The HSSP data base of protein structure-sequence alignments

By Christopher Sander, Reinhard Schneider. 1993

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

A series of PDB related databases for everyday needs (2010, background): “The structural homology plot (18) describes at which percentage sequence identity an alignment of a given length is an indication that the aligned proteins have a similar structure.”
Comparison of sequence profiles. Strategies for structural predictions using sequence information (2008, background): “The specific value of the threshold depends on the length of the alignment ~ Sander & Schneider, 1993 !”
Local Protein Structures (2007, background): “Based on HSSP families [331], sequence based clusters were created and the most frequently occurring structure in each”
How well is enzyme function conserved as a function of pairwise sequence identity? (2003, methodology): “– 37 To extend sequence comparison into the twilight zone, Rost employed the HSSP (homology-derived structures of proteins) score (a score derived from sequence identity to indicate whether two sequences might have similar structures) to measure the sequence similarity between two proteins.(36,38) H”
Exploiting the past and the future in protein secondary structure prediction (1999, methodology): “In all but two experiments (see below), profiles were obtained from the HSSP database (Schneider et al., 1997) available at http://www.”
ConSurf: an algorithmic tool for the identification of functional regions in proteins by surface mapping of phylogenetic information. (2001, methodology): “Thus, counting the differences between each pair of amino acids in the alignment may lead to a misestimation of replacement frequency, even after weighing each pair comparison by its sequence distance.(44) Using a tree-based”
Evolutionary Conserved Positions Define Protein Conformational Diversity (2016, methodology): “Multiple structure-sequence alignments were obtained from the HSSP (homology-derived structures of proteins) database[85] that merge structural and sequence information of proteins.”
Predicting protein structure using hidden Markov models (1997, methodology): “For each of these structures, we constructed an hmm (a structure model) using the associated HSSP alignment [22] of the structure and its homologs as the initial basis.”
Protein–protein interaction and quaternary structure (2008, methodology): “Given the aligned sequences of N homologous proteins, the variability at sequence position i is commonly measured by the Shannon entropy (Sander & Schneider, 1993 ; Elcock & McCammon, 2001 ; Caffrey et al. 2004 ; Guharoy & Chakrabarti, 2005) : s(i)=x X k=1, T pk ln pk (7) pk is the fraction of the…”
Correlated mutations contain information about protein-protein interaction. (1997, methodology): “From the HSSP Data Base (Sander & Schneider, 1993). f Xd, the harmonic weighted difference between the binned distributions of distances between all residues and correlated pairs of positions in the ®rst domain (see Methods). g As f but for residue pairs in the second domain. h As f but for pairs of”
Transmembrane helices predicted at 95% accuracy (1995, background): “…for which the 3D structure can be predicted rather accurately by homology modelling is constantly increasing (today more than 25% of all sequences in the SWISSPROT sequence data base (Bairoch & Boeckmann, 1994) can be modelled with reasonable accuracy by homology (Sander & Schneider, 1994)).”
Protein–Protein Interaction Hotspots Carved into Sequences (2007, background): “The distributions of residue conservation (x-axis, HSSP [46] conservation score) are compared between the entire sequences of the proteins in the dataset (black circles), hotspots (blue diamonds), and residues with no effect (measured by alanine scans) on protein–protein binding (red triangles).”