8UGW image
Deposition Date 2023-10-06
Release Date 2024-12-18
Last Version Date 2025-03-12
Entry Detail
PDB ID:
8UGW
Title:
Computational design of highly signaling active membrane receptors through de novo solvent-mediated allosteric networks
Biological Source:
Source Organism:
Tequatrovirus T4 (Taxon ID: 10665)
Homo sapiens (Taxon ID: 9606)
Host Organism:
Method Details:
Experimental Method:
Resolution:
3.90 Å
R-Value Free:
0.33
R-Value Work:
0.30
Space Group:
P 21 21 21
Macromolecular Entities
Polymer Type:polypeptide(L)
Molecule:Endolysin,Adenosine receptor A2a
Gene (Uniprot):E, ADORA2A
Chain IDs:A
Chain Length:472
Number of Molecules:1
Biological Source:Tequatrovirus T4, Homo sapiens
Ligand Molecules
Primary Citation
Computational design of highly signalling-active membrane receptors through solvent-mediated allosteric networks.
Nat.Chem. 17 429 438 (2025)
PMID: 39849110 DOI: 10.1038/s41557-024-01719-2

Abstact

Protein catalysis and allostery require the atomic-level orchestration and motion of residues and ligand, solvent and protein effector molecules. However, the ability to design protein activity through precise protein-solvent cooperative interactions has not yet been demonstrated. Here we report the design of 14 membrane receptors that catalyse G protein nucleotide exchange through diverse engineered allosteric pathways mediated by cooperative networks of intraprotein, protein-ligand and -solvent molecule interactions. Consistent with predictions, the designed protein activities correlated well with the level of plasticity of the networks at flexible transmembrane helical interfaces. Several designs displayed considerably enhanced thermostability and activity compared with related natural receptors. The most stable and active variant crystallized in an unforeseen signalling-active conformation, in excellent agreement with the design models. The allosteric network topologies of the best designs bear limited similarity to those of natural receptors and reveal an allosteric interaction space larger than previously inferred from natural proteins. The approach should prove useful for engineering proteins with novel complex protein binding, catalytic and signalling activities.

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Primary Citation of related structures