DOI: 10.5061/dryad.c59zw3r4v
title: Protein structure alignments and structural similarity score code for: Benchmarking methods of protein structure alignment

description: The function of a protein is primarily determined by its structure and
 amino acid sequence. Many biological questions of interest rely on being
 able to accurately determine the group of structures to which domains of a
 protein belong (often referred to as their `fold'); this can be done
 through alignment and comparison of protein structures. This fundamental
 task underpins predicting function, identification of homology, and
 testing hypotheses about the way "protein-space'' is
 organised. Dozens of different methods for Protein Structure Alignment
 (PSA) have been proposed that use a wide range of techniques.
   The aim of this study is to determine the ability of
 PSA methods to identify pairs of protein domains known to share differing
 levels of structural similarity, and to assess their utility for
 clustering domains from several different folds into known
 groups.  We present the results of a comprehensive investigation
 into eighteen PSA methods; to our knowledge this is the largest piece of
 independent research on this topic.   Overall,
 SP-AlignNS (nonsequential) was found to be the best method for
 classification, and also one of the best performing methods for
 clustering.  Methods (where possible) were split into the
 algorithm used to find the optimal alignment and the score used to assess
 similarity.   This allowed us to largely separate the
 algorithm from the score it maximises and thus, to assess their
 effectiveness independently of each other.
   Surprisingly, we found that some hybrids of mismatched
 scores and algorithms performed better than either of the native methods
 at classification and, in some cases, clustering as well. It is hoped that
 this investigation and the accompanying discussion will be useful for
 researchers selecting or designing methods to align protein structures.
description: <strong>Alignments: </strong>Contained in the
 classification folder of this dataset are alignments of 500 randomly
 selected 'pivot' domains to protein domains from the same
 family, same superfamily, same fold, same class and different classes.
 These are generally named using the numbers 0-499 and the letters f,s,fo,c
 and d (for decoy). These alignments were performed with eighteen different
 protein structure alignment methods, as can be seen from the folders. The
 exception to this was Fr-TM-Align, which was used to perform alignments
 for these same protein pairs several different times with different length
 normalisation methods. Contained in the clustering
 folder of this dataset are all vs all comparisons of fifty proteins
 performed by the same eighteen alignment methods. These proteins were
 selected to be from ten different folds, with five representatives from
 each. <strong>Code: </strong>Contained in
 the code folder are python modules to calculate structural similarity
 scores associated with different original methods. These all require a
 .pdb file containing two aligned proteins and a .fasta file showing which
 residues are aligned to which.
description: The identities of all proteins in the alignments uploaded can be
 found in the supplementary material of "Benchmarking Methods of
 Protein Structure Alignment".