Abstract

The protein quaternary structure is very important to the biological process. Predicting their attributes is an essential task in computational biology for the advancement of the proteomics. However, the existing methods did not consider sufficient properties of amino acid. To end this, we proposed a hybrid method Quad-PRE to predict protein quaternary structure attributes using the properties of amino acid, predicted secondary structure, predicted relative solvent accessibility, and position-specific scoring matrix profiles and motifs. Empirical evaluation on independent dataset shows that Quad-PRE achieved higher overall accuracy 81.7%, especially higher accuracy 92.8%, 93.3%, and 90.6% on discrimination for trimer, hexamer, and octamer, respectively. Our model also reveals that six features sets are all important to the prediction, and a hybrid method is an optimal strategy by now. The results indicate that the proposed method can classify protein quaternary structure attributes effectively.

Highlights

  • As is well known, the prediction of protein quaternary structure attributes plays an important role in the structure bioinformatics

  • We proposed a new method Quad-PRE to predict protein quaternary structures attributes among 6 states only based on the primary sequences, removing both pentamer and heptamer because of insufficient data

  • The choice of the penalty factor C and the kernel function type is very important since support vector machine (SVM) is sensitive to parameterization

Read more

Summary

Introduction

The prediction of protein quaternary structure attributes (such as monomer, dimmer, trimer, tetramer, pentamer, hexamer, heptamer, and octamer) plays an important role in the structure bioinformatics. It can confirm how many subunits form the protein. It is the real requirement for the Anfinsen’s dogma [1]. A variety of experimental techniques can determine protein quaternary structure. The oligomers may be homooligomers or heterooligomers; the former consist of identical polypeptide chains, whereas the latter are nonidentical.

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

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 call