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Concerns with computational protein engineering programmes IPRO and OptMAVEn and metabolic pathway engineering

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Summary

Computational models in engineering research can be complex and difficult to understand. This opinion piece highlights challenges with protein and metabolic pathway models, finding they often fail to predict reliable engineering strategies.

Keywords:
computational pathway engineeringmodellingprotein engineering

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Protein Engineering
  • Metabolic Engineering

Background:

  • Engineering research increasingly relies on complex computational models.
  • The complexity of these models hinders reproducibility and understanding for reviewers and readers.
  • Existing models like IPRO, OptMAVEn, and optStoic present significant challenges.

Purpose of the Study:

  • To critically evaluate the utility and reliability of specific computational models in protein and metabolic engineering.
  • To share negative experiences encountered with the IPRO, OptMAVEn, and optStoic models.
  • To address the difficulties in discerning the value and understanding the code of complex engineering models.

Main Methods:

  • This is an opinion piece based on practical experience with computational models.
  • The author details negative outcomes using IPRO and OptMAVEn for protein engineering.
  • The author discusses issues encountered with the optStoic metabolic pathway model.

Main Results:

  • The computational protein engineering models IPRO and OptMAVEn did not yield reliable predictions for engineering proteins in the author's experience.
  • The optStoic metabolic pathway model also presented problems, failing to provide dependable insights.
  • Overall, these models were found to be unreliable for predicting successful engineering strategies.

Conclusions:

  • Complex computational models in engineering, including IPRO, OptMAVEn, and optStoic, can be unreliable.
  • There is a need for improved transparency and validation of computational models in scientific research.
  • The practical application of these specific models for protein and metabolic engineering is questionable based on reported experiences.