摘要：Transcription factors (TFs) play important roles in many biochemical processes. Many human genetic disorders have been associated with mutations in the genes encoding these transcription factors, and so those mutations became targets for medications and drug design. In parallel, since many transcription factors act either as tumor suppressors or oncogenes, their mutations are mostly associated with cancer. In this perspective, we studied the
GATA3 transcription factor when bound to
DNA in a crystal structure and assessed the effect of different mutations encountered in patients with different diseases and phenotypes. We generated all missense mutants of
GATA3 protein and DNA within the adjacent and the opposite
GATA3:DNA complex models. We mutated every amino acid and studied the new binding of the complex after each mutation. Similarly, we did for every
DNA base. We applied Poisson-Boltzmann electrostatic calculations feeding into free energy calculations. After analyzing our data, we identified amino acids and DNA bases keys for binding. Furthermore, we validated those findings against experimental genetic data. Our results are the first to propose in silico modeling for
GATA:DNA bound complexes that could be used to score effects of missense mutations in other classes of transcription factors involved in common and genetic diseases.
