Rachael Kretsch

Come learn about super interesting and cool DNA structure at our nucleic acid structure webinar by Cameron Mackereth "Unusual DNA architecture in a dopamine-bound aptamer complex" on March 5

Meeting ID: 934 4593 5624
Passcode: 802843

Mailing list: groups.google.com/g/casp-rna-sig

Come learn about new tricks with DMS next week at our nucleic acid structure webinar by Tony Mustoe "Teaching an old dog new tricks: Using DMS to map higher-order RNA structures and folding thermodynamics"

Meeting ID: 934 4593 5624
Passcode: 802843

Mailing list: groups.google.com/g/casp-rna-sig

Please join us for our next nucleic acid structure webinar, "Template-based RNA structure prediction advanced through a blind code competition," presented by Rhiju Das, G. John Rao, Toshiyuki Oda, Yehyun Kim, Raehyun Kim, Hyunkin Kim.

Mailing list: groups.google.com/g/casp-rna-sig

Very excited for our next webinar in 1 week featuring Hani Goodarzi discussing "Building Structure-Aware Models of RNA-Protein Interactions Through Explicit Context-Free Grammar Encoding". Mailing list: groups.google.com/g/casp-rna-sig

Join us for our next seminar featuring Marta Szachniuk, one of the leading experts in the computational biology of RNA 3D structure. She will discuss RNA entanglements. Mailing list: groups.google.com/g/casp-rna-sig

The beauty of symmetric, homo-oligomeric biomolecular complexes cannot be denied— nature builds these from RNA as well! Here’s to the years ahead, as the community uncovers what these assemblies can teach us about RNA biophys and functions, and how they may inspire future biotechnology.

On Wednesday join us for our next Nucleic Acid Structure webinar by Dr Yun-Xing Wang
"Snapshot structure vs. conformational space of RNA under physiologically relevant Mg2+ concentrations"
This will not be recorded please join live. Join the mailing list groups.google.com/g/casp-rna-sig

Registration to the next RNA BENASQUE meeting July 05-17 2026 is open.
benasque.org/2026rna/

Yes, Benasque is my profile pic. This #RNA meeting puts together for 2 weeks researchers in computational methods for structural RNA. 9th edition already! #RNAsky

CASP RNA SIG Welcome nucleic acid enthusiasts to the Special Interest Group (SIG) focused different aspects of nucleic acid 3D structure prediction, including but not limited to obtaining experimental data, buildi...

Recording (and most of our past seminars) are released here, www.youtube.com/@CASPRNASIG, enjoy!

Indeed this seminar will be given by none other than the amazing George Ghanim @automnenine.bsky.social , come learn about how human retrotranposons work and interact with their target DNA

We have restarted our global Nucleic Acid Strcuture webinar series to bring the expiremental and computational communities together to discuss new developments in the field. Join us this Thursday for the next webinar. Sign up to our mailing list here: groups.google.com/g/casp-rna-sig

When I determed OLE's structure, a transmembrane RNP was staring at me. Took a little bravery to propose this in our manuscript, so I am stoked to see the experts elaborate further. Past data does not rule out OLE RNA spanning the membrane, but data is still needed. Excited for future OLE studies!

And of course thanks to John Moult and Andriy Kryshtafovych for helping recruit all these amazing structural biologists to donate their structures and time to the CASP effort. Thanks for letting me coordinate this paper for the second time, such a cool collection works!

(10) @emillk.bsky.social , Nikolaj H. Zwergius and @esandersen.bsky.social discuss 2’F modified RNA origami and protein-binding aptamer
(11) Heewhan Shin and @phoeberice.bsky.social discuss SPβ LSI-RDF synaptic complex
(12) Reinhard Albrecht, Yimin Hu and Marcus D. Hartmann discuss UDE bound to DNA

(7) Shekhar Jadhav, Michela Nigro, and Marco Marcia discuss group IIC intron
(8) Liu Wang, Jiahao Xie, and Zhaoming Su discuss ROOL RNA nanocage
(9) @rachael-kretsch.bsky.social , Yuan Wu, Rhiju Das, Wah Chiu discuss OLE RNA dimer

(3) Anna Lewicka, Yoshita Srivastava and Joseph A. Piccirilli discuss a 3’ CITE
(4) @cpricejones.bsky.social discusses ZTP riboswitches
(5) Hsuan-Ai Chen and Claudia Höbartner discuss SAMURI
(6) Eric Largy, Philip E. Johnson, and @cdmackereth.bsky.social discuss a DNA aptamer

We each analysed the predictions for the target we expirementally determined, resulting in 12 excellent chapters:
(1) @jgezelle.bsky.social and @lenasteckelberg.bsky.social ‪‪discuss a xrRNA
(2) Manju Ojha and Deepak Koirala discuss HIV RRE SLII

So much fun working with and learning from some of the best NA structural biologists across the world. It is the hard work of experimental structural biologists that will provide the data and, perhaps most importantly, set the goal-posts for what structure prediction should be aiming to achieve.

Functional relevance of CASP16 nucleic acid predictions as evaluated by structure providers Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, exper...

Nucleic acid structural biologists expose that many CASP16 predictions, even ones obtaining high scores by CASP metrics, are inaccurate in the most functionally relevant regions! Read more insights on functionally relevant features by the expert structure determiners (doi.org/10.1101/2025...).

I am excited to see the innovation that will progress nucleic acid structure prediction accuracy as evaluated in RNA puzzles and CASP17! I am perhaps even more excited to see the new ideas that will push our notion of “structure” (or what objectives structure prediction should have) farther.

CASP16 did challenge predictors with very challenging large RNAs with no previous structures. While no predictors were able to tackle these problems, there are early indications that human experts and automated methods can extract tertiary information from MSAs if sufficiently deep!

Despite, sub-human performance, servers have seen a jump in performance in CASP16; for the first time servers are able to improve on best available structure template.

The dependence on template availability was observed in RNA-RNA, NA-protein, and NA-ligand interaction prediction in our RNA-multimer, hybrid and NA-ligand category assessments. These categories and the prediction of DNA aptamer structure remain key future challenges.

Throughout the history of NA structure prediction, accuracy has been dependent on template availability, a trend that unfortunately continues in CASP16. Protein structure prediction has shown this is a surmountable challenge.

Prediction of other motifs, such as A-minor interactions, that form long range interactions important for stitching together the 3D structure remains challenging.

However, CASP16 participants, including automated methods trRosettaRNA and AF3, are more accurate at predicting secondary structure than popular secondary structure prediction algorithms.

Although the AF3-server can now predict nucleic acid structure, its performance on nucleic acid monomer structure prediction was average; 12 groups out-performed AF3.

As in CASP15, expert human groups ranked best across targets and categories. These groups are increasingly using deep-learning algorithms to sample structures, which they often then refine or select using physics based algorithms or expert knowledge.

Work by @alissahummer.com, Shujun He, Rongqing Yuan, Jing Zhang, Thomas Karagianes, Qian Cong, Andriy Kryshtafovych, Rhiju Das, and sizable participation of scientists across the world which provided 42 targets and predictions from 65 groups.

Assessment of nucleic acid structure prediction in CASP16 Consistently accurate 3D nucleic acid structure prediction would facilitate studies of the diverse RNA and DNA molecules underlying life. In CASP16, blind predictions for 42 targets canvassing a full ...

What is the status of nucleic acid structure prediction? Our analysis of CASP16 (doi.org/10.1101/2025...) reveals human expertise is still necessary for the most accurate prediction, but accuracy still heavily relies on templates; having seen a similar structure already.