Two different approaches are currently used in STRuster to identify invariant regions, a smoothing approach is used to identify backbone invariant regions, and a different clustering approach is used to identify invariant regions in specific sites where the residues are not necessarily contiguous in the sequence. We intend to develop a single common approach applicable for the identification of invariant regions.
In the analysis of side-chain conformation the side-chain centroid is used. The centroid representation is robust regarding residue substitutions or missing atom coordinates, but it is not very sensitive to small conformational differences. We intend to implement alternative approaches that are more sensitive to small differences in the side-chain conformations.
To demonstrate the capabilities of STRuster, we have focused on the analysis of models determined by X-ray crystallography. They correspond to the majority of the current entries, in PDB (85%). Most of the remaining entries in PDB have been obtained by NMR spectroscopy. They were excluded from the current study mostly for practical reasons. Nevertheless, NMR models can also be analysed with STRuster: in particular, one can group the models by clustering, analyse the structural variation with the S matrix or compare models with the V matrix. The T, R, X and U matrices cannot currently be computed for NMR models as they rely on estimates of coordinate uncertainty. As the method matures we will consider to implement a measure of coordinate uncertainty for NMR models, so that STRuster can also be applied to these models.
The main motivation to develop STRuster was to provide a tool for the detailed structural analysis of specific proteins. Drug targets and proteins of medical interest are obvious relevant candidates, for which there is a considerable amount of structural information available. In particular, we are currently applying STRuster in the backbone and side-chain structure analysis of hepatitis C viral proteins (HCV). For example, there are currently 38 PDB entries for HCV NS5B, an RNA-dependent RNA polymerase, which is the focus of intensive research as a target for new antiviral drugs. For 32 of these entries, the protein is associated with different ligands. The number of actual models is much higher (63), as some entries, include two models in the asymmetric unit. The amount of structural data is similar for the HCV protease, and is considerably larger for some of the HIV drug targets.
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