scholarly journals Determining the interaction status and evolutionary fate of duplicated homomeric proteins

2020 ◽  
Author(s):  
Saurav Mallik ◽  
Dan S Tawfik

AbstractOligomeric proteins are central to life. Duplication and divergence of their genes is a key evolutionary driver, also because duplications can yield very different outcomes. Given a homomeric ancestor, duplication can yield two paralogs that form two distinct homomeric complexes, or a heteromeric complex comprising both paralogs. Alternatively, one paralog remains a homomer while the other acquires a new partner. However, so far, conflicting trends have been noted with respect to which fate dominates, primarily because different methods and criteria are being used to assign the interaction status of paralogs. Here, we systematically analyzed all Saccharomyces cerevisiae and Escherichia coli oligomeric complexes that include paralogous proteins. We found that the proportions of homo-hetero duplication fates strongly depend on a variety of factors, yet that nonetheless, rigorous filtering gives a consistent picture. In E. coli about 50%, of the paralogous pairs appear to have retained the ancestral homomeric interaction, whereas in S. cerevisiae only ∼10% retained a homomeric state. This difference was also observed when unique complexes were counted instead of paralogous gene pairs. We further show that this difference is accounted for by multiple cases of heteromeric yeast complexes that share common ancestry with homomeric bacterial complexes. Our analysis settles contradicting trends and conflicting previous analyses, and provides a systematic and rigorous pipeline for delineating the fate of duplicated oligomers in any organism for which protein-protein interaction data are available.

Author(s):  
Hugo Willy

Recent breakthroughs in high throughput experiments to determine protein-protein interaction have generated a vast amount of protein interaction data. However, most of the experiments could only answer the question of whether two proteins interact but not the question on the mechanisms by which proteins interact. Such understanding is crucial for understanding the protein interaction of an organism as a whole (the interactome) and even predicting novel protein interactions. Protein interaction usually occurs at some specific sites on the proteins and, given their importance, they are usually well conserved throughout the evolution of the proteins of the same family. Based on this observation, a number of works on finding protein patterns/motifs conserved in interacting proteins have emerged in the last few years. Such motifs are collectively termed as the interaction motifs. This chapter provides a review on the different approaches on finding interaction motifs with a discussion on their implications, potentials and possible areas of improvements in the future.


2011 ◽  
Vol 16 (2) ◽  
Author(s):  
Dariusz Plewczynski ◽  
Tomas Klingström

AbstractStudying the interactome is one of the exciting frontiers of proteomics, as shown lately at the recent bioinformatics conferences (for example ISMB 2010, or ECCB 2010). Distribution of data is facilitated by a large number of databases. Metamining databases have been created in order to allow researchers access to several databases in one search, but there are serious difficulties for end users to evaluate the metamining effort. Therefore we suggest a new standard, “Good Interaction Data Metamining Practice” (GIDMP), which could be easily automated and requires only very minor inclusion of statistical data on each database homepage. Widespread adoption of the GIDMP standard would provide users with: a standardized way to evaluate the statistics provided by each metamining database, thus enhancing the end-user experiencea stable contact point for each database, allowing the smooth transition of statisticsa fully automated system, enhancing time- and cost-effectiveness.The proposed information can be presented as a few hidden lines of text on the source database www page, and a constantly updated table for a metamining database included in the source/credits web page.


Yeast ◽  
2001 ◽  
Vol 18 (6) ◽  
pp. 523-531 ◽  
Author(s):  
Haretsugu Hishigaki ◽  
Kenta Nakai ◽  
Toshihide Ono ◽  
Akira Tanigami ◽  
Toshihisa Takagi

Sign in / Sign up

Export Citation Format

Share Document