Literature DB >> 27410729

Using Evolution to Guide Protein Engineering: The Devil IS in the Details.

Liskin Swint-Kruse1.   

Abstract

For decades, protein engineers have endeavored to reengineer existing proteins for novel applications. Overall, protein folds and gross functions can be readily transferred from one protein to another by transplanting large blocks of sequence (i.e., domain recombination). However, predictably fine-tuning function (e.g., by adjusting ligand affinity, specificity, catalysis, and/or allosteric regulation) remains a challenge. One approach has been to use the sequences of protein families to identify amino acid positions that change during the evolution of functional variation. The rationale is that these nonconserved positions could be mutated to predictably fine-tune function. Evolutionary approaches to protein design have had some success, but the engineered proteins seldom replicate the functional performances of natural proteins. This Biophysical Perspective reviews several complexities that have been revealed by evolutionary and experimental studies of protein function. These include 1) challenges in defining computational and biological thresholds that define important amino acids; 2) the co-occurrence of many different patterns of amino acid changes in evolutionary data; 3) difficulties in mapping the patterns of amino acid changes to discrete functional parameters; 4) the nonconventional mutational outcomes that occur for a particular group of functionally important, nonconserved positions; 5) epistasis (nonadditivity) among multiple mutations; and 6) the fact that a large fraction of a protein's amino acids contribute to its overall function. To overcome these challenges, new goals are identified for future studies.
Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 27410729      PMCID: PMC4945580          DOI: 10.1016/j.bpj.2016.05.030

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  78 in total

1.  A closer view of the conformation of the Lac repressor bound to operator.

Authors:  C E Bell; M Lewis
Journal:  Nat Struct Biol       Date:  2000-03

2.  Thermodynamic prediction of protein neutrality.

Authors:  Jesse D Bloom; Jonathan J Silberg; Claus O Wilke; D Allan Drummond; Christoph Adami; Frances H Arnold
Journal:  Proc Natl Acad Sci U S A       Date:  2005-01-11       Impact factor: 11.205

3.  Extrinsic interactions dominate helical propensity in coupled binding and folding of the lactose repressor protein hinge helix.

Authors:  Hongli Zhan; Liskin Swint-Kruse; Kathleen Shive Matthews
Journal:  Biochemistry       Date:  2006-05-09       Impact factor: 3.162

4.  A combinatorial histidine scanning library approach to engineer highly pH-dependent protein switches.

Authors:  Megan L Murtaugh; Sean W Fanning; Tressa M Sharma; Alexandra M Terry; James R Horn
Journal:  Protein Sci       Date:  2011-08-03       Impact factor: 6.725

Review 5.  A survey on prediction of specificity-determining sites in proteins.

Authors:  Abhijit Chakraborty; Saikat Chakrabarti
Journal:  Brief Bioinform       Date:  2014-01-10       Impact factor: 11.622

6.  The spatial architecture of protein function and adaptation.

Authors:  Richard N McLaughlin; Frank J Poelwijk; Arjun Raman; Walraj S Gosal; Rama Ranganathan
Journal:  Nature       Date:  2012-10-07       Impact factor: 49.962

7.  Engineering an allosteric transcription factor to respond to new ligands.

Authors:  Noah D Taylor; Alexander S Garruss; Rocco Moretti; Sum Chan; Mark A Arbing; Duilio Cascio; Jameson K Rogers; Farren J Isaacs; Sriram Kosuri; David Baker; Stanley Fields; George M Church; Srivatsan Raman
Journal:  Nat Methods       Date:  2015-12-21       Impact factor: 28.547

Review 8.  Parallel dynamics and evolution: Protein conformational fluctuations and assembly reflect evolutionary changes in sequence and structure.

Authors:  Joseph A Marsh; Sarah A Teichmann
Journal:  Bioessays       Date:  2013-11-25       Impact factor: 4.345

9.  Evolution of oligomeric state through allosteric pathways that mimic ligand binding.

Authors:  Tina Perica; Yasushi Kondo; Sandhya P Tiwari; Stephen H McLaughlin; Katherine R Kemplen; Xiuwei Zhang; Annette Steward; Nathalie Reuter; Jane Clarke; Sarah A Teichmann
Journal:  Science       Date:  2014-12-19       Impact factor: 47.728

10.  ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures.

Authors:  Meytal Landau; Itay Mayrose; Yossi Rosenberg; Fabian Glaser; Eric Martz; Tal Pupko; Nir Ben-Tal
Journal:  Nucleic Acids Res       Date:  2005-07-01       Impact factor: 16.971

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  14 in total

1.  Homolog comparisons further reconcile in vitro and in vivo correlations of protein activities by revealing over-looked physiological factors.

Authors:  Sudheer Tungtur; Kristen M Schwingen; Joshua J Riepe; Chamitha J Weeramange; Liskin Swint-Kruse
Journal:  Protein Sci       Date:  2019-08-09       Impact factor: 6.725

2.  RheoScale: A tool to aggregate and quantify experimentally determined substitution outcomes for multiple variants at individual protein positions.

Authors:  Abby M Hodges; Aron W Fenton; Larissa L Dougherty; Andrew C Overholt; Liskin Swint-Kruse
Journal:  Hum Mutat       Date:  2018-08-28       Impact factor: 4.878

3.  Searching for a mechanistic description of pairwise epistasis in protein systems.

Authors:  Jonathan E Barnes; Craig R Miller; Frederick Marty Ytreberg
Journal:  Proteins       Date:  2022-03-11

4.  funtrp: identifying protein positions for variation driven functional tuning.

Authors:  Maximilian Miller; Daniel Vitale; Peter C Kahn; Burkhard Rost; Yana Bromberg
Journal:  Nucleic Acids Res       Date:  2019-12-02       Impact factor: 16.971

5.  Identification of biochemically neutral positions in liver pyruvate kinase.

Authors:  Tyler A Martin; Tiffany Wu; Qingling Tang; Larissa L Dougherty; Daniel J Parente; Liskin Swint-Kruse; Aron W Fenton
Journal:  Proteins       Date:  2020-06-27

6.  MHCEpitopeEnergy, a Flexible Rosetta-Based Biotherapeutic Deimmunization Platform.

Authors:  Brahm J Yachnin; Vikram Khipple Mulligan; Sagar D Khare; Chris Bailey-Kellogg
Journal:  J Chem Inf Model       Date:  2021-04-26       Impact factor: 6.162

7.  Computational predictors fail to identify amino acid substitution effects at rheostat positions.

Authors:  M Miller; Y Bromberg; L Swint-Kruse
Journal:  Sci Rep       Date:  2017-01-30       Impact factor: 4.379

8.  Allostery and Epistasis: Emergent Properties of Anisotropic Networks.

Authors:  Paul Campitelli; S Banu Ozkan
Journal:  Entropy (Basel)       Date:  2020-06-16       Impact factor: 2.524

9.  Engineering substrate promiscuity in halophilic alcohol dehydrogenase (HvADH2) by in silico design.

Authors:  Jennifer Cassidy; Larah Bruen; Elena Rosini; Gianluca Molla; Loredano Pollegioni; Francesca Paradisi
Journal:  PLoS One       Date:  2017-11-30       Impact factor: 3.240

10.  Rheostat positions: A new classification of protein positions relevant to pharmacogenomics.

Authors:  Aron W Fenton; Braelyn M Page; Arianna Spellman-Kruse; Bruno Hagenbuch; Liskin Swint-Kruse
Journal:  Med Chem Res       Date:  2020-06-07       Impact factor: 1.965

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