Skip to main navigation Skip to search Skip to main content

Prediction of Protein Quaternary Structures

  • Akbar Vaseghi
  • , M. Faridounnia
  • , Soheila Shokrollahzade
  • , Samad Jahandideh
  • , Kuo-Chen Chou

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract


Summary
Determination of the protein structure and understanding its function is essential for any relevant medical, engineering, or pharmaceutical applications. Therefore, the study of quaternary structure of proteins, despite all the obstacles in acquiring data from large macromolecular assemblies, is one of the major goals in biomolecular sciences. This chapter discusses respectively protein structure prediction, template‐based predictions, critical assessment of protein structure prediction (CASP), and quaternary structure prediction. Homology modeling and threading methods are two types of template‐based approaches. The homology modeling method needs to have the homologous protein structure as template and threading methods are a new approach in fold recognition, in which the tool attempts to fit the sequence in the known structures. A few sequence‐based computational methods have been developed for the prediction of protein quaternary structure using statistical models or machine learning methods.
Original languageEnglish
Title of host publicationPattern recognition in computational molecular biology
Subtitle of host publicationtechniques and approaches
EditorsMourad Elloumi
Place of PublicationHoboken, NJ
PublisherWiley
Chapter14
Pages251-265
Number of pages15
ISBN (Print)9781118893685
DOIs
Publication statusPublished - 2016

Publication series

NameWiley series on bioinformatics: computational techniques and engineering

Keywords

  • critical assessment of protein structure prediction
  • machine learning methods
  • protein structure prediction
  • quaternary structure prediction

Fingerprint

Dive into the research topics of 'Prediction of Protein Quaternary Structures'. Together they form a unique fingerprint.

Cite this