Target Alcohols
The two alcohols we are trying to produce are linalool and nerolidol, terpene alcohols that interact with GABA-A receptors to produce anxiety-relieving effects.
Linalool Chemical Structure
An acyclic monoterpene alcohol with chemical formula C10H18O. It features two double bonds (a diene), a hydroxyl group (alcohol), and two methyl groups.
Nerolidol Chemical Structure
An acyclic terpene alcohol with chemical formula C15H26O. It contains three double bonds (a triene), a hydroxyl group (alcohol), and three methyl groups.
Plasmid & Enzyme Models
The pJT1 plasmid is responsible for introducing linalool and nerolidol synthases to promote the production of these alcohols, as well as overexpressing the farnesyl pyrophosphate (FPP) synthase. Linalool and FPP both have the same precursor: GPP. If FPP synthase was not overexpressed, linalool would compete with FPP for GPP, resulting in lower yield.
Linalool & Nerolidol Synthase Models
(Actinidia chinensis nerolidol:linalool synthase AcNES1)
Farnesyl Pyrophosphate Synthase Model
(Farnesyl pyrophosphate synthase Erg20p Swiss model)
pJT1 Plasmid
The plasmid introduces linalool and nerolidol synthases and overexpresses FPP synthase, ensuring sufficient precursor for production.
GABA-A Receptor Interaction Simulations
Linalool and nerolidol modulate GABAergic neurotransmission as positive allosteric modulators, meaning they increase receptor responsiveness to endogenous ligands and thereby enhance anxiolytic, sedative, and relaxation effects.
Hence, we ran 10 different prediction simulations of each terpene’s binding interactions with GABA-A receptors to estimate binding affinity and stability. Here we present 3 sample predictions of Linalool's interaction with GABA-A(Left) and 3 of nerolidol's interaction (right):
Linalool Predictions
Figure 1: Binding affinity plotted against confidence metric for 10 different predictions of linalool-receptor interaction, indicating moderate binding affinity and relatively low confidence for top hits.
*cLDDT = structural confidence score (higher = better); Binding affinity = docking score to predict relative affinity and stability*
Most confident molecular structure prediction: linalool and GABA receptor
Nerolidol Predictions
Figure 2: Binding affinity plotted against confidence metric for 10 different predictions of nerolidol-receptor interaction, indicating moderate binding affinity and relatively low confidence for top hits. However, values are less spread out compared to linalool-receptor binding.
Most confident molecular structure prediction: nerolidol and GABA-A receptor
