A Balanced View Of Nucleic Acid Structural Modeling

Nucleic acid modeling is a changing field. A new alphabet has arisen, complementing the Leontis-Westhof nomenclature, and which enables a more complete representation of nucleic acid structure. Recent success in solving protein structure by deep learning has turned RNA into the next frontier in structure prediction. The Cryo-Electron Microscopy revolution has created a demand for new fitting methods for nucleic acids. Under all of this lies a substrate of dynamical modeling and quality evaluation software.

In this Research Topic, we aim to bring together a balanced view of the multiple threads of  development in this vibrant and changing field. We wish to present a balanced view of current work in nucleic acid modeling, spanning alphabets, density map fitting, and structure prediction, as well as the underlying dynamics and quality control technology.

We solicit reviews and original research articles in the following areas:

• Structural alphabets


• Density map fitting


• Structure prediction methods


• Dynamics


• Quality evaluation methods

Keywords: deep learning, structural alphabets, CryoEM, electron microscopy, structural prediction, density fitting, structural quality evaluation

Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.