- Protein-DNA Binding Site Prediction with Sequence-Dependent Force Field Energy Minimization
- Project Year:
2024
- REU Student (s):
Ryan Ding | University of California-San Diego CA
- Student 1 Institution:
University of California-San Diego
- Project Mentor:
Wilma Olson
- Project Mentor Area:
Chemistry and Chemical Biology
- Project Abstract:
The conformational preferences of B-DNA sequences hold significant research value, particularly in the context of gene expression and DNA replication processes. Equally important are the interactions between protein structures that bind to these sequences and impact the conformational preferences of the complex. However, identifying the ideal binding site to which the protein should be bound on a sequence can be challenging, as differing locations may lead to less favorable conformations that impact DNA processes. We present a method that utilizes sequence-dependent force field models derived from high-resolution structures to predict the ideal binding site for a protein structure on a DNA sequence. We enhance existing energy minimization protocols within the emDNA software and conduct a case study using the DNA gyrase enzyme and a 601 base pair DNA minicircle. Through iteratively energy minimization procedure across a sequence with varying protein binding sites, we are able to calculate and derive low-energy states of the protein-DNA complex which may reveal ideal binding locations and thus make educated inferences that may assist in solving crystal structures.
