Thermodynamic model of interaction of small ligands with DNA

TL;DR

This paper presents a thermodynamic model linking DNA-ligand stability constants to complex lifetime, simplifying dynamic analysis of biomolecules and enabling new insights into DNA hydration, tautomerization, and structural states.

Contribution

It introduces a novel approach connecting stability constants to dynamic lifetimes, expanding the analysis of DNA interactions and structural transitions.

Findings

Hydration energy increases after DNA transition from B to unordered state

Identification of the number of wrong Watson-Crick pairs in DNA

Quantitative estimation of metal-induced tautomerization events

Abstract

We have managed to correlate the stability constants of complex formation, which can be registered in equilibrium state, to the dynamic characteristic of the complex lifetime. Thus, the principal concept of molecular biophysics regarding biomolecule, structure-dynamics-function can be reformatted as structure-stability-function. It should be specially noted that such an approach highly simplifies end widens the time interval of investigation of dynamic characteristics of macromolecules. Study of hydration energy and hydration number by kinetic curves of water desorption from Na-DNA humidified fibers by glow discharge atomic spectral analysis of hydrogen allowed us to reveal that after transition of DNA from B form to unordered state the activation energy of hydrated water desorption increases by 0.65kcal/Mole of water. This increase of energy is 0.1 kcal/Mole for transition from B to C form (from 20 to 10 water molecules per nucleotide) and 0.55 kcal/Mole for the one from C form to A unordered state (from 10 to 5 molecules per nucleotide). Simultaneous use of UDS and AES allows identifying the number of Wrong Watson-Crick pairs in DNA. The quantitative analysis is based on increase of informativity of UDS via its combination with atomic-emission spectroscopy. The number of the total metal-induced tautomerization makes six hundred per million base pairs of DNA. Such approach enables estimation of risk factors during clinical check-ups and evaluation of DNA suitability for nanotechnological purposes.