Difference between revisions of "Werner Syndrome"
Line 75: | Line 75: | ||
For the Structural Biologist involved in the study of proteins and interested in structure-function relationships or comparative modeling, an accurate alignment is as important as a significant similarity between the sequences [56]. This justifies that, while studying protein structures, one should be careful and dedicate efforts to the generation and analysis of such alignments. In this context, a sequence alignment can be defined as a method of comparison that takes into account typical conservations, substitutions, insertions and deletions of amino acids and represents those in a graphical format. In general, amino acids substitutions not related to changes in physico-chemical properties are considered as conservatives of protein function and structure. On the other hand, when a substitution leads to physico-chemical changes it is frequently non-conservative (although exceptions can be observed to both rules). For this reason, when evaluating the conservation of the structure and function of a protein from its amino acids substitutions, one should be capable of evaluating the relation between this residues. This can be accomplished, for example, by grouping amino acids together according to their properties in a Venn diagram (figure 1). In this context, an optimal alignment can be defined as the one with highest score, given a certain scoring system that considers these characteristics. |
For the Structural Biologist involved in the study of proteins and interested in structure-function relationships or comparative modeling, an accurate alignment is as important as a significant similarity between the sequences [56]. This justifies that, while studying protein structures, one should be careful and dedicate efforts to the generation and analysis of such alignments. In this context, a sequence alignment can be defined as a method of comparison that takes into account typical conservations, substitutions, insertions and deletions of amino acids and represents those in a graphical format. In general, amino acids substitutions not related to changes in physico-chemical properties are considered as conservatives of protein function and structure. On the other hand, when a substitution leads to physico-chemical changes it is frequently non-conservative (although exceptions can be observed to both rules). For this reason, when evaluating the conservation of the structure and function of a protein from its amino acids substitutions, one should be capable of evaluating the relation between this residues. This can be accomplished, for example, by grouping amino acids together according to their properties in a Venn diagram (figure 1). In this context, an optimal alignment can be defined as the one with highest score, given a certain scoring system that considers these characteristics. |
||
− | The first computer programs capable of computing biological comparison of sequences in a reasonable amount of time were originated more than 25 years ago. From this point on, the process of inferring homology from sequence similarity became routine and considerably more reliable. |
+ | The first computer programs capable of computing biological comparison of sequences in a reasonable amount of time were originated more than 25 years ago. From this point on, the process of inferring homology from sequence similarity became routine and considerably more reliable. However, despite the fact that sequence alignment is a well established method, homology inference from sequence similarity can be rather controversial. For this reason, to infeer homology between two proteins, one should not only consider the similarity between those, but also evaluate how likely is that the proteins are actually biologically related [56]. Usually, a 30% sequence similarity is considered an accurate cut-off above which two proteins can be considered possible homologues. The second step then is to conclude that this similarity is not a result of a convergence from evolutionary unrelated origins. To guide this evaluation one can take advantage of specific features of related sequences that can be recognized by mathematical models and well distinguished from what is observed in randomly generated sequences relationships [57]. In 2005, Pearson and Sterk presented important conclusions that include: i) ii) |
+ | Conclusões apresentadas por Pearson e Sterk em seu artigo de 2005 [56] são: i) pontuações |
||
+ | |||
+ | atribuídas à alinhamentos de sequências não-relacionadas são indistinguíveis de pontuações |
||
+ | |||
+ | atribuídas à alinhamentos de sequências geradas de forma aleatória; ii) se uma pontuação |
||
+ | |||
(To be continued) |
(To be continued) |
Revision as of 13:15, 19 May 2011
Contents
ABOUT THIS WIKI
This Wiki Page was created and it is maintained by Mainá Bitar for the "Protein Structure and Function Analysis Practical" of 2011 (SS).
WERNER SYNDROME
You can Download a PDF version of this information here: Media:WS.pdf.
Introduction
The Werner Syndrome (WS) is an autosomal recessive disorder, also known as Adult Progeria. The syndrome was described for the first time in 1904 by Otto Werner (and therefore, named after him), in his PhD thesis entitled “Über katarakt in Verbindung mit Sklerodermie” (which can be translated to “About cataracts connected to sclerodermia”). In the first 90 years of research concerning WS, over 1000 patients were reported, 75% of which were Japanese descent (figure 1) [1]. WS is one of the several types of segmental progeroid syndromes, which affect multiple tissues and organs (on the other hand, unimodal syndromes predominantly affect a single organ) [2].
Figure 1: Distribution of Werner Syndrome by nationality as registered from 1904 until 1994 [1]. All countries with at least one patient is shaded.
Symptoms
As one can expect, the most notable symptoms of WS mimic the background of the most general condition called Progeria, with a complex phenotype of accelerated aging. The patients prematurely acquire the appearance of someone several decades older, accompanied by loss or graying of hair, scleroderma-like skin and voice alterations, usually around the second or third decade of life [3]. The phenotype of WS was previously summarized as a “caricature of aging” [1]. In general, the subjects develop normally until adolescence, when there is absence of the common growth spurt. The clinical manifestations usually include atherosclerosis, osteoporosis, diabetes, lenticular cataracts, heart failure, cancer and other age-related conditions that appear during early adulthood, following puberty (figure 2) [1, 2]. The typical cause of death is cancer or cardiovascular disease, often occurring between the fourth and fifth decades of life. While in 1966, the median age of death was 47 years [4], in 1997, Makoto Goto reported a surprising median age of death of 54 years [2]. At the cellular level, a reduction in the replicative rate is often observed (cellular senescence) and genomic instability is present in the form of chromosome breaks and translocations, as well as large deletions at the molecular level. A higher occurrence of somatic mutations is also related to the syndrome [1-4].
Figure 2: Appearance of symptoms in Werner Syndrome patients. The horizontal axis represents the average age at which each clinical manifestation occurs, according to Makoto Goto in his study from 1997 [1].
Related Gene and Protein
The gene related to WS (WRN) was identified as located in the chromosome 8p12 and cloned for the first time in 1996 [5] and pointed as homologous to members of the DNA helicase family. Later on, the protein was shown to catalyze DNA unwinding, as expected [5]. The protein was predicted to have 1,432 amino acids and 35 exons, from which 34 are protein coding. At first, four mutations at this gene were identified in WS patients, all correlated to truncated proteins of no more than 1,250 amino acids. The mutated proteins were shorter, but did not present any effects on the helicase domain itself, which is situated between amino acids 569 and 859. Five additional mutations were identified shortly after, being two nonsense mutations, one mutation at a splice-junction site and a deletion leading to a frameshift [3]. The majority of these mutations directly affect the helicase domain, two of those are located within the domain and other two lead to its loss with truncated proteins.
The WRN gene can be divided into three distinct regions. The N-terminal portion, comprising codons 1-539 is mainly acid and first it was described as presenting no homology to known genes. Currently, this region is known to contain an exonuclease domain, an unusual feature among members of this protein family [6]. Similar high concentration of acidic residues are also observed in other DNA repair-deficiency disorders. The median portion of the gene, from codon 540 to 963 is closely related to other helicases from several organisms, presenting all seven conserved motifs that characterize the protein. The C-terminal end of the WRN gene enclosures a nuclear localization signal (NLS) [7]. Two additional domains are found between the helicase domain and the NLS, namely a RecQ helicase conserved region (RQC) and a helicase RNaseD C-terminal conserved region (HDRC, figure 3) [2]. The WRN protein is likely to act on DNA repair, recombination and replication as well as in the maintenance of telomeres.
Figure 3: Basic structure of the WRN gene, with known domains highlighted according to description made by Friedrich et al. [2].
The majority of the 60 first described mutations associated to the occurrence of WS are related to the loss of the NLS, causing the protein to accumulate outside the nucleus and therefore be incapable of performing its function [2]. Nevertheless, in the past year, 18 new mutations were reported, yielding a total of 71 WRN disease associated mutations identified in clinically diagnosed patients (table 1) [2].
Table 1: Mutations of the WRN gene associated to the Werner Syndrome, according to the mutation report by Friedrick et al., 2010. The total number of known mutations by class is given [2].
References
1. Goto M (1997). Hierarchical deterioration of body systems in Werner’s syndrome: Implications for normal ageing. Mechanisms of Ageing and Development, 98:239–254
2. Friedrich K, Lee L, Leistritz DF, Nurnberg G, Saha B, Hisama FM, Eyman DK, Lessel D, Nurnberg P, Li C, Garcia FVMJ, Kets CM, Schmidtke J, Cruz VT, Van den Akker PC, Boak J, Peter D, Compoginis G, Cefle K, Ozturk S, Lopez N, Wessel T, Poot M, Ippel PF, Groff-Kellermann B, Hoehn H, Martin GM, Kubisch C and Oshima J (2010). WRN mutations in Werner syndrome patients: genomic rearrangements, unusual intronic mutations and ethnic-specific alterations. Human Genetics, 128:103-11
3. Yu CE, Oshima J, Wijsman EM, Nakura J, Miki T, Piussan C, Matthews S, Fu YH, Mulligan J, Martin GM, Schellenberg GD and the Werner's Syndrome Collaborative Group (1997). Mutations in the consensus helicase domains of the Werner Syndrome gene. The American Society of Human Genetics, 60:330-341
4. Epstein CJ, Martin GM, Schultz AL, Motulsky AG (1966). Werner's syndrome: a review of its symptomatology, natural history, pathologic features, genetics and relationship to the natural aging process. Medicine, 45:177-221
5. Yu CE, Oshima J, Fu YH, Wijsman EM, Hisama F, Alisch R, Matthews S, Nakura J, Miki T, Ouais S, Martin GM, Mulligan J, Schellenberg GD (1996). Positional cloning of the Werner’s syndrome gene. Science, 272:258–262
6. Huang S, Li B, Gray MD, Oshima J, Mian IS, Campisi J (1998) The premature ageing syndrome protein, WRN, is a 3' → 5' exonuclease. Nature Genetics, 20:114–116
7. Suzuki T, Shiratori M, Furuichi Y, Matsumoto T (2001). Diverged nuclear localization of Werner helicase in human and mouse cells. Oncogene, 20:2551-2558
A. Huang S, Lee L, Hanson NB, Lenaerts C, Hoehn H, Poot M, Rubin CD, Chen DF, Yang CC, Juch H, Dorn T, Spiegel R, Oral EA, Abid M, Battisti C, Lucci-Cordisco E, Neri G, Steed EH, Kidd A, Isley W, Showalter D, Vittone JL, Konstantinow A, Ring J, Meyer P, Wenger SL, von Herbay A, Wollina U, Schuelke M, Huizenga CR, Leistritz DF, Martin GM, Mian IS and Oshima J (2006). The spectrum of WRN mutations in Werner syndrome patients. Human Mutation, 27:558-567
SEQUENCE ALIGNMENT
17.05
About Sequence Alignments
For the Structural Biologist involved in the study of proteins and interested in structure-function relationships or comparative modeling, an accurate alignment is as important as a significant similarity between the sequences [56]. This justifies that, while studying protein structures, one should be careful and dedicate efforts to the generation and analysis of such alignments. In this context, a sequence alignment can be defined as a method of comparison that takes into account typical conservations, substitutions, insertions and deletions of amino acids and represents those in a graphical format. In general, amino acids substitutions not related to changes in physico-chemical properties are considered as conservatives of protein function and structure. On the other hand, when a substitution leads to physico-chemical changes it is frequently non-conservative (although exceptions can be observed to both rules). For this reason, when evaluating the conservation of the structure and function of a protein from its amino acids substitutions, one should be capable of evaluating the relation between this residues. This can be accomplished, for example, by grouping amino acids together according to their properties in a Venn diagram (figure 1). In this context, an optimal alignment can be defined as the one with highest score, given a certain scoring system that considers these characteristics.
The first computer programs capable of computing biological comparison of sequences in a reasonable amount of time were originated more than 25 years ago. From this point on, the process of inferring homology from sequence similarity became routine and considerably more reliable. However, despite the fact that sequence alignment is a well established method, homology inference from sequence similarity can be rather controversial. For this reason, to infeer homology between two proteins, one should not only consider the similarity between those, but also evaluate how likely is that the proteins are actually biologically related [56]. Usually, a 30% sequence similarity is considered an accurate cut-off above which two proteins can be considered possible homologues. The second step then is to conclude that this similarity is not a result of a convergence from evolutionary unrelated origins. To guide this evaluation one can take advantage of specific features of related sequences that can be recognized by mathematical models and well distinguished from what is observed in randomly generated sequences relationships [57]. In 2005, Pearson and Sterk presented important conclusions that include: i) ii) Conclusões apresentadas por Pearson e Sterk em seu artigo de 2005 [56] são: i) pontuações
atribuídas à alinhamentos de sequências não-relacionadas são indistinguíveis de pontuações
atribuídas à alinhamentos de sequências geradas de forma aleatória; ii) se uma pontuação
(To be continued)