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Protein function ultimately depends on protein structure, but experimental methods for characterising protein structure can never keep pace with the genome-driven deluge of sequence data. Plugging the gap are bioinformatics methods which can predict structures either by exploiting known structures as templates (homology modelling) or without that information (fragment-based ab initio methods covariance-based algorithms). An impressive diversity of bioinformatics methods can be used to extract maximum value from structures, both experimental and modelled.
