Genome-wide prediction of minor-groove electrostatic potential enables biophysical modeling of protein-DNA binding.

Abstract:

:Protein-DNA binding is a fundamental component of gene regulatory processes, but it is still not completely understood how proteins recognize their target sites in the genome. Besides hydrogen bonding in the major groove (base readout), proteins recognize minor-groove geometry using positively charged amino acids (shape readout). The underlying mechanism of DNA shape readout involves the correlation between minor-groove width and electrostatic potential (EP). To probe this biophysical effect directly, rather than using minor-groove width as an indirect measure for shape readout, we developed a methodology, DNAphi, for predicting EP in the minor groove and confirmed the direct role of EP in protein-DNA binding using massive sequencing data. The DNAphi method uses a sliding-window approach to mine results from non-linear Poisson-Boltzmann (NLPB) calculations on DNA structures derived from all-atom Monte Carlo simulations. We validated this approach, which only requires nucleotide sequence as input, based on direct comparison with NLPB calculations for available crystal structures. Using statistical machine-learning approaches, we showed that adding EP as a biophysical feature can improve the predictive power of quantitative binding specificity models across 27 transcription factor families. High-throughput prediction of EP offers a novel way to integrate biophysical and genomic studies of protein-DNA binding.

journal_name

Nucleic Acids Res

journal_title

Nucleic acids research

authors

Chiu TP,Rao S,Mann RS,Honig B,Rohs R

doi

10.1093/nar/gkx915

subject

Has Abstract

pub_date

2017-12-01 00:00:00

pages

12565-12576

issue

21

eissn

0305-1048

issn

1362-4962

pii

4430925

journal_volume

45

pub_type

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