Protein-RNA interactions regulate diverse biological processes and are increasingly exploited in therapeutic RNA discovery, but accurate inferences of nucleotide preferences and reliable structure prediction remain challenging. Here, we present PRIS, a unified structure-based deep-learning framework that combines two complementary components: PRISeq for nucleotide probability estimation at each RNA position and PRIScore for residue-nucleotide distance prediction to discriminate native-like from incorrect poses. Both share a feature extractor that integrates an Anti-Symmetric Graph Attention Network (A-GAT) with sparse k-Maximum Inner Product (k-MPI) attention to capture long-range interactions across large graphs. PRIScore improves the selection of native-like protein-RNA predictions generated by AlphaFold3, achieving a top-1 success rate of 81.91% on a docking benchmark, compared to 79.26% for AlphaFold3. The selected structures are then fed into PRISeq, which infers position-specific binding preferences and screens RNA libraries. On a PWM benchmark, PRISeq achieved a mean absolute error (MAE) of 0.75, outperforming FoldX, Rosetta-based scoring functions, and NA-MPNN. In virtual screening against MS2 protein, PRISeq screens 129,248 RNA hairpins within 11.95 seconds, achieving the highest EF0.5% of 14.40, approximately double the best baseline. PRIS also effectively enriches active aptamers against NELF-E and GFP while preserving sequence diversity. By integrating structure selection with binding-preference inference, PRIS provides an efficient framework for large-scale RNA library screening and aptamer design.
Yi-Hao Zhao, Jing Han, Ji-Ke Wang et al.· bioRxiv· 0 citations
Clematis florida
var.
Plena
(
C. florida
) holds significant potential as a topical treatment for immune-mediated polyarthritis (IMPA); however, its active fractions and mechanisms of action remain poorly understood. Given the chemical complexity of herbal remedies, this study adopted a bioactivity- and mechanism-driven approach, focusing on the effects of polarity-based fractions rather than isolated compounds.
C. florida
was extracted with 70% ethanol and sequentially partitioned into petroleum ether (PE), ethyl acetate (EA),
n
-butanol (BU), and water (WA) fractions. Phytochemical analysis was conducted to determine the distribution of saponins and flavonoids. Anti-inflammatory and analgesic activities were evaluated using xylene-induced ear edema and acetic acid-induced writhing models, respectively. Therapeutic efficacy was assessed in a rat model of adjuvant-induced arthritis via topical application. Joint tissues were analyzed using H&E and Safranin O–Fast Green staining, immunohistochemistry, and Western blotting to investigate histological changes and signaling pathways (ERK and NF-κB).
Phytochemical analysis revealed that the extract is rich in saponins and flavonoids, which exhibit distinct distribution patterns across fractions of varying polarity. All fractions exhibited anti-inflammatory effects in the ear edema model and analgesic activity in the writhing test. In the arthritis model, topical application of the EA, BU, and WA fractions significantly attenuated paw swelling and reduced serum levels of TNF-α, COX-2, rheumatoid factor, and IL-6. Histological staining confirmed partial protection against joint destruction. Mechanistic studies revealed that these fractions enhanced ERK phosphorylation and suppressed NF-κB activation in joint tissues.
The EA, BU, and WA fractions of
C. florida
possess significant topical therapeutic potential against IMPA. The anti-arthritic effects are likely associated with the modulation of ERK and NF-κB signaling pathways. This study elucidates the pharmacodynamic basis of
C. florida
fractions, positioning them as promising candidates for the development of topical treatments for animal joint disorders.
Ting Lei, Jiabing Zheng, Jie Han et al.· Frontiers in Veterinary Scie...· 0 citations
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