Basic Information

Gene Symbol
afmid
Assembly
GCA_902806795.1
Location
CADCXV010001361.1:812568-840446[-]

Transcription Factor Domain

TF Family
zf-C2H2
Domain
zf-C2H2 domain
PFAM
PF00096
TF Group
Zinc-Coordinating Group
Description
The C2H2 zinc finger is the classical zinc finger domain. The two conserved cysteines and histidines co-ordinate a zinc ion. The following pattern describes the zinc finger. #-X-C-X(1-5)-C-X3-#-X5-#-X2-H-X(3-6)-[H/C] Where X can be any amino acid, and numbers in brackets indicate the number of residues. The positions marked # are those that are important for the stable fold of the zinc finger. The final position can be either his or cys. The C2H2 zinc finger is composed of two short beta strands followed by an alpha helix. The amino terminal part of the helix binds the major groove in DNA binding zinc fingers. The accepted consensus binding sequence for Sp1 is usually defined by the asymmetric hexanucleotide core GGGCGG but this sequence does not include, among others, the GAG (=CTC) repeat that constitutes a high-affinity site for Sp1 binding to the wt1 promoter [1].
Hmmscan Out
# of c-Evalue i-Evalue score bias hmm coord from hmm coord to ali coord from ali coord to env coord from env coord to acc
1 14 0.0042 0.18 12.3 2.4 1 23 56 79 56 79 0.97
2 14 0.00046 0.02 15.3 0.6 1 23 85 108 85 108 0.94
3 14 8.5e-06 0.00036 20.7 4.5 1 23 114 137 114 137 0.98
4 14 0.0042 0.18 12.3 2.4 1 23 143 166 143 166 0.97
5 14 1.8 76 4.0 0.5 5 23 251 270 250 270 0.94
6 14 1.8 76 4.0 0.5 5 23 319 338 318 338 0.94
7 14 7e-05 0.003 17.8 0.5 1 23 354 377 354 377 0.97
8 14 3.5e-05 0.0015 18.8 1.7 1 23 383 406 383 406 0.96
9 14 0.0031 0.13 12.7 5.9 1 23 457 480 457 480 0.97
10 14 9.7e-06 0.00041 20.6 2.8 1 23 486 509 486 509 0.98
11 14 0.00038 0.016 15.5 0.3 3 23 517 538 516 538 0.95
12 14 0.0091 0.39 11.2 0.3 1 23 544 567 544 567 0.97
13 14 4.6e-05 0.0019 18.4 0.5 1 23 573 596 573 596 0.97
14 14 0.0013 0.056 13.8 0.4 1 23 603 626 603 626 0.96

Sequence Information

Coding Sequence
ATGCCTTACGCCGAGCTCCCGTTGCATAACGAATATCAGTACGAACTCAGACACCTTATGGTGGGTATTTTCTTGAGATTCTTCATCGTCTCCTTAGTTGACGATTACAGAAGTTTCAATTGGATATATTTacaccaaaggacaatacacgaaggtcgcaaagattttgcatgtgacagatgtgaaataaaatttgggCTCCaatgtaatttgaaaaaacaccaaaagacagtccacgaaggacgcaaagattttgcatgtgataagtgcgagaaaaagttcggacaaaaatcggGTTTGCTTTACCACCAAATGGCAACACACGaaagtcgtaaagattatacatgtgacaagtgcgagaaaaaatttgtgcatAAATCGTATTTGTTTTTGCACCAaaggacaatacacgaaggtcgcaaagattttgcatgtgacagatgtgaaataaaatttgggCTCCaatgtaatttgaaaaaacaccaaaagacggtgcacgaaagtcgcaaagattacgtatgcgacaagtCCATCAAAGGAAAGTACAtgaaggtcagaaagattttgcttgcgaTAAATGCAAGAAGATATTTGCACACAAACCGAATTTGCTCGTACACCGAAAGACGGtgcacgaaagtcgcaaagattacggatgcgacaagtgtgagaagaaattcgtaCACAAATCTAGTTTACTTTCGCACCAAAAGACTATTCATGAAGGCCGGAAAGATTTTGCTCTTAAcgaagtgcgaaaaaaaattttgggttCGCAGAACTTTGATcatgcaccaaaaaacagtccatgaggatCGCAAAGATTGCCCACGGtgcacgaaagtcgcaaagattacggatgcgacaagtgtgagaagaaattcgtaCACAAATCTAGTTTACTTTCGCACCAAAAGACTATTCATGAAGGCCGGAAAGATTTTGCTCTTAAcgaagtgcgaaaaaaaattttgggttCGCAGAACTTTGATcatgcaccaaaaaacagtccatgaggatCGCAAAGATTGCCCGaccgtacacgaaggtcgaaaagattacgcatgtgatgaATGCGGGAAGAAATTCGGACTTAAACAGTATTTGTTcattcaccaaaagacagtacacgagggtcgcaaagattttgcatgtaacgcatgcgataaaaaattcggacaaaaatcgcatttgatCAGTCACCAAAAGTCAGTCCACGAAGTggATCGAGATCGAGTATCgactatatgtatacatcgtATCCCGCGACAAGCTCAGATGTTCGTGGAAGATCGACGCTGTGTGGAGCGCACGGCATGCTTCGAGGTGCTACTCatcattAAGGCAGTCCACgagagtcgcaaagatttcgcatgtgaccaatgcgagaaaaaatatggCCATAAACACCATTTGCTCATTCATCGaaggacagtacatgaaggtcgcaaggacTTCTCATGCcccaattgcgagaagaaatttggacaaaaacaacatttacgtgtgcaccaaaagacagtacacgaaggtcaaaaAGATAATGCATGCGGCAGTTGTGACAAgaagtttggacaaaaaccaaatttgctcagacaccaaaaagaAGTACATGAGGGtcaaaaagatttcgcatgtgatgtttgtgagcagaaatttggagaaaaagcgACAATGatcagacacaaaaaaacagtccatgaaggtcgcaaaaacttcgcatgcgacaagtgcgagaaaacaTTTGGGCTTAAACAAAATTTACTTGTGCACCAAAGAacggtacacgaaggtcgtcacaaagattttgaatgcgacaagtgcgagaaaaagtttggacGCAAATCGATTTTGGTTATGCACCAAAGGGCAGTCCACGAAAGacgcaaagattttgaatctgacaaacagttcacgagggtcgcaaagactacgcatgcgacgagtgtgaaaagaaattcggacacaAATCGACTTTGGTTATGCACCAAAgtacagtacacgagggtcgcaaagatcatgcatgcgacagCAACGGCCCAGGTACGAGGCAGCATCGAACACGAGCTCGACGTGCCCTACGCGGCCAGCGAGAAGGCCAAGTACGACGTCTACGGGACCAATTTGCCCGATGacgcGCCGATACTGCTGTTCATACACGGAGGCTACTGGATGGAGTTCAGCAAGGACCTGTCGGGTTTCGCCGTGCCGAATTTCGTGGCCAACGGCGTGAAGGTCGTCCTCGCCGGCTACGATCTCTGCCCGAATGTTCGACTACCTGACATAGTCCGTCAAATCAAGACGCTCGTCGCTAAGCTGCTGAACCTGGCTAAAAATTTGGGCTCCAAAGGCGTATGGCTGGCCGGCCACAGTGCAGGCGCCCACCTGGCCGCGAGTCTCCTGCACGACCCCGAGTGGCTGGCGGCGAATCGCGCCTCGCTGGCTTGGCTCAAGGGCGCCTGGTTCCTAAGCGGCGTCTACGCCCTCGAGCCTCTGCTCCAGACCAGCGTCCAGGAGGCCCTCAAACTCACGCCGGAGGAGATAGAGAAGTACACGTTCGCGCCCCTGGACGAGGATAAGCAAAAGTTGAGTCAACAGCACAGCGGCCTGGACAATTTCAAAGCCGTCGTGGTCGTGGGCGAGAGCGACTCGCCGATCTTCGTCGAGGAATCGAGACGTTACGCTCGCAGGCTCACGAGCATCGTCGACAACGTCGAGTAtctgctgctgagaaacgacGTGGATCACTTCGACATCGTGGAAAATCTGACCAAGGCCGATTTCGTCCTGTCCAGGCACATGGTCGACTCCATCAAACGGTGCGTGTGGTTCGTTGGTCACAGCGCCGGCGCGCACTTGTTCTCCTGCTTACTGAACGACCGTGCCTGGTTCGAGCTGAACTCGGCGCTCCGTCCGGAGCATCTGGCGCTGCTGCGAGGCGTCGTTCTCGTCAGCGGCCTGTACGAGATCGAACCGGTGCTGCGCACCAGTAATCAGGAGACGCTTAAACTGACTAAGTACGTATTTACAACATGA
Protein Sequence
MPYAELPLHNEYQYELRHLMVGIFLRFFIVSLVDDYRSFNWIYLHQRTIHEGRKDFACDRCEIKFGLQCNLKKHQKTVHEGRKDFACDKCEKKFGQKSGLLYHQMATHESRKDYTCDKCEKKFVHKSYLFLHQRTIHEGRKDFACDRCEIKFGLQCNLKKHQKTVHESRKDYVCDKSIKGKYMKVRKILLAINARRYLHTNRICSYTERRCTKVAKITDATSVRRNSYTNLVYFRTKRLFMKAGKILLLTKCEKKFWVRRTLIMHQKTVHEDRKDCPRCTKVAKITDATSVRRNSYTNLVYFRTKRLFMKAGKILLLTKCEKKFWVRRTLIMHQKTVHEDRKDCPTVHEGRKDYACDECGKKFGLKQYLFIHQKTVHEGRKDFACNACDKKFGQKSHLISHQKSVHEVDRDRVSTICIHRIPRQAQMFVEDRRCVERTACFEVLLIIKAVHESRKDFACDQCEKKYGHKHHLLIHRRTVHEGRKDFSCPNCEKKFGQKQHLRVHQKTVHEGQKDNACGSCDKKFGQKPNLLRHQKEVHEGQKDFACDVCEQKFGEKATMIRHKKTVHEGRKNFACDKCEKTFGLKQNLLVHQRTVHEGRHKDFECDKCEKKFGRKSILVMHQRAVHERRKDFESDKQFTRVAKTTHATSVKRNSDTNRLWLCTKVQYTRVAKIMHATATAQVRGSIEHELDVPYAASEKAKYDVYGTNLPDDAPILLFIHGGYWMEFSKDLSGFAVPNFVANGVKVVLAGYDLCPNVRLPDIVRQIKTLVAKLLNLAKNLGSKGVWLAGHSAGAHLAASLLHDPEWLAANRASLAWLKGAWFLSGVYALEPLLQTSVQEALKLTPEEIEKYTFAPLDEDKQKLSQQHSGLDNFKAVVVVGESDSPIFVEESRRYARRLTSIVDNVEYLLLRNDVDHFDIVENLTKADFVLSRHMVDSIKRCVWFVGHSAGAHLFSCLLNDRAWFELNSALRPEHLALLRGVVLVSGLYEIEPVLRTSNQETLKLTKYVFTT

Similar Transcription Factors

Sequence clustering based on sequence similarity using MMseqs2

100% Identity
-
90% Identity
-
80% Identity
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