Evaluation of Free Energy Calculations for the Prioritization of Macrocycle Synthesis.Paulsen, J.L., Yu, H.S., Sindhikara, D., Wang, L., Appleby, T.C., Villasenor, A.G., Schmitz, U., Shivakumar, D.
(2020) J Chem Inf Model
- PubMed: 32539379
- DOI: 10.1021/acs.jcim.0c00132
- Structures With Same Primary Citation
- PubMed Abstract:
A tremendous research and development effort was exerted toward combating chronic hepatitis C, ultimately leading to curative oral treatments, all of which are targeting viral proteins. Despite the advantage of numerous targets allowing for broad hep ...
A tremendous research and development effort was exerted toward combating chronic hepatitis C, ultimately leading to curative oral treatments, all of which are targeting viral proteins. Despite the advantage of numerous targets allowing for broad hepatitis C virus (HCV) genotype coverage, the only host target inhibitors that advanced into clinical development were Cyclosporin A based cyclophilin inhibitors. While cyclosporine-based molecules typically require a fermentation process, Gilead successfully pursued a fully synthetic, oral program based on Sanglifehrin A. The drug discovery process, though greatly helped by facile crystallography, was still hampered by the limitations in the accuracy of predictive computational methods for prioritizing compound ideas. Recent advances in accuracy and speed of free energy perturbation (FEP) methods, however, are attractive for prioritizing and de-risking synthetically challenging molecules and potentially could have had a significant impact on the speed of the development of this program. Here in our simulated prospective study, the binding free energies of 26 macrocyclic cyclophilin inhibitors were blindly predicted using FEP+ to test this hypothesis. The predictions had a low mean unsigned error (MUE) (1.1 kcal/mol) and accurately reproduced many design decisions from the program, suggesting that FEP+ has the potential to drive synthetic chemistry efforts by more accurately ranking compounds with non-intuitive structure-activity relationships (SAR).
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