In their 2013 papers, Liang et al1,2 presented a large congeneric series of ligands aimed at exploring two areas of binding within the TYK2 active site: the first explored the hinge region while the second investigated the linker region1. A set of 16 ligands from the first paper is now commonly used as the TYK2 benchmark dataset to test the predictive abilities of FEP. Here we expand on the norm, showing the power of Free Energy Perturbation (FEP) in predicting unknown ligand binding affinities and importantly, how we would triage the results. As the compounds originate from the same project and share a 4-aminopyridine benzamide core, this presented the opportunity to use the TYK2 system from our own Flare™ FEP benchmark experiment for prospective calculations on additional compounds. In this webinar, we will guide you through an efficient workflow using computational methods that are available within Cresset’s software, Flare to arrive at accurate binding free energies for ‘new’ ligand suggestions with the TYK2 system.
The methods used include:
- Molecular Dynamics (MD)
- Water analysis solving the Ornstein-Zernike equation (3D-RISM)
- Alignment of ligands for FEP (Conformation Hunt & Align)
- Relative binding free-energy (RBFE) perturbation theory (FEP) in both benchmark (for known ligands) and production (involving ligands with unknown activities) modes.
By presenting the FEP results from both the benchmark results and the blind production study, we will show you that Flare FEP can quickly provide valuable insights in drug discovery projects, such as the TYK2 example we discuss here.
References
- Liang J., et al. Lead Optimization of a 4‑Aminopyridine Benzamide Scaffold To Identify Potent, Selective, and Orally Bioavailable TYK2 Inhibitors, J. Med. Chem. 2013, 56, 4521−4536. https://doi.org/10.1021/jm400266t
- Liang J., et al. Lead identification of novel and selective TYK2 inhibitors, European Journal of Medicinal Chemistry, 2013, 67, 175 – 187. https://doi.org/10.1016/j.ejmech.2013.03.070
