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Other Glycolytic Pathways01:24

Other Glycolytic Pathways

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The pentose phosphate pathway (PPP) operates in parallel with glycolysis, facilitating the metabolism of both pentoses and glucose. This pathway consists of two distinct phases: the oxidative and non-oxidative phases. While it does not directly generate ATP, the intermediates formed during the process can integrate into glycolysis, contributing to cellular energy metabolism when required.Oxidative Phase: NADPH ProductionThe oxidative phase of the pentose phosphate pathway is primarily...
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Metabolism encompasses all biochemical reactions in a living organism, facilitating both the breakdown and synthesis of biomolecules. These metabolic processes are categorized into catabolic and anabolic pathways, which operate in a coordinated manner to ensure energy balance and cellular function.Catabolic Pathways and Energy ReleaseCatabolic pathways involve the breakdown of complex macromolecules such as carbohydrates, lipids, and proteins into smaller structures like monosaccharides, fatty...
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Amino acid biosynthesis is essential for cell growth, protein synthesis, and metabolic regulation. Cells generate essential and non-essential amino acids from metabolic intermediates to sustain vital biological functions. These intermediates originate from key metabolic pathways: glycolysis, the tricarboxylic acid (TCA) cycle, and the pentose phosphate pathway. Important precursors include α-ketoglutarate, pyruvate, oxaloacetate, phosphoenolpyruvate, and erythrose-4-phosphate, which...
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Cellular respiration is a fundamental metabolic process that enables organisms to generate energy from organic molecules. One of its central pathways is the tricarboxylic acid (TCA) cycle, also known as the Krebs cycle, which plays a crucial role in energy production and biosynthetic processes.Conversion of Pyruvate to Acetyl-CoAThe pyruvate generated from glycolysis undergoes oxidative decarboxylation by the pyruvate dehydrogenase complex, producing acetyl-CoA, one molecule of NADH, and one...
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Metabolic pathway engineering: Perspectives and applications.

Abhijit Dasgupta1, Nirmalya Chowdhury2, Rajat K De3

  • 1Department of Data Science, School of Interdisciplinary Studies, University of Kalyani, Kalyani, Nadia 741235, West Bengal, India.

Computer Methods and Programs in Biomedicine
|March 22, 2020
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Summary
This summary is machine-generated.

Metabolic engineering enhances microbial and plant production of valuable compounds. Advanced methods like inverse metabolic engineering, metabolic control analysis, and AI optimize these processes for drug discovery and industrial applications.

Keywords:
Artificial intelligence,CRISPR-Cas9Drug discoveryGenomicsInverse metabolic engineeringMCASecondary metabolitesTALENsZFNs

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Area of Science:

  • Biotechnology
  • Synthetic Biology

Background:

  • Metabolic engineering utilizes microbes and plants as biocatalysts for producing secondary metabolites.
  • These metabolites are vital resources for industrial chemicals, pharmaceuticals, and fuels.
  • Metabolic engineering in microorganisms and plants aids drug discovery.

Purpose of the Study:

  • To review the perspectives and applications of metabolic engineering in microorganisms and plants.
  • To elaborate on the relationship between inverse metabolic engineering, metabolic control analysis (MCA), and modern metabolic engineering.
  • To discuss strategies for efficient and optimal metabolic engineering, including AI applications.

Main Methods:

  • Genome-scale mathematical models integrating metabolic, signal transduction, gene regulatory, and protein-protein interaction networks.
  • Experimental validation of models.
  • Incorporation of omics data, inverse metabolic engineering, metabolic control analysis (MCA), and artificial intelligence (AI).

Main Results:

  • Genome-scale models provide essential knowledge of cell physiology and metabolism for metabolic engineering.
  • Omics data integration is crucial for drug discovery applications.
  • Inverse metabolic engineering and MCA are key to developing advanced metabolic engineering models.

Conclusions:

  • Metabolic engineering offers significant potential for drug discovery and the production of valuable compounds.
  • Inverse metabolic engineering and MCA are integral to modern metabolic engineering strategies.
  • AI and genomics data integration, particularly for silent metabolic clusters, enhance metabolic engineering efficiency and optimization.