Protein Modeling and Structural Prediction
Proteins perform crucial functions in every living cell. The genetic information in every organismʼs DNA encodes the proteinʼs amino acid sequence, which determines its three-dimensional structure, which, in turn, determines its function. In this postgenomic era, protein sequence information can be obtained relatively easily through experimental means. Sequence databases already contain millions of protein sequences and continue to grow. Structural information, however, is harder to obtain through experimental means – we currently know the structure of about 75000 proteins. Knowledge of a proteinʼs structure is extremely useful in understanding its molecular function and in developing drugs that bind to it. Thus, computational techniques have been developed to bridge the ever-increasing gap between the number of known protein sequences and structures.
In addition to proteins in general, this chapter discusses the specific importance of membrane proteins, which make up about one-third of all known proteins. Membrane proteins control communication and transport into and out of every living cell and are involved in many medically important processes. Over half of current drug targets are membrane proteins.
A brief introduction to protein sequence and structure is followed by an overview of common techniques used in the process of computational protein structure prediction. Emphasis is put on two particularly hard problems, namely protein loop modeling and the structural prediction of membrane proteins.
KeywordsDihedral Angle Protein Structure Prediction Steric Clash Template Protein Model Quality Assessment
basic local alignment search tool
blocks of amino acids substitution matrix
critical assessment of techniques for protein structure prediction
define secondary structure of proteins
environment-specific substitution table
model quality assessment program
protein data bank
predicted hydrophobic and transmembrane
qualitative model energy aNalysis
scorematrx leading intramembrane
- 11.1.B. Alberts, A. Johnson, J. Lewis, M. Raff, K. Robets, P. Walter: Molecular Biology of the Cell, 4th edn. (Garland Science, New York 2002)Google Scholar
- 11.6.J.M. Berg, J.L. Tymoczko, L. Stryer: Biochemistry, 5th edn. (Freeman, New York 2002)Google Scholar
- 11.24.R. Das, B. Qian, S. Raman, R. Vernon, J. Thompson, P. Bradley, S. Khare, M.D. Tyka, D. Bhat, D. Chivian, D.E. Kim, W.H. Sheffler, L. Malmström, A.M. Wollacott, C. Wang, I. Andre, D. Baker: Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home, Proteins 69(S8), 118–128 (2007)CrossRefGoogle Scholar
- 11.27.C.M. Deane: Protein Structure Prediction: Amino Acid Propensities and Comparative Modelling (Univ. of Cambridge, Cambridge 2000)Google Scholar
- 11.33.D. Petrey, Z. Xiang, C.L. Tang, L. Xie, M. Gimpelev, T. Mitros, C.S. Soto, S. Goldsmith-Fischman, A. Kernytsky, A. Schlessinger, I.Y. Koh, E. Alexov, B. Honig: Using multiple structure alignments, fast model building, and energetic analysis in fold recognition and homology modeling, Proteins 53(6), 430–435 (2003)CrossRefGoogle Scholar
- 11.46.Y. Choi, C.M. Deane: FREAD revisited: Accurate loop structure prediction using a database search algorithm, Proteins 78(6), 1431–1440 (2010)Google Scholar
- 11.62.G.E. Tusnády, Z. Dosztányi, I. Simon: PDB: Selection and membrane localization of transmembrane proteins in the protein data bank, Nucleic Acids Res. 33(1), D275–D278 (2005)Google Scholar