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NAD

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Concentration-dependent dual effects of exogenous sucrose on nitrogen metabolism in Andrographis paniculata.

Scientific reports
The effects of exogenous sucrose (Suc) concentrations (0, 0.5, 1, 5, 10 mmol L) on carbon (C) and nitrogen (N) metabolisms were investigated in a medicinal plant Andrographis paniculata (Chuanxinlian). Suc application with the concentration of 0.5-5 ...

Flux prediction using artificial neural network (ANN) for the upper part of glycolysis.

PloS one
The selection of optimal enzyme concentration in multienzyme cascade reactions for the highest product yield in practice is very expensive and time-consuming process. The modelling of biological pathways is a difficult process because of the complexi...

Recognizing five molecular ligand-binding sites with similar chemical structure.

Journal of computational chemistry
Accurate identification of ligand-binding sites and discovering the protein-ligand interaction mechanism are important for understanding proteins' functions and designing new drugs. Meanwhile, accurate computational prediction and mechanism research ...

The NAD-mitophagy axis in healthy longevity and in artificial intelligence-based clinical applications.

Mechanisms of ageing and development
Nicotinamide adenine dinucleotide (NAD) is an important natural molecule involved in fundamental biological processes, including the TCA cycle, OXPHOS, β-oxidation, and is a co-factor for proteins promoting healthy longevity. NAD depletion is associa...

Label-free metabolic clustering through unsupervised pixel classification of multiparametric fluorescent images.

Analytica chimica acta
Autofluorescence microscopy is a promising label-free approach to characterize NADH and FAD metabolites in live cells, with potential applications in clinical practice. Although spectrally resolved lifetime imaging techniques can acquire multiparamet...

Identifying metastatic ability of prostate cancer cell lines using native fluorescence spectroscopy and machine learning methods.

Scientific reports
Metastasis is the leading cause of mortalities in cancer patients due to the spreading of cancer cells to various organs. Detecting cancer and identifying its metastatic potential at the early stage is important. This may be achieved based on the qua...

Rossmann-toolbox: a deep learning-based protocol for the prediction and design of cofactor specificity in Rossmann fold proteins.

Briefings in bioinformatics
The Rossmann fold enzymes are involved in essential biochemical pathways such as nucleotide and amino acid metabolism. Their functioning relies on interaction with cofactors, small nucleoside-based compounds specifically recognized by a conserved βαβ...

Employ machine learning to identify NAD+ metabolism-related diagnostic markers for ischemic stroke and develop a diagnostic model.

Experimental gerontology
Ischemic stroke (IS) is a severe condition regulated by complex molecular alterations. This study aimed to identify potential nicotinamide adenine dinucleotide (NAD+) metabolism-associated diagnostic markers of IS and explore their associations with ...

Deep learning for NAD/NADP cofactor prediction and engineering using transformer attention analysis in enzymes.

Metabolic engineering
Understanding and manipulating the cofactor preferences of NAD(P)-dependent oxidoreductases, the most widely distributed enzyme group in nature, is increasingly crucial in bioengineering. However, large-scale identification of the cofactor preference...

NAD_MCNN: Combining Protein Language Models and Multiwindow Convolutional Neural Networks for Deacetylase NAD+ Binding Site Prediction.

Chemical biology & drug design
Sirtuins, a class of NAD+ -dependent deacetylases, play a key role in aging, metabolism, and longevity. Their interaction with NAD+ at the catalytic site is crucial for function, but experimental methods to map NAD+ binding sites are time consuming. ...