Literature DB >> 32505941

Practically useful protein-design methods combining phylogenetic and atomistic calculations.

Jonathan Weinstein1, Olga Khersonsky2, Sarel J Fleishman3.   

Abstract

Our ability to design new or improved biomolecular activities depends on understanding the sequence-function relationships in proteins. The large size and fold complexity of most proteins, however, obscure these relationships, and protein-optimization methods continue to rely on laborious experimental iterations. Recently, a deeper understanding of the roles of stability-threshold effects and biomolecular epistasis in proteins has led to the development of hybrid methods that combine phylogenetic analysis with atomistic design calculations. These methods enable reliable and even single-step optimization of protein stability, expressibility, and activity in proteins that were considered outside the scope of computational design. Furthermore, ancestral-sequence reconstruction produces insights on missing links in the evolution of enzymes and binders that may be used in protein design. Through the combination of phylogenetic and atomistic calculations, the long-standing goal of general computational methods that can be universally applied to study and optimize proteins finally seems within reach.
Copyright © 2020 Elsevier Ltd. All rights reserved.

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Year:  2020        PMID: 32505941      PMCID: PMC7289631          DOI: 10.1016/j.sbi.2020.04.003

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  57 in total

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Review 3.  Deep sequencing methods for protein engineering and design.

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Journal:  Curr Opin Struct Biol       Date:  2016-11-22       Impact factor: 6.809

4.  A relationship between protein stability and protein function.

Authors:  B K Shoichet; W A Baase; R Kuroki; B W Matthews
Journal:  Proc Natl Acad Sci U S A       Date:  1995-01-17       Impact factor: 11.205

5.  Deep mutational scanning: a new style of protein science.

Authors:  Douglas M Fowler; Stanley Fields
Journal:  Nat Methods       Date:  2014-08       Impact factor: 28.547

6.  A "fuzzy"-logic language for encoding multiple physical traits in biomolecules.

Authors:  Shira Warszawski; Ravit Netzer; Dan S Tawfik; Sarel J Fleishman
Journal:  J Mol Biol       Date:  2014-10-13       Impact factor: 5.469

7.  Complete Switch of Reaction Specificity of an Aldolase by Directed Evolution In Vitro: Synthesis of Generic Aliphatic Aldol Products.

Authors:  Sebastian Junker; Raquel Roldan; Henk-Jan Joosten; Pere Clapés; Wolf-Dieter Fessner
Journal:  Angew Chem Int Ed Engl       Date:  2018-07-04       Impact factor: 15.336

8.  Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces.

Authors:  Shira Warszawski; Aliza Borenstein Katz; Rosalie Lipsh; Lev Khmelnitsky; Gili Ben Nissan; Gabriel Javitt; Orly Dym; Tamar Unger; Orli Knop; Shira Albeck; Ron Diskin; Deborah Fass; Michal Sharon; Sarel J Fleishman
Journal:  PLoS Comput Biol       Date:  2019-08-23       Impact factor: 4.475

9.  HotSpot Wizard: a web server for identification of hot spots in protein engineering.

Authors:  Antonin Pavelka; Eva Chovancova; Jiri Damborsky
Journal:  Nucleic Acids Res       Date:  2009-05-21       Impact factor: 16.971

10.  Directed -in vitro- evolution of Precambrian and extant Rubiscos.

Authors:  Bernardo J Gomez-Fernandez; Eva Garcia-Ruiz; Javier Martin-Diaz; Patricia Gomez de Santos; Paloma Santos-Moriano; Francisco J Plou; Antonio Ballesteros; Monica Garcia; Marisa Rodriguez; Valeria A Risso; Jose M Sanchez-Ruiz; Spencer M Whitney; Miguel Alcalde
Journal:  Sci Rep       Date:  2018-04-03       Impact factor: 4.379

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  7 in total

1.  LoopGrafter: a web tool for transplanting dynamical loops for protein engineering.

Authors:  Joan Planas-Iglesias; Filip Opaleny; Pavol Ulbrich; Jan Stourac; Zainab Sanusi; Gaspar P Pinto; Andrea Schenkmayerova; Jan Byska; Jiri Damborsky; Barbora Kozlikova; David Bednar
Journal:  Nucleic Acids Res       Date:  2022-04-19       Impact factor: 19.160

Review 2.  Data-driven computational protein design.

Authors:  Vincent Frappier; Amy E Keating
Journal:  Curr Opin Struct Biol       Date:  2021-04-25       Impact factor: 7.786

3.  Computationally designed pyocyanin demethylase acts synergistically with tobramycin to kill recalcitrant Pseudomonas aeruginosa biofilms.

Authors:  Chelsey M VanDrisse; Rosalie Lipsh-Sokolik; Olga Khersonsky; Sarel J Fleishman; Dianne K Newman
Journal:  Proc Natl Acad Sci U S A       Date:  2021-03-23       Impact factor: 12.779

4.  Engineered Enzymes Enable Selective N-Alkylation of Pyrazoles With Simple Haloalkanes.

Authors:  Ludwig L Bengel; Benjamin Aberle; Alexander-N Egler-Kemmerer; Samuel Kienzle; Bernhard Hauer; Stephan C Hammer
Journal:  Angew Chem Int Ed Engl       Date:  2021-01-21       Impact factor: 15.336

5.  Stable and Functionally Diverse Versatile Peroxidases Designed Directly from Sequences.

Authors:  Shiran Barber-Zucker; Vladimir Mindel; Eva Garcia-Ruiz; Jonathan J Weinstein; Miguel Alcalde; Sarel J Fleishman
Journal:  J Am Chem Soc       Date:  2022-02-18       Impact factor: 15.419

6.  Assessing and enhancing foldability in designed proteins.

Authors:  Dina Listov; Rosalie Lipsh-Sokolik; Stéphane Rosset; Che Yang; Bruno E Correia; Sarel Jacob Fleishman
Journal:  Protein Sci       Date:  2022-09       Impact factor: 6.993

7.  The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes.

Authors:  Rosalie Lipsh-Sokolik; Dina Listov; Sarel J Fleishman
Journal:  Protein Sci       Date:  2020-10-28       Impact factor: 6.725

  7 in total

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