Increasing protein stability by inferring substitution effects from high-throughput experiments

  1. Rasmus Krogh Norrild
  2. Kristoffer Enøe Johansson
  3. Charlotte O’Shea
  4. Jens Preben Morth
  5. Kresten Lindorff-Larsen
  6. Jakob Rahr Winther

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Abstract

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  1. Version published to 10.1016/j.crmeth.2022.100333
  2. ASAPbio crowd review

    Review coordinated via ASAPbio’s crowd preprint review

    This review reflects comments and contributions by Ruchika Bajaj, Michael Robicheaux, Akihito Inoue, Justin Ouedraogo and Kunal Shah. Review synthesized by Ruchika Bajaj.

    The paper reports the use of an optimized computational model, GMMA, by preparing a randomly mutated protein library and screening the mutant library using an in-vivo genetic sensor for folding for successful protein engineering efforts.

    Here are a few points of feedback on the paper.

    1. In the second paragraph of section “Resilience towards mutations reflects thermodynamic stability”, the manuscript refers to the design of degenerate primers, “These were designed to cover the C-terminal half of edF106, amino acid residues 48-97”. Further explanation for designing degenerate primers for these specific positions would be helpful to the reader, for example by adding references from the literature. In the same paragraph, when mentioning the size of the library (10,000 - 20,000), it would be good to explain the reason for the specified size of this library.
    2. The section “GMMA analysis discovers stability effects”, mentions that, “Reliable stability effects could be assigned to 374 out of the 838 unique substitutions in the library”. Further explanation may be provided in this regard, for example to describe why/what variables could lead to unreliable stability scores for tested substitutions.
    3. The study evaluated MM3 and MM6 combinations for the additivity of stability. It would be relevant to mention if other combinations like MM4 and MM5 were evaluated.
    4. Fig 2b: more points could be taken on the steep regions.
    5. For Supplementary Figures 4 and 5, please provide an explanation of curves or straight lines and explain the angle of fitted lines.
    6. In the section “stability measurements validate GMMA”, in the sentence, “Thus, mutations which could be stabilizing in the fusion might behave differently outside of the CPOP context.”, would it be possible to elaborate more on this statement to clarify how the behavior may differ?.
    7. Please indicate specific mutated amino acids in multiple mutants: MM3, MM6 and MM9, for comparison.
    8. Please label residues in Figure 6b.
    9. In the section, “Crystal structures show increased similarity to the 1FB0 design template”, the statement, “Only one or two would yield crystals indicative of a conformational change taking place in order to stabilize the crystal lattice.” Conformational change is questionable here, especially with low RMSD values. Would it be possible to elaborate on the statement or reframe it.
    10. “showed much better agreement with its original design template spinach thioredoxin (PDB: 1FB0).” It may be helpful to provide some further context about this in the Introduction and conclusions sections.
    11. In the section “structure and sequence-based methods do not predict most stabilizing variants”, the text mentions the discrepancies in rosetta and GMMM. It may be relevant to provide some further discussion on what may be behind those discrepancies.
    12. Although the mutated protein has been crystallized, a discussion on protein expression or oligomerization after the mutation and its relation to thermal stability would be helpful for the study.
    13. A major point which has not been mentioned in this study is scoring of these mutations according to their function, functional aspects are important for the purpose of protein engineering and thus this could be relevant. It will also be good to correlate the stability of these mutants with its function to comprehend the protein engineering effort.
    14. Minor point: In the section “Initial library transformation”, please change “scraped off” to picked off.
    15. Supplementary Table 4: Wilson B factor value is missing for eMM9. A possible explanation for the difference in the number of macromolecules in MM9 and eMM9 variants would be helpful. Is there a possibility of change in crystallographic oligomerization ? Any information regarding regions of protein where Ramachandran outliers are located would be helpful.
  3. Version published to 10.1101/2022.05.18.492418v1 on bioRxiv