Abstract
Transporters mediate the movement of compounds across the membranes that separate the cell from its environment and across the inner membranes surrounding cellular compartments. It is estimated that one third of a proteome consists of membrane proteins, and many of these are transport proteins. Given the increase in the number of genomes being sequenced, there is a need for computational tools that predict the substrates that are transported by the transmembrane transport proteins. In this paper, we present TranCEP, a predictor of the type of substrate transported by a transmembrane transport protein. TranCEP combines the traditional use of the amino acid composition of the protein, with evolutionary information captured in a multiple sequence alignment (MSA), and restriction to important positions of the alignment that play a role in determining the specificity of the protein. Our experimental results show that TranCEP significantly outperforms the state-of-the-art predictors. The results quantify the contribution made by each type of information used.
Highlights
Transmembrane proteins are gates that organize a variety of vital cellular functions including cell signaling, trafficking, metabolism, and energy production
In looking forward to how we might improve on approaches that rely on the amino acid composition of the protein, we developed a roadmap, whereby the composition information would be combined with evolutionary information as captured by an multiple sequence alignment (MSA), and by positional information [24] about the residues responsible for determining the specificity of the transporter
The highest Matthews correlation coefficient (MCC) was obtained by TMC-transitive consistency score (TCS)-pair amino acid composition (PAAC), which is the method chosen for our predictor TranCEP
Summary
Transmembrane proteins are gates that organize a variety of vital cellular functions including cell signaling, trafficking, metabolism, and energy production. While the amino acid sequence of many membrane proteins is available, they are among the least characterized proteins in terms of their structure and function. The Genome-Blast (G-Blast) [33] screens proteins against all the entries in Transporter Classification Database (TCDB) [34] using Blast to retrieve the top hit, and HMMTOP [35] to determine the TMS for the query and the hit sequence. It is an integral part of a manual protocol of Saier’s lab to predict the transport proteins for a genome [36]. The nearest neighbour approach achieved a balanced accuracy of 67.0%
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
