More for less in structural genomics.
Structural genomics is the idea of covering protein space so that every protein sequence comes within model building distance of a protein of known structure. Unfortunately, reproducing the structural alignment of distantly related proteins is a difficult challenge to existing sequence alignment and motif search software. We have developed a new transitive alignment algorithm (MaxFlow), which generates accurate alignments between proteins deep in the twilight zone of sequence similarity, below 20% sequence identity. In particular, MaxFlow reliably identifies conserved core motifs between proteins which are only indirect PSI-Blast neighbours. Based on MaxFlow alignments, useful 3D models can be generated for all members of a superfamily from as few as a single structural template--despite hundreds of representatives at 40% sequence identity level and patchy detection of homology by PSI-Blast. We propose novel strategies for target prioritization using MaxFlow scores to predict the optimal templates in a superfamily. Our results support an increase in the granularity of covering protein space that has potentially enormous economic implications for planning the transition to the full production phase of structural genomics.
Heger
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A
Institute of Biotechnology, PO Box 56, 00014 University of Helsinki, Finland.
Holm
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L
D000465:Algorithms; D020816:Amino Acid Motifs; D023281:Genomics / Q000379:methods*; D008958:Models, Molecular; D011487:Protein Conformation; D015203:Reproducibility of Results; D016415:Sequence Alignment / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D012984:Software; D040681:Structural Homology, Protein; D014510:Urease / Q000737:chemistry
D014510:Urease