Explicit treatment of active-site waters enhances quantum mechanical/implicit solvent scoring: Inhibition of CDK2 by new pyrazolo[1,5-a]pyrimidines
| Authors | |
|---|---|
| Year of publication | 2017 |
| Type | Article in Periodical |
| Magazine / Source | European Journal of Medicinal Chemistry |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1016/j.ejmech.2016.12.023 |
| Field | Pharmacology and pharmaceutical chemistry |
| Keywords | Cyclin-dependent kinase 2; ATP-competitive type I inhibitors; Pyrazolopyrimidine; Quantum mechanical scoring; Protein-ligand binding; Molecular dynamics; Water thermodynamics; X-ray crystal structure |
| Description | We present comprehensive testing of solvent representation in quantum mechanics (QM)-based scoring of protein-ligand affinities. To this aim, we prepared 21 new inhibitors of cyclin-dependent kinase 2 (CDK2) with the pyrazolo[1,5-a]pyrimidine core, whose activities spanned three orders of magnitude. The crystal structure of a potent inhibitor bound to the active CDK2/cyclin A complex revealed that the biphenyl substituent at position 5 of the pyrazolo[1,5-a]pyrimidine scaffold was located in a previously unexplored pocket and that six water molecules resided in the active site. Using molecular dynamics, protein-ligand interactions and active-site water H-bond networks as well as thermodynamics were probed. Thereafter, all the inhibitors were scored by the QM approach utilizing the COSMO implicit solvent model. Such a standard treatment failed to produce a correlation with the experiment (R-2 = 0.49). However, the addition of the active-site waters resulted in significant improvement (R-2 = 0.68). The activities of the compounds could thus be interpreted by taking into account their specific noncovalent interactions with CDK2 and the active-site waters. In summary, using a combination of several experimental and theoretical approaches we demonstrate that the inclusion of explicit solvent effects enhance QM/COSMO scoring to produce a reliable structure activity relationship with physical insights. More generally, this approach is envisioned to contribute to increased accuracy of the computational design of novel inhibitors. (C) 2016 Elsevier Masson SAS. All rights reserved. |
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