The molecular basis of the antidepressant action of the magic mushroom extract, psilocin

Ali Asghar Hakami Zanjani*, Teresa Quynh Tram Nguyen, Luise Jacobsen, Himanshu Khandelia

*Kontaktforfatter

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Abstract

Magic mushrooms, and their extract psilocybin, are well-known for their psychedelic properties and recreational use. Psilocin, the bio-active form of psilocybin, can potentially treat various psychiatric diseases. Psilocin putatively exerts its psychedelic effect as an agonist to the serotonin 2A receptor (5-HT2AR), which is also the receptor for the neurological hormone serotonin. The two key chemical differences between the two molecules are first, that the primary amine in serotonin is replaced with a tertiary amine in psilocin, and second, the hydroxyl group is substituted differently on the aromatic ring. Here, we find that psilocin can bind to 5-HT2AR with an affinity higher than serotonin, and provide the molecular logic behind the higher binding affinity of psilocin using extensive molecular dynamics simulations and free energy calculations. The binding free energy of psilocin is dependent upon the protonation states of the ligands, as well as that of the key residue in the binding site: Aspartate 155. We find that the tertiary amine of psilocin, and not the altered substitution of the hydroxyl group in the ring is responsible for the increased affinity of psilocin. We propose design rules for effective antidepressants based on molecular insights from our simulations.

OriginalsprogEngelsk
Artikelnummer140914
TidsskriftBBA Proteins and Proteomics
Vol/bind1871
Udgave nummer4
Antal sider9
ISSN1570-9639
DOI
StatusUdgivet - 1. jul. 2023

Bibliografisk note

Funding Information:
AAHZ and HK are supported by a Novo Nordisk Foundation Grant No. NNF18OC0034936. LJ and HK are supported by a Lundbeckfonden Ascending Investigator grant. The simulations were performed on the ABACUS 2.0 supercomputer at the Danish e-Science Center at SDU, and on the Kay supercomputer under the PRACE DECI Grant No. ANNEX. The financial support by the Novo Nordisk Foundation grant (number NNF18OC0032608) for the ROBUST-project is also acknowledged.

Publisher Copyright:
© 2023

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