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Related Concept Videos

Translation01:31

Translation

Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Translation01:31

Translation

Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Translation01:31

Translation

Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Proteins are called the...

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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
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Artificial Intelligence Transforming Post-Translational Modification Research.

Doo Nam Kim1, Tianzhixi Yin2, Tong Zhang1

  • 1Biological Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Blvd, Richland, WA 99352, USA.

Bioengineering (Basel, Switzerland)
|January 24, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) aids in understanding post-translational modifications (PTMs), which are crucial protein changes. This review explores AI applications for PTM site prediction and function analysis, introducing a data pipeline for AI training.

Keywords:
Post-Translational Modificationartificial intelligencedeep learningmachine learning

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Area of Science:

  • Biochemistry and Molecular Biology
  • Computational Biology and Bioinformatics

Background:

  • Post-translational modifications (PTMs) are essential covalent alterations to proteins after synthesis.
  • PTMs significantly influence protein function, cellular processes, and molecular structures.
  • Understanding PTMs is vital for evolutionary studies and comprehending biological complexity.

Purpose of the Study:

  • To explore the application of artificial intelligence (AI) in post-translational modification (PTM) research.
  • To discuss the advantages and rationales for employing AI in PTM functional analysis.
  • To compare various deep learning architectures for predicting PTM sites and regulatory functions.

Main Methods:

  • Review and comparison of deep learning architectures and programs for PTM site prediction.
  • Discussion of recent applications of language models in PTM research.
  • Description of a high-throughput PTM data generation pipeline for AI training and prediction.

Main Results:

  • AI, particularly deep learning and language models, shows significant potential in predicting PTM sites.
  • AI tools can elucidate the regulatory functions of various post-translational modifications.
  • A novel data pipeline facilitates AI model development for PTM analysis.

Conclusions:

  • AI offers powerful tools for advancing the study of post-translational modifications.
  • Future AI models can be improved to further contribute to PTM bioengineering.
  • This work highlights AI's role in deciphering the complex landscape of protein modifications.