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Improving Translational Accuracy02:07

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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...
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Translational Regulation01:29

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Translational regulation in prokaryotes ensures efficient protein synthesis by controlling ribosome access to mRNA. This regulation is mediated by secondary RNA structures, including translational riboswitches, RNA thermometers, and small RNAs (sRNAs), which respond to intracellular and environmental signals to modulate gene expression.Translational RiboswitchesRiboswitches in the leader region of mRNAs can regulate translation by altering the accessibility of the Shine-Dalgarno (SD) sequence,...
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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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Cotranslational Protein Translocation01:20

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Translocation of proteins across membranes is an ancient process that occurs even in bacteria and archaebacteria. In fact, the components of the translocation machinery are still conserved between prokaryotes and eukaryotes.
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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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Building Robustness into Translational Research.

Betül R Erdogan1, Martin C Michel2

  • 1Department of Pharmacology, School of Pharmacy, Ankara University, Ankara, Turkey.

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|October 11, 2019
PubMed
Summary
This summary is machine-generated.

Preclinical studies require careful design to ensure therapeutic candidates translate to human patients. Incorporating animal model heterogeneity and addressing potential biases are crucial for ethical and economic success in drug development.

Keywords:
AgeComorbidityHeterogeneityRobustnessSexTranslational research

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Area of Science:

  • Preclinical research
  • Translational science
  • Drug development

Background:

  • Nonclinical studies are foundational for advancing therapeutic candidates to clinical trials.
  • Ensuring translational robustness in these studies is vital for ethical and economic considerations.
  • Heterogeneity in patient populations necessitates reflection in preclinical study designs.

Purpose of the Study:

  • To highlight the importance of translational robustness in nonclinical studies.
  • To identify key factors influencing the predictive value of preclinical research for human outcomes.
  • To emphasize the need for careful consideration of biases in translational studies.

Main Methods:

  • Review of principles for designing robust preclinical studies.
  • Analysis of factors contributing to translational success or failure.
  • Discussion of sources of bias specific to translational research.

Main Results:

  • Findings confirmed across multiple species increase the likelihood of human relevance.
  • Incorporating heterogeneity (e.g., animal strains, sex, age, comorbidities) enhances model translatability but requires larger sample sizes.
  • Potential biases include model limitations, treatment timing, dosing, and pharmacokinetic differences.

Conclusions:

  • Translational robustness in nonclinical studies is paramount for successful drug development.
  • Preclinical study designs must account for biological variability and potential biases.
  • A balanced approach considering all factors is essential for each study and program.