Massively parallel protein-protein interaction measurement by sequencing (MP3-seq) enables rapid screening of protein heterodimers.


Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
16 Aug 2023
Historique:
pubmed: 18 2 2023
medline: 18 2 2023
entrez: 17 2 2023
Statut: epublish

Résumé

Protein-protein interactions (PPIs) regulate many cellular processes, and engineered PPIs have cell and gene therapy applications. Here we introduce massively parallel protein-protein interaction measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast-two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs, and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Finally, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics simulation energy terms to predict MP3-seq values. We find that AF-M and AF-M complex prediction-based models could be valuable for pre-screening interactions, but that measuring interactions experimentally remains necessary to rank their strengths quantitatively.

Identifiants

pubmed: 36798377
doi: 10.1101/2023.02.08.527770
pmc: PMC9934699
pii:
doi:

Types de publication

Preprint

Langues

eng

Auteurs

Alexander Baryshev (A)

Department of Electrical & Computer Engineering, University of Washington, Seattle, WA 98195, USA.

Alyssa La Fleur (A)

Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA 98195, USA.

Benjamin Groves (B)

Department of Electrical & Computer Engineering, University of Washington, Seattle, WA 98195, USA.

Cirstyn Michel (C)

Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.

David Baker (D)

Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.
Institute for Protein Design, University of Washington, Seattle, WA 98195, USA.
Department of Bioengineering, University of Washington, Seattle, WA, USA.
Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.

Ajasja Ljubetič (A)

Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.
Institute for Protein Design, University of Washington, Seattle, WA 98195, USA.
Department for Synthetic Biology and Immunology, National Institute of Chemistry, Ljubljana SI-1000, Slovenia.

Georg Seelig (G)

Department of Electrical & Computer Engineering, University of Washington, Seattle, WA 98195, USA.
Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA 98195, USA.

Classifications MeSH