Hamodrakas, S. J. | bioRxiv Science

bioRxiv2019

PerMemDB: a database for eukaryotic peripheral membrane proteins

The majority of all proteins in cells interact with membranes either permanently or temporarily. Peripheral membrane proteins form transient complexes with membrane proteins and/or lipids, via non-covalent interactions and are of outmost importance, due to numerous cellular functions in which they participate. In an effort to collect data regarding this heterogeneous group of proteins we designed and constructed a database, called PerMemDB. PerMemDB is currently the most complete and comprehensive repository of data for eukaryotic peripheral membrane proteins deposited in UniProt or predicted with the use of MBPpred - a computational method that specializes in the detection of proteins that interact non-covalently with membrane lipids, via membrane binding domains. The first version of the database contains 241173 peripheral membrane proteins from 1216 organisms. All entries have cross-references to other databases, literature references and annotation regarding their interactions with other proteins. Moreover, additional sequence annotation of the characteristic domains that allow these proteins to interact with membranes is available, due to the application of MBPpred. Through the web interface of PerMemDB, users can browse the contents of the database, submit advanced text searches and BLAST queries against the protein sequences deposited in PerMemDB. We expect this repository to serve as a source of information for the development of prediction algorithms regarding peripheral membrane proteins, in addition to proteome-wide analyses. Availabilityhttp://bioinformatics.biol.uoa.gr/permemdb Contactveconom@biol.uoa.gr Supplementary informationhttp://83.212.109.111:8085/assets/Nastou_Supplement.xlsx

bioinformatics↗

bioRxiv2018

Analysis of Single Nucleotide Polymorphisms in human Voltage-Gated Ion Channels

Voltage-Gated Ion Channels (VGICs) are one of the largest groups of transmembrane proteins. Due to their major role in the generation and propagation of electrical signals, VGICs are considered important from a medical viewpoint and their dysfunction is often associated with a group of diseases known as \"Channelopathies\". We identified disease associated mutations and polymorphisms in these proteins through mapping missense Single Nucleotide Polymorphisms (SNPs) from the UniProt and ClinVar databases on their amino acid sequence, taking into consideration their special topological and functional characteristics. Statistical analysis revealed that disease associated SNPs are mostly found in the Voltage Sensor Domain - and especially at its fourth transmembrane segment (S4) - and in the Pore Loop. Both these regions are extremely important for the activation and ion conductivity of VGICs. Moreover, amongst the most frequently observed mutations are those of arginine to glutamine, to histidine or to cysteine, which can probably be attributed to the extremely important role of arginine residues in the regulation of membrane potential in these proteins. We suggest that topological information in combination with genetic variation data can contribute towards a better evaluation of the effect of currently unclassified mutations in VGICs. It is hoped that potential associations with certain disease phenotypes will be revealed in the future, with the use of similar approaches.

bioinformatics↗