ArticlePloS one2020
TranCEP: Predicting the substrate class of transmembrane transport proteins using compositional, evolutionary, and positional information.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 29 citations in OpenAlex.
- Computational approaches to enzymatic reaction assignment: a review of methods, validations, and future directions.Briefings in bioinformatics · 2025Review
- Application of Protein Structure Encodings and Sequence Embeddings for Transporter Substrate Prediction.Molecules (Basel, Switzerland) · 2025Article
- DeepMolecules: a web server for predicting enzyme and transporter-small molecule interactions.Nucleic acids research · 2025Article
- NA_mCNN: Classification of Sodium Transporters in Membrane Proteins by Integrating Multi-Window Deep Learning and ProtTrans for Their Therapeutic Potential.Journal of proteome research · 2025Article
- SPOT: A machine learning model that predicts specific substrates for transport proteins.PLoS biology · 2024Article
- A multimodal Transformer Network for protein-small molecule interactions enhances predictions of kinase inhibition and enzyme-substrate relationships.PLoS computational biology · 2024Article
- Transporter annotations are holding up progress in metabolic modeling.Frontiers in systems biology · 2024Article
- Article
- TranSyT, an innovative framework for identifying transport systems.Bioinformatics (Oxford, England) · 2023Article
- ISTRF: Identification of sucrose transporter using random forest.Frontiers in genetics · 2022Article
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Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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