Incorporating efficient radial basis function networks and significant amino acid pairs for predicting GTP binding sites in transport proteins.

Nguyen-Quoc-Khanh Le,Yu-Yen Ou

doi:10.1186/s12859-016-1369-y

Abstract

BackgroundGuanonine-protein (G-protein) is known as molecular switches inside cells, and is very important in signals transmission from outside to inside cell. Especially in transport protein, most of G-proteins play an important role in membrane trafficking; necessary for transferring proteins and other molecules to a variety of destinations outside and inside of the cell. The function of membrane trafficking is controlled by G-proteins via Guanosine triphosphate (GTP) binding sites. The GTP binding sites active G-proteins initiated to membrane vesicles by interacting with specific effector proteins. Without the interaction from GTP binding sites, G-proteins could not be active in membrane trafficking and consequently cause many diseases, i.e., cancer, Parkinson… Thus it is very important to identify GTP binding sites in membrane trafficking, in particular, and in transport protein, in general.ResultsWe developed the proposed model with a cross-validation and examined with an independent dataset. We achieved an accuracy of 95.6% for evaluating with cross-validation and 98.7% for examining the performance with the independent data set. For newly discovered transport protein sequences, our approach performed remarkably better than similar methods such as GTPBinder, NsitePred and TargetSOS. Moreover, a friendly web server was developed for identifying GTP binding sites in transport proteins available for all users.ConclusionsWe approached a computational technique using PSSM profiles and SAAPs for identifying GTP binding residues in transport proteins. When we included SAAPs into PSSM profiles, the predictive performance achieved a significant improvement in all measurement metrics. Furthermore, the proposed method could be a power tool for determining new proteins that belongs into GTP binding sites in transport proteins and can provide useful information for biologists.

Highlights

Guanonine-protein (G-protein) is known as molecular switches inside cells, and is very important in signals transmission from outside to inside cell
Composition of amino acid analysis We calculated the occurrence frequency of all amino acids inside the dataset to analyse the composition of Guanosine triphosphate (GTP) binding sites and non-GTP binding sites in Position specific scoring matrix (PSSM) + Significant amino acid pairs (SAAP) 261
Because GTP binding sites have an important role in the process of transporters, predicting them is an important issue in bioinformatics and computational biology

Summary

Introduction

Guanonine-protein (G-protein) is known as molecular switches inside cells, and is very important in signals transmission from outside to inside cell. In transport protein, most of G-proteins play an important role in membrane trafficking; necessary for transferring proteins and other molecules to a variety of destinations outside and inside of the cell. Without the interaction from GTP binding sites, G-proteins could not be active in membrane trafficking and cause many diseases, i.e., cancer, Parkinson. Membrane trafficking is the important process in transport protein, in which proteins and other macromolecules are transferred to various destinations inside and outside of the cell. This process uses membrane-bound vesicles and vesicular transporters as mediates transport to establish the absorption of molecules within a vesicle. There is a need to develop techniques such as computational techniques for identifying GTP binding sites in membrane trafficking (especially in transport protein)

Methods

Results

Conclusion