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@ARTICLE{ElHarrar:903713,
      author       = {El Harrar, Till and Davari, Mehdi D. and Jaeger, Karl-Erich
                      and Schwaneberg, Ulrich and Gohlke, Holger},
      title        = {{C}ritical {A}ssessment of {S}tructure-based {A}pproaches
                      to {I}mprove {P}rotein {R}esistance in {A}queous {I}onic
                      {L}iquids by {E}nzyme-wide {S}aturation {M}utagenesis},
      journal      = {Computational and structural biotechnology journal},
      volume       = {20},
      issn         = {2001-0370},
      address      = {Gotenburg},
      publisher    = {Research Network of Computational and Structural
                      Biotechnology (RNCSB)},
      reportid     = {FZJ-2021-05353},
      pages        = {399-409},
      year         = {2022},
      abstract     = {Ionic liquids (IL) and aqueous ionic liquids (aIL) are
                      attractive (co-)solvents for green industrial processes
                      involving biocatalysts, but often reduce enzyme activity.
                      Experimental and computational methods are applied to
                      predict favorable substitution sites and, most often,
                      subsequent site-directed surface charge modifications are
                      introduced to enhance enzyme resistance towards aIL.
                      However, almost no studies evaluate the prediction precision
                      with random mutagenesis or the application of simple
                      data-driven filtering processes. Here, we systematically and
                      rigorously evaluated the performance of 22 previously
                      described structure-based approaches to increase enzyme
                      resistance to aIL based on an experimental complete
                      site-saturation mutagenesis library of BsLipA screened
                      against four aIL. We show that, surprisingly, most of the
                      approaches yield low gain in precision (GiP) values,
                      particularly for predicting relevant positions: 14
                      approaches perform worse than random mutagenesis.
                      Encouragingly, exploiting experimental information on the
                      thermostability of BsLipA or structural weak spots of BsLipA
                      predicted by rigidity theory yields GiP = 3.03 and 2.39 for
                      relevant variants and GiP = 1.61 and 1.41 for relevant
                      positions. Combining five simple-to-compute physicochemical
                      and evolutionary properties substantially increases the
                      precision of predicting relevant variants and positions,
                      yielding GiP = 3.35 and 1.29. Finally, combining these
                      properties with predictions of structural weak spots
                      identified by rigidity theory additionally improves GiP for
                      relevant positions up to 4-fold to ∼10 and sustains or
                      increases GiP for relevant positions, resulting in a
                      prediction precision of $∼90\%$ compared to $∼9\%$ in
                      random mutagenesis. This combination should be applicable to
                      other enzyme systems for guiding protein engineering
                      approaches towards improved aIL resistance.},
      cin          = {JSC / NIC / IBI-7 / IBG-4},
      ddc          = {570},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)NIC-20090406 /
                      I:(DE-Juel1)IBI-7-20200312 / I:(DE-Juel1)IBG-4-20200403},
      pnm          = {2171 - Biological and environmental resources for
                      sustainable use (POF4-217) / 2172 - Utilization of renewable
                      carbon and energy sources and engineering of ecosystem
                      functions (POF4-217) / 5111 - Domain-Specific Simulation
                      $\&$ Data Life Cycle Labs (SDLs) and Research Groups
                      (POF4-511) / Forschergruppe Gohlke $(hkf7_20200501)$ / 5241
                      - Molecular Information Processing in Cellular Systems
                      (POF4-524)},
      pid          = {G:(DE-HGF)POF4-2171 / G:(DE-HGF)POF4-2172 /
                      G:(DE-HGF)POF4-5111 / $G:(DE-Juel1)hkf7_20200501$ /
                      G:(DE-HGF)POF4-5241},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {35070165},
      UT           = {WOS:000819903300011},
      doi          = {10.1016/j.csbj.2021.12.018},
      url          = {https://juser.fz-juelich.de/record/903713},
}