Prediction of DNA binding motifs from 3D models of transcription factors; identifying TLX3 regulated genes.

ABSTRACT: Proper cell functioning depends on the precise spatio-temporal expression of its genetic material. Gene expression is controlled to a great extent by sequence-specific transcription factors (TFs). Our current knowledge on where and how TFs bind and associate to regulate gene expression is incomplete. A structure-based computational algorithm (TF2DNA) is developed to identify binding specificities of TFs. The method constructs homology models of TFs bound to DNA and assesses the relative binding affinity for all possible DNA sequences using a knowledge-based potential, after optimization in a molecular mechanics force field. TF2DNA predictions were benchmarked against experimentally determined binding motifs. Success rates range from 45% to 81% and primarily depend on the sequence identity

SUBMITTER: Pujato M 

PROVIDER: S-EPMC4267649 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature