Towards an automatic method of predicting protein structure by homology: an evaluation of suboptimal sequence alignments.
A major problem in predicting protein structure by homology modelling is that the sequence alignment from which the model is built may not be the best one in terms of the correct equivalencing of residues assessed by structural or functional criteria. A useful strategy is to generate and examine a number of suboptimal alignments as better alignments can often be found away from the optimal. A procedure to filter rapidly suboptimal alignments based on measurement of core volumes and packing pair potentials is investigated. The approach is benchmarked on three pairs of sequences which are non-trivial to align correctly, namely two immunoglobulin domains, plastocyanin with azurin and two distant globin sequences. It is shown to be useful to reduce a large ensemble of possible alignments down to a few which correspond more closely to the correct (structure based) alignment.
Saqi
M A
MA
Biomolecular Modelling Laboratory, Imperial Cancer Research Fund, London, UK.
Bates
P A
PA
Sternberg
M J
MJ
D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D006801:Humans; D008969:Molecular Sequence Data; D011487:Protein Conformation; D016415:Sequence Alignment / Q000379:methods*; D017385:Sequence Homology