Cryo-EM structure of the gastric proton pump with bound DQ-06Cryo-EM structure of the gastric proton pump with bound DQ-06

Structural highlights

8ijw is a 2 chain structure with sequence from Sus scrofa. Full crystallographic information is available from OCA. For a guided tour on the structure components use FirstGlance.
Method:Electron Microscopy, Resolution 2.19Å
Ligands:, , , , ,
Resources:FirstGlance, OCA, PDBe, RCSB, PDBsum, ProSAT

Function

ATP4A_PIG Catalyzes the hydrolysis of ATP coupled with the exchange of H(+) and K(+) ions across the plasma membrane. Responsible for acid production in the stomach.

Publication Abstract from PubMed

Existing drugs often suffer in their effectiveness due to detrimental side effects, low binding affinity or pharmacokinetic problems. This may be overcome by the development of distinct compounds. Here, we exploit the rich structural basis of drug-bound gastric proton pump to develop compounds with strong inhibitory potency, employing a combinatorial approach utilizing deep generative models for de novo drug design with organic synthesis and cryo-EM structural analysis. Candidate compounds that satisfy pharmacophores defined in the drug-bound proton pump structures, were designed in silico utilizing our deep generative models, a workflow termed Deep Quartet. Several candidates were synthesized and screened according to their inhibition potencies in vitro, and their binding poses were in turn identified by cryo-EM. Structures reaching up to 2.10 A resolution allowed us to evaluate and re-design compound structures, heralding the most potent compound in this study, DQ-18 (N-methyl-4-((2-(benzyloxy)-5-chlorobenzyl)oxy)benzylamine), which shows a K(i) value of 47.6 nM. Further high-resolution cryo-EM analysis at 2.08 A resolution unambiguously determined the DQ-18 binding pose. Our integrated approach offers a framework for structure-based de novo drug development based on the desired pharmacophores within the protein structure.

Deep learning driven de novo drug design based on gastric proton pump structures.,Abe K, Ozako M, Inukai M, Matsuyuki Y, Kitayama S, Kanai C, Nagai C, Gopalasingam CC, Gerle C, Shigematsu H, Umekubo N, Yokoshima S, Yoshimori A Commun Biol. 2023 Sep 19;6(1):956. doi: 10.1038/s42003-023-05334-8. PMID:37726448[1]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

References

  1. Abe K, Ozako M, Inukai M, Matsuyuki Y, Kitayama S, Kanai C, Nagai C, Gopalasingam CC, Gerle C, Shigematsu H, Umekubo N, Yokoshima S, Yoshimori A. Deep learning driven de novo drug design based on gastric proton pump structures. Commun Biol. 2023 Sep 19;6(1):956. PMID:37726448 doi:10.1038/s42003-023-05334-8

8ijw, resolution 2.19Å

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