The Carbohydrate-Active enZYme database (CAZy; www.cazy.org) has been providing the reference classification of carbohydrate-active enzymes (CAZymes) for >30 years. Based on literature survey, the sequence-based families of CAZymes are enriched with functional data by using the International Union of Biochemistry and Molecular Biology Enzyme Commission (EC) number system. However, this system was not developed to search or compare functional information. To better harness functional information, we have developed CAZac (CAZyme activity descriptor), a multicriterion system that describes CAZymes' mechanisms, glycosidic bond orientations, subsites and inter-residue connectivities. This new system, implemented for glycoside hydrolases, glycoside phosphorylases, transglycosidases, polysaccharide lyases and lytic polysaccharide monooxygenases allows complex searches in the CAZy database to uncover the evolution of substrate specificity and mechanisms of CAZymes across families.
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http://dx.doi.org/10.1093/nar/gkae1045 | DOI Listing |
Anal Chem
January 2025
Separation Science Group, Department of Organic and Macromolecular Chemistry, Ghent University, Krijgslaan 281 S4bis, B-9000 Ghent, Belgium.
Addressing the global challenge of ensuring access to safe drinking water, especially in developing countries, demands cost-effective, eco-friendly, and readily available technologies. The persistence, toxicity, and bioaccumulation potential of organic pollutants arising from various human activities pose substantial hurdles. While high-performance liquid chromatography coupled with high-resolution mass spectrometry (HPLC-HRMS) is a widely utilized technique for identifying pollutants in water, the multitude of structures for a single elemental composition complicates structural identification.
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January 2025
College of Chemistry, Chemical Engineering and Materials Science, Soochow University, Suzhou 215006, China.
Low-temperature direct ammonia fuel cell (DAFC) stands out as a more secure technology than the hydrogen fuel cell system, while there is still a lack of elegant bottom-up synthesis procedures for efficient ammonia oxidation reaction (AOR) electrocatalysts. The widely accepted d-band center, even with consideration of the d-band width, usually fails to describe variations in AOR reactivity in many practical conditions, and a more accurate activity descriptor is necessary for a less empirical synthesis path. Herein, the upper d-band edge, ε, derived from the d-band model, is identified as an effective descriptor for accurately establishing the descriptor-activity relationship.
View Article and Find Full Text PDFBMC Chem
January 2025
LAQV@REQUIMTE/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, Porto, 4169-007, Portugal.
Mood disorders affect the daily lives of millions of people worldwide. The search for more efficient therapies for mood disorders remains an active field of research. In silico approaches can accelerate the search for inhibitors against protein targets related to mood disorders.
View Article and Find Full Text PDFEnviron Int
December 2024
Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China.
Chemically induced neurotoxicity is a critical aspect of chemical safety assessment. Traditional and costly experimental methods call for the development of high-throughput virtual screening. However, the small datasets of neurotoxicity have limited the application of advanced deep learning techniques.
View Article and Find Full Text PDFSci Adv
January 2025
Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA.
The application of statistical modeling in organic chemistry is emerging as a standard practice for probing structure-activity relationships and as a predictive tool for many optimization objectives. This review is aimed as a tutorial for those entering the area of statistical modeling in chemistry. We provide case studies to highlight the considerations and approaches that can be used to successfully analyze datasets in low data regimes, a common situation encountered given the experimental demands of organic chemistry.
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