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NameDr. Antonio Bauza Riera
Organization or InstitutionUniversity of Florida
TopicComputational Chemistry
Title

On the importance of DNA structure in TF-DNA binding: A theoretical approach.

Author(s)

Antonio Bauza, Alberto Perez

Author Institution(s)

University of Florida

Abstract

Understanding the mechanisms that rely beneath gene regulation is considered a grand challenge in biology.[1] This is ultimately related to the ability of TF (Transcription Factors) to bind specific DNA regions along our genome (from 6 to 8 base pairs).[2] Given the huge number of DNA sequences where a TF can potentially bind and the thousands of times each shows up in the genome: How do TF recognize their binding partners? Community-efforts such as ENCODE[3] (Encyclopedia of the DNA Elements) have tried to tackle this issue from a pure sequence approach. But, the rules behind gene regulation and TF binding remain elusive. The role of DNA structure is not fully understood and generally overlooked in genome wide studies.

In this study we aim to evaluate the effect of the DNA sequence and structure in the binding affinity of four TF families (CREB bZIP:SSCRE, TATA-box, Sex-determining region Y and P22 c2 repressor). To achieve this goal, we have carried out MD (Molecular Dynamics) simulations of both native TF-DNA and several mutant-DNA complexes using the AMBER ff14SB (protein) and parmbsc1 (DNA) Force Fields in an explicit solvent box (TIP3P water model). Our results show how changes in sequence translate into structural changes and how those might have an impact on binding affinity. Furthermore, these changes are not generalized between all protein families – likely highlighting the difficulties in a sequence only approach to understand gene regulation rules. We coined the term indirect readout for describing the structural impact of the DNA conformation upon binding and concluded that it is family dependent.

[1] Smith, N. C.; Matthews, J. M. Mechanisms of DNA-binding Specificity and Functional Gene Regulation by Transcription Factors. Curr. Opin. Struct. Biol. 2016, 38, 68-74.

[2] Pan, Y.; Tsai, C.-J.; Ma, B.; Nussinov, R. Mechanisms of Transcription Factor Selectivity. Trends Genet. 2010, 26, 75-83.

[3] https://www.encodeproject.org/