Breaking the Glass Ceiling in Simulation and Modeling: Women in Pharmaceutical Discovery.

The topic of gender equality within the United States workforce is receiving a great deal of attention. The field of chemistry is no exception and is increasingly focused on taking steps to achieve gender diversity within the chemistry workforce. Over the past several years, many computational chemistry groups within large pharmaceutical companies have realized growth in the number of women, and here we discuss the key factors that we believe have played a role in attracting and retaining the authors of this review as computational chemists in pharma. Furthermore, we combine our professional experiences in the context of how computational methodology and technology have evolved over the past decades and how that evolution has facilitated the inclusion of more women into the field. Our hope is to be a part of a solution and provide insight that will allow the chemistry workforce to continue to make steps forward in attaining gender diversity in the workplace.

Mathematical and Structural Characterization of Strong Nonadditive Structure-Activity Relationship Caused by Protein Conformational Changes.

In medicinal chemistry, accurate prediction of additivity-based structure-activity relationship (SAR) analysis rests on three assumptions: (1) a consistent binding pose of the central scaffold, (2) no interaction between the R group substituents, and (3) a relatively rigid binding pocket in which the R group substituents act independently. Previously, examples of nonadditive SAR have been documented in systems that deviate from the first two assumptions. Local protein structural change upon ligand binding, through induced fit or conformational selection, although a well-known phenomenon that invalidates the third assumption, has not been linked to nonadditive SAR conclusively. Here, for the first time, we present clear structural evidence that the formation of a hydrophobic pocket upon ligand binding in PDE2 catalytic site reduces the size of another distinct subpocket and contributes to strong nonadditive SAR between two otherwise distant R groups.

Discovery of Selective Phosphodiesterase 1 Inhibitors with Memory Enhancing Properties.

A series of potent thienotriazolopyrimidinone-based PDE1 inhibitors was discovered. X-ray crystal structures of example compounds from this series in complex with the catalytic domain of PDE1B and PDE10A were determined, allowing optimization of PDE1B potency and PDE selectivity. Reduction of hERG affinity led to greater than a 3000-fold selectivity for PDE1B over hERG. 6-(4-Methoxybenzyl)-9-((tetrahydro-2H-pyran-4-yl)methyl)-8,9,10,11-tetrahydropyrido[4',3':4,5]thieno[3,2-e][1,2,4]triazolo[1,5-c]pyrimidin-5(6H)-one was identified as an orally bioavailable and brain penetrating PDE1B enzyme inhibitor with potent memory-enhancing effects in a rat model of object recognition memory.

Design and Synthesis of Novel and Selective Phosphodiesterase 2 (PDE2a) Inhibitors for the Treatment of Memory Disorders.

A series of potent and selective [1,2,4]triazolo[1,5-a]pyrimidine PDE2a inhibitors is reported. The design and improvement of the binding properties of this series was achieved using X-ray crystal structures in conjunction with careful analysis of electronic and structural requirements for the PDE2a enzyme. One of the lead compounds, compound 27 (DNS-8254), was identified as a potent and highly selective PDE2a enzyme inhibitor with favorable rat pharmacokinetic properties. Interestingly, the increased potency of compound 27 was facilitated by the formation of a halogen bond with the oxygen of Tyr827 present in the PDE2a active site. In vivo, compound 27 demonstrated significant memory enhancing effects in a rat model of novel object recognition. Taken together, these data suggest that compound 27 may be a useful tool to explore the pharmacology of selective PDE2a inhibition.

Characterizing the effects of the juxtamembrane domain on vascular endothelial growth factor receptor-2 enzymatic activity, autophosphorylation, and inhibition by axitinib.

The catalytic domains of protein kinases are commonly treated as independent modular units with distinct biological functions. Here, the interactions between the catalytic and juxtamembrane domains of VEGFR2 are studied. Highly purified preparations of the receptor tyrosine kinase VEGFR2 catalytic domain without (VEGFR2-CD) and with (VEGFR2-CD/JM) the juxtamembrane (JM) domain were characterized by kinetic, biophysical, and structural methods. Although the catalytic parameters for both constructs were similar, the autophosphorylation rate of VEGFR2-CD/JM was substantially faster than VEGFR2-CD. The first event in the autophosphorylation reaction was phosphorylation of JM residue Y801 followed by phosphorylation of activation loop residues in the CD. The rates of activation loop autophosphorylation for the two constructs were determined to be similar. The autophosphorylation rate of Y801 was invariant on enzyme concentration, which is consistent with an intramolecular reaction. In addition, the first biochemical characterization of the advanced clinical compound axitinib is reported. Axitinib was found to have 40-fold enhanced biochemical potency toward VEGFR2-CD/JM (K(i) = 28 pM) compared to VEGFR2-CD, which correlates better with cellular potency. Calorimetric studies, including a novel ITC compound displacement method, confirmed the potency and provided insight into the thermodynamic origin of the potency differences. A structural model for the VEGFR2-CD/JM is proposed based on the experimental findings reported here and on the JM position in c-Kit, FLT3, and CSF1/cFMS. The described studies identify potential functions of the VEGFR2 JM domain with implications to both receptor biology and inhibitor design.

Hierarchy of simulation models in predicting structure and energetics of the Src SH2 domain binding to tyrosyl phosphopeptides.

Structure and energetics of the Src Src Homology 2 (SH2) domain binding with the recognition phosphopeptide pYEEI and its mutants are studied by a hierarchical computational approach. The proposed structure prediction strategy includes equilibrium sampling of the peptide conformational space by simulated tempering dynamics with the simplified, knowledge-based energy function, followed by structural clustering of the resulting conformations and binding free energy evaluation of a single representative from each cluster, a cluster center. This protocol is robust in rapid screening of low-energy conformations and recovers the crystal structure of the pYEEI peptide. Thermodynamics of the peptide-SH2 domain binding is analyzed by computing the average energy contributions over conformations from the clusters, structurally similar to the predicted peptide bound structure. Using this approach, the binding thermodynamics for a panel of studied peptides is predicted in a better agreement with the experiment than previously suggested models. However, the overall correlation between computed and experimental binding affinity remains rather modest. The results of this study show that small differences in binding free energies between the Ala and Gly mutants of the pYEEI peptide are considerably more difficult to predict than the structure of the bound peptides, indicating that accurate computational prediction of binding affinities still remains a major methodological and technical challenge.