Computational exploration of the network of sequence flow between protein structures.
We investigate small sequence adjustments (of one or a few amino acids) that induce large conformational transitions between distinct and stable folds of proteins. Such transitions are intriguing from evolutionary and protein-design perspectives. They make it possible to search for ancient protein structures or to design protein switches that flip between folds and functions. A network of sequence flow between protein folds is computed for representative structures of the Protein Data Bank. The computed network is dense, on an average each structure is connected to tens of other folds. Proteins that attract sequences from a higher than expected number of neighboring folds are more likely to be enzymes and alpha/beta fold. The large number of connections between folds may reflect the need of enzymes to adjust their structures for alternative substrates. The network of the Cro family is discussed, and we speculate that capacity is an important factor (but not the only one) that determines protein evolution. The experimentally observed flip from all alpha to alpha + beta fold is examined by the network tools. A kinetic model for the transition of sequences between the folds (with only protein stability in mind) is proposed. Proteins 2010. (c) 2009 Wiley-Liss, Inc.
Cao
Baoqiang
B
Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas 78712, USA.
Elber
Ron
R
D000595:Amino Acid Sequence; D030562:Databases, Protein; D019143:Evolution, Molecular; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein
D011506:Proteins