Combination of HDX-MS and in silico modeling to study enzymatic reactivity and stereo-selectivity at different solvent conditions.


Journal

Journal of pharmaceutical and biomedical analysis
ISSN: 1873-264X
Titre abrégé: J Pharm Biomed Anal
Pays: England
ID NLM: 8309336

Informations de publication

Date de publication:
15 Apr 2020
Historique:
received: 09 12 2019
revised: 29 01 2020
accepted: 31 01 2020
pubmed: 10 2 2020
medline: 15 12 2020
entrez: 10 2 2020
Statut: ppublish

Résumé

The higher-order structure of a protein defines its function, and protein structural dynamics are often essential for protein binding and enzyme catalysis. Methods for protein characterization in solution are continuously being developed to understand and explore protein conformational changes with regards to function and activity. The goal of this study was to survey the use of combining HDX-MS global conformational screening with in silico modeling and continuous labeling peptide-level HDX-MS as an approach to highlight regions of interest within an enzyme required for biocatalytic processes. We surveyed in silico modeling correlated with peptide level HDX-MS experiments to characterize and localize transaminase enzyme structural dynamics at different conditions. This approach was orthogonally correlated with a global Size-Exclusion-HDX (SEC-HDX) screen for global conformational comparison and global alpha-helical content measurements by circular dichroism. Enzymatic activity and stereo-selectivity of transaminases were compared at different reaction-solution conditions that forced protein conformational changes by increasing acetonitrile concentration. The experimental peptide-level HDX-MS results demonstrated similar trends to the modeling data showing that certain regions remained folded in transaminases ATA-036 and ATA-303 with increasing acetonitrile concentration, which is also associated with shifting stereoselectivity. HDX modeling, SEC-HDX and CD experimental data showed that transaminase ATA-234 had the highest level of global unfolding with increasing acetonitrile concentration compared to the other two enzymes, which correlated with drastically reduced product conversion in transamination reaction. The combined HDX modeling/experimental workflow, based on enzymatic reactions studied at different conditions to induce changes in enzyme conformation, could be used as a tool to guide directed evolution efforts by identifying and focusing on the regions of an enzyme required for reaction product conversion and stereoselectivity.

Identifiants

pubmed: 32036298
pii: S0731-7085(19)32972-3
doi: 10.1016/j.jpba.2020.113141
pii:
doi:

Substances chimiques

Enzymes 0
Peptides 0
Proteins 0
Solvents 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

113141

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Alexey A Makarov (AA)

Merck & Co., Inc., Process Research & Development, Rahway, NJ 07065, USA. Electronic address: alexey.makarov@merck.com.

Roxana E Iacob (RE)

Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA.

Gregory F Pirrone (GF)

Merck & Co., Inc., Process Research & Development, Rahway, NJ 07065, USA.

Agustina Rodriguez-Granillo (A)

Merck & Co., Inc., Computational and Structural Chemistry, Rahway, NJ 07065, USA.

Leo Joyce (L)

Merck & Co., Inc., Process Research & Development, Rahway, NJ 07065, USA.

Ian Mangion (I)

Merck & Co., Inc., Process Research & Development, Rahway, NJ 07065, USA.

Jeffrey C Moore (JC)

Merck & Co., Inc., Process Research & Development, Rahway, NJ 07065, USA.

Edward C Sherer (EC)

Merck & Co., Inc., Computational and Structural Chemistry, Rahway, NJ 07065, USA.

John R Engen (JR)

Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA.

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Classifications MeSH