Protein family

A protein family is a group of evolutionarily-related proteins. In many cases a protein family has a corresponding gene family, in which each gene encodes a corresponding protein with a 1:1 relationship. The term protein family should not be confused with family as it is used in taxonomy.

The human cyclophilin family, as represented by the structures of the isomerase domains of some of its members.

Proteins in a family descend from a common ancestor and typically have similar three-dimensional structures, functions, and significant sequence similarity. The most important of these is sequence similarity (usually amino acid sequence) since it is the strictest indicator of homology and therefore the clearest indicator of common ancestry. There is a fairly well developed framework for evaluating the significance of similarity between a group of sequences using sequence alignment methods. Proteins that do not share a common ancestor are very unlikely to show statistically significant sequence similarity, making sequence alignment a powerful tool for identifying the members of protein families.

Families are sometimes grouped together into larger clades called superfamilies based on structural and mechanistic similarity, even if there is no identifiable sequence homology.

Currently, over 60,000 protein families have been defined,[1] although ambiguity in the definition of protein family leads different researchers to wildly varying numbers.

Terminology and usage

As with many biological terms, the use of protein family is somewhat context dependent; it may indicate large groups of proteins with the lowest possible level of detectable sequence similarity, or very narrow groups of proteins with almost identical sequence, function, and three-dimensional structure, or any kind of group in-between. To distinguish between these situations, the term protein superfamily is often used for distantly related proteins whose relatedness is not detectable by sequence similarity, but only from shared structural features.[2][3][4] Other terms such as protein class, group, clan and sub-family have been coined over the years, but all suffer similar ambiguities of usage. A common usage is that superfamilies (structural homology) contain families (sequence homology) which contain sub-families. Hence a superfamily, such as the PA clan of proteases, has far lower sequence conservation than one of the families it contains, the C04 family. It is unlikely that an exact definition will be agreed and to it is up to the reader to discern exactly how these terms are being used in a particular context.

Above, sequence conservation of 250 members of the PA clan proteases (superfamily). Below, sequence conservation of 70 members of the C04 protease family. Arrows indicate catalytic triad residues. Aligned on the basis of structure by DALI

.

Protein domains and motifs

The concept of protein family was conceived at a time when very few protein structures or sequences were known; at that time, primarily small, single-domain proteins such as myoglobin, hemoglobin, and cytochrome c were structurally understood. Since that time, it was found that many proteins comprise multiple independent structural and functional units or domains. Due to evolutionary shuffling, different domains in a protein have evolved independently. This has led, in recent years, to a focus on families of protein domains. A number of online resources are devoted to identifying and cataloging such domains (see list of links at the end of this article).

Regions of each protein have differing functional constraints (features critical to the structure and function of the protein). For example, the active site of an enzyme requires certain amino acid residues to be precisely oriented in three dimensions. On the other hand, a protein–protein binding interface may consist of a large surface with constraints on the hydrophobicity or polarity of the amino acid residues. Functionally constrained regions of proteins evolve more slowly than unconstrained regions such as surface loops, giving rise to discernible blocks of conserved sequence when the sequences of a protein family are compared (see multiple sequence alignment). These blocks are most commonly referred to as motifs, although many other terms are used (blocks, signatures, fingerprints, etc.). Again, many online resources are devoted to identifying and cataloging protein motifs (see list at end of article).

Evolution of protein families

According to current consensus, protein families arise in two ways. Firstly, the separation of a parent species into two genetically isolated descendent species allows a gene/protein to independently accumulate variations (mutations) in these two lineages. This results in a family of orthologous proteins, usually with conserved sequence motifs. Secondly, a gene duplication may create a second copy of a gene (termed a paralog). Because the original gene is still able to perform its function, the duplicated gene is free to diverge and may acquire new functions (by random mutation). Certain gene/protein families, especially in eukaryotes, undergo extreme expansions and contractions in the course of evolution, sometimes in concert with whole genome duplications. This expansion and contraction of protein families is one of the salient features of genome evolution, but its importance and ramifications are currently unclear.

Phylogenetic tree of RAS superfamily. Tree was created using FigTree (Free online software).

Use and importance of protein families

As the total number of sequenced proteins increases and interest expands in proteome analysis, there is an ongoing effort to organize proteins into families and to describe their component domains and motifs. Reliable identification of protein families is critical to phylogenetic analysis, functional annotation, and the exploration of diversity of protein function in a given phylogenetic branch. The Enzyme Function Initiative (EFI) is using protein families and superfamilies as the basis for development of a sequence/structure-based strategy for large scale functional assignment of enzymes of unknown function.[5]

The algorithmic means for establishing protein families on a large scale are based on a notion of similarity. Most of the time the only similarity we have access to is sequence similarity.

Protein family resources

There are many biological databases that record examples of protein families and allow users to identify if newly identified proteins belong to a known family. Here are a few examples:

  • Pfam - Protein families database of alignments and HMMs
  • PROSITE - Database of protein domains, families and functional sites
  • PIRSF - SuperFamily Classification System
  • PASS2 - Protein Alignment as Structural Superfamilies v2 - PASS2@NCBS[6]
  • SUPERFAMILY - Library of HMMs representing superfamilies and database of (superfamily and family) annotations for all completely sequenced organisms
  • SCOP and CATH - classifications of protein structures into superfamilies, families and domains

Similarly many database-searching algorithms exist, for example:

  • BLAST - DNA sequence similarity search
  • BLASTp - Protein sequence similarity search
  • OrthoFinder: a fast, scalable and accurate method for clustering proteins into families (orthogroups) [7][8]


gollark: This is another maybe technically accurate (at an even greater stretch) but ridiculous interpretation. If people don't exist, it is not in fact possible to remove them.
gollark: This sort of thing makes natural languages quite annoying, but you can help by, well, not picking the most emotionally charged word which "technically matches".
gollark: If I say "that person is a criminal" you might very well have a worsened opinion of them, even if I know that all they actually did was jaywalking or something. It's technically not *false* to call them that but misleads.
gollark: Using a word which is technically right by a dictionary definition can be misleading because it has connotations which possible alternate choices of word don't.
gollark: They are important. Words aren't clear cut definitions like, say, mathematical objects, and the dictionary just points to some common uses.

See also

Protein families

References

  1. Kunin V, Cases I, Enright AJ, de Lorenzo V, Ouzounis CA (2003). "Myriads of protein families, and still counting". Genome Biology. 4 (2): 401. doi:10.1186/gb-2003-4-2-401. PMC 151299. PMID 12620116.
  2. Dayhoff MO (December 1974). "Computer analysis of protein sequences". Federation Proceedings. 33 (12): 2314–6. PMID 4435228.
  3. Dayhoff MO, McLaughlin PJ, Barker WC, Hunt LT (1975). "Evolution of sequences within protein superfamilies". Die Naturwissenschaften. 62 (4): 154–161. Bibcode:1975NW.....62..154D. doi:10.1007/BF00608697.
  4. Dayhoff MO (August 1976). "The origin and evolution of protein superfamilies". Federation Proceedings. 35 (10): 2132–8. PMID 181273.
  5. Gerlt JA, Allen KN, Almo SC, Armstrong RN, Babbitt PC, Cronan JE, Dunaway-Mariano D, Imker HJ, Jacobson MP, Minor W, Poulter CD, Raushel FM, Sali A, Shoichet BK, Sweedler JV (November 2011). "The Enzyme Function Initiative". Biochemistry. 50 (46): 9950–62. doi:10.1021/bi201312u. PMC 3238057. PMID 21999478.
  6. Gandhimathi A, Nair AG, Sowdhamini R (January 2012). "PASS2 version 4: an update to the database of structure-based sequence alignments of structural domain superfamilies". Nucleic Acids Research. 40 (Database issue): D531–4. doi:10.1093/nar/gkr1096. PMC 3245109. PMID 22123743.
  7. Emms DM, Kelly S (August 2015). "OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy". Genome Biology. 16: 157. doi:10.1186/s13059-015-0721-2. PMC 4531804. PMID 26243257.
  8. Emms DM, Kelly S (November 2019). "OrthoFinder: phylogenetic orthology inference for comparative genomics". Genome Biology. 20 (1): 238. doi:10.1186/s13059-019-1832-y. PMC 6857279. PMID 31727128.
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