Computational design of Periplasmic binding protein biosensors guided by molecular dynamics.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
17 Jun 2024
Historique:
received: 21 01 2024
accepted: 30 05 2024
medline: 17 6 2024
pubmed: 17 6 2024
entrez: 17 6 2024
Statut: aheadofprint

Résumé

Periplasmic binding proteins (PBPs) are bacterial proteins commonly used as scaffolds for substrate-detecting biosensors. In these biosensors, effector proteins (for example fluorescent proteins) are inserted into a PBP such that the effector protein's output changes upon PBP-substate binding. The insertion site is often determined by comparison of PBP apo/holo crystal structures, but random insertion libraries have shown that this can miss the best sites. Here, we present a PBP biosensor design method based on residue contact analysis from molecular dynamics. This computational method identifies the best previously known insertion sites in the maltose binding PBP, and suggests further previously unknown sites. We experimentally characterise fluorescent protein insertions at these new sites, finding they too give functional biosensors. Furthermore, our method is sufficiently flexible to both suggest insertion sites compatible with a variety of effector proteins, and be applied to binding proteins beyond PBPs.

Identifiants

pubmed: 38885277
doi: 10.1371/journal.pcbi.1012212
pii: PCOMPBIOL-D-24-00104
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1012212

Informations de copyright

Copyright: © 2024 O’Shea et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Jack M O'Shea (JM)

School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.
School of Natural Sciences, Technical University of Munich, Center for Functional Protein Assemblies (CPA), Garching, Germany.

Peter Doerner (P)

School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.

Annis Richardson (A)

School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.

Christopher W Wood (CW)

School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.

Classifications MeSH