Basic Information

Gene Symbol
sd
Assembly
GCA_018150985.1
Location
JAECWU010000052.1:3260509-3279020[+]

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 0.42 3.9e+03 -1.7 0.0 33 49 59 75 34 78 0.63
2 2 1.2e-10 1.1e-06 28.9 0.0 2 36 152 188 151 191 0.90

Sequence Information

Coding Sequence
ATGTGTTCAAATTGCGTCGACGTTGGCGTTGACGTTATCTTGGCTGTGGCTGTCAACAGCGCCAAAGCAGCGCATCCCATTCTCGAAATCAAACTAAAACTAAAAGCTCTGCAAATAGTCAATGTTAGTGAAGCGGGTGAGCAGCAGCTGCTGCTGCTACATTGGTGGAGCAAGGAGGGGGCCAGGCGGGCACCTGTTATCAACATTTATTTAAAAAACGATACAGAAGACGGCACCAAAGTGGCGCCGTTCTCCAAACATTTGGATTCCCTTGAGGAATTTAAGGGATTGTCGGTTGGACCCGGCACCATACCATCCCCGTGGACACCAGTGAATGCCGGTCCGCCGGGTCCACTCGGATCGGCAGACACAAATGGCAGCATGGTGGATAGCAAAAATTTGGATGTGGGCGATATGAGCGATGATGAAAAAGATCTATCATCAGCCGATGCCGAAGGTGTTTGGAGTCCAGACATTGAACAAAGCTTTCAAGAGGCATTATCAATATATCCGCCATGTGGACGCAGGAAAATTATTTTATCCGATGAGGGTAAAATGTATGGTAAGTTGAACAAATAA
Protein Sequence
MCSNCVDVGVDVILAVAVNSAKAAHPILEIKLKLKALQIVNVSEAGEQQLLLLHWWSKEGARRAPVINIYLKNDTEDGTKVAPFSKHLDSLEEFKGLSVGPGTIPSPWTPVNAGPPGPLGSADTNGSMVDSKNLDVGDMSDDEKDLSSADAEGVWSPDIEQSFQEALSIYPPCGRRKIILSDEGKMYGKLNK

Similar Transcription Factors

Sequence clustering based on sequence similarity using MMseqs2

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