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000903713 1001_ $$0P:(DE-Juel1)176217$$aEl Harrar, Till$$b0$$ufzj
000903713 245__ $$aCritical Assessment of Structure-based Approaches to Improve Protein Resistance in Aqueous Ionic Liquids by Enzyme-wide Saturation Mutagenesis
000903713 260__ $$aGotenburg$$bResearch Network of Computational and Structural Biotechnology (RNCSB)$$c2022
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000903713 520__ $$aIonic liquids (IL) and aqueous ionic liquids (aIL) are attractive (co-)solvents for green industrial processes involving biocatalysts, but often reduce enzyme activity. Experimental and computational methods are applied to predict favorable substitution sites and, most often, subsequent site-directed surface charge modifications are introduced to enhance enzyme resistance towards aIL. However, almost no studies evaluate the prediction precision with random mutagenesis or the application of simple data-driven filtering processes. Here, we systematically and rigorously evaluated the performance of 22 previously described structure-based approaches to increase enzyme resistance to aIL based on an experimental complete site-saturation mutagenesis library of BsLipA screened against four aIL. We show that, surprisingly, most of the approaches yield low gain in precision (GiP) values, particularly for predicting relevant positions: 14 approaches perform worse than random mutagenesis. Encouragingly, exploiting experimental information on the thermostability of BsLipA or structural weak spots of BsLipA predicted by rigidity theory yields GiP = 3.03 and 2.39 for relevant variants and GiP = 1.61 and 1.41 for relevant positions. Combining five simple-to-compute physicochemical and evolutionary properties substantially increases the precision of predicting relevant variants and positions, yielding GiP = 3.35 and 1.29. Finally, combining these properties with predictions of structural weak spots identified by rigidity theory additionally improves GiP for relevant positions up to 4-fold to ∼10 and sustains or increases GiP for relevant positions, resulting in a prediction precision of ∼90% compared to ∼9% in random mutagenesis. This combination should be applicable to other enzyme systems for guiding protein engineering approaches towards improved aIL resistance.
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000903713 7001_ $$0P:(DE-HGF)0$$aDavari, Mehdi D.$$b1
000903713 7001_ $$0P:(DE-Juel1)131457$$aJaeger, Karl-Erich$$b2
000903713 7001_ $$0P:(DE-HGF)0$$aSchwaneberg, Ulrich$$b3
000903713 7001_ $$0P:(DE-Juel1)172663$$aGohlke, Holger$$b4$$eCorresponding author
000903713 773__ $$0PERI:(DE-600)2694435-2$$a10.1016/j.csbj.2021.12.018$$gp. S2001037021005274$$p399-409$$tComputational and structural biotechnology journal$$v20$$x2001-0370$$y2022
000903713 8564_ $$uhttps://juser.fz-juelich.de/record/903713/files/Invoice_OAD0000171845.pdf
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000903713 8564_ $$uhttps://juser.fz-juelich.de/record/903713/files/P03v17_MS_TE_final.pdf$$yOpenAccess
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