Abstract
BackgroundMembrane transport proteins (transporters) move hydrophilic substrates across hydrophobic membranes and play vital roles in most cellular functions. Transporters represent a diverse group of proteins that differ in topology, energy coupling mechanism, and substrate specificity as well as sequence similarity. Among the functional annotations of transporters, information about their transporting substrates is especially important. The experimental identification and characterization of transporters is currently costly and time-consuming. The development of robust bioinformatics-based methods for the prediction of membrane transport proteins and their substrate specificities is therefore an important and urgent task.ResultsSupport vector machine (SVM)-based computational models, which comprehensively utilize integrative protein sequence features such as amino acid composition, dipeptide composition, physico-chemical composition, biochemical composition, and position-specific scoring matrices (PSSM), were developed to predict the substrate specificity of seven transporter classes: amino acid, anion, cation, electron, protein/mRNA, sugar, and other transporters. An additional model to differentiate transporters from non-transporters was also developed. Among the developed models, the biochemical composition and PSSM hybrid model outperformed other models and achieved an overall average prediction accuracy of 76.69% with a Mathews correlation coefficient (MCC) of 0.49 and a receiver operating characteristic area under the curve (AUC) of 0.833 on our main dataset. This model also achieved an overall average prediction accuracy of 78.88% and MCC of 0.41 on an independent dataset.ConclusionsOur analyses suggest that evolutionary information (i.e., the PSSM) and the AAIndex are key features for the substrate specificity prediction of transport proteins. In comparison, similarity-based methods such as BLAST, PSI-BLAST, and hidden Markov models do not provide accurate predictions for the substrate specificity of membrane transport proteins. TrSSP: The Transporter Substrate Specificity Prediction Server, a web server that implements the SVM models developed in this paper, is freely available at http://bioinfo.noble.org/TrSSP.
Highlights
Membrane transport proteins, known as transporters, transport hydrophilic substrates across hydrophobic membranes within an individual cell or between cells, and play important roles in several cellular functions, including cell metabolism, ion homeostasis, signal transduction, binding with small molecules in extracellular space, the recognition process in the immune system, energy transduction, osmoregulation, and physiological and developmental processes [1]
We found that our support vector machine (SVM) model based on biochemical composition and evolutionary information could accurately predict substrate specificity
The hybrid model that included the biochemical composition and this position-specific scoring matrices (PSSM) profile achieved an accuracy of 83.27%, 67.14%, 76.15%, 81.43%, 74.69%, 78.57%, 66.71%, and 78.12% and an accuracy of 84.44%, 68.33%, 71.11%, 81.67%, 83.33%, 80.56%, 69.44%, and 80.00% for amino acid transporters, anion transporters, cation transporters, electron transporters, protein/mRNA transporters, sugar transporters, and other transporters, respectively, of which the performances were analyzed based on both the main dataset and the independent dataset
Summary
Known as transporters, transport hydrophilic substrates across hydrophobic membranes within an individual cell or between cells, and play important roles in several cellular functions, including cell metabolism, ion homeostasis, signal transduction, binding with small molecules in extracellular space, the recognition process in the immune system, energy transduction, osmoregulation, and physiological and developmental processes [1]. Transporters represent a diverse group of proteins that differ in topology, energy coupling mechanism, and substrate specificity. Membrane transport proteins (transporters) move hydrophilic substrates across hydrophobic membranes and play vital roles in most cellular functions. Transporters represent a diverse group of proteins that differ in topology, energy coupling mechanism, and substrate specificity as well as sequence similarity. The development of robust bioinformatics-based methods for the prediction of membrane transport proteins and their substrate specificities is an important and urgent task
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.
