Journal Article

FZJ-2019-05275

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Chasing the Full Free Energy Landscape of Neuroreceptor/Ligand Unbinding by Metadynamics Simulations

Capelli, R. (Corresponding author)FZJ* ; Bochicchio, A. ; Piccini, G. ; Casasnovas, R. ; Carloni, P. (Corresponding author)FZJ* ; Parrinello, M.

2019
Washington, DC

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Please use a persistent id in citations: http://hdl.handle.net/2128/23218  doi:10.1021/acs.jctc.9b00118

Abstract: Predicting the complete free energy landscape associated with protein–ligand unbinding may greatly help designing drugs with highly optimized pharmacokinetics. Here we investigate the unbinding of the iperoxo agonist to its target human neuroreceptor M2, embedded in a neuronal membrane. By feeding out-of-equilibrium molecular simulations data in a classification analysis, we identify the few essential reaction coordinates of the process. The full landscape is then reconstructed using an exact enhanced sampling method, well-tempered metadynamics in its funnel variant. The calculations reproduce well the measured affinity, provide a rationale for mutagenesis data, and show that the ligand can escape via two different routes. The allosteric modulator LY2119620 turns out to hamper both escapes routes, thus slowing down the unbinding process, as experimentally observed. This computationally affordable protocol is totally general, and it can be easily applied to determine the full free energy landscape of membrane receptors/drug interactions.

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Contributing Institute(s):

1. Computational Biomedicine (IAS-5)
2. Computational Biomedicine (INM-9)

Research Program(s):

1. 574 - Theory, modelling and simulation (POF3-574) (POF3-574)

Appears in the scientific report 2019

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Database coverage:
; ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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