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Accelerated adaptive integration method.

ABSTRACT: Conformational changes that occur upon ligand binding may be too slow to observe on the time scales routinely accessible using molecular dynamics simulations. The adaptive integration method (AIM) leverages the notion that when a ligand is either fully coupled or decoupled, according to ?, barrier heights may change, making some conformational transitions more accessible at certain ? values. AIM adaptively changes the value of ? in a single simulation so that conformations sampled at one value of ? seed the conformational space sampled at another ? value. Adapting the value of ? throughout a simulation, however, does not resolve issues in sampling when barriers remain high regardless of the ? value. In this work, we introduce a new method, called Accelerated AIM (AcclAIM), in which the potential energy function is flattened at intermediate values of ?, promoting the exploration of conformational space as the ligand is decoupled from its receptor. We show, with both a simple model system (Bromocyclohexane) and the more complex biomolecule Thrombin, that AcclAIM is a promising approach to overcome high barriers in the calculation of free energies, without the need for any statistical reweighting or additional processors.

SUBMITTER: Kaus JW

PROVIDER: S-EPMC4025579 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Accelerated adaptive integration method.

Kaus Joseph W JW Arrar Mehrnoosh M McCammon J Andrew JA

The journal of physical chemistry. B 20140506 19

Conformational changes that occur upon ligand binding may be too slow to observe on the time scales routinely accessible using molecular dynamics simulations. The adaptive integration method (AIM) leverages the notion that when a ligand is either fully coupled or decoupled, according to λ, barrier heights may change, making some conformational transitions more accessible at certain λ values. AIM adaptively changes the value of λ in a single simulation so that conformations sampled at one value o ...[more]

PMID: 24780083

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Project description:BackgroundThe demand for biobased polymers is increasing steadily worldwide. Microbial hosts for production of their monomeric precursors such as glutarate are developed. To meet the market demand, production hosts have to be improved constantly with respect to product titers and yields, but also shortening bioprocess duration is important.ResultsIn this study, adaptive laboratory evolution was used to improve a C. glutamicum strain engineered for production of the C5-dicarboxylic acid glutarate by flux enforcement. Deletion of the L-glutamic acid dehydrogenase gene gdh coupled growth to glutarate production since two transaminases in the glutarate pathway are crucial for nitrogen assimilation. The hypothesis that strains selected for faster glutarate-coupled growth by adaptive laboratory evolution show improved glutarate production was tested. A serial dilution growth experiment allowed isolating faster growing mutants with growth rates increasing from 0.10 h-1 by the parental strain to 0.17 h-1 by the fastest mutant. Indeed, the fastest growing mutant produced glutarate with a twofold higher volumetric productivity of 0.18 g L-1 h-1 than the parental strain. Genome sequencing of the evolved strain revealed candidate mutations for improved production. Reverse genetic engineering revealed that an amino acid exchange in the large subunit of L-glutamic acid-2-oxoglutarate aminotransferase was causal for accelerated glutarate production and its beneficial effect was dependent on flux enforcement due to deletion of gdh. Performance of the evolved mutant was stable at the 2 L bioreactor-scale operated in batch and fed-batch mode in a mineral salts medium and reached a titer of 22.7 g L-1, a yield of 0.23 g g-1 and a volumetric productivity of 0.35 g L-1 h-1. Reactive extraction of glutarate directly from the fermentation broth was optimized leading to yields of 58% and 99% in the reactive extraction and reactive re-extraction step, respectively. The fermentation medium was adapted according to the downstream processing results.ConclusionFlux enforcement to couple growth to operation of a product biosynthesis pathway provides a basis to select strains growing and producing faster by adaptive laboratory evolution. After identifying candidate mutations by genome sequencing causal mutations can be identified by reverse genetics. As exemplified here for glutarate production by C. glutamicum, this approach allowed deducing rational metabolic engineering strategies.

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Accelerated adaptive integration method.

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Accelerated adaptive integration method.

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