Protein structure prediction based on sequence similarity.
The observation that similar protein sequences fold into similar three-dimensional structures provides a basis for the methods which predict structural features of a novel protein based on the similarity between its sequence and sequences of known protein structures. Similarity over entire sequence or large sequence fragment(s) enables prediction and modeling of entire structural domains while statistics derived from distributions of local features of known protein structures make it possible to predict such features in proteins with unknown structures. The accuracy of models of protein structures is sufficient for many practical purposes such as analysis of point mutation effects, enzymatic reactions, interaction interfaces of protein complexes, and active sites. Protein models are also used for phasing of crystallographic data and, in some cases, for drug design. By using models one can avoid the costly and time-consuming process of experimental structure determination. The purpose of this chapter is to give a practical review of the most popular protein structure prediction methods based on sequence similarity and to outline a practical approach to protein structure prediction. While the main focus of this chapter is on template-based protein structure prediction, it also provides references to other methods and programs which play an important role in protein structure prediction.
Jaroszewski
Lukasz
L
The Burnham Institute, La Jolla, CA, USA.
D000465:Algorithms; D019295:Computational Biology; D003198:Computer Simulation; D030562:Databases, Protein; D008958:Models, Molecular; D017510:Protein Folding; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000235:genetics*; D016415:Sequence Alignment / Q000706:statistics & numerical data*; D017386:Sequence Homology, Amino Acid; D012984:Software; D012985:Software Design; D040681:Structural Homology, Protein
D011506:Proteins