↓ Skip to main content

Protein Structure Prediction

Overview of attention for book
Cover of 'Protein Structure Prediction'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Protein Structure Modeling with MODELLER
  3. Altmetric Badge
    Chapter 2 Protein Structure Prediction
  4. Altmetric Badge
    Chapter 3 The MULTICOM Protein Tertiary Structure Prediction System
  5. Altmetric Badge
    Chapter 4 Modeling of Protein Side-Chain Conformations with RASP
  6. Altmetric Badge
    Chapter 5 Direct Coupling Analysis for Protein Contact Prediction
  7. Altmetric Badge
    Chapter 6 ITScorePro: An Efficient Scoring Program for Evaluating the Energy Scores of Protein Structures for Structure Prediction
  8. Altmetric Badge
    Chapter 7 Assessing the Quality of Modelled 3D Protein Structures Using the ModFOLD Server
  9. Altmetric Badge
    Chapter 8 3D-SURFER 2.0: Web Platform for Real-Time Search and Characterization of Protein Surfaces.
  10. Altmetric Badge
    Chapter 9 SPOT-Seq-RNA: Predicting Protein–RNA Complex Structure and RNA-Binding Function by Fold Recognition and Binding Affinity Prediction
  11. Altmetric Badge
    Chapter 10 Protein Structure Prediction
  12. Altmetric Badge
    Chapter 11 Prediction of Intrinsic Disorder in Proteins Using MFDp2
  13. Altmetric Badge
    Chapter 12 Modeling Protein–Protein Complexes Using the HADDOCK Webserver “Modeling Protein Complexes with HADDOCK”
  14. Altmetric Badge
    Chapter 13 Predicting the Structure of Protein–Protein Complexes Using the SwarmDock Web Server
  15. Altmetric Badge
    Chapter 14 DOCK/PIERR: Web Server for Structure Prediction of Protein–Protein Complexes
  16. Altmetric Badge
    Chapter 15 Pairwise and Multimeric Protein-Protein Docking Using the LZerD Program Suite.
  17. Altmetric Badge
    Chapter 16 Protocols for Efficient Simulations of Long-Time Protein Dynamics Using Coarse-Grained CABS Model
Attention for Chapter 2: Protein Structure Prediction
Altmetric Badge

Readers on

89 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Protein Structure Prediction
Chapter number 2
Book title
Protein Structure Prediction
Published in
Methods in molecular biology, January 2014
DOI 10.1007/978-1-4939-0366-5_2
Pubmed ID
Book ISBNs
978-1-4939-0365-8, 978-1-4939-0366-5

Källberg M, Margaryan G, Wang S, Ma J, Xu J, Morten Källberg, Gohar Margaryan, Sheng Wang, Jianzhu Ma, Jinbo Xu


Assigning functional properties to a newly discovered protein is a key challenge in modern biology. To this end, computational modeling of the three-dimensional atomic arrangement of the amino acid chain is often crucial in determining the role of the protein in biological processes. We present a community-wide web-based protocol, RaptorX server ( http://raptorx.uchicago.edu ), for automated protein secondary structure prediction, template-based tertiary structure modeling, and probabilistic alignment sampling.Given a target sequence, RaptorX server is able to detect even remotely related template sequences by means of a novel nonlinear context-specific alignment potential and probabilistic consistency algorithm. Using the protocol presented here it is thus possible to obtain high-quality structural models for many target protein sequences when only distantly related protein domains have experimentally solved structures. At present, RaptorX server can perform secondary and tertiary structure prediction of a 200 amino acid target sequence in approximately 30 min.

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 1%
Pakistan 1 1%
Unknown 87 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 27%
Student > Bachelor 15 17%
Student > Doctoral Student 10 11%
Researcher 10 11%
Student > Master 10 11%
Other 10 11%
Unknown 10 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 35%
Biochemistry, Genetics and Molecular Biology 28 31%
Computer Science 4 4%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Chemistry 2 2%
Other 9 10%
Unknown 13 15%