From: chemistry-request at ccl.net <br />
To: chemistry-request at ccl.net<br />
Date: Wed Dec 20 12:07:04 2023<br />
Subject: 24.01.18 <span class="fancysmall">Calculating ligand binding affinities at the lipid /membrane interface P2Y1 GPCR complex, Online</span><br />

<pre>Royston
Conf_Description: Register here - <a href="https://www.cresset-group.com/about/events/calculating-ligand-binding-affinities-lipid-membra/" target="_blank">https://www.cresset-group.com/about/events/calculating-ligand-binding-affinities-lipid-membra/</a>


Date: Thursday 18th January, 2024
Time: 2pm GMT / 3pm CET / 9am EST / 6:30pm IST
Duration: 45 minutes

G protein-coupled receptors (GPCRs) are a very large and important class of
 drug targets. They are also a very difficult class in terms of modeling 
with adequate accuracy the necessarily many atoms that constitute the 
protein, ligands, membrane lipids and solvent. Faster and more accurate 
computational solutions are required for these challenging systems. In this 
session we discuss a workflow using computational chemistry methods that are 
available within Cressets CADD software platform, Flare to arrive at 
accurate binding free energies for a set of P2Y1 ligands bound to a 
lipid-exposed binding site.  

The methods are: 
- Molecular Dynamics (MD)  
- Water analysis solving the Ornstein-Zernike equation (3D-RISM) 
- Alignment of ligands for FEP (Conf Hunt &amp; Align) 
- Relative binding free-energy (RBFE) perturbation theory (Flare FEP).
 
We show that using MD, water analysis and careful ligand alignment prior 
to RBFE calculations can result in reliable predictions for protein-ligand 
binding affinities even in the case where the ligand is at the lipid-protein 
interface. Until recently the computational cost of such a large system 
(93,255 atoms) would be prohibitively large. Implementing methods that 
ensurea stable and appropriately hydrated binding site (a suitable snapshot 
of in vivo binding action) as input to the RBFE calculation results in an 
efficient process for setting up the RBFE job to yield accurate results. 
The RBFE calculation itself is improved, in terms of efficiency, by the 
implementation of adaptive Lambda () schedules and automated intermediate 
generation. The results that will be presented show that the predicted 
binding free energy of 30 ligands matches the measured experimental 
affinity closely (mean unsigned error is 1.17 kcal/mol). This difficult 
computational problem can now be solved relatively quickly with good 
accuracy by using these methods, and, in principle this workflow could be 
extended to further membrane protein targets in drug discovery.</pre>
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