Differential Water Thermodynamics Determine ... - ACS Publications

Article pubs.acs.org/jcim

Differential Water Thermodynamics Determine PI3K-Beta/Delta Selectivity for Solvent-Exposed Ligand Modifications Daniel Robinson,† Thomas Bertrand,§ Jean-Christophe Carry,‡ Frank Halley,‡ Andreas Karlsson,§ Magali Mathieu,§ Hervé Minoux,§ Marc-Antoine Perrin,∥ Benoit Robert,∥ Laurent Schio,*,§ and Woody Sherman*,† †

Schrodinger, 120 W 45th St, New York, New York 10036, United States Medicinal Chemistry, §Structure Design and Informatics, ∥Analytical Sciences, Sanofi, 13, quai Jules Guesde, 94403 Vitry-sur-Seine, France

‡

S Supporting Information *

ABSTRACT: Phosphoinositide 3-kinases (PI3Ks) are involved in important cellular functions and represent desirable targets for drug discovery efforts, especially related to oncology; however, the four PI3K subtypes (α, β, γ, and δ) have highly similar binding sites, making the design of selective inhibitors challenging. A series of inhibitors with selectivity toward the β subtype over δ resulted in compound 3(S), which has entered a phase I/Ib clinical trial for patients with advanced PTEN-deficient cancer. Interestingly, X-ray crystallography revealed that the modifications making inhibitor 3(S) and related compounds selective toward the β-isoform do not interact directly with either PI3Kβ or PI3Kδ, thereby confounding rationalization of the SAR. Here, we apply explicit solvent molecular dynamics and solvent thermodynamic analysis using WaterMap in an effort to understand the unusual affinity and selectivity trends. We find that differences in solvent energetics and water networks, which are modulated upon binding of different ligands, explain the experimental affinity and selectivity trends. This study highlights the critical role of water molecules in molecular recognition and the importance of considering water networks in drug discovery efforts to rationalize and improve selectivity.

■

INTRODUCTION The phosphoinositide 3-kinase (phosphatidylinositol-4,5-bisphosphate 3-kinase; PI3K) family of phospholipid kinases is implicated in the regulation of diverse cellular processes, including proliferation, survival, glucose transport, and platelet function.1 Class IA PI3Ks comprising PI3Kα, β, and δ are implicated in human cancers,2 leading to the discovery, development, and clinical evaluation of inhibitors of this class of lipid kinases.3 Most of the PI3K inhibitors initially in clinical development inhibited all class I PI3K isoforms; however, several reports supported the clinical development of isoformspecific inhibitors.4,5 The essential nonredundant role of PI3Kα, β, and δ, together with the putative off-target side effects attributed to pan-PI3K inhibitors, has triggered the search for isoform selective inhibitors.6 PI3Kδ selective inhibitors were among the first to reach the clinic for the treatment of multiple myeloma and various forms of leukemia and lymphoma,7 and recently Idelalisib was the first PI3K inhibitor to reach the market.8 The PI3Kα oncogene was found to be activated through hotspot mutations (the most common being E545K and H1047R),9 conferring constitutive activation of the kinase. Because of these mutations, PI3Kα was regarded as a promising target for anticancer therapeutics and has attracted interest in drug research leading to the © XXXX American Chemical Society

development of specific inhibitors currently in the clinic to treat solid tumors harboring the mutations.10 More recently, the PI3Kβ isoform was found to be involved in the phosphorylation of AKT in PTEN-deficient or deleted cell lines.11,12 This discovery has initiated the search for selective PI3Kβ inhibitors, which have been found from a variety of approaches, including pharmacophore-directed design,12 TGX221 rescaffolding,13−17 and structure-based optimization of a high throughput screening lead.18−20 In this paper, we aim to understand a particular series of PI3Kβ-selective small molecule pyrimidone-indoline-amide inhibitors with unintuitive SAR,20 of which one molecule in the series reached the clinic. Specifically, efforts to improve the solubility of lead compound 2-[2-(2,3-dihydro-indol-1-yl)-2oxo-ethyl]-6-morpholin-4-yl-3H-pyrimidin-4-one (1), which was highly active toward both PI3Kβ and PI3Kδ, resulted in unexpected and advantageous improvements in selectivity toward PI3Kβ. Indeed, the site of substitution was chosen because it was directed toward solvent and was not expected to modulate binding activity to either PI3Kβ or PI3Kδ. Furthermore, the binding sites of PI3Kβ or PI3Kδ are highly Received: October 23, 2015

A

DOI: 10.1021/acs.jcim.5b00641 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX

Article

Journal of Chemical Information and Modeling

Figure 1. (A) Superposition of X-ray structures of PI3Kβ (PDB ID 4BFR, cyan) and PI3Kδ (PDB ID 4V0I, orange) with the ligand 3(S) shown as green spheres. The glycine-rich loop (GRL) is above the ligand, and the hinge is to the left of the ligand. Both 4BFR and 4V0I are cocrystallized with ligand 3(S). (B) Surface of PI3Kδ colored by residue identity to PI3Kβ with residue differences shown in orange. Directly above the ligand are residues 729Arg/772Tyr in PI3Kβ and 708Lys/751Phe in PI3Kδ. The orange on the upper left side of the image is 769Lys/771Lys/783Val in PI3Kβ and 748Gln/750Thr/762Met in PI3Kδ, which are at the beginning/end of the glycine-rich loop (GRL). Finally, 856Asp (PI3Kβ) and 836Asn (PI3Kδ) are in orange in the bottom left of the image. This residue position is involved in the key water network that forms the basis of the selectivity described in this work. Residues within 6 Å of the ligand have 81% sequence identity and 92% similarity.

to combine water sampling/energetics with docking programs.47,48 More recently, WaterMap was shown to accurately characterize the differences in thermodynamics (entropy, enthalpy, and free energy) associated with variations in aryl sulfonamide inhibitors binding to carbonic anhydrase II (CAII), where the modifications to the ligands were pointing toward solvent.49,50 Such calculations differ from previous applications of WaterMap in that the changes in binding energies could not be accurately determined by solvent displacement energetics based on a single apo WaterMap calculationin such cases, it is essential to model both solvent displacement and solvent rearrangement upon binding. In the work presented here, we follow the protocol described in Snyder et al.50 and Breiten et al.,49 which involves running WaterMap simulations with each of the ligands present and then integrating over the volume of solvent within a fixed distance from the ligands. This approach offers a more complete description of the changes in solvent energetics associated with ligand binding, albeit at an added computational expense, as it accounts for both displaced and rearranged water molecules. To understand the unintuitive selectivity differences described above, we ran WaterMap calculations on both PI3Kβ and PI3Kδ with different ligands in the series and compared the energetics of the waters within a fixed volume from the ligands. Crucially, in order to understand the molecular basis of selectivity for the PI3Kβ selective compound 3(S) and related compounds, the simulations had to be run with the ligand present, and energetics were assessed by integrating over all water molecules around the ligand, as described above. This more complete description of binding solvation has previously been shown to explain entropy/ enthalpy compensation and the hydrophobic effect for solvent exposed hydrophobic modifications49−51 and the effect of Hofmeister ions on ligand binding.52 Within this study, there was no need to run WaterMap calculations on the apo enzymes

conservedresidues within 6 Å of the ligand have 81% sequence identity and 92% similarity (see Figure 1). The point of substitution on the ligand studied here is not pointing directly toward any of the side chains with differences between the two structures. Nonetheless, the addition of a methyl at a chiral center in 1 improved selectivity toward PI3Kβ over PI3Kδ, resulting in compound 3(S), which reached the clinic. Indeed, the X-ray structures of compound 3(S) bound to both PI3Kβ and PI3Kδ reveal no direct interactions between the added methyl and either of the proteins.20 To explain the SAR of the compounds in this series, we studied the network of water molecules around the ligand modification, since most other possible explanations for the observed selectivity could be ruled out due to the solventexposed, nonpolar nature of the substitution, the high sequence similarity in the binding sites, and the conserved binding mode in both PI3Kβ and PI3Kδ isoforms. As such, we performed molecular dynamics simulations, solvent clustering, and statistical thermodynamic analysis using WaterMap21,22 to estimate the entropy, enthalpy, and free energy of water molecules around the ligand. WaterMap has been used to predict protein−ligand binding trends for several target classes, including protein kinases,23,24 GPCRs,25 proteases,26 PDZ domains,27 and other targets.28 The resulting energetics from WaterMap can be used to detect regions of unfavorable waters (hot spots)28 and changes in affinity due to water displacement upon binding.25,27,29,30 Additional applications of WaterMap have shown promise in relating binding kinetics to the energy of binding site waters.31−33 Several other computational approaches exist to characterize waters around proteins and ligands, including approaches based on explicit solvent MD (like WaterMap),34−39 Monte Carlo-based sampling,40,41 hybrid explicit/implicit solvent,42 local solvent density around a solute using spatial solute−solvent distribution functions,43−45 structural bioinformatics approaches,46 and ways B


Article

Journal of Chemical Information and Modeling Scheme 1. Synthesis of Compounds 1−7 and Intermediates A and Ba

a

Reagents and conditions: (a) NaOH, THF, rt, 48 h, 100%; (b) EDCI, pyridine, DMF, rt, 16 h, 6−78%.

the placement cannot be determined unambiguously by X-ray density alone. However, because molecular dynamics simulations are sensitive to initial coordinates, we refined the structure with PrimeX59,60 in search of a conformation for Met920 in PI3Kβ that would be consistent between the different structures in the asymmetric unit and with the PI3Kδ conformation. Upon refinement with PrimeX, the crystal structure remained largely unchanged along with the RFree value of 0.28. In addition, after the refinement, Met920 was consistently placed in both PI3Kβ chains in the asymmetric unit and was consistent with the placement of the equivalent residue (Met900) in PI3Kδ. WaterMap Calculations. WaterMap is a molecular dynamics-based method that predicts the locations and thermodynamic properties (entropy, enthalpy, and free energy) of explicit water molecules around a protein. The computational algorithms used by WaterMap and the theoretical basis for the method are fully described elsewhere.21,22 Briefly, WaterMap analyzes the water molecules around the binding site of a protein from many frames of a molecular dynamics trajectory. Regions of high water density (high occupancy) are identified as “hydration sites,” and their corresponding enthalpies and entropies are computed relative to bulk solvent using inhomogeneous solvation theory.61,62 In the work presented here, we follow a protocol similar to that in Snyder et al.50 and Breiten et al.,49 which involves running WaterMap simulations with each of the ligands present and then integrating over the solvent within a fixed distance from the ligands. Performing “holo-WaterMap” calculations like this are much more computationally demanding (a separate WaterMap calculation is needed for each ligand) but offers a more complete description of the changes in solvent energetics associated with ligand binding. In this work we use a distance of 6.5 Å for the integration region, which accounts for the first two shells of water, although the results were statistically indistinguishable for an integration radius in the range of 5.0 Å to 8.0 Å. A Python script called watermap_holo_scoring.py is freely available from Schrödinger (www.schrodinger.com) to perform the volume energy integration of the WaterMap calculation output. Calculations on the apo enzyme were not performed in this work because relative, not absolute, energies between different inhibitors binding to the PI3Kβ and PI3Kδ were of interest.

since the property of interest was selectivity, which we obtained by taking the difference in solvent energetics for a given ligand in each of the PI3Kβ or PI3Kδ structures and then comparing that quantity between different ligands.

■

MATERIALS AND METHODS Compound Synthesis and Characterization. The studied compounds 1−7 were obtained via condensation of intermediate B with the appropriate indolines in the presence of EDCI, as depicted in Scheme 1. Enantiomerically pure 3−7 were obtained either by resolution of the corresponding racemates via chiral chromatography or by condensation of intermediate B with the appropriate enantiomerically pure indolines. Intermediates A and B have been described previously.17−19,22 In Vitro PI3K Enzyme Assay. The biochemical assay was performed at 100 μM ATP concentration, with recombinant human PI3K enzyme isoforms at different concentrations, using phosphatidylinositol 4,5-biphosphate (PIP2) as the substrate. The assay format used was homogeneous time-resolved fluorescence (HTRF), which allows detection of phosphatidylinositol 3,4,5-triphosphate (PIP3) formed as a result of phosphorylation of PIP2 by PI3K isoforms such as α, β, γ, or δ. All measurements were performed at least two times, and the reported values are the average of all experiments. Experimental values were reproducible and tended to be within 2-fold Crystal Structure Preparation. X-ray crystal structures of PI3Kβ (PDB ID 4BFR) and PI3Kδ (PDB ID 4V0I) were prepared with the Protein Preparation Wizard53 in Maestro.54 In short, the H-bond network was optimized by flipping the terminal χ angle for Asn, Gln, and His side chains. Neutral and protonated states of Asp, Glu, and His residues were sampled, and hydroxyl/thiol hydrogens were rotated. Finally, an all-atom minimization with a 0.3 Å heavy-atom RMSD cutoff was performed using the Impref module of Impact55 and the OPLS2005 force field.56−58 These settings were determined to be appropriate for virtual screening structure preparation based on previous work.54 No water molecules were present around the binding site of either structure, and investigation of the electron density did not reveal any density peaks that would be attributable to water molecules around the binding site. The superimposed X-ray structures of PI3Kβ and PI3Kδ are shown in Figure 1, along with the binding site view showing the location of the three residue differences around the ligand mapped onto the molecular surface of PI3Kβ. The crystal structure of PI3Kβ contained two protein chains. The structures were highly similar around the binding site with the exception of Met920, which was in a different rotameric state. Analysis of the crystallographic density revealed no density peak for the terminal methyl of Met920, indicating that

■

RESULTS AND DISCUSSION The motivation of the work presented here is to explain unintuitive SAR and selectivity exhibited by the substituted derivatives of compound 1 toward PI3Kβ over PI3Kδ by studying the thermodynamics of water molecules around the solvent-exposed substitutions. The solvent-exposed nature of C


Article

Journal of Chemical Information and Modeling the substitutions on compound 1, coupled with the highly similar binding sites (see description below, and in Figure 1), make rationalization of the changes in affinity and selectivity challenging by means of traditional modeling tools that focus on direct protein−ligand interactions or ligand energetics (strain, preorganization, or desolvation). The ligand binding mode, as evident in the 4BFR (PI3Kβ) and 4V0I (PI3Kδ) crystal structures, is indistinguishable between the isoforms, ruling out differences in ligand strain or ligand desolvation as primary contributors to the observed selectivity. In addition to understanding the molecular origins of selectivity in this particular system, we hope that this work will provide a framework for the rational design of selective inhibitors where direct contacts with the protein are highly conservedthis problem has long plagued the discovery of kinase-based therapeutics and other targets with highly homologous isoforms. As shown in Figure 1A, the overall folds of PI3Kβ and PI3Kδ are conserved and the binding sites are highly homologous, resulting in conserved interactions (see Figure 1B) for the ligands in this study (Table 1). Specifically, residues 772Tyr/ 751Phe (PI3Kβ/PI3Kδ) in the orange group above the ligand are in the glycine rich loop, and the side chains point away from ligand (closest side chain atom is >5 Å from the ligand and >9

Å from the point of substitution in ligand 1). Also in the orange group above the ligand are 729Arg/708Lys, which are farther away than the previous pair (closest ligand atom is >9 Å), and the side chains are solvent exposed. In the orange group at the top left of the image are 769Lys/748Gln, with the side chains being solvent exposed and the closest distance between the ligand and side chain atom >10 Å. 783Val/762Met are also part of the orange group at the top left of Figure 1 and have a closest atom distance to the ligand of >8 Å. Finally, in the orange region on the bottom left of Figure 1 are 856Asp/836Asn, with a closest distance to the ligand of >6.0 Å. However, the side chains are directed toward the ligand, and as we explain below, these residues are involved in a water network that connects with the ligand and can provide a selectivity handle for this series. Finally, 852Glu/832Asp are also in the orange group in the bottom left of Figure 1, but they are further from the ligand (>8.0 Å) and directed away from the ligand toward bulk solvent. Analysis of direct molecular interactions (van der Waals, electrostatic, H-bonds, etc.) did not reveal any trends with the experimentally determined affinity or selectivity, as might be anticipated based on the above analysis of the residue differences around the ligand. Therefore, we set forth to study an important but frequently overlooked aspect of molecular recognition: the changes in the solvation thermodynamics within the binding site upon complex formation with different ligands. We used WaterMap, as described in the Materials and Methods section, to determine the location and thermodynamic properties (entropy, enthalpy, and free energy) associated with the water molecules surrounding each of the ligands shown in Table 1 when bound to either PI3Kβ or PI3Kδ. Figure 2A and B show the predicted positions and excess free energies of water molecules in the binding sites of PI3Kβ and PI3Kδ bound to compound 1. There are a large number of water molecules present around the ligand in both kinase isoforms, as expectedin general, regions lacking water molecules are very rare, given that nature abhors a vacuum. For the purposes of this discussion, we shall concentrate on a particular conserved water molecule, which we denote as Water #1, that is located near the 2-position of the dihydroindole moiety of compound 1 and was determined in our analysis of the WaterMap results to be a potential source of the observed affinity and selectivity trends (see below). In both PI3Kβ and PI3Kδ, Water #1 is computed to be highly unstable, with similar values for the excess free energy (6.0 and 5.8 kcal/mol in PI3Kβ and PI3Kδ, respectively). The high excess free energy of Water #1 in both kinase isoforms suggests that simply displacing the water molecule, thereby transferring it back to bulk solution, should lead to a gain in binding energy for the ligand. Visual analysis of the three-dimensional structure suggests that compounds with the non-hydrogen R group pointing down in Table 1 (R-down) around the 2-position of the dihydroindole ring are optimally suited for displacing Water #1 (see Table 1 caption for up/down nomenclature; the nonstandard stereochemistry nomenclature is used here because the absolute stereochemical designation changes upon extension of the R-group from ethyl to propyl, and we are primarily interested in the spatial location of the R-group in the binding site). Indeed, WaterMap calculations show the displacement of Water #1 by all R-down enantiomers in Table 1 and a concomitant computed gain in binding affinity toward both targets. Consistent with this observation, we see in Table 1 that all of the R-down enantiomers are highly potent on both

Table 1. IC50 Values and Associated PI3Kβ/PI3Kδ Selectivity for the Pyrimidone Indoline Amide Series Studied in This Worka

compound ID*

R1

R2

R-up/downb substitution

PI3Kβ (nM)

PI3Kδ (nM)

fold selectivity

1 3(S) 3(R) 4(S) 4(R) 5(R) 5(S) 6(R) 6(S) 7(R) 7(S)

H H Me H Et H cPr H iPr H Ph

H Me H Et H cPr H iPr H Ph H

R-up R-down R-up R-down R-up R-down R-up R-down R-up R-down

4 23 6 135 10 381 2 615 4 470 4

28 468 6 1233 11 1610 2 1231 1 1984 5

7.0 20 1.0 9.1 1.1 4.2 1.0 2.0 0.25 4.2 1.25

a

Reported IC50 values are the average of at least two measurements. Individual measurements are provided in the Supporting Information, Table S4. Absolute configuration was determined by single compound crystallization for compounds 4(R), 5(R), and 6(S) (see Supporting Information Table S3 for X-ray single crystal diffraction data) and by protein cocrystallization for compound 7(S) [results not shown]. bIn the text, “R-up” refers to the compounds with the non-H R group in the up position based on this figure, whereas “R-down” refers to the compounds with the non-H R group pointing down. This nonstandard stereochemistry nomenclature has been used in this work because the absolute stereochemical designation changes upon extension of the Rgroup (between ethyl and propyl), and the spatial location of the Rgroup is the critical factor in determining selectivity in this series, not the absolute stereochemical designation. D


Article


Figure 2. Predicted hydration site positions and free energies in (A) PI3Kβ and (B) PI3Kδ with compound 1 bound. Hydration sites are colored by free energy, as computed by WaterMap, with red being unfavorable and green being favorable relative to bulk water. The hydration site referred to as “Water #1” in the text is shown as a larger sphere. Hydration site energies are shown in kcal/mol. For the unsubstituted ligand 1 shown here, the energy of Water #1 is similar between the PI3Kβ and PI3Kδ isoforms.

Figure 3. Energetics of Water #1 with ligands 3(S) (A and B) and 4(S) (C and D) for PI3Kβ (A and C) and PI3Kδ (B and D) The increased destabilization of Water #1 (red sphere) is observed going from PI3Kβ to PI3Kδ, consistent with experimental observations that the (R-up) chirality ligands impart selectivity toward PI3Kβ even with a loss of potency to both PI3Kβ and PI3Kδ. The energy of Water #1 in the presence of unsubstituted compound 1 is shown in Figure 2 and is roughly equienergetic. The selectivity for variants of compound 1 can be explained by the differential destabilization of trapping this water in PI3Kβ versus PI3Kδ.

compounds 3(S) and 4(S) improve the β-isoform-selectivity relative to compound 1in fact, all R-up enantiomers show greater selectivity toward PI3Kβ than their enantiomerically related R-down counterpart. Interestingly, each of the R-up enantiomers bind less tightly to PI3Kβ than compound 1, sometimes significantly so, yet they still yield improvements in selectivity over PI3Kδ. Put another way, the R-up enantiomers

kinase isoforms, maintaining or improving activity relative to compound 1 but not achieving the desired selectivity toward PI3Kβ. While none of the R-down enantiomers improve the isoform selectivity for this series, the R-up enantiomers (the compounds that point the R group “up” as shown on the 2D structure in Table 1) do modulate selectivity. As seen in Table 1, E


Article

Journal of Chemical Information and Modeling of compound 1 variants bind less tightly to both PI3Kβ and PI3Kδ, but the destabilization is more severe in PI3Kδ than PI3Kβ, thereby leading to the observed and desired selectivity. A qualitative explanation for the selective destabilization induced by the R-up compounds can be obtained by examining the results of the WaterMap calculations, in particular examining the differential energetics of Water #1 in PI3Kβ and PI3Kδ. Figure 3 shows the WaterMap results for compounds 3(S) (Figure 3A and B) and 4(S) (Figure 3C and D) bound to PI3Kβ and PI3Kδ, respectively. Two key insights are observed: (1) Increasing the size of the R-up substituent leads to progressively more destabilization of Water #1 in both PI3Kβ and PI3Kδ (i.e., larger groups lead to worse binding due to more destabilization of Water #1). This trend persists for all R-Up enantiomers in Table 1 and explains the general decrease in binding affinity observed with larger substituents. (2) This destabilization of Water #1 upon substitutions in the R-up position is computed to be more significant in PI3Kδ than PI3Kβ, and the degree of destabilization increases for larger groups that trap Water #1 more completely. These two findings offer an explanation for the general increase in PI3Kβ isoform selectivity gained with the R-up enantiomers, which comes at a loss of potency relative to compound 1, albeit a lesser loss in PI3Kβ than PI3Kδ. The comparison between experimental binding energies of the R-up enantiomers and the free energy Water #1 are shown in Figure 4 for each of the ligands in Table 1 for which Water

Table 2. Comparison between Computed and Experimental Binding Free Energies for All Compounds in Table 1a PI3Kβ

a

PI3Kδ

compound

ΔG WM

ΔG exptl.

ΔG WM

ΔG exptl.

1 2 3(S) 3(R) 4(S) 4(R) 5(R) 5(S) 6(R) 6(S) 7(R) 7(S) R2

0.00 0.76 −0.04 −0.45 6.06 0.72 6.65 0.12 4.88 0.22 6.23 −3.30 0.74

0.00 1.92 1.04 0.24 2.09 0.54 2.70 −0.41 2.98 0.00 2.83 0.00

0.00 −1.36 0.84 −3.59 1.87 −3.87 1.86 −3.25 2.65 −3.32 4.16 −3.63 0.80

0.00 1.80 1.67 −0.91 2.24 −0.55 2.40 −1.56 2.24 −1.98 2.53 −1.02

Energies are given in kcal/mol relative to compound 1.

R-up enantiomers, which is why the water eventually evacuates, and is consistent with the experimental binding affinities. While the above analysis qualitatively explains the experimentally observed activity and selectivity variation for the ligands in Table 1, a more quantitative analysis would facilitate comparisons between the PI3K-isoforms and potentially offer a predictive method that could be used for other ligand series and/or other targets. Forming a general approach to compute a quantitative relationship between WaterMap hydration site energetics and binding affinity/selectivity requires a more holistic approach that accounts for all of the hydration thermodynamics within a region around the ligand upon binding, since water networks can involve multiple hydration shells and one does not know a priori which water molecules might be contributing to observed SAR. This can be achieved by integrating (adding) the free energy density of the water molecules within a fixed volume surrounding the ligands in each protein−ligand complexes, as described in the Materials and Methods section. The results of applying this approach to all compounds in this work are presented in Table 2, which shows a strong correlation between the integrated water energetics and the observed binding energies for both PI3K isoforms. In this analysis, we see the general trend in destabilization of the surrounding water network going from the R-down to the R-up stereochemistry. To better understand the structural origins of the observed selectivity, we analyzed the binding site water molecules and nearby binding site residues in both PI3Kβ and PI3Kδ. As noted previously, most of the residues lining the binding site are identical between the isoforms, and the hydration structure was very similar. However, analysis of the water network originating from Water #1 leads to a pair of residues that differ between the isoforms. In PI3Kβ, Asp856 is located ∼7 Å from the nearest atom of compound 3(S) and is connected to Water #1 through a series of intermediate water molecules (Figure 5A). In PI3Kδ, the equivalent residue is Asn836, which is also located ∼7 Å from the ligand and is connected to Water #1 by an alternative network of intermediate water molecules (Figure 5B). The WaterMap analysis suggests that, upon ligand binding and the trapping of Water #1, the charged residue (Asp856) in PI3Kβ is able to more adequately stabilize Water #1 through its network of intervening water molecules than the equivalent neutral residue (Asn836) in PI3Kδ. Indeed, we observe an

Figure 4. Comparison between the experimental binding energies and the free energy of Water #1 for the R-up enantiomers. PI3Kβ is shown in blue, and PI3Kδ is in red. Energies are in kcal/mol. The experimental binding free energy (ΔGexpt) encompasses the total binding energy of the system, whereas the WaterMap free energy (ΔGWM) shown here includes only the energy of Water #1, hence the differences in the magnitude of the energies.

#1 is present. For the compounds with larger substituents (6(S) and 7(S)), the energetics of Water #1 become so unfavorable that it mostly evacuates from the site, so those compounds are not included in Figure 4. However, the energetics of these evacuated regions can be accounted for by a more holistic integration of the total water energetics in the system, as explained below and shown in Table 2. Nonetheless, while Water #1 is not present for the larger R-up enantiomers, we can infer that the energetics are worse than for the smaller F


Article


toward PI3Kβ, even at the expense of losing potency to both PI3Kβ and PI3Kδ. This strategy of preferential destabilization could be a generally effective mechanism for achieving selectivity in other targets, given that the on-target potency is sufficiently high. Additionally, we have shown how integrating the solvent free energy density from a WaterMap calculation can be used to give a more quantitative estimate of the solvation effects of ligand chemical modifications. As computational tools to analyze the thermodynamics of water molecules around proteins and in protein−ligand complexes become more common in computational chemistry applications, we hope that this study will provide a basis for exploring hydration site thermodynamics to gain selectivity and will provide useful ideas to researchers in their pursuit of novel and effective drugs.

Figure 5. Water network connecting Water #1 to (A) Asp856 in PI3Kβ and (B) Asn836 in PI3Kδ with compound 3(S). Distances between the waters are shown next to the dotted lines.

■

ASSOCIATED CONTENT

* Supporting Information S

average of 0.5 more H-bonds to Water #1 from the other water molecules in PI3Kβ versus PI3Kδ, suggesting that the H-bond network is more stable in the PI3Kβ binding site upon hydrophobic modifications to compound 1. As such, Water #1 and its surrounding network of water molecules is more able to tolerate the destabilizing influences of the R-up compounds in PI3Kβ than PI3Kδ, which enclose Water #1 in a more hydrophobic environment, leading to the observed selectivity between the isoforms.

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jcim.5b00641. Details about chemistry (section S-1); biochemistry (section S-2); single crystal diffraction data (section S3); PI3Kδ-Cpd3 crystallization, data collection, and refinement statistics (section S-4); and individual IC50 measurements (section S-5) (PDF)

■

■

AUTHOR INFORMATION

Corresponding Authors

CONCLUSIONS Obtaining selectivity between related proteins is a major challenge in the discovery of new pharmaceutical agents and it is important to explore all conceivable means of obtaining differential activity between related targets. In some instances, selectivity can be obtained through leveraging differences in direct interactions with the protein, such as hydrogen bonds, hydrophobic packing, or building into pockets of different shapes. However, in the case of highly homologous structures, such as the PI3K family of proteins, the opportunity to find such features is rare. Recently, there have been a number of studies that reveal the importance of binding site water molecules in driving protein− ligand affinity and selectivityeven highly homologous proteins can have exploitable differences in solvent structure.23,24,27,63−65 Here, we have expanded on the previous works by quantifying the energetic changes associated with the reorganization of the solvent structure upon ligand binding and comparing the values between two highly homologous targets (PI3Kβ and PI3Kδ). In addition, the mechanism by which selectivity is achieved appears to be somewhat different and rather subtle as compared with previously published examples. In general, the earlier works have found that gains in selectivity could be explained by displacing a water molecule with higher excess free energy in one target than another target. However, in the PI3K example studied here, the water molecule in the regions of the ligand substitutions was comparable in energy between the PI3Kβ and PI3Kδ in the presence of the lead compound 1, and displacing it with modifications to compound 1 led to similar gains in affinity to both β and δ isoforms (i.e., no gains in selectivity). However, it was not the displacement of this water but the differential destabilization of the water molecule upon substitutions that further destabilized this water in PI3Kδ by trapping it in a more hydrophobic environment (see Table 1), thereby producing the preferred selectivity

*E-mail: Laurent.Schio@sanofi.com. *E-mail: [email protected]. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS The authors would like to thank Cécile Delorme, Olivier Courtin, Véronique Charrier, Véronique Lalleman, and MarieFrance Bachelot for their work on the biochemical assays.

■

REFERENCES

(1) Fruman, D. A.; Meyers, R. E.; Cantley, L. C. Phosphoinositide Kinases. Annu. Rev. Biochem. 1998, 67, 481−507. (2) Fan, Q.-W.; Knight, Z. A.; Goldenberg, D. D.; Yu, W.; Mostov, K. E.; Stokoe, D.; Shokat, K. M.; Weiss, W. A. A Dual PI3 Kinase/mTOR Inhibitor Reveals Emergent Efficacy in Glioma. Cancer Cell 2006, 9, 341−349. (3) Maira, S.-M.; Voliva, C.; Garcia-Echeverria, C. Class IA Phosphatidylinositol 3-Kinase: From Their Biologic Implication in Human Cancers to Drug Discovery. Expert Opin. Ther. Targets 2008, 12, 223−238. (4) Ihle, N. T.; Powis, G. The Biological Effects of Isoform-Specific PI3-Kinase Inhibition. Curr. Opin. Drug. Discovery Devel. 2010, 13, 41− 49. (5) Ito, K.; Caramori, G.; Adcock, I. M. Therapeutic Potential of Phosphatidylinositol 3-Kinase Inhibitors in Inflammatory Respiratory Disease. J. Pharmacol. Exp. Ther. 2007, 321, 1−8. (6) Brana, I.; Siu, L. L. Clinical Development of Phosphatidylinositol 3-Kinase Inhibitors for Cancer Treatment. BMC Med. 2012, 10, 161. (7) Norman, P. Selective PI3Kδ Inhibitors, a Review of the Patent Literature. Expert Opin. Ther. Pat. 2011, 21, 1773−1790. (8) Keating, G. M. Idelalisib: A Review of Its Use in Chronic Lymphocytic Leukaemia and Indolent Non-Hodgkin’s Lymphoma. Target Oncol. 2015, 10, 141−151. (9) Samuels, Y.; Wang, Z.; Bardelli, A.; Silliman, N.; Ptak, J.; Szabo, S.; Yan, H.; Gazdar, A.; Powell, S. M.; Riggins, G. J. High Frequency of

G


Article

Journal of Chemical Information and Modeling Mutations of the PIK3CA Gene in Human Cancers. Science 2004, 304, 554−554. (10) Zhao, Y.; Zhang, X.; Chen, Y.; Lu, S.; Peng, Y.; Wang, X.; Guo, C.; Zhou, A.; Zhang, J.; Luo, Y.; et al. Crystal Structures of PI3Kα Complexed with PI103 and Its Derivatives: New Directions for Inhibitors Design. ACS Med. Chem. Lett. 2014, 5, 138−142. (11) Wee, S.; Wiederschain, D.; Maira, S.-M.; Loo, A.; Miller, C.; Stegmeier, F.; Yao, Y.-M.; Lengauer, C.; de Beaumont, R. PTENDeficient Cancers Depend on PIK3CB. Proc. Natl. Acad. Sci. U. S. A. 2008, 105, 13057−13062. (12) Jia, S.; Liu, Z.; Zhang, S.; Liu, P.; Zhang, L.; Lee, S. H.; Zhang, J.; Signoretti, S.; Loda, M.; Roberts, T. M.; Zhao, J. J. Essential Roles of PI(3)K−P110β in Cell Growth, Metabolism and Tumorigenesis. Nature 2008, 454, 776−779. (13) Kim, J.; Hong, S.; Hong, S. Discovery of New AminopyrimidineBased Phosphoinositide 3-Kinase Beta (PI3Kβ) Inhibitors with Selectivity over PI3Kα. Bioorg. Med. Chem. Lett. 2011, 21, 6977−6981. (14) Lin, H.; Erhard, K.; Hardwicke, M. A.; Luengo, J. I.; Mack, J. F.; McSurdy-Freed, J.; Plant, R.; Raha, K.; Rominger, C. M.; Sanchez, R. M.; Schaber, M. D.; Schulz, M. J.; Spengler, M. D.; Tedesco, R.; Xie, R.; Zeng, J. J.; Rivero, R. A. Synthesis and Structure−Activity Relationships of Imidazo[1,2-a]Pyrimidin-5(1h)-Ones as a Novel Series of Beta Isoform Selective Phosphatidylinositol 3-Kinase Inhibitors. Bioorg. Med. Chem. Lett. 2012, 22, 2230−2234. (15) Sanchez, R. M.; Erhard, K.; Hardwicke, M. A.; Lin, H.; McSurdy-Freed, J.; Plant, R.; Raha, K.; Rominger, C. M.; Schaber, M. D.; Spengler, M. D.; et al. Synthesis and Structure−Activity Relationships of 1,2,4-Triazolo[1,5-a]Pyrimidin-7(3h)-Ones as Novel Series of Potent B Isoform Selective Phosphatidylinositol 3-Kinase Inhibitors. Bioorg. Med. Chem. Lett. 2012, 22, 3198−3202. (16) Lin, H.; Schulz, M. J.; Xie, R.; Zeng, J.; Luengo, J. I.; Squire, M. D.; Tedesco, R.; Qu, J.; Erhard, K.; Mack, J. F.; et al. Rational Design, Synthesis, and SAR of a Novel Thiazolopyrimidinone Series of Selective PI3K-Beta Inhibitors. ACS Med. Chem. Lett. 2012, 3, 524− 529. (17) Yu, H.; Moore, M. L.; Erhard, K.; Hardwicke, M. A.; Lin, H.; Luengo, J. I.; McSurdy-Freed, J.; Plant, R.; Qu, J.; Raha, K.; et al. [3a,4]-Dihydropyrazolo[1,5a]Pyrimidines: Novel, Potent, and Selective Phosphatidylinositol-3-Kinase B Inhibitors. ACS Med. Chem. Lett. 2013, 4, 230−234. (18) Certal, V.; Halley, F.; Virone-Oddos, A.; Thompson, F.; FilocheRommé, B.; El-Ahmad, Y.; Carry, J.-C.; Delorme, C.; Karlsson, A.; Abecassis, P.-Y.; Vincent, L.; Bonnevaux, H.; Nicolas, J.-P.; Morales, R.; Michot, N.; Vade, I.; Louboutin, A.; Perron, S.; Doerflinger, G.; Tric, B.; Monget, S.; Lengauer, C.; Schio, L. Preparation and Optimization of New 4-(Morpholin-4-Yl)-(6-Oxo-1,6-Dihydropyrimidin-2-Yl)Amide Derivatives as PI3Kβ Inhibitors. Bioorg. Med. Chem. Lett. 2012, 22, 6381−6384. (19) Certal, V.; Halley, F.; Virone-Oddos, A.; Delorme, C.; Karlsson, A.; Rak, A.; Thompson, F.; Filoche-Rommé, B.; El-Ahmad, Y.; Carry, J.-C.; Abecassis, P.-Y.; Lejeune, P.; Vincent, L.; Bonnevaux, H.; Nicolas, J.-P.; Bertrand, T.; Marquette, J.-P.; Michot, N.; Benard, T.; Below, P.; Vade, I.; Chatreaux, F.; Lebourg, G.; Pilorge, F.; Angouillant-Boniface, O.; Louboutin, A.; Lengauer, C.; Schio, L. Discovery and Optimization of New Benzimidazole- and BenzoxazolePyrimidone Selective PI3Kβ Inhibitors for the Treatment of Phosphatase and Tensin Homologue (PTEN)-Deficient Cancers. J. Med. Chem. 2012, 55, 4788−4805. (20) Certal, V.; Carry, J.-C.; Halley, F.; Virone-Oddos, A.; Thompson, F.; Filoche-Rommé, B.; El-Ahmad, Y.; Karlsson, A.; Charrier, V.; Delorme, C.; Rak, A.; Abecassis, P.-Y.; Amara, C.; Vincent, L.; Bonnevaux, H.; Nicolas, J.-P.; Mathieu, M.; Bertrand, T.; Marquette, J.-P.; Michot, N.; Benard, T.; Perrin, M.-A.; Lemaitre, O.; Guerif, S.; Perron, S.; Monget, S.; Gruss-Leleu, F.; Doerflinger, G.; Guizani, H.; Brollo, M.; Delbarre, L.; Bertin, L.; Richepin, P.; Loyau, V.; Garcia-Echeverria, C.; Lengauer, C.; Schio, L. Discovery and Optimization of Pyrimidone Indoline Amide PI3Kβ Inhibitors for the Treatment of Phosphatase and Tensin Homologue (PTEN)-Deficient Cancers. J. Med. Chem. 2014, 57, 903−920.

(21) Abel, R.; Young, T.; Farid, R.; Berne, B. J.; Friesner, R. A. Role of the Active-Site Solvent in the Thermodynamics of Factor Xa Ligand Binding. J. Am. Chem. Soc. 2008, 130, 2817−2831. (22) Young, T.; Abel, R.; Kim, B.; Berne, B. J.; Friesner, R. A. Motifs for Molecular Recognition Exploiting Hydrophobic Enclosure in Protein Ligand Binding. Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 808− 813. (23) Myrianthopoulos, V.; Kritsanida, M.; Gaboriaud-Kolar, N.; Magiatis, P.; Ferandin, Y.; Durieu, E.; Lozach, O.; Cappel, D.; Soundararajan, M.; Filippakopoulos, P.; Sherman, W.; Knapp, S.; Meijer, L.; Mikros, E.; Skaltsounis, A.-L. Novel Inverse Binding Mode of Indirubin Derivatives Yields Improved Selectivity for DYRK Kinases. ACS Med. Chem. Lett. 2012, 4, 22−26. (24) Robinson, D. D.; Sherman, W.; Farid, R. Understanding Kinase Selectivity through Energetic Analysis of Binding Site Waters. ChemMedChem 2010, 5, 618−627. (25) Higgs, C.; Beuming, T.; Sherman, W. Hydration Site Thermodynamics Explain SARs for Triazolylpurines Analogues Binding to the A2a Receptor. ACS Med. Chem. Lett. 2010, 1, 160−164. (26) Shah, F.; Gut, J.; Legac, J.; Shivakumar, D.; Sherman, W.; Rosenthal, P. J.; Avery, M. A. Computer-Aided Drug Design of Falcipain Inhibitors: Virtual Screening, Structure-Activity Relationships, Hydration Site Thermodynamics, and Reactivity Analysis. J. Chem. Inf. Model. 2012, 52, 696−710. (27) Beuming, T.; Farid, R.; Sherman, W. High Energy Water Sites Determine Peptide Binding Affinity and Specificity of PDZ Domains. Protein Sci. 2009, 18, 1609−1619. (28) Beuming, T.; Che, Y.; Abel, R.; Kim, B.; Shanmugasundaram, V.; Sherman, W. Thermodynamic Analysis of Water Molecules at the Surface of Proteins and Applications to Binding Site Prediction and Characterization. Proteins: Struct., Funct., Genet. 2012, 80, 871−883. (29) Abel, R.; Salam, N. K.; Shelley, J.; Farid, R.; Friesner, R. A.; Sherman, W. Contribution of Explicit Solvent Effects to the Binding Affinity of Small-Molecule Inhibitors in Blood Coagulation Factor Serine Proteases. ChemMedChem 2011, 6, 1049−1066. (30) Kamps, J. J. A. G.; Huang, J.; Poater, J.; Xu, C.; Pieters, B. J. G. E.; Dong, A.; Min, J.; Sherman, W.; Beuming, T.; Matthias Bickelhaupt, F.; Li, H.; Mecinović, J. Chemical Basis for the Recognition of Trimethyllysine by Epigenetic Reader Proteins. Nat. Commun. 2015, 6, 8911. (31) Tran, Q.-T.; Williams, S.; Farid, R.; Erdemli, G.; Pearlstein, R. The Translocation Kinetics of Antibiotics through Porin OmpC: Insights from Structure-Based Solvation Mapping Using WaterMap. Proteins: Struct., Funct., Genet. 2013, 81, 291−299. (32) Pearlstein, R. A.; Sherman, W.; Abel, R. Contributions of Water Transfer Energy to Protein-Ligand Association and Dissociation Barriers: WaterMap Analysis of a Series of P38α Map Kinase Inhibitors. Proteins: Struct., Funct., Genet. 2013, 81, 1509−1526. (33) Pearlstein, R. A.; Hu, Q. Y.; Zhou, J.; Yowe, D.; Levell, J.; Dale, B.; Kaushik, V. K.; Daniels, D.; Hanrahan, S.; Sherman, W.; Abel, R. New Hypotheses About the Structure-Function of Proprotein Convertase Subtilisin/Kexin Type 9: Analysis of the Epidermal Growth Factor Like Repeat a Docking Site Using WaterMap. Proteins: Struct., Funct., Genet. 2010, 78, 2571−2586. (34) Nguyen, C. N.; Kurtzman Young, T.; Gilson, M. K. Grid Inhomogeneous Solvation Theory: Hydration Structure and Thermodynamics of the Miniature Receptor Cucurbit[7]Uril. J. Chem. Phys. 2012, 137, 044101. (35) Huggins, D. J.; Marsh, M.; Payne, M. C. Thermodynamic Properties of Water Molecules at a Protein-Protein Interaction Surface. J. Chem. Theory Comput. 2011, 7, 3514−3522. (36) Cui, G.; Swails, J. M.; Manas, E. S. Spam: A Simple Approach for Profiling Bound Water Molecules. J. Chem. Theory Comput. 2013, 9, 5539−5549. (37) Velez-Vega, C.; McKay, D. J. J.; Kurtzman, T.; Aravamuthan, V.; Pearlstein, R. A.; Duca, J. S. Estimation of Solvation Entropy and Enthalpy Via Analysis of Water Oxygen-Hydrogen Correlations. J. Chem. Theory Comput. 2015, 11, 5090−5102. H


Article

Journal of Chemical Information and Modeling (38) Hu, B.; Lill, M. A. Watsite: Hydration Site Prediction Program with Pymol Interface. J. Comput. Chem. 2014, 35, 1255−1260. (39) Gerogiokas, G.; Southey, M. W. Y.; Mazanetz, M. P.; Hefeitz, A.; Bodkin, M.; Law, R. J.; Michel, J. Evaluation of Water Displacement Energetics in Protein Binding Sites with Grid Cell Theory. Phys. Chem. Chem. Phys. 2015, 17, 8416−8426. (40) Michel, J.; Tirado-Rives, J.; Jorgensen, W. L. Prediction of the Water Content in Protein Binding Sites. J. Phys. Chem. B 2009, 113, 13337−13346. (41) Michel, J.; Tirado-Rives, J.; Jorgensen, W. L. Energetics of Displacing Water Molecules from Protein Binding Sites: Consequences for Ligand Optimization. J. Am. Chem. Soc. 2009, 131, 15403− 15411. (42) Bayden, A. S.; Moustakas, D. T.; Joseph-McCarthy, D.; Lamb, M. L. Evaluating Free Energies of Binding and Conservation of Crystallographic Waters Using Szmap. J. Chem. Inf. Model. 2015, 55, 1552−1565. (43) Truchon, J.-F.; Pettitt, B. M.; Labute, P. A Cavity Corrected 3DRISM Functional for Accurate Solvation Free Energies. J. Chem. Theory Comput. 2014, 10, 934−941. (44) Imai, T.; Kovalenko, A.; Hirata, F. Solvation Thermodynamics of Protein Studied by the 3D-RISM Theory. Chem. Phys. Lett. 2004, 395, 1−6. (45) Misin, M.; Fedorov, M. V.; Palmer, D. S. Communication: Accurate Hydration Free Energies at a Wide Range of Temperatures from 3D-RISM. J. Chem. Phys. 2015, 142, 091105. (46) Fernández, A.; Scott, R. Dehydron: A Structurally Encoded Signal for Protein Interaction. Biophys. J. 2003, 85, 1914−1928. (47) Forli, S.; Olson, A. J. A Force Field with Discrete Displaceable Waters and Desolvation Entropy for Hydrated Ligand Docking. J. Med. Chem. 2012, 55, 623−638. (48) Ross, G. A.; Morris, G. M.; Biggin, P. C. Rapid and Accurate Prediction and Scoring of Water Molecules in Protein Binding Sites. PLoS One 2012, 7, e32036. (49) Breiten, B.; Lockett, M. R.; Sherman, W.; Fujita, S.; Al-Sayah, M. H.; Lange, H.; Bowers, C. M.; Heroux, A.; Krilov, G.; Whitesides, G. M. Water Networks Contribute to Enthalpy/Entropy Compensation in Protein-Ligand Binding. J. Am. Chem. Soc. 2013, 135, 15579−15584. (50) Snyder, P. W.; Mecinović, J.; Moustakas, D. T.; Thomas, S. W., III; Harder, M.; Mack, E. T.; Lockett, M. R.; Héroux, A.; Sherman, W.; Whitesides, G. M. Mechanism of the Hydrophobic Effect in the Biomolecular Recognition of Arylsulfonamides by Carbonic Anhydrase. Proc. Natl. Acad. Sci. U. S. A. 2011, 108, 17889−17894. (51) Lockett, M. R.; Lange, H.; Breiten, B.; Heroux, A.; Sherman, W.; Rappoport, D.; Yau, P. O.; Snyder, P. W.; Whitesides, G. M. The Binding of Benzoarylsulfonamide Ligands to Human Carbonic Anhydrase Is Insensitive to Formal Fluorination of the Ligand. Angew. Chem., Int. Ed. 2013, 52, 7714−7717. (52) Fox, J. M.; Kang, K.; Sherman, W.; Héroux, A.; Sastry, G. M.; Baghbanzadeh, M.; Lockett, M. R.; Whitesides, G. M. Interactions between Hofmeister Anions and the Binding Pocket of a Protein. J. Am. Chem. Soc. 2015, 137, 3859−3866. (53) Sastry, G. M.; Adzhigirey, M.; Day, T.; Annabhimoju, R.; Sherman, W. Protein and Ligand Preparation: Parameters, Protocols, and Influence on Virtual Screening Enrichments. J. Comput.-Aided Mol. Des. 2013, 27, 221−234. (54) Maestro, V9.3; Schrödinger, Inc.: Portland, OR, 2012. http:// www.schrodinger.com/. (55) Banks, J. L.; Beard, H. S.; Cao, Y.; Cho, A. E.; Damm, W.; Farid, R.; Felts, A. K.; Halgren, T. A.; Mainz, D. T.; Maple, J. R.; Murphy, R.; Philipp, D. M.; Repasky, M. P.; Zhang, L. Y.; Berne, B. J.; Friesner, R. A.; Gallicchio, E.; Levy, R. M. Integrated Modeling Program, Applied Chemical Theory (IMPACT). J. Comput. Chem. 2005, 26, 1752−1780. (56) Jorgensen, W. L.; Tirado-Rives, J. The OPLS Potential Function for Proteins. Energy Minimizations for Crystals of Cyclic Peptides and Crambin. J. Am. Chem. Soc. 1988, 110, 1657−1666. (57) Kaminski, G. A.; Friesner, R. A.; Tirado-Rives, J.; Jorgensen, W. L. Evaluation and Reparametrization of the OPLS-Aa Force Field for

Proteins Via Comparison with Accurate Quantum Chemical Calculations on Peptides. J. Phys. Chem. B 2001, 105, 6474−6487. (58) Shivakumar, D.; Williams, J.; Wu, Y.; Damm, W.; Shelley, J.; Sherman, W. Prediction of Absolute Solvation Free Energies Using Molecular Dynamics Free Energy Perturbation and the OPLS Force Field. J. Chem. Theory Comput. 2010, 6, 1509−1519. (59) Primex, V1.9; Schrödinger, Inc.: Portland, OR, 2012. http:// www.schrodinger.com/. (60) Bell, J. A.; Cao, Y.; Gunn, J. R.; Day, T.; Gallicchio, E.; Zhou, Z.; Levy, R.; Farid, R. Primex and the Schrödinger Computational Chemistry Suite of Programs. International Tables for Crystallography 2012, F18, 534−538. (61) Lazaridis, T. Inhomogeneous Fluid Approach to Solvation Thermodynamics. 2. Applications to Simple Fluids. J. Phys. Chem. B 1998, 102, 3542−3550. (62) Lazaridis, T. Inhomogeneous Fluid Approach to Solvation Thermodynamics. 1. Theory. J. Phys. Chem. B 1998, 102, 3531−3541. (63) Knegtel, R.; Robinson, D. D. A Role for Hydration in Interleukin-2 Inducible T Cell Kinase (ITK) Selectivity. Mol. Inf. 2011, 30, 950−959. (64) Newman, A. H.; Beuming, T.; Banala, A. K.; Donthamsetti, P.; Pongetti, K.; LaBounty, A.; Levy, B.; Cao, J.; Michino, M.; Luedtke, R. R.; Javitch, J. A.; Shi, L. Molecular Determinants of Selectivity and Efficacy at the Dopamine D3 Receptor. J. Med. Chem. 2012, 55, 6689− 6699. (65) Brodney, M. A.; Barreiro, G.; Ogilvie, K.; Hajos-Korcsok, E.; Murray, J.; Vajdos, F.; Ambroise, C.; Christoffersen, C.; Fisher, K.; Lanyon, L.; Liu, J.; Nolan, C. E.; Withka, J. M.; Borzilleri, K. A.; Efremov, I.; Oborski, C. E.; Varghese, A.; O’Neill, B. T. Spirocyclic Sulfamides as B-Secretase 1 (BACE-1) Inhibitors for the Treatment of Alzheimer’s Disease: Utilization of Structure Based Drug Design, WaterMap, and CNS Penetration Studies to Identify Centrally Efficacious Inhibitors. J. Med. Chem. 2012, 55, 9224−9239.

I


Differential Water Thermodynamics Determine ... - ACS Publications

Recommend Documents