Basic Information

Gene Symbol
sd_1
Assembly
GCA_028454225.1
Location
CM052209.1:7368786-7380082[-]

Transcription Factor Domain

TF Family
TEA
Domain
TEA domain
PFAM
PF01285
TF Group
Helix-turn-helix
Description
The TEA domain is a DNA-binding region of about 66 to 68 amino acids that has been named after the two proteins that originally defined the domain: TEF-1 and AbaA. The TEA domain is located toward the N terminus of eukaryotic transcription factors of the TEA/ATTS family. It shows a three-helix bundle with a homeodomain fold [3, 1]. Two α-helices are nearly anti-parallel and pack on either side of the third one, which is the DNA-recognition helix of the TEA domain. Phosphorylation of one or both of the two conserved serines found on the DNA-binding surface could interfere with DNA-binding activity, by introducing electrostatic repulsion and/or steric hindrance, and help regulate the transcription factor activity of the proteins [2, 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 2 0.25 2.2e+03 -1.0 2.9 23 41 15 35 4 57 0.73
2 2 1.3e-10 1.2e-06 28.8 0.0 2 35 140 175 139 183 0.86

Sequence Information

Coding Sequence
ATGATGCATCGACACCGGCACAGTCCGCCCGAACGCAAGAAGAATGGAAGAAGGAGACTACGGGAAAAGAGGAACGAAAAAAAAGAGGAAAGAAACCGGTTGTTGCCTTTCCAGCAGCTGTCTTCCGAGTTAATCTCGAGAAAGATCGAGCAGGCGAAGAAGAAACGATATCTCGGCGTGACTCGACTCGACTCGGCTCGGCTCGGCTCGGCTCCGTTCTGCTCGATCGACATCGAACACGGTTTCCCGTTCCTGAAGACTGGCAGTGCGGTGGCTGCAGCCGACACCATTTCCGCGCCGTGGACTCCAGCGAGTTCCGGGCCGCCGCCCGACGCGAACGGCTCCGGCTCGGATACCAAGAACCTCGACGTTGGTGAAATTAGCGATGACGAGAAGGACTTATCGGCAGCGGACGCGGAGGGTGTGTGGTCACCGGATATCGAGCAAAGCTTCCAGGAAGCCCTCACCATATATCCGCCATGCGGCCGACGCAAAATCATCCTGTCCGACGAAGGGAAGATGTACGAGAAGTTCGGCGATCGTTCTAGTCGTGGCAGCTATTTGCTAGACACCGAGTAG
Protein Sequence
MMHRHRHSPPERKKNGRRRLREKRNEKKEERNRLLPFQQLSSELISRKIEQAKKKRYLGVTRLDSARLGSAPFCSIDIEHGFPFLKTGSAVAAADTISAPWTPASSGPPPDANGSGSDTKNLDVGEISDDEKDLSAADAEGVWSPDIEQSFQEALTIYPPCGRRKIILSDEGKMYEKFGDRSSRGSYLLDTE

Similar Transcription Factors

Sequence clustering based on sequence similarity using MMseqs2

100% Identity
-
90% Identity
-
80% Identity
-