Zinc metalloproteins are involved in many biological processes and play crucial biochemical roles across all domains of life. Local structure around the zinc ion, especially the coordination geometry (CG), is dictated by the protein sequence and is often directly related to the function of the protein. Current methodologies in characterizing zinc metalloproteins' CG consider only previously reported CG models based mainly on nonbiological chemical context. Exceptions to these canonical CG models are either misclassified or discarded as "outliers." Thus, we developed a less-biased method that directly handles potential exceptions without pre-assuming any CG model. Our study shows that numerous exceptions could actually be further classified and that new CG models are needed to characterize them. Also, these new CG models are cross-validated by strong correlation between independent structural and functional annotation distance metrics, which is partially lost if these new CGs models are ignored. Furthermore, these new CG models exhibit functional propensities distinct from the canonical CG models.
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http://dx.doi.org/10.1002/prot.24834 | DOI Listing |
Plant Dis
January 2025
University of California Davis, Cooperative Extension, Napa, California, United States;
The timely detection of viral pathogens in vineyards is a critical aspect of management. Diagnostic methods can be labor-intensive and may require specialized training or facilities. The emergence of artificial intelligence (AI) has the potential to provide innovative solutions for disease detection but requires a significant volume of high-quality data as input.
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View Article and Find Full Text PDFHum Brain Mapp
February 2025
U1172 - LilNCog (Lille Neuroscience & Cognition), Univ. Lille, Inserm, CHU Lille, Lille, France.
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