Earticle

초록

영어

Predicting protein 3D structures from the amino acid sequence is still a hard and unsolved task after five decades of efforts. High-resolution models can be built only if the target protein has a known homologue. If not, it must be built from scratch which yields in most cases to protein models of low-resolution, i.e. far from their native structure. In this paper, we present a new refinement method of 3D protein predicted models. The new method relies on the motion that the atoms in a protein take randomly in the 3D space leading to folding. Experimental results using the CASP benchmark show the assessment and the quality of the new method in comparison with the traditional methods that depend on molecular dynamics simulation.We prove that 55 % of cases were successfully enhanced by the new method.

목차

Abstract
 1. Introduction
 2. Background
  2.1 Random Walk
  2.2 Energy Function
 3. Materials and Methods
  3.1 Data Used
  3.2 Proposed Method
 4. Experimental Results
 5. Conclusions and Future Work
 References

키워드

저자

• Shaheera Rashwan [ Informatics Research Institute, City of Scientific Research and Technological Applications, Borg Elarab, Alexandria, Egypt ] Corresponding Author
• Bayumy A. B. Youssef [ Informatics Research Institute, City of Scientific Research and Technological Applications, Borg Elarab, Alexandria, Egypt ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605