2016
DOI: 10.1186/s12859-016-1295-z
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DASP3: identification of protein sequences belonging to functionally relevant groups

Abstract: BackgroundDevelopment of automatable processes for clustering proteins into functionally relevant groups is a critical hurdle as an increasing number of sequences are deposited into databases. Experimental function determination is exceptionally time-consuming and can’t keep pace with the identification of protein sequences. A tool, DASP (Deacon Active Site Profiler), was previously developed to identify protein sequences with active site similarity to a query set. Development of two iterative, automatable met… Show more

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Cited by 6 publications
(21 citation statements)
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References 34 publications
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“…Each discrete cluster is examined for validity as a functionally relevant cluster by creating a profile for the cluster members and analyzing if a DASP search of PDB distinctly identifies only cluster members. To support TuLIP, a new version of DASP, DASP2, was developed to improve the efficiency of database searching and overcome certain edge case anomalies noted in the original DASP implementation (see Methods).…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Each discrete cluster is examined for validity as a functionally relevant cluster by creating a profile for the cluster members and analyzing if a DASP search of PDB distinctly identifies only cluster members. To support TuLIP, a new version of DASP, DASP2, was developed to improve the efficiency of database searching and overcome certain edge case anomalies noted in the original DASP implementation (see Methods).…”
Section: Resultsmentioning
confidence: 99%
“… DASP method using ASPs to search for sequences that contain functional site features similar to those represented in the original profile. Sequence databases can be searched for proteins containing active site features similar to those in the original ASP using a tool called DASP; DASP2 was developed to improve input and algorithmic details. As described in Methods, the ASP is split into individual motifs (representing the colored, structurally continuous fragments in Fig.…”
Section: Introductionmentioning
confidence: 99%
“…Table 4 indicates the features of five different methods that can be used to classify Prx proteins to the subgroup level. These methods include HMM search against the SFLD database [10], use of the MISST algorithm [4] which builds on DASPs [20], BLAST search against the PREX database [3], search against the NCBI Conserved Domains database (CDD) [21], and the method described in this work named Prx_3-merSVM.…”
Section: Classification Process Comparisonmentioning
confidence: 99%
“…The classification process employed by Harper et al makes use of alignment against active site profiles (ASP) [20,22], where an active site profile consists of multiple (usually 4 to 5) sequence fragments for which the residues are within 10 angstroms in structural space of known active site key residues. The Harper annotations [4] are considered the current gold standard for Prx annotations.…”
Section: Classification Performance Comparisonmentioning
confidence: 99%
“…There are various automatic tools available for classification of proteins into isofunctional families using sequence similarity, active site characteristics, and phylogenetic relationships (Brown, Krishnamurthy, and Sjölander 2007; Lee, Rentzsch, and Orengo 2010; de Melo-Minardi, Bastard, and Artiguenave 2010; Leuthaeuser et al 2016; Knutson et al 2017). Alternatively, the structure of a protein family can be interactively explored using sequence similarity networks (SSNs) (Atkinson et al 2009; Copp et al 2018).…”
Section: Introductionmentioning
confidence: 99%