Evidence map›Paper›PMID 34813065›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Using Molecular Simulation to Guide Protein Engineering for Biocatalysis in Organic Solvents.

Haiyang Cui, Markus Vedder, Ulrich Schwaneberg, Mehdi D Davari

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Haiyang CuiLehrstuhl für Biotechnologie, RWTH Aachen University, Aachen, Germany.
Markus VedderLehrstuhl für Biotechnologie, RWTH Aachen University, Aachen, Germany.
Ulrich SchwanebergLehrstuhl für Biotechnologie, RWTH Aachen University, Aachen, Germany.
Mehdi D DavariLehrstuhl für Biotechnologie, RWTH Aachen University, Aachen, Germany. m.davari@biotec.rwth-aachen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biocatalysis in organic solvents (OSs) is very appealing for the industry in producing bulk and/or fine chemicals, such as pharmaceuticals, biodiesel, and fragrances. The poor performance of enzymes in OSs (e.g., reduced activity, insufficient stability, and deactivation) negates OSs' excellent solvent properties. Molecular dynamics (MD) simulations provide a complementary method to study the relationship between enzymes dynamics and the stability in OSs. Here we describe computational procedure for MD simulation of enzymes in OSs with an example of Bacillus subtilis lipase A (BSLA) in dimethyl sulfoxide (DMSO) cosolvent with software GROMACS. We discuss main essential practical issues considered (such as choice of force field, parameterization, simulation setup, and trajectory analysis). The core part of this protocol (enzyme-OS system setup, analysis of structural-based and solvation-based observables) is transferable to other enzymes and any OS systems. Combining with experimental studies, the obtained molecular knowledge is most likely to guide researchers to access rational protein engineering approaches to tailor OS resistant enzymes and expand the scope of biocatalysis in OS media. Finally, we discuss potential solutions to overcome the remaining challenges of computational biocatalysis in OSs and briefly draw future directions for further improvement in this field.

Indexed as

Molecular Dynamics SimulationBiocatalysisPharmaceutical PreparationsProtein EngineeringSolventsPharmaceutical PreparationsSolventsBiocatalysisGROMACSMolecular dynamics simulationOrganic solventsProtein engineering

Identifiers

PMID34813065

What OpenQuestion holds

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Registered trials

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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.