Motivation: Chemical shifts (CS) are an important source of structural information of macromolecules such as RNA. In addition to the scarce availability of CS for RNA, the observed values are prone to errors due to a wrong re-calibration or miss assignments. Different groups have dedicated their efforts to correct CS systematic errors on RNA. Despite this, there are not automated and freely available algorithms for evaluating the referencing of RNA 13 C CS before their deposition to the BMRB or re-reference already deposited CS with systematic errors. Results: Based on an existent method we have implemented an open source python module to correct 13 C CS (from here on 13Cexp) systematic errors of RNAs and then return the results in 3 formats including the nmrstar one. Availability and implementation: This software is available on GitHub at https://github.com/BIOS-IMASL/13Check_RNA under a MIT license. Supplementary information: Supplementary data are available at Bioinformatics online.

UNLABELLED: The differences between observed and predicted (13)C(α) chemical shifts can be used as a sensitive probe with which to detect possible local flaws in protein structures. For this reason, we previously introduced CheShift, a Web server for protein structure validation. Now, we present CheShift-2 in which a graphical user interface is implemented to render such local flaws easily visible. A series of applications to 15 ensembles of conformations illustrate the ability of CheShift-2 to locate the main structural flaws rapidly and accurately on a per-residue basis. Since accuracy plays a central role in CheShift predictions, the treatment of histidine (His) is investigated here by exploring which form of His should be used in CheShift-2. AVAILABILITY: CheShift-2 is free of charge for academic use and can be accessed from www.cheshift.com