Unraveling individual host-guest interactions in molecular recognition from first principles quantum mechanics: Insights into the nature of nicotinic acetylcholine receptor agonist binding.

drug design intermolecular interactions local coupled cluster local energy decomposition molecular recognition protein-ligand interactions

Journal

Journal of computational chemistry
ISSN: 1096-987X
Titre abrégé: J Comput Chem
Pays: United States
ID NLM: 9878362

Informations de publication

Date de publication:
15 02 2021
Historique:
received: 28 08 2020
revised: 30 10 2020
accepted: 02 11 2020
pubmed: 25 11 2020
medline: 15 9 2021
entrez: 24 11 2020
Statut: ppublish

Résumé

Drug binding to a protein target is governed by a complex pattern of noncovalent interactions between the ligand and the residues in the protein's binding pocket. Here we introduce a generally applicable, parameter-free, computational method that allows for the identification, quantification, and analysis of the key ligand-residue interactions responsible for molecular recognition. Our strategy relies on Local Energy Decomposition analysis at the "gold-standard" coupled cluster DLPNO-CCSD(T) level. In the study case shown in this paper, nicotine and imidacloprid binding to the nicotinic acetylcholine receptor, our approach provides new insights into how individual amino acids in the active site determine sensitivity and selectivity of the ligands, extending and refining classical pharmacophore hypotheses. By inference, the method is applicable to any kind of host/guest interactions with potential applications in industrial biocatalysis and protein engineering.

Identifiants

pubmed: 33232540
doi: 10.1002/jcc.26454
doi:

Substances chimiques

Ligands 0
Neonicotinoids 0
Nicotinic Agonists 0
Nitro Compounds 0
Receptors, Nicotinic 0
imidacloprid 3BN7M937V8

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

293-302

Informations de copyright

© 2020 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.

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Auteurs

Michael Edmund Beck (ME)

Department Computational Life Science, Bayer AG, Division Cropscience, Monheim am Rhein, Germany.

Frank Neese (F)

Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr, Germany.

Giovanni Bistoni (G)

Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr, Germany.

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