Computational Methods for Protein Structure Prediction and Modeling

1. Front Matter

   Pages I-XX

   PDF

2. A Historical Perspective and Overview of Protein Structure Prediction

   • John C. Wooley, Yuzhen Ye

   Pages 1-43

3. Empirical Force Fields

   • Alexander D. MacKerell Jr.

   Pages 45-69

4. Knowledge-Based Energy Functions for Computational Studies of Proteins

   • Xiang Li, Jie Liang

   Pages 71-123

5. Computational Methods for Domain Partitioning of Protein Structures

   • Stella Veretnik, Ilya Shindyalov

   Pages 125-145

6. Protein Structure Comparison and Classification

   • Orhan Çamoğlu, Ambuj K. Singh

   Pages 147-180

7. Computation of Protein Geometry and Its Applications: Packing and Function Prediction

   • Jie Liang

   Pages 181-206

8. Local Structure Prediction of Proteins

   • Victo A. Simossis, Jaap Heringa

   Pages 207-254

9. Protein Contact Map Prediction

   • Xin Yuan, Christopher Bystroff

   Pages 255-277

10. Modeling Protein Aggregate Assembly and Structure

    • Jun-tao Guo, Carol K. Hall, Ying Xu, Ronald Wetzel

    Pages 279-317

11. Homology-Based Modeling of Protein Structure

    • Zhexin Xiang

    Pages 319-357

12. Modeling Protein Structures Based on Density Maps at Intermediate Resolutions

    • Jianpeng Ma

    Pages 359-388

13. Back Matter

    Pages 389-395

    PDF

An ultimate goal of modern biology is to understand how the genetic blueprint of cells(genotype)determinesthestructure,function,andbehaviorofalivingorganism (phenotype). At the center of this scienti?c endeavor is characterizing the bioch- ical and cellular roles of proteins, the working molecules of the machinery of life. A key to understanding of functional proteins is the knowledge of their folded str- tures in a cell, as the structures provide the basis for studying proteins’ functions and functional mechanisms at the molecular level. Researchers working on structure determination have traditionally selected - dividual proteins due to their functional importance in a biological process or pa- way of particular interest. Major research organizations often have their own protein X-ray crystallographic or/and nuclear magnetic resonance facilities for structure - termination, which have been conducted at a rate of a few to dozens of structures a year. Realizing the widening gap between the rates of protein identi?cation (through DNA sequencing and identi?cation of potential genes through bioinformatics an- ysis) and the determination of protein structures, a number of large scienti?c init- tives have been launched in the past few years by government funding agencies in the United States, Europe, and Japan, with the intention to solve protein structures en masse, an effort called structural genomics. A number of structural genomics centers (factory-like facilities) have been established that promise to produce solved protein structures in a similar fashion to DNA sequencing.

• Biophysics
• algorithms
• biochemistry
• bioinformatics
• modeling protein structures
• protein sequence
• protein sequence information
• protein structure
• protein structure prediction

• Department of Biochemistry and Molecular Biology, University of Georgia, Athens, USA

  Ying Xu

• Department of Computer Science Digital Biology Laboratory, University of Missouri-Columbia, Columbia, USA

  Dong Xu

• Department of Bioengineering Center for Bioinformatics, University of Illinois at Chicago, Chicago, USA

  Jie Liang

Dr. Ying Xu is Regents-GRA Eminent Scholar and Professor at the University of Georgia.  Dr. Dong Xu is the Director of the Digital Biology Laboratory at the University of Missouri-Columbia.  Dr. Jie Liang is the Director for the Center for Bioinformatics at the University of Illinois at Chicago.

Policies and ethics