Objectives

To provide pre-calculated, annotated multiple sequence alignments (MSAs) for all proteins for which the 3D structure is available in the protein structure database, PDB. To provide, on-the-fly, high-quality multiple sequence alignments for all other sequences and structures not (yet) in the PDB. Additionally, software will be provided to visualize the (MSAs) and data derived from them in multiple, different ways.

Description

The HSSP database contains for each PDB file a multiple sequence alignment against the UniProt protein sequence database. HSSP has been updated weekly for the past 15 years, and despite the growth of both the PDB and UniProt, the weekly update regime will be maintainable for the foreseeable future, and will be continued throughout the duration of the NewProt project.

The HSSP database contains for each PDB file a multiple sequence alignment against the UniProt protein sequence database. HSSP has been updated weekly for the past 15 years, and despite the growth of both the PDB and UniProt, the weekly update regime will be maintainable for the foreseeable future, and will be continued throughout the duration of the NewProt project.

HSSP files hold valuable information because they hold sequence conservation and variability data. HSSP files also tend to produce better alignments than the often used combination of BLAST and CLUSTAL. The HSSP software will be rewritten to incorporate a series of novel insights obtained over the past decade (this will be done in a collaboration with Chris sander and Reinhard Scheider; the original HSSP authors). The quality (improvement) will be validated by comparing the HSSP alignments with a series of structure based MSAs produces by partner BIOP. (It is unfortunately still far too time consuming to produce structure based MSAs for all PDB files).

The HSSP derived variability information will be mapped on the structure coordinates and made available as a YASARA View scene (such scenes can be executed directly by the YASARA View version on the user's in-house computer). In case only very few residue types make up the majority at a certain residue position (i.e. residue 17 is 72% Asp, 16% Glu and 2% something else), the predicted optimal rotamers for the majority residue types will be made visible, and correlations between such positions will be detected and made visible. Additionally, the MSAs will be made available in a series of commonly used formats to ease the in-house usage with other software packages by the SSP users.