The severe acute respiratory syndrome coronavirus (SARS-CoV/CoV-2) genome encodes 16 non-structural proteins (nsps), which coordinate cell remodeling, virus replication and participate in viral evasion. Notably, nsp3 contains a protein module termed Macro domain, which carries IFN antagonist activity that interferes with host innate immunity response. This domain is able to bind and hydrolyze ADP-ribose derivatives. This activity is correlated to viral escape and thus makes Macro domains a valuable therapeutic target. In the present paper, we report a SARS-CoV Macro domain structure in complex with a MOPS molecule. Based on our structural data, molecular docking was performed on a set of MOPS analogs in the ADP-ribose binding pocket. We present an ELISA-based assay to select hits based on the inhibition of recombinant SARS-CoV/CoV-2 Macro domain-ADP-ribose complex formation. Among the tested analogs, MOPSO and CAPSO are the more efficient in inhibiting ADP-ribose-binding. Structural analysis of these molecules in the ADP-ribose pocket reveals potential interactions with amino acid residues involved in the coordination of ADP-ribose. Overall, these findings suggest that MOPSO and CAPSO bear potential to be used as a scaffold for the design of Macro domain-specific inhibitors.
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http://dx.doi.org/10.1111/febs.70039 | DOI Listing |
FEBS J
March 2025
Aix Marseille Université, CNRS, AFMB UMR 7257, Marseille, France.
The severe acute respiratory syndrome coronavirus (SARS-CoV/CoV-2) genome encodes 16 non-structural proteins (nsps), which coordinate cell remodeling, virus replication and participate in viral evasion. Notably, nsp3 contains a protein module termed Macro domain, which carries IFN antagonist activity that interferes with host innate immunity response. This domain is able to bind and hydrolyze ADP-ribose derivatives.
View Article and Find Full Text PDFPLoS One
March 2025
College of Civil Engineering and Architecture, Xinjiang University, Urumqi, China.
Many studies have investigated tunnel face failure using the discrete element method (DEM). However, DEM simulations that incorporate water-soil interactions in tunnel face failure are still limited. In this study, the coupled CFD-DEM method is employed to simulate the progressive failure of the shield tunnel face in both saturated and dry sand.
View Article and Find Full Text PDFPeerJ Comput Sci
February 2025
College of Law and Sociology, Qinghai Normal University, Xining, Qinghai, China.
The burgeoning field of natural language processing (NLP) has witnessed exponential growth, captivating researchers due to its diverse practical applications across industries. However, the intricate nature of legal texts poses unique challenges for conventional text extraction methods. To surmount these challenges, this article introduces a pioneering legal text extraction model rooted in fuzzy language processing and metaphor recognition, tailored for the domain of online environment governance.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
March 2025
Millennium Institute Foundational Research on Data, Santiago, Chile.
Background: Clinical decision-making in healthcare often relies on unstructured text data, which can be challenging to analyze using traditional methods. Natural Language Processing (NLP) has emerged as a promising solution, but its application in clinical settings is hindered by restricted data availability and the need for domain-specific knowledge.
Methods: We conducted an experimental analysis to evaluate the performance of various NLP modeling paradigms on multiple clinical NLP tasks in Spanish.
J Chromatogr A
February 2025
School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning 110016, China. Electronic address:
This study presents an innovative approach for the quality evaluation of traditional Chinese medicine (TCM) by integrating three-dimensional (3D) data processing with machine learning, aimed at enhancing the efficiency and accuracy of HPLC-DAD data analysis. Through 3D data integration, multi-dimensional signals from the time and wavelength domains are transformed into two-dimensional data, simplifying the analytical process while ensuring precise quantification of component contents. Building on this foundation, dynamic time warping (DTW) and correlation optimized warping (COW) algorithms were applied to effectively resolve retention time drift across different sample batches, achieving both global and local alignment of chromatographic peak shapes.
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