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Activity cliffs (ACs) are an important type of structure-activity relationship in medicinal chemistry where small structural changes result in unexpectedly large differences in biological activity. Being able to predict these changes would have a profound impact on lead optimization of drug candidates. Free-energy perturbation is an ideal tool for predicting relative binding energy differences for small structural modifications, but its performance for ACs is unknown. Here, we show that FEP can on average predict ACs to within 1.39 kcal/mol of experiment (∼1 log unit of activity). We performed FEP calculations with two different software methods: Schrödinger-Desmond FEP+ and GROMACS implementations. There was qualitative agreement in the results from the two methods, and quantitatively the error for one data set was identical, 1.43 kcal/mol, but FEP+ performed better in the second, with errors of 1.17 versus 1.90 kcal/mol. The results have far-reaching implications, suggesting well-implemented FEP calculations can have a major impact on computational drug design.

Covalent labeling of G protein-coupled receptors (GPCRs) by small molecules is a powerful approach to understand binding modes, mechanism of action, pharmacology, and even facilitate structure elucidation. We report the first covalent positive allosteric modulator (PAM) for a class C GPCR, the mGlu 2 receptor. Three putatively covalent mGlu 2 PAMs were designed and synthesized. Pharmacological characterization identified 2 to bind the receptor covalently. Computational modeling combined with receptor mutagenesis revealed T791 7.29×30 as the likely position of covalent interaction. We show how this covalent ligand can be used to characterize the PAM binding mode and that it is a valuable tool compound in studying receptor function and binding kinetics. Our findings advance the understanding of the mGlu 2 PAM interaction and suggest that 2 is a valuable probe for further structural and chemical biology approaches.

Bivalent ligands have emerged as chemical tools to study G protein-coupled receptor dimers. Using a combination of computational, chemical, and biochemical tools, here we describe the design of bivalent ligand 13 with high affinity ( K DB1 = 21 pM) for the dopamine D 2 receptor (D 2 R) homodimer. Bivalent ligand 13 enhances the binding affinity relative to monovalent compound 15 by 37-fold, indicating simultaneous binding at both protomers. Using synthetic peptides with amino acid sequences of transmembrane (TM) domains of D 2 R, we provide evidence that TM6 forms the interface of the homodimer. Notably, the disturber peptide TAT-TM6 decreased the binding of bivalent ligand 13 by 52-fold and had no effect on monovalent compound 15, confirming the D 2 R homodimer through TM6 ex vivo. In conclusion, by using a versatile multivalent chemical platform, we have developed a precise strategy to generate a true bivalent ligand that simultaneously targets both orthosteric sites of the D 2 R homodimer.

Novel spiroaminodihydropyrroles probing for optimized interactions at the P3 pocket of β-secretase 1 (BACE1) were designed with the use of free energy perturbation (FEP) calculations. The resulting molecules showed pIC50 potencies in enzymatic BACE1 inhibition assays ranging from approximately 5 to 7. Good correlation was observed between the predicted activity from the FEP calculations and experimental activity. Simulations run with a default 5 ns approach delivered a mean unsigned error (MUE) between prediction and experiment of 0.58 and 0.91 kcal/mol for retrospective and prospective applications, respectively. With longer simulations of 10 and 20 ns, the MUE was in both cases 0.57 kcal/mol for the retrospective application, and 0.69 and 0.59 kcal/mol for the prospective application. Other considerations that impact the quality of the calculations are discussed. This work provides an example of the value of FEP as a computational tool for drug discovery.