PHROG

PHROG clusters prokaryotic viral proteins into remote homologous groups using HMM profile-profile comparisons to improve functional annotation and comparative analysis of viral protein families.


Key Features:

  • Remote Homology Detection: Uses HMM profile-profile comparisons to detect distant homologous relationships among viral proteins.
  • Large-scale Clustering: Processes 17,473 reference prokaryotic viruses and their proteins, clustering 868,340 of 938,864 proteins into 38,880 groups.
  • Depth and Homogeneity: Produces clustering depth reported as twice that of classical methods while maintaining homogeneity within clusters.
  • Cluster Annotation Coverage: Includes manual inspection against reference sequence databases to annotate 5,108 clusters, covering 50.6% of the protein dataset and classified into nine viral-specific functional categories.

Scientific Applications:

  • Functional Annotation: Provides annotated clusters for viral proteins, covering 5,108 clusters (50.6% of proteins) assigned to nine functional categories.
  • Comparative Analysis: Supplies a detailed classification of viral protein families to support comparative analyses and investigation of evolutionary patterns and ecological roles.
  • Annotation of New Sequences: Supports annotation of future prokaryotic viral sequences to aid studies of virus evolution and ecology.

Methodology:

Clusters are generated using HMM profile-profile comparisons for remote homology detection and grouping of proteins into homogeneous clusters based on distant evolutionary relationships.

Topics

Details

Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Programming Languages:
PHP
Added:
12/16/2021
Last Updated:
12/16/2021

Operations

Publications

Terzian P, Olo Ndela E, Galiez C, Lossouarn J, Pérez Bucio RE, Mom R, Toussaint A, Petit M, Enault F. PHROG: families of prokaryotic virus proteins clustered using remote homology. NAR Genomics and Bioinformatics. 2021;3(3). doi:10.1093/nargab/lqab067. PMID:34377978. PMCID:PMC8341000.

PMID: 34377978
PMCID: PMC8341000
Funding: - H2020 European Research Council: 685778

Documentation