Computational studies on eukaryotic transmembrane β-barrel proteins
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Biology
- Keywords
- Eukaryotic Beta Barrels, profile Hidden Markov Models (pHMMs)
- Copyright
- © 2018 Roumia et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. Computational studies on eukaryotic transmembrane β-barrel proteins. PeerJ Preprints 6:e27318v1 https://doi.org/10.7287/peerj.preprints.27318v1
Abstract
Transmembrane β-barrel proteins perform multiple cellular functions such as passive transport of ions and allowing the flux of molecules. Also, they act as enzymes, transporters, receptors and virulence factors. Even though, in the last few years, several families of eukaryotic β-barrel outer membrane proteins (OMPs) have been discovered, the computational characterization of these families is far from complete. The PFAM database includes only very few characteristic profiles for these families and, in most cases, the profile Hidden Markov Models where trained using both prokaryotic and eukaryotic proteins. Here, we present, for the first time, a comprehensive computational analysis of eukaryotic transmembrane β- barrels. Ten characteristic pHMMs were build that can discriminate eukaryotic β-barrels from other classes of β-barrel proteins (globular and bacterial) and are, also, capable of discriminating between mitochondrial and chloroplastic ones. Specifically, we built six new pHMMs for the chloroplastic β-barrel families not included in the PFAM database and, also, updated the profile for MDM10 family (PF12519) and divided the porin family (PF01459) into two separated families VDAC and TOM40. We hope that all the pHMMs presented here will be used for the detection and characterization of eukaryotic OMPs in newly discovered proteomes.
Author Comment
This is an abstract which has been accepted for the BBCC2018 Conference