4Q1U image
Deposition Date 2014-04-04
Release Date 2015-02-18
Last Version Date 2024-10-09
Entry Detail
PDB ID:
4Q1U
Keywords:
Title:
Serum paraoxonase-1 by directed evolution with the K192Q mutation
Biological Source:
Source Organism:
hybrid (Taxon ID: 37965)
Host Organism:
Method Details:
Experimental Method:
Resolution:
2.30 Å
R-Value Free:
0.21
R-Value Work:
0.17
R-Value Observed:
0.17
Space Group:
P 43 21 2
Macromolecular Entities
Polymer Type:polypeptide(L)
Molecule:Serum paraoxonase/arylesterase 1
Chain IDs:A
Chain Length:355
Number of Molecules:1
Biological Source:hybrid
Primary Citation
Catalytic stimulation by restrained active-site floppiness-the case of high density lipoprotein-bound serum paraoxonase-1.
J.Mol.Biol. 427 1359 1374 (2015)
PMID: 25644661 DOI: 10.1016/j.jmb.2015.01.013

Abstact

Despite the abundance of membrane-associated enzymes, the mechanism by which membrane binding stabilizes these enzymes and stimulates their catalysis remains largely unknown. Serum paraoxonase-1 (PON1) is a lipophilic lactonase whose stability and enzymatic activity are dramatically stimulated when associated with high-density lipoprotein (HDL) particles. Our mutational and structural analyses, combined with empirical valence bond simulations, reveal a network of hydrogen bonds that connect HDL binding residues with Asn168--a key catalytic residue residing >15Å from the HDL contacting interface. This network ensures precise alignment of N168, which, in turn, ligates PON1's catalytic calcium and aligns the lactone substrate for catalysis. HDL binding restrains the overall motion of the active site and particularly of N168, thus reducing the catalytic activation energy barrier. We demonstrate herein that disturbance of this network, even at its most far-reaching periphery, undermines PON1's activity. Membrane binding thus immobilizes long-range interactions via second- and third-shell residues that reduce the active site's floppiness and pre-organize the catalytic residues. Although this network is critical for efficient catalysis, as demonstrated here, unraveling these long-rage interaction networks is challenging, let alone their implementation in artificial enzyme design.

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