Year: 2018
Type: review
Abstract: The transcriptional activation domains (TADs) are critical for life, yet intrinsically disordered polypeptides with no specific consensus sequence, interacting with multiple targets via low-specificity fuzzy contacts. The recent integration of machine learning approaches in biochemistry allows analysis of large experimental datasets of functional TADs as a whole and clear observation of TAD features. The emerging picture describes TADs as sequences without consensus but with a variety of detergent-like mini-motifs enriched in negatively charged and aromatic amino acids. Comparison of the canonical direct coactivator recruitment model and a new model describing TADs as nucleosome detergents that trigger chromatin remodeling during gene activation helps solve a fundamental enigma of molecular biology spanning 30 years.
Source: Trends in Biochemical Sciences
Author: Alexandre M. Erkine
Institution: Butler University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $7,030
Funder: National Science Foundation
OpenAlex ID: W2895309377