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Analyzing and Building Nucleic Acid Structures with 3DNA

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NNDB: An Expanded Database of Nearest Neighbor Parameters for Predicting Stability of Nucleic Acid Secondary

Abhinav Mittal¹, Douglas H Turner², David H Mathews¹

¹Department of Biochemistry & Biophysics, University of Rochester Medical Center, Rochester, NY 14642, USA; Center for RNA Biology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Journal of Molecular Biology

|March 24, 2024

Summary

The Nearest Neighbor Database now includes DNA and modified RNA parameters, enhancing RNA and DNA secondary structure prediction. This updated resource offers accessible thermodynamic data for modeling molecular structures.

Keywords:

Nearest Neighbor Analysis Nucleic Acid Folding Thermodynamics RNA Secondary Structure Prediction

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Area of Science:

Biophysics
Computational Biology
Molecular Biology

Background:

Nearest neighbor thermodynamic parameters are crucial for predicting RNA and DNA secondary structures.
Accurate thermodynamic models are essential for understanding molecular ensembles.
The Nearest Neighbor Database (NNDB) has been a key resource for these parameters.

Purpose of the Study:

To expand the NNDB with new thermodynamic parameter sets.
To include parameters for DNA and modified RNA (including m⁶A).
To redesign the NNDB website for improved accessibility and usability.

Main Methods:

Incorporation of new thermodynamic datasets for DNA and modified RNA.
Redesign of the NNDB web interface utilizing the Quarto publishing system.
Provision of downloadable resources including parameter sets and a PDF version.

Main Results:

The NNDB now offers comprehensive nearest neighbor parameters for RNA (1999, 2004 sets) and DNA.
Expanded parameter sets include those for RNA with N6-methyladenosine (m⁶A).
The redesigned website provides enhanced access to functional forms, parameter values, and calculations.

Conclusions:

The expanded NNDB provides a more versatile resource for thermodynamic modeling of nucleic acid structures.
The updated database supports broader applications in RNA and DNA secondary structure prediction.
The accessible, redesigned platform facilitates research in biophysics and computational biology.