scholarly journals DAVI: a tool for clustering and visualising protein domain architectures

2021 ◽  
Author(s):  
Nathan Jawadi Chadi ◽  
Paul Saighi ◽  
Fabio Rocha Jimenez Vieira ◽  
Juliana Silva Bernardes

The characterization of protein functions is one of the main challenges in bioinformatics. Proteins are often composed of individual units termed domains, motifs that can evolve independently. The domain architecture of a given protein is the particular order and the content of its numerous domains. Some computational approaches predict the most likely domain architecture for a set of proteins. However, a few numbers of visualization tools exist, and most of them are unavailable. Here we present DAVI, an efficient and user-friendly web server for protein domain architecture clustering and visualization. DAVI accepts the output of most used domain architecture prediction tools and also produces domain architectures for a set of protein sequences. It provides a rich visualization for comparing, analyzing, and visualizing domain architectures.

2020 ◽  
Vol 48 (W1) ◽  
pp. W72-W76 ◽  
Author(s):  
Vadim M Gumerov ◽  
Igor B Zhulin

Abstract Key steps in a computational study of protein function involve analysis of (i) relationships between homologous proteins, (ii) protein domain architecture and (iii) gene neighborhoods the corresponding proteins are encoded in. Each of these steps requires a separate computational task and sets of tools. Currently in order to relate protein features and gene neighborhoods information to phylogeny, researchers need to prepare all the necessary data and combine them by hand, which is time-consuming and error-prone. Here, we present a new platform, TREND (tree-based exploration of neighborhoods and domains), which can perform all the necessary steps in automated fashion and put the derived information into phylogenomic context, thus making evolutionary based protein function analysis more efficient. A rich set of adjustable components allows a user to run the computational steps specific to his task. TREND is freely available at http://trend.zhulinlab.org.


2012 ◽  
Vol 12 (1) ◽  
pp. 6 ◽  
Author(s):  
Xue-Cheng Zhang ◽  
Zheng Wang ◽  
Xinyan Zhang ◽  
Mi Ha Le ◽  
Jianguo Sun ◽  
...  

2013 ◽  
Vol 58 (1) ◽  
Author(s):  
Anna Siwińska ◽  
Piotr Bąska ◽  
Emilia Daniłowicz-Luebert ◽  
Kamil Januszkiewicz ◽  
Ewa Długosz ◽  
...  

AbstractAncylostoma ceylanicum belongs to a group of soil-transmitted helminths, which infect almost 576 mln people worldwide and are a major cause of anaemia and malnutrition. Upon contact with a permissive host, third-stage larvae (L3) residing in the environment become activated larvae (ssL3), a process associated with changes in the profile of gene expression. Ancylostoma secreted proteins (ASPs) are the major proteins secreted during larvae activation and play a crucial role in hookworm adaptation to parasitism. Here we report the cloning using RACE-PCR technique of three novel ASPs from the hookworm A. ceylanicum (Ace-asp-3, Ace-asp-4, and Ace-asp-5) and computational analysis of the protein sequences. All three proteins contain SCP (Sperm Coating Protein) domain characteristic for previously described ASP proteins. Real-time PCR analysis shows significant up-regulation of Ace-asp-3 and Ace-asp-5 expression in adult worms and correlated down-regulation in ssL3 larvae. On the other hand, expression of Ace-asp-4 was increased in ssL3 stages and decreased in adult parasites.


Genes ◽  
2011 ◽  
Vol 2 (3) ◽  
pp. 449-501 ◽  
Author(s):  
Alinda Nagy ◽  
György Szláma ◽  
Eszter Szarka ◽  
Mária Trexler ◽  
László Bányai ◽  
...  

In view of the fact that appearance of novel protein domain architectures (DA) is closely associated with biological innovations, there is a growing interest in the genome-scale reconstruction of the evolutionary history of the domain architectures of multidomain proteins. In such analyses, however, it is usually ignored that a significant proportion of Metazoan sequences analyzed is mispredicted and that this may seriously affect the validity of the conclusions. To estimate the contribution of errors in gene prediction to differences in DA of predicted proteins, we have used the high quality manually curated UniProtKB/Swiss-Prot database as a reference. For genome-scale analysis of domain architectures of predicted proteins we focused on RefSeq, EnsEMBL and NCBI’s GNOMON predicted sequences of Metazoan species with completely sequenced genomes. Comparison of the DA of UniProtKB/Swiss-Prot sequences of worm, fly, zebrafish, frog, chick, mouse, rat and orangutan with those of human Swiss-Prot entries have identified relatively few cases where orthologs had different DA, although the percentage with different DA increased with evolutionary distance. In contrast with this, comparison of the DA of human, orangutan, rat, mouse, chicken, frog, zebrafish, worm and fly RefSeq, EnsEMBL and NCBI’s GNOMON predicted protein sequences with those of the corresponding/orthologous human Swiss-Prot entries identified a significantly higher proportion of domain architecture differences than in the case of the comparison of Swiss-Prot entries. Analysis of RefSeq, EnsEMBL and NCBI’s GNOMON predicted protein sequences with DAs different from those of their Swiss-Prot orthologs confirmed that the higher rate of domain architecture differences is due to errors in gene prediction, the majority of which could be corrected with our FixPred protocol. We have also demonstrated that contamination of databases with incomplete, abnormal or mispredicted sequences introduces a bias in DA differences in as much as it increases the proportion of terminal over internal DA differences. Here we have shown that in the case of RefSeq, EnsEMBL and NCBI’s GNOMON predicted protein sequences of Metazoan species, the contribution of gene prediction errors to domain architecture differences of orthologs is comparable to or greater than those due to true gene rearrangements. We have also demonstrated that domain architecture comparison may serve as a useful tool for the quality control of gene predictions and may thus guide the correction of sequence errors. Our findings caution that earlier genome-scale studies based on comparison of predicted (frequently mispredicted) protein sequences may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins. A reassessment of the DA evolution of orthologous and paralogous proteins is presented in an accompanying paper [1].


2009 ◽  
Vol 37 (5) ◽  
pp. 1061-1065 ◽  
Author(s):  
Gary J. Doherty ◽  
Richard Lundmark

The role of endocytosis in controlling a multitude of cell biological events is well established. Molecular and mechanistic characterization of endocytosis has predominantly focused on CME (clathrin-mediated endocytosis), although many other endocytic pathways have been described. It was recently shown that the BAR (Bin/amphiphysin/Rvs) and Rho GAP (GTPase-activating protein) domain-containing protein GRAF1 (GTPase regulator associated with focal adhesion kinase-1) is found on prevalent, pleiomorphic endocytic membranes, and is essential for the major, clathrin-independent endocytic pathway that these membranes mediate. This pathway is characterized by its ability to internalize GPI (glycosylphosphatidylinositol)-anchored proteins, bacterial toxins and large amounts of extracellular fluid. These membrane carriers are highly dynamic and associated with the activity of the small G-protein Cdc42 (cell division cycle 42). In the present paper, we review the role of GRAF1 in this CLIC (clathrin-independent carrier)/GEEC (GPI-anchored protein-enriched early endocytic compartment) endocytic pathway and discuss the current understanding regarding how this multidomain protein functions at the interface between membrane sculpting, small G-protein signalling and endocytosis.


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