Results 151 to 160 of about 365,379 (338)
SETDB2 epigenetically represses Smad3 transcription by increasing H3K9me3 enrichment at its promoter, thereby mitigating podocyte dysfunction in DKD. The transcription factor TCF21 binds directly to the Setdb2 promoter and enhances its expression in podocytes. Abstract Podocyte dysfunction represents both an early pathological hallmark and a key driver
Lanfang Li +14 more
wiley +1 more source
A non-canonical monovalent zinc finger stabilizes the integration of Cfp1 into the H3K4 methyltransferase complex COMPASS [PDF]
Yidai Yang +9 more
openalex +1 more source
Development of Dimethylsulfonium Probes for Broad Profiling of Methyllysine Reader Proteins
Development of oligoglycine‐based dimethylsulfonium probes for unbiased crosslinking to methyllysine readers. The general probe facilitates profiling of site‐specific methyllysine readers, evaluation of selectivity and activity of reader inhibitors, and global profiling of methyllysine readers.
Jinyu Yang +3 more
wiley +1 more source
A substrate promiscuous and regioselective O‐methyltransferase, SmOMT, is functionally and structurally characterized. A double mutant, SmOMTE152A/I306A, exhibited enhanced catalytic activity. By coupling this mutant with a mutant halide methyltransferase, AtHMTV140T, for SAM regeneration, a superior artificial fusion enzyme, AtHMTV140T‐L95‐SmOMTE152A ...
Xiran Xiong +11 more
wiley +1 more source
Abstract Background and Aims Intrahepatic cholangiocarcinoma (ICC) is a deadly but poorly understood disease, and its treatment options are very limited. The aim of this study was to identify the molecular drivers of ICC and search for therapeutic targets.
Yuto Shiode +16 more
wiley +1 more source
The m6A methyltransferase WTAP plays a key role in the development of diffuse large B-cell lymphoma via regulating the m6A modification of catenin beta 1 [PDF]
Shuangshuang Guo +7 more
openalex +1 more source
Generating Dynamic Structures Through Physics‐Based Sampling of Predicted Inter‐Residue Geometries
While static structure prediction has been revolutionized, modeling protein dynamics remains elusive. trRosettaX2‐Dynamics is presented to address this challenge. This framework leverages a Transformer‐based network to predict inter‐residue geometric constraints, guiding conformation generation via physics‐based iterative sampling. The resulting method
Chenxiao Xiang +3 more
wiley +1 more source

