Low complexity regions in proteins

Last updated

Low complexity regions (LCRs) in protein sequences, also defined in some contexts as compositionally biased regions (CBRs), are regions in protein sequences that differ from the composition and complexity of most proteins that is normally associated with globular structure. [1] [2] LCRs have different properties from normal regions regarding structure, function and evolution.

Contents

Structure

LCRs were originally thought to be unstructured and flexible linkers that served to separate the structured (and functional) domains of complex proteins, [3] but they are also capable of forming secondary structures, like helices (more often) and even sheets. [4] They may play a structural role in proteins such as collagens, myosin, keratins, silk, cell wall proteins. [5] Tandem repeats of short oligopeptides that are rich in glycine, proline, serine or threonine are capable of forming flexible structures that bind ligands under certain pH and temperature conditions. [6] Proline is a well-known alpha-helix breaker, however, amino acid repeats composed of proline may form poly-proline helices. [7]

Functions

LCRs were originally thought as ‘junk’ regions or as neutral linkers between domains; however, experimental and computational evidence increasingly indicates that they may play important adaptive and conserved roles, relevant to biotechnology, heterologous protein expression, medicine, as well as to our understanding of protein evolution. [8]

LCRs of eukaryotic proteins have been involved in human diseases, [9] [10] especially neurodegenerative ones, where they tend to form amyloids in humans and other eukaryotes. [11]

They have been reported to have adhesive roles, [12] function in excreted sticky proteins used for prey capture, [13] or have roles as transducers of molecular movement, e.g. in the prokaryotic TonB/TolA systems. [14]

LCRs may form surfaces for interaction with phospholipid bilayers, [15] or as positive charge clusters for DNA binding, [8] [16] [17] or as negative or even histidine-acidic charge clusters for coordinating calcium, magnesium or zinc ions. [8] [16]

They may also play important roles in protein translation, as tRNA ‘sponges’, slowing down translation in order to allow time for the correct folding of the nascent polypeptide chain. [18] They may even function as frame-shift checkpoints, by shifting to an unusual amino acid content that makes the protein highly unstable or insoluble, which in turn triggers fast recycling, before any further cellular damage. [19] [20]

Analyses on model and non-model eukaryotic proteomes have revealed that LCRs are frequently found in proteins involved in binding of nucleic acids (DNA or RNA), in transcription, receptor activity, development, reproduction and immunity whereas metabolic proteins are depleted of LCRs. [3] [21] [22] [23] A bioinformatics study of the Uniprot annotation of LCR containing proteins observed that 44% (9751/22259) of Bacterial and 44% (662/1521) of Archaeal LCRs are detected in proteins of unknown function, however, a significant number of proteins of known function (from many different species), especially those involved in translation and the ribosome, nucleic acid binding, metal-ion binding, and protein folding were also found to contain LCRs. [8]

Properties

LCRs are more abundant in eukaryotes, but they also have a significant presence in many prokaryotes. [8] On average, 0.05 and 0.07% of the bacterial and archaeal proteomes (total amino acids of LCRs in a given proteome/total amino acids of that proteome) form LCRs whereas for five model eukaryotic proteomes (human, fruitfly, yeast, fission yeast, Arabidopsis) this coverage was significantly higher (on average, 0.4%; between 2 and 23 times higher than prokaryotes). [8]

Eukaryotic LCRs tend to be longer than prokaryotic LCRs. [8] The average size of a eukaryotic LCR is 42 amino acids long, whereas bacterial, archaeal and phage LCRs are 38, 36 and 33 amino acids long, respectively. [8]

In the Archaea, the halobacterium Natrialba magadii has the highest number of LCRs and the highest enrichment for LCRs. [8] In Bacteria, Enhygromyxa salina, a delta proteobacterium that belongs to myxobacteria has the highest number of LCRs and the highest enrichment for LCRs. [8] Intriguingly, four of the top five bacteria with the highest enrichment for LCRs are also myxobacteria. [8]

The three most enriched amino acids within LCRs of Bacteria are proline, glycine and alanine, whereas in Archaea they are threonine, aspartate and proline. [8] In Phages, they are alanine, glycine and proline. [8] Glycine and proline emerge as very enriched amino acids in all three evolutionary lineages, whereas alanine is highly enriched in Bacteria and Phages but not enriched in Archaea. On the other hand, hydrophobic (M, I, L, V) and aromatic amino acids (F, Y, W) as well as cysteine, arginine and asparagine are heavily under-represented in LCRs. [8] Very similar trends for amino acids with a high (G, A, P, S, Q) and low (M, V, L, I, W, F, R, C) occurrence within LCRs have been observed in eukaryotes as well. [24] [21] This observed pattern of certain amino acids being over-represented (enriched for) or under-represented in LCRs could be partially explained by the energy cost for synthesis or metabolism of each of the amino acids. [8] Another possible explanation, which does not exclude the previous explanation of energy cost could be the reactivity of certain amino acids. [8] For example, Cysteine is a very reactive amino acid that would not be tolerated in high numbers within a small region of a protein. [25] Similarly, extremely hydrophobic regions can form non-specific protein–protein interactions among themselves and with other moderately hydrophobic regions [26] [27] in mammalian cells. Thus, their presence may disturb the balance of protein-protein interaction networks within the cell, especially if the carrier proteins are highly expressed. [8] A third explanation may be based on micro-evolutionary forces and, more specifically, on the bias of DNA polymerase slippage for certain di- tri- or tetra-nucleotides . [8]

Amino acid enrichment for certain functional categories of LCRs

A bioinformatics analysis of prokaryotic LCRs identified 5 types of amino acid enrichment, for certain functional categories of LCRs: [8]

Based on the above observations and analyses, a Neural Network webserver named LCR-hound has been developed to predict LCRs and their function. [8]

Evolution

LCRs are very interesting from a micro and macro evolutionary perspective. [8] They may be generated by DNA slippage, recombination and repair. [28] Thus, they are linked to recombination hotspots and may even possibly facilitate cross-over. [29] [30] By originating from genetic instability, they may cause, at the DNA level, a certain region of the protein to expand or contract and even cause frame-shifts (phase-variants) that affect microbial pathogenicity or provide raw material for evolution. [31] Most intriguingly, they may provide a window into the very early evolution of life. [8] [32] During early evolution, when only few amino acids were available and the primary genetic code was still expanding its repertoire, the first proteins were assumed to be short, repetitive and therefore, of low complexity. [33] [34] Thus, modern LCRs could represent primordial aspects of the evolution towards the protein world and may provide clues about the functions of the early proto-peptides. [8]

Most studies have focused on the evolution, functional and structural role of eukaryotic LCRs. [8] However, a comprehensive study of prokaryotic LCRs from many diverse prokaryotic lineages provides a unique opportunity to understanding the origin, evolution and nature of these regions. Due to the high effective population size and short generation times of prokaryotes, the de novo emergence of a mildly or moderately deleterious amino acid repeat or LCR should quickly be filtered out by strong selective forces. [8] This must be especially the case for LCRs found in highly expressed proteins, since they should also have a great impact on the energy burden of protein translation. [35] [36] Thus, any prokaryotic LCRs that constitute evolutionary accidents with no functional significance should not be fixed by genetic drift and consequently should not demonstrate any levels of conservation among moderately distant evolutionary relatives. [8] On the contrary, any LCR found among homologs of several moderately distant prokaryotic species should very probably reserve a functional role. [8]

LCRs and the protopeptides of the early genetic code

The amino acids with the highest frequency in LCRs are glycine and alanine, with their respective codons GGC and GCC being the most frequent, as well as complementary. [8] In eukaryotes and more specifically in chordates (such as human, mouse, chicken, zebrafish and sea squirt), alanine- and glycine-rich LCRs are over-represented in recently formed LCRs and probably are better tolerated by the cell. [37] Intriguingly, it has also been suggested that they represent the very first two amino acids [38] and codons [34] [39] [40] of the early genetic code. Thus, these two codons and their respective amino acids must have been constituents of the earliest oligopeptides, with a length of 10–55 amino acids [41] and very low complexity. Based on several different criteria and sources of data, Higgs and Pudritz [38] suggest G, A, D, E, V, S, P, I, L, T as the early amino acids of the genetic code. Trifonov's work largely agrees with this categorization and proposes that the early amino acids in chronological order are G, A, D, V, S, P, E, L, T, R. An evolutionary analysis observed that many of the amino acids of the suggested very early genetic code (with the exception of the hydrophobic ones) are significantly enriched in bacterial LCRs. [8] Most of the later additions to the genetic code are significantly under-represented in bacterial LCRs. [8] They thus hypothesize and propose that, in a cell-free environment, the early genetic code may have also produced low complexity oligo-peptides from valine and leucine. [8] However, later on, within a more complex cellular environment, these highly hydrophobic LCRs became inappropriate or even toxic from a protein interaction perspective and have been selected against ever since. [8] In addition, they further hypothesize that the very early protopeptides did not have a nucleic acid binding role, [8] because DNA and RNA-binding LCRs are highly enriched in glycine, arginine and lysine, however, arginine and lysine are not among the amino acids of the proposed early genetic code.

Detection methods

Low complexity regions in proteins can be computationally detected from sequence using various methods and definitions, as reviewed in. [2] Among the most popular methodologies to identify LCRs is by measuring their Shannon entropy. [1] The lower the value of the calculated entropy, the more homogeneous the region is in terms of amino acid content. In addition, a Neural Network webserver, LCR-hound has been developed to predict the function of an LCR, based on its amino acid or di-amino acid content. [8] Compression-based tools have also been used to perform such analysis providing higher sensitivity while mitigating the risk of overestimation inherent in other methods. [42]

Related Research Articles

<span class="mw-page-title-main">Amino acid</span> Organic compounds containing amine and carboxylic groups

Amino acids are organic compounds that contain both amino and carboxylic acid functional groups. Although over 500 amino acids exist in nature, by far the most important are the 22 α-amino acids incorporated into proteins. Only these 22 appear in the genetic code of life.

<span class="mw-page-title-main">Genetic code</span> Rules by which information encoded within genetic material is translated into proteins

The genetic code is the set of rules used by living cells to translate information encoded within genetic material into proteins. Translation is accomplished by the ribosome, which links proteinogenic amino acids in an order specified by messenger RNA (mRNA), using transfer RNA (tRNA) molecules to carry amino acids and to read the mRNA three nucleotides at a time. The genetic code is highly similar among all organisms and can be expressed in a simple table with 64 entries.

<span class="mw-page-title-main">Messenger RNA</span> RNA that is read by the ribosome to produce a protein

In molecular biology, messenger ribonucleic acid (mRNA) is a single-stranded molecule of RNA that corresponds to the genetic sequence of a gene, and is read by a ribosome in the process of synthesizing a protein.

<span class="mw-page-title-main">SH3 domain</span> Small protein domain found in some kinases and GTPases

The SRC Homology 3 Domain is a small protein domain of about 60 amino acid residues. Initially, SH3 was described as a conserved sequence in the viral adaptor protein v-Crk. This domain is also present in the molecules of phospholipase and several cytoplasmic tyrosine kinases such as Abl and Src. It has also been identified in several other protein families such as: PI3 Kinase, Ras GTPase-activating protein, CDC24 and cdc25. SH3 domains are found in proteins of signaling pathways regulating the cytoskeleton, the Ras protein, and the Src kinase and many others. The SH3 proteins interact with adaptor proteins and tyrosine kinases. Interacting with tyrosine kinases, SH3 proteins usually bind far away from the active site. Approximately 300 SH3 domains are found in proteins encoded in the human genome. In addition to that, the SH3 domain was responsible for controlling protein-protein interactions in the signal transduction pathways and regulating the interactions of proteins involved in the cytoplasmic signaling.

Non-coding DNA (ncDNA) sequences are components of an organism's DNA that do not encode protein sequences. Some non-coding DNA is transcribed into functional non-coding RNA molecules. Other functional regions of the non-coding DNA fraction include regulatory sequences that control gene expression; scaffold attachment regions; origins of DNA replication; centromeres; and telomeres. Some non-coding regions appear to be mostly nonfunctional, such as introns, pseudogenes, intergenic DNA, and fragments of transposons and viruses. Regions that are completely nonfunctional are called junk DNA.

The coding region of a gene, also known as the coding sequence (CDS), is the portion of a gene's DNA or RNA that codes for a protein. Studying the length, composition, regulation, splicing, structures, and functions of coding regions compared to non-coding regions over different species and time periods can provide a significant amount of important information regarding gene organization and evolution of prokaryotes and eukaryotes. This can further assist in mapping the human genome and developing gene therapy.

<span class="mw-page-title-main">Translation (biology)</span> Cellular process of protein synthesis

In biology, translation is the process in living cells in which proteins are produced using RNA molecules as templates. The generated protein is a sequence of amino acids. This sequence is determined by the sequence of nucleotides in the RNA. The nucleotides are considered three at a time. Each such triple results in addition of one specific amino acid to the protein being generated. The matching from nucleotide triple to amino acid is called the genetic code. The translation is performed by a large complex of functional RNA and proteins called ribosomes. The entire process is called gene expression.

<span class="mw-page-title-main">Single-nucleotide polymorphism</span> Single nucleotide in genomic DNA at which different sequence alternatives exist

In genetics and bioinformatics, a single-nucleotide polymorphism is a germline substitution of a single nucleotide at a specific position in the genome. Although certain definitions require the substitution to be present in a sufficiently large fraction of the population, many publications do not apply such a frequency threshold.

<span class="mw-page-title-main">Point mutation</span> Replacement, insertion, or deletion of a single DNA or RNA nucleotide

A point mutation is a genetic mutation where a single nucleotide base is changed, inserted or deleted from a DNA or RNA sequence of an organism's genome. Point mutations have a variety of effects on the downstream protein product—consequences that are moderately predictable based upon the specifics of the mutation. These consequences can range from no effect to deleterious effects, with regard to protein production, composition, and function.

<span class="mw-page-title-main">Leucine zipper</span> DNA-binding structural motif

A leucine zipper is a common three-dimensional structural motif in proteins. They were first described by Landschulz and collaborators in 1988 when they found that an enhancer binding protein had a very characteristic 30-amino acid segment and the display of these amino acid sequences on an idealized alpha helix revealed a periodic repetition of leucine residues at every seventh position over a distance covering eight helical turns. The polypeptide segments containing these periodic arrays of leucine residues were proposed to exist in an alpha-helical conformation and the leucine side chains from one alpha helix interdigitate with those from the alpha helix of a second polypeptide, facilitating dimerization.

A DNA-binding domain (DBD) is an independently folded protein domain that contains at least one structural motif that recognizes double- or single-stranded DNA. A DBD can recognize a specific DNA sequence or have a general affinity to DNA. Some DNA-binding domains may also include nucleic acids in their folded structure.

<span class="mw-page-title-main">Gene</span> Sequence of DNA or RNA that codes for an RNA or protein product

In biology, the word gene has two meanings. The Mendelian gene is a basic unit of heredity. The molecular gene is a sequence of nucleotides in DNA that is transcribed to produce a functional RNA. There are two types of molecular genes: protein-coding genes and non-coding genes.

Gene structure is the organisation of specialised sequence elements within a gene. Genes contain most of the information necessary for living cells to survive and reproduce. In most organisms, genes are made of DNA, where the particular DNA sequence determines the function of the gene. A gene is transcribed (copied) from DNA into RNA, which can either be non-coding (ncRNA) with a direct function, or an intermediate messenger (mRNA) that is then translated into protein. Each of these steps is controlled by specific sequence elements, or regions, within the gene. Every gene, therefore, requires multiple sequence elements to be functional. This includes the sequence that actually encodes the functional protein or ncRNA, as well as multiple regulatory sequence regions. These regions may be as short as a few base pairs, up to many thousands of base pairs long.

<span class="mw-page-title-main">DNA annotation</span> The process of describing the structure and function of a genome

In molecular biology and genetics, DNA annotation or genome annotation is the process of describing the structure and function of the components of a genome, by analyzing and interpreting them in order to extract their biological significance and understand the biological processes in which they participate. Among other things, it identifies the locations of genes and all the coding regions in a genome and determines what those genes do.

<span class="mw-page-title-main">Genome evolution</span> Process by which a genome changes in structure or size over time

Genome evolution is the process by which a genome changes in structure (sequence) or size over time. The study of genome evolution involves multiple fields such as structural analysis of the genome, the study of genomic parasites, gene and ancient genome duplications, polyploidy, and comparative genomics. Genome evolution is a constantly changing and evolving field due to the steadily growing number of sequenced genomes, both prokaryotic and eukaryotic, available to the scientific community and the public at large.

<span class="mw-page-title-main">Edward Trifonov</span> Israeli molecular biophysicist

Edward Nikolayevich Trifonov is a Russian-born Israeli molecular biophysicist and a founder of Israeli bioinformatics. In his research, he specializes in the recognition of weak signal patterns in biological sequences and is known for his unorthodox scientific methods.

Proline-rich protein 21 (PRR21) is a protein of the family of proline-rich proteins. It is encoded by the PRR21 gene, which is found on human chromosome 2, band 2q37.3. The gene exists in several species, both vertebrates and invertebrates, including humans. However, the protein have few conserved regions among species.

<span class="mw-page-title-main">Protein tandem repeats</span>

An array of protein tandem repeats is defined as several adjacent copies having the same or similar sequence motifs. These periodic sequences are generated by internal duplications in both coding and non-coding genomic sequences. Repetitive units of protein tandem repeats are considerably diverse, ranging from the repetition of a single amino acid to domains of 100 or more residues.

CIMAP1C is a gene in humans that encodes the CIMAP1C protein. It is also often referred to as ODF3L1. CIMAP1C is expressed in low levels throughout the body with high expression levels in the testes. It is highly conserved in mammals and reptiles but not present in birds or amphibians, indicating it arose around 300 million years ago.

References

  1. 1 2 Wootton JC (September 1994). "Non-globular domains in protein sequences: Automated segmentation using complexity measures". Computers & Chemistry. 18 (3): 269–285. doi:10.1016/0097-8485(94)85023-2. PMID   7952898.
  2. 1 2 Mier P, Paladin L, Tamana S, Petrosian S, Hajdu-Soltész B, Urbanek A, Gruca A, Plewczynski D, Grynberg M, Bernadó P, Gáspári Z, Ouzounis CA, Promponas VJ, Kajava AV, Hancock JM, Tosatto SC, Dosztanyi Z, Andrade-Navarro MA (30 January 2019). "Disentangling the complexity of low complexity proteins". Brief Bioinform. 21 (2): 458–472. doi: 10.1093/bib/bbz007 . PMC   7299295 . PMID   30698641.
  3. 1 2 Huntley MA, Golding GB (2002-07-01). "Simple sequences are rare in the Protein Data Bank". Proteins: Structure, Function, and Genetics. 48 (1): 134–140. doi:10.1002/prot.10150. ISSN   0887-3585. PMID   12012345. S2CID   42193081.
  4. Kumari B, Kumar R, Kumar M (2015). "Low complexity and disordered regions of proteins have different structural and amino acid preferences". Molecular BioSystems. 11 (2): 585–594. doi:10.1039/C4MB00425F. ISSN   1742-206X. PMID   25468592.
  5. Luo H, Nijveen H (2014-07-01). "Understanding and identifying amino acid repeats". Briefings in Bioinformatics. 15 (4): 582–591. doi:10.1093/bib/bbt003. ISSN   1467-5463. PMC   4103538 . PMID   23418055.
  6. Matsushima N, Yoshida H, Kumaki Y, Kamiya M, Tanaka T, Kretsinger YI (2008-11-30). "Flexible Structures and Ligand Interactions of Tandem Repeats Consisting of Proline, Glycine, Asparagine, Serine, and/or Threonine Rich Oligopeptides in Proteins". Current Protein & Peptide Science. 9 (6): 591–610. doi:10.2174/138920308786733886. PMID   19075749 . Retrieved 2020-11-03.
  7. Adzhubei AA, Sternberg MJ, Makarov AA (June 2013). "Polyproline-II Helix in Proteins: Structure and Function". Journal of Molecular Biology. 425 (12): 2100–2132. doi:10.1016/j.jmb.2013.03.018. PMID   23507311.
  8. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 Ntountoumi C, Vlastaridis P, Mossialos D, Stathopoulos C, Iliopoulos I, Promponas V, Oliver SG, Amoutzias GD (2019-11-04). "Low complexity regions in the proteins of prokaryotes perform important functional roles and are highly conserved". Nucleic Acids Research. 47 (19): 9998–10009. doi:10.1093/nar/gkz730. ISSN   0305-1048. PMC   6821194 . PMID   31504783. CC-BY icon.svg Text was copied from this source, which is available under a Creative Commons Attribution 4.0 International License.
  9. Karlin S, Brocchieri L, Bergman A, Mrazek J, Gentles AJ (2002-01-08). "Amino acid runs in eukaryotic proteomes and disease associations". Proceedings of the National Academy of Sciences. 99 (1): 333–338. Bibcode:2002PNAS...99..333K. doi: 10.1073/pnas.012608599 . ISSN   0027-8424. PMC   117561 . PMID   11782551.
  10. Mirkin SM (2007-06-21). "Expandable DNA repeats and human disease". Nature. 447 (7147): 932–940. Bibcode:2007Natur.447..932M. doi:10.1038/nature05977. ISSN   0028-0836. PMID   17581576. S2CID   4397592.
  11. Kumari B, Kumar R, Chauhan V, Kumar M (2018-10-30). "Comparative functional analysis of proteins containing low-complexity predicted amyloid regions". PeerJ. 6: e5823. doi: 10.7717/peerj.5823 . ISSN   2167-8359. PMC   6214233 . PMID   30397544.
  12. So CR, Fears KP, Leary DH, Scancella JM, Wang Z, Liu JL, Orihuela B, Rittschof D, Spillmann CM, Wahl KJ (2016-11-08). "Sequence basis of Barnacle Cement Nanostructure is Defined by Proteins with Silk Homology". Scientific Reports. 6 (1): 36219. Bibcode:2016NatSR...636219S. doi:10.1038/srep36219. ISSN   2045-2322. PMC   5099703 . PMID   27824121.
  13. Haritos VS, Niranjane A, Weisman S, Trueman HE, Sriskantha A, Sutherland TD (2010-11-07). "Harnessing disorder: onychophorans use highly unstructured proteins, not silks, for prey capture". Proceedings of the Royal Society B: Biological Sciences. 277 (1698): 3255–3263. doi:10.1098/rspb.2010.0604. ISSN   0962-8452. PMC   2981920 . PMID   20519222.
  14. Brewer S, Tolley M, Trayer I, Barr G, Dorman C, Hannavy K, Higgins C, Evans J, Levine B, Wormald M (1990-12-20). "Structure and function of X-Pro dipeptide repeats in the TonB proteins of Salmonella typhimurium and Escherichia coli". Journal of Molecular Biology. 216 (4): 883–895. doi:10.1016/S0022-2836(99)80008-4. PMID   2266560.
  15. Robison AD, Sun S, Poyton MF, Johnson GA, Pellois JP, Jungwirth P, Vazdar M, Cremer PS (2016-09-08). "Polyarginine Interacts More Strongly and Cooperatively than Polylysine with Phospholipid Bilayers". The Journal of Physical Chemistry B. 120 (35): 9287–9296. doi:10.1021/acs.jpcb.6b05604. ISSN   1520-6106. PMC   5912336 . PMID   27571288.
  16. 1 2 Zhu ZY, Karlin S (1996-08-06). "Clusters of charged residues in protein three-dimensional structures". Proceedings of the National Academy of Sciences. 93 (16): 8350–8355. Bibcode:1996PNAS...93.8350Z. doi: 10.1073/pnas.93.16.8350 . ISSN   0027-8424. PMC   38674 . PMID   8710874.
  17. Kushwaha AK, Grove A (2013-02-01). "C-terminal low-complexity sequence repeats of Mycobacterium smegmatis Ku modulate DNA binding". Bioscience Reports. 33 (1): 175–84. doi:10.1042/BSR20120105. ISSN   0144-8463. PMC   3553676 . PMID   23167261.
  18. Frugier M, Bour T, Ayach M, Santos MA, Rudinger-Thirion J, Théobald-Dietrich A, Pizzi E (2010-01-21). "Low Complexity Regions behave as tRNA sponges to help co-translational folding of plasmodial proteins". FEBS Letters. 584 (2): 448–454. doi: 10.1016/j.febslet.2009.11.004 . PMID   19900443. S2CID   24172658.
  19. Tyedmers J, Mogk A, Bukau B (November 2010). "Cellular strategies for controlling protein aggregation". Nature Reviews Molecular Cell Biology. 11 (11): 777–788. doi:10.1038/nrm2993. ISSN   1471-0072. PMID   20944667. S2CID   22449895.
  20. Ling J, Cho C, Guo LT, Aerni HR, Rinehart J, Söll D (2012-12-14). "Protein Aggregation Caused by Aminoglycoside Action Is Prevented by a Hydrogen Peroxide Scavenger". Molecular Cell. 48 (5): 713–722. doi:10.1016/j.molcel.2012.10.001. PMC   3525788 . PMID   23122414.
  21. 1 2 Haerty W, Golding GB (October 2010). Bonen L (ed.). "Low-complexity sequences and single amino acid repeats: not just "junk" peptide sequences". Genome. 53 (10): 753–762. doi:10.1139/G10-063. ISSN   0831-2796. PMID   20962881.
  22. Faux NG (2005-03-21). "Functional insights from the distribution and role of homopeptide repeat-containing proteins". Genome Research. 15 (4): 537–551. doi:10.1101/gr.3096505. ISSN   1088-9051. PMC   1074368 . PMID   15805494.
  23. Albà M, Tompa P, Veitia R (2007), Volff JN (ed.), "Amino Acid Repeats and the Structure and Evolution of Proteins", Genome Dynamics, 3, Basel: KARGER: 119–130, doi:10.1159/000107607, ISBN   978-3-8055-8340-4, PMID   18753788 , retrieved 2020-11-03
  24. Marcotte EM, Pellegrini M, Yeates TO, Eisenberg D (1999-10-15). "A census of protein repeats". Journal of Molecular Biology. 293 (1): 151–160. doi:10.1006/jmbi.1999.3136. PMID   10512723.
  25. Marino SM, Gladyshev VN (2012-02-10). "Analysis and Functional Prediction of Reactive Cysteine Residues". Journal of Biological Chemistry. 287 (7): 4419–4425. doi: 10.1074/jbc.R111.275578 . ISSN   0021-9258. PMC   3281665 . PMID   22157013.
  26. Dorsman JC (2002-06-15). "Strong aggregation and increased toxicity of polyleucine over polyglutamine stretches in mammalian cells". Human Molecular Genetics. 11 (13): 1487–1496. doi: 10.1093/hmg/11.13.1487 . PMID   12045202.
  27. Oma Y, Kino Y, Sasagawa N, Ishiura S (2004-05-14). "Intracellular Localization of Homopolymeric Amino Acid-containing Proteins Expressed in Mammalian Cells". Journal of Biological Chemistry. 279 (20): 21217–21222. doi: 10.1074/jbc.M309887200 . ISSN   0021-9258. PMID   14993218. S2CID   23798438.
  28. Ellegren H (2004-06-01). "Microsatellites: simple sequences with complex evolution". Nature Reviews Genetics. 5 (6): 435–445. doi:10.1038/nrg1348. ISSN   1471-0056. PMID   15153996. S2CID   11975343.
  29. Verstrepen KJ, Jansen A, Lewitter F, Fink GR (2005-09-01). "Intragenic tandem repeats generate functional variability". Nature Genetics. 37 (9): 986–990. doi:10.1038/ng1618. ISSN   1061-4036. PMC   1462868 . PMID   16086015.
  30. Siwach P, Pophaly SD, Ganesh S (2006-07-01). "Genomic and Evolutionary Insights into Genes Encoding Proteins with Single Amino Acid Repeats". Molecular Biology and Evolution. 23 (7): 1357–1369. doi: 10.1093/molbev/msk022 . ISSN   1537-1719. PMID   16618963.
  31. Moxon R, Bayliss C, Hood D (2006-12-01). "Bacterial Contingency Loci: The Role of Simple Sequence DNA Repeats in Bacterial Adaptation". Annual Review of Genetics. 40 (1): 307–333. doi:10.1146/annurev.genet.40.110405.090442. ISSN   0066-4197. PMID   17094739.
  32. Toll-Riera M, Rado-Trilla N, Martys F, Alba MM (2012-03-01). "Role of Low-Complexity Sequences in the Formation of Novel Protein Coding Sequences". Molecular Biology and Evolution. 29 (3): 883–886. doi: 10.1093/molbev/msr263 . ISSN   0737-4038. PMID   22045997.
  33. Ohno S, Epplen JT (1983-06-01). "The primitive code and repeats of base oligomers as the primordial protein-encoding sequence". Proceedings of the National Academy of Sciences. 80 (11): 3391–3395. Bibcode:1983PNAS...80.3391O. doi: 10.1073/pnas.80.11.3391 . ISSN   0027-8424. PMC   394049 . PMID   6574491.
  34. 1 2 Trifonov EN (September 2009). "The origin of the genetic code and of the earliest oligopeptides". Research in Microbiology. 160 (7): 481–486. doi:10.1016/j.resmic.2009.05.004. PMID   19524038.
  35. Akashi H, Gojobori T (2002-03-19). "Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis". Proceedings of the National Academy of Sciences. 99 (6): 3695–3700. Bibcode:2002PNAS...99.3695A. doi: 10.1073/pnas.062526999 . ISSN   0027-8424. PMC   122586 . PMID   11904428.
  36. Barton MD, Delneri D, Oliver SG, Rattray M, Bergman CM (2010-08-17). Bähler J (ed.). "Evolutionary Systems Biology of Amino Acid Biosynthetic Cost in Yeast". PLOS ONE. 5 (8): e11935. Bibcode:2010PLoSO...511935B. doi: 10.1371/journal.pone.0011935 . ISSN   1932-6203. PMC   2923148 . PMID   20808905.
  37. Radó-Trilla N, Albà M (2012). "Dissecting the role of low-complexity regions in the evolution of vertebrate proteins". BMC Evolutionary Biology. 12 (1): 155. Bibcode:2012BMCEE..12..155R. doi: 10.1186/1471-2148-12-155 . ISSN   1471-2148. PMC   3523016 . PMID   22920595.
  38. 1 2 Higgs PG, Pudritz RE (June 2009). "A Thermodynamic Basis for Prebiotic Amino Acid Synthesis and the Nature of the First Genetic Code". Astrobiology. 9 (5): 483–490. arXiv: 0904.0402 . Bibcode:2009AsBio...9..483H. doi:10.1089/ast.2008.0280. ISSN   1531-1074. PMID   19566427. S2CID   9039622.
  39. Trifonov E (2000-12-30). "Consensus temporal order of amino acids and evolution of the triplet code". Gene. 261 (1): 139–151. doi:10.1016/S0378-1119(00)00476-5. PMID   11164045.
  40. Trifonov EN (2004-08-01). "The Triplet Code From First Principles". Journal of Biomolecular Structure and Dynamics. 22 (1): 1–11. doi:10.1080/07391102.2004.10506975. ISSN   0739-1102. PMID   15214800. S2CID   28509952.
  41. Ferris JP, Hill AR, Liu R, Orgel LE (1996-05-02). "Synthesis of long prebiotic oligomers on mineral surfaces". Nature. 381 (6577): 59–61. Bibcode:1996Natur.381...59F. doi:10.1038/381059a0. hdl: 2060/19980119839 . ISSN   0028-0836. PMID   8609988. S2CID   4351826.
  42. Silva JM, Qi W, Pinho AJ, Pratas D (2022-12-28). "AlcoR: alignment-free simulation, mapping, and visualization of low-complexity regions in biological data". GigaScience. 12. doi:10.1093/gigascience/giad101. ISSN   2047-217X. PMC   10716826 . PMID   38091509.