EFI - Enzyme Similarity Tool

This web resource is supported by a Research Resource from the National Institute of General Medical Sciences (R24GM141196-01).
The tools are available without charge or license to both academic and commercial users.
The new Taxonomy Tool and Filter by Taxonomy feature facilitate higher resolution analyses of focused regions of sequence-function space using UniProt IDs instead of UniRef90 clusters or UniRef90 clusters instead of UniRef50 clusters. The J Mol Biol article describing these is available on the JMB Resources training page.

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Submission Name: IP91_RSS_UniRef50_NoFragments

Network Name: IP91_RSS_UniRef50_NoFragments_Minlen140_AS11

The parameters used for the initial submission and the finalization are summarized in the table below.

Analysis Summary

Analysis Job Number26642
Network NameIP91_RSS_UniRef50_NoFragments_Minlen140_AS11
Alignment Score11
Minimum Length140
Maximum Length50,000
Total Number of Sequences After Filtering63,359

Dataset Summary

EST Job Number26155 (Original Dataset)
Database VersionUniProt: 2022-04 / InterPro: 91
Input OptionFamilies (Option B)
Job NameIP91_RSS_UniRef50_NoFragments
E-Value for SSN Edge Calculation5
Pfam / InterPro FamilyIPR000385, IPR001989, IPR002684, IPR003698, IPR003739, IPR004383, IPR004558, IPR004559, IPR005839, IPR005840, IPR005909, IPR005911, IPR005980, IPR006463, IPR006466, IPR006467, IPR006638, IPR007197, IPR010505, IPR010722, IPR010723, IPR011101, IPR011843, IPR012726, IPR012837, IPR012838, IPR012839, IPR013483, IPR013704, IPR013848, IPR013917, IPR014191, IPR016431, IPR016771, IPR016779, IPR016863, IPR017200, IPR017672, IPR017742, IPR017833, IPR017834, IPR019939, IPR019940, IPR020050, IPR020612, IPR022431, IPR022432, IPR022447, IPR022459, IPR022462, IPR022881, IPR022946, IPR023404, IPR023805, IPR023807, IPR023819, IPR023820, IPR023821, IPR023822, IPR023858, IPR023862, IPR023863, IPR023867, IPR023868, IPR023874, IPR023880, IPR023885, IPR023886, IPR023891, IPR023897, IPR023904, IPR023912, IPR023913, IPR023930, IPR023969, IPR023979, IPR023980, IPR023984, IPR023992, IPR023993, IPR023995, IPR024001, IPR024007, IPR024016, IPR024017, IPR024018, IPR024021, IPR024023, IPR024025, IPR024032, IPR024177, IPR024521, IPR024560, IPR024924, IPR025895, IPR026322, IPR026332, IPR026335, IPR026344, IPR026346, IPR026351, IPR026357, IPR026401, IPR026404, IPR026407, IPR026412, IPR026423, IPR026426, IPR026429, IPR026447, IPR026482, IPR027492, IPR027526, IPR027527, IPR027559, IPR027564, IPR027570, IPR027583, IPR027586, IPR027596, IPR027604, IPR027608, IPR027609, IPR027621, IPR027622, IPR027626, IPR027633, IPR030801, IPR030837, IPR030894, IPR030896, IPR030905, IPR030915, IPR030933, IPR030950, IPR030969, IPR030977, IPR030989, IPR031003, IPR031004, IPR031010, IPR031012, IPR031014, IPR031015, IPR031019, IPR031691, IPR032432, IPR033971, IPR033974, IPR033975, IPR033976, IPR034165, IPR034386, IPR034391, IPR034405, IPR034422, IPR034428, IPR034436, IPR034438, IPR034457, IPR034462, IPR034465, IPR034466, IPR034471, IPR034474, IPR034479, IPR034480, IPR034485, IPR034491, IPR034497, IPR034498, IPR034505, IPR034508, IPR034514, IPR034515, IPR034519, IPR034529, IPR034530, IPR034531, IPR034532, IPR034534, IPR034547, IPR034556, IPR034557, IPR034559, IPR034560, IPR034687, IPR038135, IPR039661, IPR040063, IPR040072, IPR040074, IPR040081, IPR040082, IPR040085, IPR040086, IPR040087, IPR040088, IPR041582, IPR045375, IPR045567, IPR045784, PF04055, PF06969, PF08497, PF12345, PF13186, PF16199, PF16881, PF19238, PF19288, PF19864
Number of IDs in Pfam / InterPro Family773,531
Domain Optionoff
UniRef Version50
Number of Cluster IDs in UniRef50 Family66,950
Exclude FragmentsYes
Total Number of Sequences in Dataset66,950
Total Number of Edges90,203,805
Number of Unique Sequences66,950
Convergence Ratio?0.040
Please cite your use of the EFI tools:

Rémi Zallot, Nils Oberg, and John A. Gerlt, The EFI Web Resource for Genomic Enzymology Tools: Leveraging Protein, Genome, and Metagenome Databases to Discover Novel Enzymes and Metabolic Pathways. Biochemistry 2019 58 (41), 4169-4182. https://doi.org/10.1021/acs.biochem.9b00735

Nils Oberg, Rémi Zallot, and John A. Gerlt, EFI-EST, EFI-GNT, and EFI-CGFP: Enzyme Function Initiative (EFI) Web Resource for Genomic Enzymology Tools. J Mol Biol 2023. https://doi.org/10.1016/j.jmb.2023.168018

The panels below provide files for full and representative node SSNs for download with the indicated numbers of nodes and edges. As an approximate guide, SSNs with ~2M edges can be opened with 16 GB RAM, ~5M edges can be opened with 32 GB RAM, ~10M edges can be opened with 64 GB RAM, ~20M edges can be opened with 128 GB RAM, ~40M edges can be opened with 256 GB RAM, and ~120M edges can be opened with 768 GB RAM.

Files may be transferred to the Genome Neighborhood Tool (GNT), the Color SSN utility, the Cluster Analysis utility, or the Neighborhood Connectivity utility.

Full Network ?

Each node in the network represents a single protein sequence.

# Nodes # Edges
63,359 65,099,366

 

Representative Node Networks ?

In representative node (RepNode) networks, each node in the network represents a collection of proteins grouped according to percent identity. For example, for a 75% identity RepNode network, all connected sequences that share 75% or more identity are grouped into a single node (meta node). Sequences are collapsed together to reduce the overall number of nodes, making for less complicated networks easier to load in Cytoscape.

The cluster organization is not changed, and the clustering of sequences remains identical to the full network.

% ID # Nodes # Edges
100 63,359 65,099,366
95 63,352 65,091,836
90 63,346 65,080,559
85 63,280 64,963,617
80 63,200 64,838,720
75 63,137 64,742,857
70 63,069 64,624,069
65 63,002 64,478,949
60 62,898 64,282,829
55 62,746 64,022,377
50 62,281 63,194,942
45 60,324 59,507,024
40 55,995 50,990,912

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Portions of these data are derived from the Universal Protein Resource (UniProt) databases.

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