Thermodynamic Parameter Estimation for Modified Oligonucleotides Using Molecular Dynamics Simulations.

Area of Science:

• Biophysics
• Computational Chemistry
• Molecular Biology

Background:

• RNA/DNA hybrids are crucial in therapeutic oligonucleotides.
• Accurate thermodynamic modeling is essential for designing effective nucleic acid-based therapies.
• Existing methods struggle to precisely predict parameters for chemically modified nucleic acids.

Purpose of the Study:

• To investigate and accurately determine thermodynamic parameters for a large set of RNA/DNA hybrid duplexes, including natural and modified forms.
• To evaluate the performance of molecular mechanics Poisson-Boltzmann surface area (MMPBSA) and molecular mechanics generalized Born surface area (MMGBSA) in predicting these parameters.
• To develop experimentally reliable nearest-neighbor (NN) models for predicting melting temperatures of modified nucleic acids.

Main Methods:

• Utilized molecular dynamics (MD) simulations to analyze 1300 RNA/DNA hybrid duplexes.
• Calculated hybridization enthalpy and entropy using MMPBSA and MMGBSA approaches.
• Developed empirical relationships by comparing simulation data with experimental results to correct calculated parameters.

Main Results:

• MMGBSA demonstrated superior predictive performance, high convergence, and consistency for both natural and modified duplexes compared to MMPBSA.
• MMGBSA accurately captured the stabilizing effects of 2'-O-methoxyethyl (MOE) modifications with minimal bias.
• Corrected parameters enabled the generation of NN models for reliable melting temperature predictions.

Conclusions:

• MMGBSA is a highly reliable method for thermodynamic modeling of both natural and modified nucleic acids.
• This study provides a robust framework for accurate thermodynamic predictions, offering valuable insights for nucleic acid-based therapeutic design.
• The findings support the use of MMGBSA in advancing biotechnology and the development of oligonucleotide therapeutics.