Title: Revisiting protein structure space for prediction - PDB is a covering set of small protein structures
Speaker: Daisuke Kihara
Place: Stanley Coulter (SC) 239; Tuesday, 4:30pm

Abstract

Recent protein structure prediction methods incorporate various kinds of information extracted from the PDB, such as pair-wise contact potentials, fragments excised from known proteins, inter-residue contact predictions. Thus, the viewpoint of protein structure space, i.e. the way one classify and identify protein structure similarity is crucially important. Here we have carried out structure comparisons of all representative proteins using a structure alignment method, which is based on dynamic programming algorithm. Interestingly, all small proteins up to 100 residues in length have significant structure alignments to other proteins in a different secondary structure class; i.e., on average, the best alignment assessed by the Z-score has an RMSD of 3.8 from native and covers 86.4% of the target protein^s length. In this sense, the current PDB is almost a covering set of small protein structures. For larger proteins, non-related proteins can cover a significant portion of the structure. Moreover, these top hit proteins are aligned to different parts of the target protein, so that almost the entire molecule can be covered when they are combined. These results give a new view of the nature of protein structure space, and its implications for protein structure prediction are discussed.