Rachael Kretsch
@rachael-kretsch.bsky.social
140 followers 120 following 55 posts
Biophysics PhD Student with DasLab & ChiuLab. Pairing RNA structure & cryoEM to better understand both! King's College, Science & Security '19 Harvey Mudd '18
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rachael-kretsch.bsky.social
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
automnenine.bsky.social
Hey thats me.
rachael-kretsch.bsky.social
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
rachael-kretsch.bsky.social
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
rachael-kretsch.bsky.social
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!
antonipetrov.bsky.social
🤯 Implications for OLE RNA as a natural integral membrane RNA from Ron Breaker's lab rnajournal.cshlp.org/content/earl...
rachael-kretsch.bsky.social
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!
rachael-kretsch.bsky.social
(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
rachael-kretsch.bsky.social
(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
rachael-kretsch.bsky.social
(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
rachael-kretsch.bsky.social
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
rachael-kretsch.bsky.social
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.
rachael-kretsch.bsky.social
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...).
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...
doi.org
rachael-kretsch.bsky.social
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.
rachael-kretsch.bsky.social
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!
rachael-kretsch.bsky.social
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.
rachael-kretsch.bsky.social
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.
rachael-kretsch.bsky.social
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.
rachael-kretsch.bsky.social
Prediction of other motifs, such as A-minor interactions, that form long range interactions important for stitching together the 3D structure remains challenging.
rachael-kretsch.bsky.social
However, CASP16 participants, including automated methods trRosettaRNA and AF3, are more accurate at predicting secondary structure than popular secondary structure prediction algorithms.
rachael-kretsch.bsky.social
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.
rachael-kretsch.bsky.social
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.
rachael-kretsch.bsky.social
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.
rachael-kretsch.bsky.social
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.
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 ...
doi.org
rachael-kretsch.bsky.social
Please reach out to me in a message or email if interested!
rachael-kretsch.bsky.social
We will be meeting, Thursdays 3pm UTC = 8am PDT / 11am EDT / 4pm CEST / 11pm CST. For our colleagues in the more difficult timezone, we can accommodate changes in time!
rachael-kretsch.bsky.social
We are also looking for excited scientists to help organize! For me, the SIG has been a great way to get to know the RNA community, highly recommended for all early-career scientists interested in the nucleic-acid structure prediction field!