4.7 Article

Structures of hyperstable ancestral haloalkane dehalogenases show restricted conformational dynamics

Journal

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
Volume 18, Issue -, Pages 1497-1508

Publisher

ELSEVIER
DOI: 10.1016/j.csbj.2020.06.021

Keywords

Enzyme; Haloalkane dehalogenase; Ancestral sequence reconstruction; Thermostability; X-ray crystallography; Protein simulations; Conformational flexibility; Protein design

Funding

  1. Czech Ministry of Education [02.1.01/0.0/0.0/18_046/0015975, LM2018121, LM2015047, LM2018140]
  2. European Commission [857560, 720776, 814418]
  3. Marie Sklodowska-Curie Actions (MSCA) [792772]
  4. Grant Agency of the Masaryk University (GAMU) [MUNI/H/1561/2018]
  5. Czech Grant Agency [20-15915Y]
  6. Marie Curie Actions (MSCA) [792772] Funding Source: Marie Curie Actions (MSCA)

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Ancestral sequence reconstruction is a powerful method for inferring ancestors of modern enzymes and for studying structure-function relationships of enzymes. We have previously applied this approach to haloalkane dehalogenases (HLDs) from the subfamily HLD-II and obtained thermodynamically highly stabilized enzymes (Delta T-m up to 24 degrees C), showing improved catalytic properties. Here we combined crystallographic structural analysis and computational molecular dynamics simulations to gain insight into the mechanisms by which ancestral HLDs became more robust enzymes with novel catalytic properties. Reconstructed ancestors exhibited similar structure topology as their descendants with the exception of a few loop deviations. Strikingly, molecular dynamics simulations revealed restricted conformational dynamics of ancestral enzymes, which prefer a single state, in contrast to modern enzymes adopting two different conformational states. The restricted dynamics can potentially be linked to their exceptional stabilization. The study provides molecular insights into protein stabilization due to ancestral sequence reconstruction, which is becoming a widely used approach for obtaining robust protein catalysts. (C) 2020 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

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