2023
DOI: 10.1101/2023.02.13.528271
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Optimal evaluation of energy yield and driving force in microbial metabolic pathway variants

Abstract: This work presents a methodology to evaluate the bioenergetic feasibility of alternative metabolic pathways for a given microbial conversion, optimising their energy yield and driving forces as a function of the concentration of metabolic intermediates. The tool, based on thermodynamic principles and multi-objective optimisation, accounts for pathway variants in terms of different electron carriers, as well as energy conservation (proton translocating) reactions within the pathway. The method also accommodates… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
1
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 62 publications
0
1
0
Order By: Relevance
“…A recently developed, highly efficient, computational methodology by 44 allows for the analysis of a large number of pathway configuration variants and combines the maximisation of chemiosmotic energy yield, earlier explored in 45 , with the maximization of the minimum driving force (MDF). Through this methodology the exploration of the thermodynamic landscape quantifying the trade-offs between energy yield and rate for large numbers of metabolic pathway configurations is now within computational reach.…”
mentioning
confidence: 99%
“…A recently developed, highly efficient, computational methodology by 44 allows for the analysis of a large number of pathway configuration variants and combines the maximisation of chemiosmotic energy yield, earlier explored in 45 , with the maximization of the minimum driving force (MDF). Through this methodology the exploration of the thermodynamic landscape quantifying the trade-offs between energy yield and rate for large numbers of metabolic pathway configurations is now within computational reach.…”
mentioning
confidence: 99%