Literature DB >> 34460870

The register shift rules for βαβ-motifs for de novo protein design.

Hiroto Murata1, Hayao Imakawa1, Nobuyasu Koga2,3,4, George Chikenji1.   

Abstract

A wide range of de novo design of αβ-proteins has been achieved based on the design rules, which describe secondary structure lengths and loop torsion patterns favorable for design target topologies. This paper proposes design rules for register shifts in βαβ-motifs, which have not been reported previously, but are necessary for determining a target structure of de novo design of αβ-proteins. By analyzing naturally occurring protein structures in a database, we found preferences for register shifts in βαβ-motifs, and derived the following empirical rules: (1) register shifts must not be negative regardless of torsion types for a constituent loop in βαβ-motifs; (2) preferred register shifts strongly depend on the loop torsion types. To explain these empirical rules by physical interactions, we conducted physics-based simulations for systems mimicking a βαβ-motif that contains the most frequently observed loop type in the database. We performed an exhaustive conformational sampling of the loop region, imposing the exclusion volume and hydrogen bond satisfaction condition. The distributions of register shifts obtained from the simulations agreed well with those of the database analysis, indicating that the empirical rules are a consequence of physical interactions, rather than an evolutionary sampling bias. Our proposed design rules will serve as a guide to making appropriate target structures for the de novo design of αβ-proteins.

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Year:  2021        PMID: 34460870      PMCID: PMC8405016          DOI: 10.1371/journal.pone.0256895

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  27 in total

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2.  A novel method reveals that solvent water favors polyproline II over beta-strand conformation in peptides and unfolded proteins: conditional hydrophobic accessible surface area (CHASA).

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Authors:  Patrick J Fleming; George D Rose
Journal:  Protein Sci       Date:  2005-06-03       Impact factor: 6.725

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Journal:  Nature       Date:  2019-01-09       Impact factor: 49.962

5.  Sterics and solvation winnow accessible conformational space for unfolded proteins.

Authors:  Nicholas C Fitzkee; George D Rose
Journal:  J Mol Biol       Date:  2005-09-12       Impact factor: 5.469

6.  Satisfying hydrogen bonding potential in proteins.

Authors:  I K McDonald; J M Thornton
Journal:  J Mol Biol       Date:  1994-05-20       Impact factor: 5.469

7.  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

8.  MICAN: a protein structure alignment algorithm that can handle Multiple-chains, Inverse alignments, C(α) only models, Alternative alignments, and Non-sequential alignments.

Authors:  Shintaro Minami; Kengo Sawada; George Chikenji
Journal:  BMC Bioinformatics       Date:  2013-01-18       Impact factor: 3.169

9.  De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy.

Authors:  Po-Ssu Huang; Kaspar Feldmeier; Fabio Parmeggiani; D Alejandro Fernandez Velasco; Birte Höcker; David Baker
Journal:  Nat Chem Biol       Date:  2015-11-23       Impact factor: 15.040

10.  De novo design of a non-local β-sheet protein with high stability and accuracy.

Authors:  Enrique Marcos; Tamuka M Chidyausiku; Andrew C McShan; Thomas Evangelidis; Santrupti Nerli; Lauren Carter; Lucas G Nivón; Audrey Davis; Gustav Oberdorfer; Konstantinos Tripsianes; Nikolaos G Sgourakis; David Baker
Journal:  Nat Struct Mol Biol       Date:  2018-10-29       Impact factor: 15.369

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  1 in total

1.  The Structural Rule Distinguishing a Superfold: A Case Study of Ferredoxin Fold and the Reverse Ferredoxin Fold.

Authors:  Takumi Nishina; Megumi Nakajima; Masaki Sasai; George Chikenji
Journal:  Molecules       Date:  2022-05-31       Impact factor: 4.927

  1 in total

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