AIMC Topic: NADP

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Metabolic reprogramming and machine learning-guided cofactor engineering to boost nicotinamide mononucleotide production in Escherichia coli.

Bioresource technology Mar 5, 2025
Nicotinamide mononucleotide (NMN) is a bioactive compound in NAD(P) metabolism, which exhibits diverse pharmaceutical interests. However, enhancing NMN biosynthesis faces the challange of competing with cell growth and disturbing intracellular redox ...
Escherichia coli Metabolic Reprogramming Machine Learning Quorum Sensing Metabolic Engineering NADP Oxidation-Reduction Fermentation Nicotinamide Mononucleotide
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Excited state kinetics of tryptophan and NAD(P)H in blood plasma of normal and abnormal liver conditions: A tool to understand the metabolic changes and classification.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 6, 2025
Early diagnosis at the metabolomic level is crucial for the treatment of liver cirrhosis and hepatocellular carcinoma (HCC). In this study, attempts were made to investigate the excited-state kinetics of intrinsic fluorophores, tryptophan and nicotin...
Cluster Analysis Liver Carcinoma, Hepatocellular Male Liver Cirrhosis Middle Aged Tryptophan ROC Curve NAD Spectrometry, Fluorescence Liver Neoplasms NADP Kinetics Female Adult Humans
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Measuring Metabolic Changes in Cancer Cells Using Two-Photon Fluorescence Lifetime Imaging Microscopy and Machine-Learning Analysis.

Journal of biophotonics Nov 25, 2024
Two-photon (2P) fluorescence lifetime imaging microscopy (FLIM) was used to track cellular metabolism with drug treatment of auto-fluorescent coenzymes NAD(P)H and FAD in living cancer cells. Simultaneous excitation at 800 nm of both coenzymes was co...
Flavin-Adenine Dinucleotide Microscopy, Fluorescence, Multiphoton NADP Oxidation-Reduction Doxorubicin Humans Cell Line, Tumor Image Processing, Computer-Assisted Machine Learning
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Deep learning for NAD/NADP cofactor prediction and engineering using transformer attention analysis in enzymes.

Metabolic engineering Nov 20, 2024
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...
NADP Deep Learning Protein Engineering NAD
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Rice Origin Tracing Technology Based on Fluorescence Spectroscopy and Stoichiometry.

Sensors (Basel, Switzerland) May 9, 2024
The origin of agricultural products is crucial to their quality and safety. This study explored the differences in chemical composition and structure of rice from different origins using fluorescence detection technology. These differences are mainly...
Algorithms NADP Support Vector Machine Seeds Starch Spectrometry, Fluorescence Riboflavin Oryza
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Discovery of Small-Molecule Activators for Glucose-6-Phosphate Dehydrogenase (G6PD) Using Machine Learning Approaches.

International journal of molecular sciences Feb 23, 2020
Glucose-6-Phosphate Dehydrogenase (G6PD) is a ubiquitous cytoplasmic enzyme converting glucose-6-phosphate into 6-phosphogluconate in the pentose phosphate pathway (PPP). The G6PD deficiency renders the inability to regenerate glutathione due to lack...
Glutathione X-Ray Diffraction NADP Drug Discovery Drug Evaluation, Preclinical Pentose Phosphate Pathway Oxidative Stress Protein Interaction Domains and Motifs Catalytic Domain Animals Oxidation-Reduction Humans Glucosephosphate Dehydrogenase Molecular Docking Simulation Glucosephosphate Dehydrogenase Deficiency Machine Learning
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Rossmann-toolbox: a deep learning-based protocol for the prediction and design of cofactor specificity in Rossmann fold proteins.

Briefings in bioinformatics Jan 17, 2022
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...
Flavin-Adenine Dinucleotide NAD NADP Deep Learning Proteins
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