modXNA: a modular approach to parameterization of modified nucleic acids for use with Amber force fields

Published

October 29, 2024

Author(s)

Olivia Love, Rodrigo Galindo-Murillo, Daniel Roe, Pablo D. Dans, Thomas E. Cheatham III, Christina Bergonzo

Abstract

Modified nucleic acids have surged as a popular therapeutic route, emphasizing the importance of nucleic acid research in drug discovery and development. Beyond well-known RNA vaccines, antisense oligonucleotides and aptamers can incorporate various modified nucleic acids to target specific biomolecules for various therapeutic activities. Molecular dynamics simulations can accelerate the design and development of these systems with noncanonical nucleic acids by observing intricate dynamic properties and relative stability on the all-atom level. However, modeling these modified systems is challenging due to the time and resources required to parameterize components outside default force field parameters. Here, we present modXNA, a tool to derive and build modified nucleotides for use with Amber force fields. Several nucleic acid systems varying in size and number of modification sites were used to evaluate the accuracy of modXNA parameters, and results indicate the dynamics and structure are preserved throughout the simulations. We detail the protocol for quantum mechanic charge derivation and describe a workflow for implementing modXNA in Amber molecular dynamics simulations, which includes updates and added features to CPPTRAJ.

Citation

Journal of Chemical Theory and Computation

Pub Type

Journals

Download Paper

https://doi.org/10.1021/acs.jctc.4c01164?ref=PDF

Local Download

Keywords

RNA, molecular dynamics, force field, parameterization

Citation

Love, O. , Galindo-Murillo, R. , Roe, D. , Dans, P. , Cheatham III, T. and Bergonzo, C. (2024), modXNA: a modular approach to parameterization of modified nucleic acids for use with Amber force fields, Journal of Chemical Theory and Computation, [online], https://doi.org/10.1021/acs.jctc.4c01164?ref=PDF, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=958346 (Accessed October 27, 2025)