neuronal survival both during development and during adulthood. Adult neurogenesis within the hippocampus e.g. depends greatly on FGF-2. In addition, FGF-1 and FGF-2 seem to be involved in the regulation of synaptic plasticity and processes attributed to learning and memory, at least in the hippocampus.
Most FGFs are secreted proteins that bind heparan sulfates and can, therefore, be caught up in the extracellular matrix of tissues that contain heparan sulfate proteoglycans. This local action of FGF proteins is classified as paracrine signalling, most commonly through the JAK-STAT signaling pathway or the Receptor tyrosine kinase (RTK) pathway.
Members of the FGF19 subfamily (FGF15, FGF19, FGF21, and FGF23) bind less tightly to heparan sulfates, and so can act in an endocrine fashion on far-away tissues, such as intestine, liver, kidney, adipose, and bone. For example:
- FGF15 and FGF19 (FGF15/19) are produced by intestinal cells but act on FGFR4-expressing liver cells to downregulate the key gene (CYP7A1) in the bile acid synthesis pathway.
- FGF23 is produced by bone but acts on FGFR1-expressing kidney cells to regulate the synthesis of vitamin D and phosphate homeostasis.
The crystal structures of HBGF1 have been solved and found to be related to interleukin 1-beta. Both families have the same 12-stranded beta-sheet structure, and the beta-sheets are arranged in 3 similar lobes around a central axis, 6 strands forming an anti-parallel beta-barrel. In general, the beta-sheets are well-preserved and the crystal structures superimpose in these areas. The intervening loops are less well-conserved - the loop between beta-strands 6 and 7 is slightly longer in interleukin-1 beta.
- Granulocyte-colony stimulating factor (G-CSF)
- Granulocyte-macrophage colony stimulating factor (GM-CSF)
- Nerve growth factor (NGF)
- Erythropoietin (EPO)
- Thrombopoietin (TPO)
- Myostatin (GDF-8)
- Growth Differentiation factor-9 (GDF9)
- Finklestein S.P., Plomaritoglou A. (2001). "Growth factors". In Miller L.P., Hayes R.L., eds. Co-edited by Newcomb J.K. Head Trauma: Basic, Preclinical, and Clinical Directions. New York: Wiley. pp. 165–187. ISBN 0-471-36015-5.
- Blaber M, DiSalvo J, Thomas KA (February 1996). "X-ray crystal structure of human acidic fibroblast growth factor". Biochemistry 35 (7): 2086–94. doi:10.1021/bi9521755. PMID 8652550.
- Ornitz DM, Itoh N (2001). "Fibroblast growth factors". Genome Biol. 2 (3): reviews3005.1–reviews3005.12. doi:10.1186/gb-2001-2-3-reviews3005. PMC 138918. PMID 11276432.
- Olsen SK, Garbi M, Zampieri N, Eliseenkova AV, Ornitz DM, Goldfarb M, Mohammadi M (2003). "Fibroblast growth factor (FGF) homologous factors share structural but not functional homology with FGFs". J. Biol. Chem. 278 (36): 34226–36. doi:10.1074/jbc.M303183200. PMID 12815063.
- Itoh N, Ornitz DM (January 2008). "Functional evolutionary history of the mouse Fgf gene family". Dev. Dyn. 237 (1): 18–27. doi:10.1002/dvdy.21388. PMID 18058912.
- Moore EE, Bendele AM, Thompson DL, Littau A, Waggie KS, Reardon B, Ellsworth JL (2005). "Fibroblast growth factor-18 stimulates chondrogenesis and cartilage repair in a rat model of injury-induced osteoarthritis". Osteoarthritis and Cartilage 13 (7): 623–631. doi:10.1016/j.joca.2005.03.003. PMID 15896984.
- Koga C, Adati N, Nakata K, Mikoshiba K, Furuhata Y, Sato S, Tei H, Sakaki Y, Kurokawa T, Shiokawa K, Yokoyama KK (August 1999). "Characterization of a novel member of the FGF family, XFGF-20, in Xenopus laevis". Biochemical and Biophysical Research Communications 261 (3): 756–65. doi:10.1006/bbrc.1999.1039. PMID 10441498.
- Kirikoshi H, Sagara N, Saitoh T, Tanaka K, Sekihara H, Shiokawa K, Katoh M (August 2000). "Molecular cloning and characterization of human FGF-20 on chromosome 8p21.3-p22". Biochemical and Biophysical Research Communications 274 (2): 337–43. doi:10.1006/bbrc.2000.3142. PMID 10913340.
- Potthoff MJ, Kliewer SA, Mangelsdorf DJ (2 February 2012). "Endocrine fibroblast growth factors 15/19 and 21: from feast to famine". Genes & Development 26 (4): 312–324. doi:10.1101/gad.184788.111. PMC 3289879. PMID 22302876.
- Fukumoto S (2008). "Actions and mode of actions of FGF19 subfamily members". Endocr. J. 55 (1): 23–31. doi:10.1507/endocrj.KR07E-002. PMID 17878606.
- Armelin HA (September 1973). "Pituitary extracts and steroid hormones in the control of 3T3 cell growth". Proc. Natl. Acad. Sci. U.S.A. 70 (9): 2702–6. Bibcode:1973PNAS...70.2702A. doi:10.1073/pnas.70.9.2702. PMC 427087. PMID 4354860.
- Gospodarowicz D (1974). "Localisation of a fibroblast growth factor and its effect alone and with hydrocortisone on 3T3 cell growth". Nature 249 (453): 123–7. Bibcode:1974Natur.249..123G. doi:10.1038/249123a0. PMID 4364816.
- Arese M, Chen Y, Florkiewicz RZ, Gualandris A, Shen B, Rifkin DB (1999). "Nuclear activities of basic fibroblast growth factor: potentiation of low-serum growth mediated by natural or chimeric nuclear localization signals". Mol. Biol. Cell 10 (5): 1429–44. doi:10.1091/mbc.10.5.1429. PMC 25296. PMID 10233154.
- Vlodavsky I, Korner G, Ishai-Michaeli R, Bashkin P, Bar-Shavit R, Fuks Z (1990). "Extracellular matrix-resident growth factors and enzymes: possible involvement in tumor metastasis and angiogenesis". Cancer Metastasis Rev 9 (3): 203–26. doi:10.1007/BF00046361. PMID 1705486.
- Green PJ, Walsh FS, Doherty P (1996). "Promiscuity of fibroblast growth factor receptors". BioEssays 18 (8): 639–46. doi:10.1002/bies.950180807. PMID 8760337.
- Böttcher RT, Niehrs C (2005). "Fibroblast growth factor signaling during early vertebrate development". Endocr. Rev. 26 (1): 63–77. doi:10.1210/er.2003-0040. PMID 15689573.
- Amaya E, Musci TJ, Kirschner MW (1991). "Expression of a dominant negative mutant of the FGF receptor disrupts mesoderm formation in Xenopus embryos". Cell 66 (2): 257–270. doi:10.1016/0092-8674(91)90616-7. PMID 1649700.
- Borland CZ, Schutzman JL, Stern MJ (2001). "Fibroblast growth factor signaling in Caenorhabditis elegans". BioEssays 23 (12): 1120–1130. doi:10.1002/bies.10007. PMID 11746231.
- Coumoul X, Deng CX (2003). "Roles of FGF receptors in mammalian development and congenital diseases". Birth Defects Res C Embryo Today 69 (4): 286–304. doi:10.1002/bdrc.10025. PMID 14745970.
- Sutherland D, Samakovlis C, Krasnow MA (1996). "Branchless encodes a Drosophila FGF homolog that controls tracheal cell migration and the pattern of branching". Cell 87 (6): 1091–1101. doi:10.1016/S0092-8674(00)81803-6. PMID 8978613.
- Gilbert SF. Developmental Biology. 10th edition. Sunderland (MA): Sinauer Associates; 2014. Early Development in Birds. Print
- Stegmann, TJ (May 1999). "New approaches to coronary heart disease: induction of neovascularisation by growth factors". BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy 11 (5): 301–8. doi:10.2165/00063030-199911050-00002. PMID 18031140.
- Cao R, Bråkenhielm E, Pawliuk R, Wariaro D, Post MJ, Wahlberg E, Leboulch P, Cao Y (2003). "Angiogenic synergism, vascular stability and improvement of hind-limb ischemia by a combination of PDGF-BB and FGF-2". Nature Medicine 9 (5): 604–13. doi:10.1038/nm848. PMID 12669032.
- Reuss B, von Bohlen und Halbach O (2003). "Fibroblast growth factors and their receptors in the central nervous system". Cell and Tissue Research 313 (2): 139–157. doi:10.1007/s00441-003-0756-7. PMID 12845521.
- Jones SA (2012). "Physiology of FGF15/19". Advances in experimental medicine and biology. Advances in Experimental Medicine and Biology 728: 171–82. doi:10.1007/978-1-4614-0887-1_11. ISBN 978-1-4614-0886-4. PMID 22396169.
- Razzaque MS (November 2009). "The FGF23-Klotho axis: endocrine regulation of phosphate homeostasis". Nature Reviews Endocrinology 5 (11): 611–9. doi:10.1038/nrendo.2009.196. PMC 3107967. PMID 19844248.
- Murzin AG, Lesk AM, Chothia C (January 1992). "beta-Trefoil fold. Patterns of structure and sequence in the Kunitz inhibitors interleukins-1 beta and 1 alpha and fibroblast growth factors". J. Mol. Biol. 223 (2): 531–43. doi:10.1016/0022-2836(92)90668-A. PMID 1738162.
- Eriksson AE, Cousens LS, Weaver LH, Matthews BW (April 1991). "Three-dimensional structure of human basic fibroblast growth factor". Proc. Natl. Acad. Sci. U.S.A. 88 (8): 3441–5. Bibcode:1991PNAS...88.3441E. doi:10.1073/pnas.88.8.3441. PMC 51463. PMID 1707542.
- Gimenez-Gallego G, Rodkey J, Bennett C, Rios-Candelore M, DiSalvo J, Thomas K (December 1985). "Brain-derived acidic fibroblast growth factor: complete amino acid sequence and homologies". Science 230 (4732): 1385–8. Bibcode:1985Sci...230.1385G. doi:10.1126/science.4071057. PMID 4071057.
- Fibroblast Growth Factors at the US National Library of Medicine Medical Subject Headings (MeSH)
- FGF1 in Cosmetic Products
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.
Fibroblast growth factor Provide feedback
Fibroblast growth factors are a family of proteins involved in growth and differentiation in a wide range of contexts. They are found in a wide range of organisms, from nematodes to humans . Most share an internal core region of high similarity, conserved residues in which are involved in binding with their receptors. On binding, they cause dimerisation of their tyrosine kinase receptors leading to intracellular signalling. There are currently four known tyrosine kinase receptors for fibroblast growth factors. These receptors can each bind several different members of this family. Members of this family have a beta trefoil structure. Most have N-terminal signal peptides and are secreted. A few lack signal sequences but are secreted anyway; still others also lack the signal peptide but are found on the cell surface and within the extracellular matrix. A third group remain intracellular . They have central roles in development, regulating cell proliferation, migration and differentiation. On the other hand, they are important in tissue repair following injury in adult organisms .
External database links
This tab holds annotation information from the InterPro database.
InterPro entry IPR002348The interleukin-1 (IL1) and heparin-binding growth factor (HBGF) families share low sequence similarity (about 25% [PUBMED:1849658]) but have very similar structures. Coupled with the Kunitz-type soybean trypsin inhibitors (STI), they form a structural superfamily. Despite their structural correspondence, however, they show no sequence similarity to the STI family. The crystal structures of interleukin-1 beta and HBGF1 have been solved, showing both families to have the same 12-stranded beta-sheet structure [PUBMED:1738162]; the beta-sheets are arranged in 3 similar lobes around a central axis, 6 strands forming an anti-parallel beta-barrel [PUBMED:1707542, PUBMED:4071057]. The beta-sheets are generally well preserved and the crystal structures superimpose in these areas. The intervening loops are less well conserved - the loop between beta-strands 6 and 7 is slightly longer in interleukin-1 beta.
The mapping between Pfam and Gene Ontology is provided by InterPro. If you use this data please cite InterPro.
|Molecular function||growth factor activity (GO:0008083)|
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:
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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.
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This family corresponds to a large set of related beta-trefoil proteins . The beta-trefoil is formed by six two-stranded hairpins . Three of these form a barrel structure and the other three are in a triangular array that caps the barrel. The arrangement of the secondary structures gives the molecules a pseudo 3-fold axis.
The clan contains the following 15 members:AbfB Agglutinin Botulinum_HA-17 CDtoxinA DUF569 Fascin FGF FRG1 IL1 Ins145_P3_rec Kunitz_legume MIR Ricin_B_lectin RicinB_lectin_2 Toxin_R_bind_C
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 using the family HMM. We also generate alignments using four representative proteomes (RP) sets, 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 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:
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You can download (or view in your browser) a text representation of a Pfam alignment in various formats:
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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.
MyHits provides a collection of tools to handle multiple sequence alignments. For example, one can refine a seed alignment (sequence addition or removal, re-alignment or manual edition) and then search databases for remote homologs using HMMER3.
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.
|Author:||Bateman A, Sonnhammer ELL|
|Number in seed:||77|
|Number in full:||1638|
|Average length of the domain:||113.10 aa|
|Average identity of full alignment:||32 %|
|Average coverage of the sequence by the domain:||52.07 %|
|HMM build commands:||
build method: hmmbuild -o /dev/null HMM SEED
search method: hmmsearch -Z 23193494 -E 1000 --cpu 4 HMM pfamseq
|Family (HMM) version:||13|
|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
- save a plain text representation of the tree
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 FGF domain has been found. There are 252 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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