Literature DB >> 33249652

Perturbing the energy landscape for improved packing during computational protein design.

Jack B Maguire1, Hugh K Haddox2,3, Devin Strickland4, Samer F Halabiya4, Brian Coventry3,5, Jermel R Griffin6, Surya V S R K Pulavarti6, Matthew Cummins7, David F Thieker8,9, Eric Klavins4, Thomas Szyperski6, Frank DiMaio2,3, David Baker2,3,10, Brian Kuhlman8,9.   

Abstract

The FastDesign protocol in the molecular modeling program Rosetta iterates between sequence optimization and structure refinement to stabilize de novo designed protein structures and complexes. FastDesign has been used previously to design novel protein folds and assemblies with important applications in research and medicine. To promote sampling of alternative conformations and sequences, FastDesign includes stages where the energy landscape is smoothened by reducing repulsive forces. Here, we discover that this process disfavors larger amino acids in the protein core because the protein compresses in the early stages of refinement. By testing alternative ramping strategies for the repulsive weight, we arrive at a scheme that produces lower energy designs with more native-like sequence composition in the protein core. We further validate the protocol by designing and experimentally characterizing over 4000 proteins and show that the new protocol produces higher stability proteins.
© 2020 Wiley Periodicals LLC.

Entities:  

Keywords:  De novo protein design; Rosetta molecular Modeling program; computational protein design; energy landscape; energy optimization; massively parallel protein stability measurements

Mesh:

Substances:

Year:  2020        PMID: 33249652      PMCID: PMC8299543          DOI: 10.1002/prot.26030

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  29 in total

1.  Native protein sequences are close to optimal for their structures.

Authors:  B Kuhlman; D Baker
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-12       Impact factor: 11.205

2.  Automated selection of stabilizing mutations in designed and natural proteins.

Authors:  Benjamin Borgo; James J Havranek
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-17       Impact factor: 11.205

3.  De novo design of potent and selective mimics of IL-2 and IL-15.

Authors:  Daniel-Adriano Silva; Shawn Yu; Umut Y Ulge; Jamie B Spangler; Kevin M Jude; Carlos Labão-Almeida; Lestat R Ali; Alfredo Quijano-Rubio; Mikel Ruterbusch; Isabel Leung; Tamara Biary; Stephanie J Crowley; Enrique Marcos; Carl D Walkey; Brian D Weitzner; Fátima Pardo-Avila; Javier Castellanos; Lauren Carter; Lance Stewart; Stanley R Riddell; Marion Pepper; Gonçalo J L Bernardes; Michael Dougan; K Christopher Garcia; David Baker
Journal:  Nature       Date:  2019-01-09       Impact factor: 49.962

4.  Protocols for Requirement-Driven Protein Design in the Rosetta Modeling Program.

Authors:  Sharon L Guffy; Frank D Teets; Minnie I Langlois; Brian Kuhlman
Journal:  J Chem Inf Model       Date:  2018-04-23       Impact factor: 4.956

5.  PDB-wide collection of binding data: current status of the PDBbind database.

Authors:  Zhihai Liu; Yan Li; Li Han; Jie Li; Jie Liu; Zhixiong Zhao; Wei Nie; Yuchen Liu; Renxiao Wang
Journal:  Bioinformatics       Date:  2014-10-09       Impact factor: 6.937

Review 6.  The coming of age of de novo protein design.

Authors:  Po-Ssu Huang; Scott E Boyken; David Baker
Journal:  Nature       Date:  2016-09-15       Impact factor: 49.962

Review 7.  Advances in protein structure prediction and design.

Authors:  Brian Kuhlman; Philip Bradley
Journal:  Nat Rev Mol Cell Biol       Date:  2019-08-15       Impact factor: 94.444

8.  RosettaRemodel: a generalized framework for flexible backbone protein design.

Authors:  Po-Ssu Huang; Yih-En Andrew Ban; Florian Richter; Ingemar Andre; Robert Vernon; William R Schief; David Baker
Journal:  PLoS One       Date:  2011-08-31       Impact factor: 3.240

9.  Computational design of self-assembling cyclic protein homo-oligomers.

Authors:  Jorge A Fallas; George Ueda; William Sheffler; Vanessa Nguyen; Dan E McNamara; Banumathi Sankaran; Jose Henrique Pereira; Fabio Parmeggiani; T J Brunette; Duilio Cascio; Todd R Yeates; Peter Zwart; David Baker
Journal:  Nat Chem       Date:  2016-12-05       Impact factor: 24.427

10.  Principles for designing ideal protein structures.

Authors:  Nobuyasu Koga; Rie Tatsumi-Koga; Gaohua Liu; Rong Xiao; Thomas B Acton; Gaetano T Montelione; David Baker
Journal:  Nature       Date:  2012-11-08       Impact factor: 49.962

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  19 in total

1.  Large-scale design and refinement of stable proteins using sequence-only models.

Authors:  Jedediah M Singer; Scott Novotney; Devin Strickland; Hugh K Haddox; Nicholas Leiby; Gabriel J Rocklin; Cameron M Chow; Anindya Roy; Asim K Bera; Francis C Motta; Longxing Cao; Eva-Maria Strauch; Tamuka M Chidyausiku; Alex Ford; Ethan Ho; Alexander Zaitzeff; Craig O Mackenzie; Hamed Eramian; Frank DiMaio; Gevorg Grigoryan; Matthew Vaughn; Lance J Stewart; David Baker; Eric Klavins
Journal:  PLoS One       Date:  2022-03-14       Impact factor: 3.240

Review 2.  Protein Design: From the Aspect of Water Solubility and Stability.

Authors:  Rui Qing; Shilei Hao; Eva Smorodina; David Jin; Arthur Zalevsky; Shuguang Zhang
Journal:  Chem Rev       Date:  2022-08-03       Impact factor: 72.087

3.  Engineering of Cyclodextrin Glycosyltransferase through a Size/Polarity Guided Triple-Code Strategy with Enhanced α-Glycosyl Hesperidin Synthesis Ability.

Authors:  Hanchi Chen; Yi Liu; Xiangyi Ren; Jiajun Wang; Linjiang Zhu; Yuele Lu; Xiaolong Chen
Journal:  Appl Environ Microbiol       Date:  2022-08-11       Impact factor: 5.005

4.  Stabilizing proteins, simplified: A Rosetta-based webtool for predicting favorable mutations.

Authors:  David F Thieker; Jack B Maguire; Stephan T Kudlacek; Andrew Leaver-Fay; Sergey Lyskov; Brian Kuhlman
Journal:  Protein Sci       Date:  2022-10       Impact factor: 6.993

5.  Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation.

Authors:  Tae-Eun Kim; Kotaro Tsuboyama; Scott Houliston; Cydney M Martell; Claire M Phoumyvong; Alexander Lemak; Hugh K Haddox; Cheryl H Arrowsmith; Gabriel J Rocklin
Journal:  Proc Natl Acad Sci U S A       Date:  2022-10-03       Impact factor: 12.779

6.  Protocol for iterative optimization of modified peptides bound to protein targets.

Authors:  Rodrigo Ochoa; Pilar Cossio; Thomas Fox
Journal:  J Comput Aided Mol Des       Date:  2022-10-19       Impact factor: 4.179

7.  Design of protein-binding proteins from the target structure alone.

Authors:  Longxing Cao; Brian Coventry; Inna Goreshnik; Buwei Huang; William Sheffler; Joon Sung Park; Kevin M Jude; Iva Marković; Rameshwar U Kadam; Koen H G Verschueren; Kenneth Verstraete; Scott Thomas Russell Walsh; Nathaniel Bennett; Ashish Phal; Aerin Yang; Lisa Kozodoy; Michelle DeWitt; Lora Picton; Lauren Miller; Eva-Maria Strauch; Nicholas D DeBouver; Allison Pires; Asim K Bera; Samer Halabiya; Bradley Hammerson; Wei Yang; Steffen Bernard; Lance Stewart; Ian A Wilson; Hannele Ruohola-Baker; Joseph Schlessinger; Sangwon Lee; Savvas N Savvides; K Christopher Garcia; David Baker
Journal:  Nature       Date:  2022-03-24       Impact factor: 69.504

8.  Stabilization of the SARS-CoV-2 receptor binding domain by protein core redesign and deep mutational scanning.

Authors:  Alison C Leonard; Jonathan J Weinstein; Paul J Steiner; Annette H Erbse; Sarel J Fleishman; Timothy A Whitehead
Journal:  Protein Eng Des Sel       Date:  2022-02-17       Impact factor: 1.952

9.  Protein sequence optimization with a pairwise decomposable penalty for buried unsatisfied hydrogen bonds.

Authors:  Brian Coventry; David Baker
Journal:  PLoS Comput Biol       Date:  2021-03-08       Impact factor: 4.475

10.  Stabilization of the SARS-CoV-2 Receptor Binding Domain by Protein Core Redesign and Deep Mutational Scanning.

Authors:  Alison C Leonard; Jonathan J Weinstein; Paul J Steiner; Annette H Erbse; Sarel J Fleishman; Timothy A Whitehead
Journal:  bioRxiv       Date:  2021-11-24
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