ArticlePLoS computational biology2020
A stochastic model for simulating ribosome kinetics in vivo.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 24 citations in OpenAlex.
- An empirical model of aminoacylation kinetics for E. coli class I and II aminoacyl tRNA synthetases.PLoS computational biology · 2025Article
- On the response of elongating ribosomes to forces opposing translocation.Biophysical journal · 2024Article
- Design of a self-regulating mRNA gene circuit.Scientific reports · 2024Article
- Decomposing bulk signals to reveal hidden information in processive enzyme reactions: A case study in mRNA translation.PLoS computational biology · 2024Article
- spotter: a single-nucleotide resolution stochastic simulation model of supercoiling-mediated transcription and translation in prokaryotes.Nucleic acids research · 2023Article
- Modelling ribosome kinetics and translational control on dynamic mRNA.PLoS computational biology · 2023Article
- Global and gene-specific translational regulation in Escherichia coli across different conditions.PLoS computational biology · 2022Article
- Substrate recognition and cryo-EM structure of the ribosome-bound TAC toxin of Mycobacterium tuberculosis.Nature communications · 2022Article
- Article
- Comparing antiviral strategies against COVID-19 via multiscale within-host modelling.Royal Society open science · 2021Article
- Modeling Cell-Free Protein Synthesis Systems-Approaches and Applications.Frontiers in bioengineering and biotechnology · 2020Review
- Translational Control by Ribosome Pausing in Bacteria: How a Non-uniform Pace of Translation Affects Protein Production and Folding.Frontiers in microbiology · 2020Review
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Computational modelling of in vivo protein synthesis is highly complicated, as it requires the simulation of ribosomal movement over the entire transcriptome, as well as consideration of the concentration effects from 40+ different types of tRNAs and numerous other protein factors. Here I report on the development of a stochastic model for protein translation that is capable of simulating the dynamical process of in vivo protein synthesis in a prokaryotic cell containing several thousand unique mRNA sequences, with explicit nucleotide information for each, and report on a number of biological predictions which are beyond the scope of existing models. In particular, I show that, when the complex network of concentration dependent interactions between elongation factors, tRNAs, ribosomes, and other factors required for protein synthesis are included in full detail, several biological phenomena, such as the increasing peptide elongation rate with bacterial growth rate, are predicted as emergent properties of the model. The stochastic model presented here demonstrates the importance of considering the translational process at this level of detail, and provides a platform to interrogate various aspects of translation that are difficult to study in more coarse-grained models.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.