TranCEP: Predicting transmembrane transport proteins using composition, evolutionary, and positional information
Abstract
Transporters mediate the movement of compounds across the membranes that separate the cell from its environment, and across 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 computation tools that predict the substrates which are transported by the transmembrane transport proteins.\n\nIn 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, and restriction to important positions of the alignment that play a role in determining specificity of the protein.\n\nOur experimental results show that TranCEP significantly outperforms the state of the art. The results quantify the contribution made by each kind of information used.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 28
- FWCI
- 1.22
- Field percentile
- top 24%
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- TooT-SC: Predicting Eleven Substrate Classes of Transmembrane Transport Proteins
Munira Alballa, Gregory Butler·bioRxiv·Jan 25, 2022
- A general prediction model for substrates of transport proteins
Alexander Kroll, Nico Niebuhr, … Martin J. Lercher·bioRxiv·Oct 31, 2023
- PortPred: exploiting deep learning embeddings of amino acid sequences for the identification of transporter proteins and their substrates
Marco Anteghini, Vítor A. P. Martins dos Santos, Edoardo Saccenti·Journal of Cellular BiochemistryPeer-reviewed·Oct 25, 2023
- Predicting the specific substrate for transmembrane transport proteins using BERT language model
Sima Ataei, Gregory Butler·IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)Peer-reviewed·Aug 15, 2022
- TooTranslator: Zero-Shot Classification of Specific Substrates for Transport Proteins by Language Embedding Alignment of Proteins and Chemicals
Sima Ataei, Gregory Butler·bioRxiv·Nov 13, 2025
- End-to-end mapping of membrane transport from chemical structure to microorganisms
Guillaume Gricourt, Thomas Duigou, … Jean‐Loup Faulon·bioRxiv·May 14, 2026