Dictionary based approaches for studying intrinsic DNA shape in transcription factor recognition

Abstract

Sequence-dependent intrinsic conformational dynamics confer specificity to transcriptional factor recognition of genomic DNA. Their genome-scale investigation using all-atom simulations is challenging, and alternative approaches by coarse-graining DNA into beads-and-sticks or polymer models have their own limitations. One parallel approach is what we describe here as a dictionary-based approach. This has been shown to explain several transcriptional events in biological systems but has been inadequately reviewed. These approaches represent studies based on a finite number of DNA fragments and their corresponding conformational properties, scaled up to genomes by pooling nearby fragments and machine learning models. This article aims to organize efforts made in generating these models and their recent successful applications to stimulate further development of this approach.