Accurate and sensitive quantification of protein-DNA binding affinity.
Ontology highlight
ABSTRACT: Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding
SUBMITTER: Rastogi C
PROVIDER: S-EPMC5910815 | biostudies-literature | 2018 Apr
REPOSITORIES: biostudies-literature
ACCESS DATA