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BMC Bioinformatics. 2016 Nov 11;17(1):458.

DASP3: identification of protein sequences belonging to functionally relevant groups.

Author information

1
Molecular Genetics and Genomics Program, Wake Forest University, Winston-Salem, NC, 27106, USA. jleuthae@gmail.edu.
2
Present address: University of Richmond, Gottwald Hall C302, Richmond, VA, 23173, USA. jleuthae@gmail.edu.
3
Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA.
4
Department of Physics, Wake Forest University, Winston-Salem, NC, 27106, USA.
5
Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, 94158, USA.
6
Department of Chemistry, University of Richmond, Richmond, VA, 23173, USA.

Abstract

BACKGROUND:

Development 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 methods for clustering proteins into functionally relevant groups exposed algorithmic limitations to DASP.

RESULTS:

The accuracy and efficiency of DASP was significantly improved through six algorithmic enhancements implemented in two stages: DASP2 and DASP3. Validation demonstrated DASP3 provides greater score separation between true positives and false positives than earlier versions. In addition, DASP3 shows similar performance to previous versions in clustering protein structures into isofunctional groups (validated against manual curation), but DASP3 gathers and clusters protein sequences into isofunctional groups more efficiently than DASP and DASP2.

CONCLUSIONS:

DASP algorithmic enhancements resulted in improved efficiency and accuracy of identifying proteins that contain active site features similar to those of the query set. These enhancements provide incremental improvement in structure database searches and initial sequence database searches; however, the enhancements show significant improvement in iterative sequence searches, suggesting DASP3 is an appropriate tool for the iterative processes required for clustering proteins into isofunctional groups.

KEYWORDS:

Active site profiling; Functionally relevant clustering; Misannotation; Protein function annotation

PMID:
27835946
PMCID:
PMC5106842
DOI:
10.1186/s12859-016-1295-z
[Indexed for MEDLINE]
Free PMC Article

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