Theoretical Computational Analysis Predicts Interaction Changes Due to Differences of a Single Molecule in DNA

Theoretical methods, such as molecular mechanics and molecular dynamics, are very useful in understanding differences in interactions at the single molecule level. In the life sciences, small conformational changes, including substituent modifications, often have a significant impact on function in vivo. Changes in binding interactions between nucleic acid molecules and binding proteins are a prime example. In this study, we propose a strategy to predict the complex structure of DNA-binding proteins with arbitrary DNA and analyze the differences in their interactions. We tested the utility of our strategy using the anticancer drug trifluoro-thymidine (FTD), which exerts its pharmacological effect by incorporation into DNA, and confirmed that the binding affinity of the BCL-2-associated X sequence to the p53 tetramer is increased by FTD incorporation. On the contrary, in p53-binding sequences extracted from FTD-resistant cells, the binding affinity of DNA containing FTD was found to be greatly reduced compared to normal DNA. This suggests that thymidine randomly substituted for FTD in resistant cells may acquire resistance by entering a position that inhibits binding to DNA-binding proteins. We believe that this is a versatile procedure that can also take energetics into account and will increase the importance of computational science in the life sciences.

Automated summary

In this study, a strategy to predict the complex structure of DNA-binding proteins with arbitrary DNA and analyze the differences in their interactions was proposed. It was found that the binding affinity between the BCL-2-associated X sequence and the p53 tetramer is increased by the anticancer drug trifluoro-thymidine (FTD) incorporation, while in p53-binding sequences extracted from FTD-resistant cells, the binding affinity of DNA containing FTD was greatly reduced. This suggests that thymidine randomly substituted for FTD in resistant cells may acquire resistance by inhibiting binding to DNA-binding proteins. This versatile procedure, which considers energetics, will increase the importance of computational science in the life sciences.