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High-throughput single-molecule quantification of individual base stacking energies in nucleic acids.

ABSTRACT: Base stacking interactions between adjacent bases in DNA and RNA are important for many biological processes and in biotechnology applications. Previous work has estimated stacking energies between pairs of bases, but contributions of individual bases has remained unknown. Here, we use a Centrifuge Force Microscope for high-throughput single molecule experiments to measure stacking energies between adjacent bases. We found stacking energies strongest between purines (G|A at -2.3 ± 0.2 kcal/mol) and weakest between pyrimidines (C|T at -0.5 ± 0.1 kcal/mol). Hybrid stacking with phosphorylated, methylated, and RNA nucleotides had no measurable effect, but a fluorophore modification reduced stacking energy. We experimentally show that base stacking can influence stability of a DNA nanostructure, modulate kinetics of enzymatic ligation, and assess accuracy of force fields in molecular dynamics simulations. Our results provide insights into fundamental DNA interactions that are critical in biology and can inform design in biotechnology applications.

SUBMITTER: Abraham Punnoose J

PROVIDER: S-EPMC9902561 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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High-throughput single-molecule quantification of individual base stacking energies in nucleic acids.

Abraham Punnoose Jibin J Thomas Kevin J KJ Chandrasekaran Arun Richard AR Vilcapoma Javier J Hayden Andrew A Kilpatrick Kacey K Vangaveti Sweta S Chen Alan A Banco Thomas T Halvorsen Ken K

Nature communications 20230206 1

Base stacking interactions between adjacent bases in DNA and RNA are important for many biological processes and in biotechnology applications. Previous work has estimated stacking energies between pairs of bases, but contributions of individual bases has remained unknown. Here, we use a Centrifuge Force Microscope for high-throughput single molecule experiments to measure stacking energies between adjacent bases. We found stacking energies strongest between purines (G|A at -2.3 ± 0.2 kcal/mol) ...[more]

PMID: 36746949

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Project description:Base stacking is known to make an important contribution to the stability of DNA and RNA, and accordingly, significant efforts are ongoing to calculate stacking energies using ab initio quantum mechanical methods. To date, impressive improvements have been made in the model chemistries used to perform stacking energy calculations, including extensions that include robust treatments of electron correlation with extended basis sets, as required to treat interactions where dispersion makes a significant contribution. However, those efforts typically use rigid monomer geometries when calculating the interaction energies. To overcome this, in the present work, we describe a novel internal coordinate definition that allows the relative, intermolecular orientation of stacked base monomers to be constrained during geometry optimizations while allowing full optimization of the intramolecular degrees of freedom. Use of the novel reference frame to calculate the impact of full geometry optimization versus constraining the bases to be planar on base monomer stacking energies, combined with density-fitted, spin-component scaling MP2 treatment of electron correlation, shows that full optimization makes the average stacking energy more favorable by -3.4 and -1.5 kcal/mol for the canonical A and B conformations of the 16 5' to 3' base stacked monomers. Thus, treatment of geometry optimization impacts the stacking energies to an extent similar to or greater than the impact of current state of the art increases in the rigor of the model chemistry itself used to treat base stacking. Results also indicate that stacking favors the B-form of DNA, though the average difference versus the A-form decreases from -2.6 to -0.6 kcal/mol when the intramolecular geometry is allowed to fully relax. However, stacking involving cytosine is shown to favor the A-form of DNA, with that contribution generally larger in the fully optimized bases. The present results show the importance of allowing geometry optimization, as well as properly treating the appropriate model chemistry, in studies of nucleic acid base stacking.

Dataset Information

High-throughput single-molecule quantification of individual base stacking energies in nucleic acids.

Publications

High-throughput single-molecule quantification of individual base stacking energies in nucleic acids.

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