Article pubs.acs.org/jmc
Passive Membrane Permeability in Cyclic Peptomer Scaffolds Is Robust to Extensive Variation in Side Chain Functionality and Backbone Geometry Akihiro Furukawa,†,‡ Chad E. Townsend,† Joshua Schwochert,† Cameron R. Pye,† Maria A. Bednarek,§ and R. Scott Lokey*,† †
Department of Chemistry and Biochemistry, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California 95064, United States ‡ Modality Research Laboratories, Daiichi Sankyo Co., Ltd., 1-2-58 Hiromachi, Shinagawa-ku, Tokyo 140-8710, Japan § Department of Antibody Discovery & Protein Engineering, Medimmune Ltd., Cambridge CB21 6GH, United Kingdom S Supporting Information *
ABSTRACT: Synthetic and natural cyclic peptides provide a testing ground for studying membrane permeability in nontraditional drug scaffolds. Cyclic peptomers, which incorporate peptide and N-alkylglycine (peptoid) residues, combine the stereochemical and geometric complexity of peptides with the functional group diversity accessible to peptoids. We synthesized cyclic peptomer libraries by splitpool techniques, separately permuting side chain and backbone geometry, and analyzed their membrane permeabilities using the parallel artificial membrane permeability assay. Nearly half of the side chain permutations had permeability coefficients (Papp) > 1 × 10−6 cm/s. Some backbone geometries enhanced permeability due to their ability to form more stable intramolecular hydrogen bond networks compared with other scaffolds. These observations suggest that hexameric cyclic peptomers can have good passive permeability even in the context of extensive side chain and backbone variation, and that high permeability can generally be achieved within a relatively wide lipophilicity range.
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INTRODUCTION Antibodies and other large molecules can be selected to achieve high affinity against virtually any biological target of interest, but their inability to cross cell membranes limits their therapeutic application to extracellular targets. Conversely, while most small molecule drugs are cell permeable, they generally lack the size or complexity to inhibit therapeutic targets that lack well-defined binding pockets, such as protein− protein interactions.1 The chemical space between biologics and small molecules is considered a new frontier in drug discovery, populated by compounds with drug-like passive cell permeability but whose molecular weights (MW) place them outside the range prescribed by common ADME predictors such as Lipinski’s Rule of Five.2 These “beyond Rule of Five” (bRo5) molecules, exemplified by cyclic peptide natural products such as cyclosporine A as well as a variety of model systems inspired by natural products, provide potential guideposts for mapping the factors that constrain ADME properties in this space. Previously, we reported a model system based on the cyclic hexapeptide sequence cyclo[(Leu)4-Pro-Tyr],3 which has been used to probe the impact of stereochemistry,4 N-methylation,4 α-methylation,5 side chain variation,4b,6 and conformational flexibility7 on properties such as passive membrane perme© 2016 American Chemical Society
ability, proteolytic and microsomal stability, and oral bioavailability. These studies reveal that cyclization in this and similar systems enhances membrane permeability in large part by stabilizing intramolecular hydrogen bonding (IMHB), which reduces the net energetic cost of backbone amide desolvation. Cyclization alone, however, does not ensure passive membrane permeability.4a,8 Backbone features such as amide N-methylation are often found in highly permeable cyclic peptides, serving both to stabilize nonpolar conformations as well as eliminate polar NH groups that cannot participate in IMHB. Relative stereochemistry in the backbone can also have a dramatic effect on membrane permeability.4,8,9 Depending on the ring size and presence and location of constrained (e.g., Pro) and/or flexible (e.g., Gly) residues, stereochemistry impacts lipophilicity through conformational effects (i.e., by influencing patterns of IMHB) or by direct steric shielding of polar groups by nearby side chains.10 For the cell permeable and moderately orally bioavailable cyclic peptide 1 (1NMe3, F = 28%),3 we found that substituting a single side chain with various natural and nonnatural amino acids had a profound effect on cell permeability Received: August 17, 2016 Published: October 3, 2016 9503
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and oral bioavailability, an effect that correlated with the side chain’s lipophilicity.6 In a more extensive study varying side chains as well as scaffold geometry (with respect to Nmethylation and stereochemistry), a positive correlation was observed between lipophilicity and permeability, although beyond a certain point, permeability decreased with increasing lipophilicity, presumably due to decreasing water solubility.4b On the hydrophilic end of the continuum, charged side chains such as Lys and Asp, and even polar, neutral side chains such as Ser, significantly impede passive permeability, at least in cyclic hexapeptide systems.4b,6 Indeed, cyclic peptide natural products that are known to be passively permeable contain mostly aliphatic, non-hydrogenbonding side chains.11 Although there is greater side chain variety among the natural products, the palette of lipophilic, proteinogenic side chains is quite limited compared to the vast repertoire of functionality that is synthetically accessible. This raises the question, to what extent can more functionally rich, drug-like side chains be incorporated into permeable cyclic peptide scaffolds while maintaining good permeability? We recently reported a series of hybrid macrocycles containing both peptide and N-alkylglycine (peptoid) residues.12 These cyclic “peptomers”13 offer potential benefits over both all-peptide and all-peptoid scaffolds. Peptoid units are derived from primary amine building blocks, which are far more diverse than commercially available amino acid building blocks.14 As a consequence, greater functional group variety can be easily incorporated into cyclic peptomers compared to cyclic peptides. Furthermore, cyclic peptomers can access lipophilic conformations driven by IMHB between their backbone carbonyl groups and NH groups,12 while all-peptoid macrocycles cannot. Cyclic peptomers have been applied in a variety of therapeutic contexts, for example, as bacterial quorum sensing modulators,15 melanocortin receptor 4 agonists,16 inhibitors of the polo-box domain of polo-like kinase 1,17 and histone deacetylase inhibitors18 among others.19 In our continuing efforts to investigate the combined effects of side chain functionality, backbone N-methylation, and stereochemistry on passive membrane permeability in bRo5 macrocycles, we synthesized a series of cyclic peptomer scaffolds that included diverse peptoid side chains. We found that most of the variants had moderate to good passive permeability (>1 × 10−6 cm/s), and that the major permeability determining factor was overall lipophilicity rather than stereochemistry or N-methylation, although MW also had a significant effect on permeability independent of lipophilicity. These observations suggest that cyclic peptomers represent a vast, untapped chemical space within which to design passively permeable macrocycles for therapeutic applications, and they provide further insight into the factors that govern passive permeability outside the Rule of Five.
Figure 1. Design of Library 1. (A) Structure of previously reported permeable cyclic peptide 1 and cyclic peptomer 2. (B) Library 1 was designed by permuting peptide and peptoid side chains based on the scaffold 2.
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RESULTS Design of Library 1: Permuting Side Chains on a Single Scaffold. We began with the scaffold based on 2 (L2Y6N) (Figure 1A), a hexameric cyclic peptomer with two peptoid units and good passive permeability (7.2 × 10−6 cm/s) in low-efflux Madin-Darby canine kidney (LE-MDCK) epithelial cells,12 slightly higher than that of the parent cyclic peptide 1 (Figure 1A). The Library 1 design was (Figure 1B) based on the cyclic peptomer 2, in which each of the two peptoid positions, R6 and R2, was diversified with a different set of amines (A01−A10 and A11−A20, respectively). In addition,
the peptide residue at R1 was varied to include side chains of varying size and lipophilicity: Ala, Leu, Phe, and 2naphthylalanine (2-Nal). These substitutions yielded a total of 400 permutations, which were divided into 10 sublibraries (1.1−1.10) defined by the R6 side chain (Figure 1B). The 400 member Library 1 was designed to give each member a unique exact mass within each sublibrary, facilitating analysis of the passive permeability data by LC-MS. The ultrahigh-performance liquid chromatography (UHPLC) separation coupled with analysis by high-resolution Fourier transform mass spectrometry (Orbitrap) allowed us to identify and 9504
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Figure 2. PAMPA results of Library 1. (A) LogPapp values are plotted against ALogP. Each spot represents a compound sized by % recovery (as measured by the difference in concentration of the analyte in the donor well prior to running PAMPA compared to the combined concentration in the donor and acceptor wells after completion of the PAMPA run). The purple line represents Papp: 1 × 10−6 cm/s. In this scatter plot, 30 compounds with large variation (average of Papp < standard deviation of Papp) were removed. (B) LogPapp values are plotted against ALogP in each sublibrary. The purple lines represent Papp: 1 × 10−6 cm/s. The structures of R6 are shown above each graph. (C) All 400 compounds were divided into five groups of 80 compounds each according to MW (low MW, 608.8−727.9; mid-low MW, 729.0−770.0; medium MW, 772.0−807.0; midhigh MW, 807.0−851.0; high MW, 851.1−944.2). The permeability coefficients of the top 20th percentile permeable compounds in each MW group are displayed in box plots, which summarize the distribution of data by five numbers; minimum, first quartile, median, third quartile, and maximum. (D) Plot of LogPapp vs ALogP is colored by the MW-based group.
Membrane Permeability of Library 1. Passive permeabilities were measured for all sublibraries using the parallel artificial membrane permeability assay (PAMPA),22 which measures diffusion across a solution of 1% lecithin in ndodecane sandwiched in a filter disc separating two aqueous compartments (the donor and acceptor wells). In a previous report, we determined permeabilities of cyclic peptides from complex mixtures using a combination of LC-MS and deconvolution by resynthesis.23 Here, we designed the library so that each member had a unique molecular formula, allowing us to calculate permeability coefficients (Papp) for all 40 members contained within each sublibrary (Table S1). The relationship between experimental permeabilities and ALogP followed a binomial distribution with a maximum at AlogP ∼ 3 (Figure 2A). Almost half the compounds in the
quantify all 40 members of each sublibrary mixture as separate pools. Library 1 was also designed to cover a wide lipophilicity and MW range. To quantify lipophilicity, we used the calculated octanol−water partition coefficient “ALogP”.20 Like the more familiar “cLogP”, ALogP is a regression model derived from experimental partition coefficients from a training set of thousands of small molecules. However, unlike cLogP, which is based on molecular fragments and a corresponding set of correction factors, ALogP is based on typed atoms and has been shown to be more accurate than cLogP for molecules with >45 atoms.21 The ALogP values varied from −0.56 to 7.54, and MW varied from 608.8 to 944.2 (Figure S1). The library was synthesized by split-pool SPPS using the appropriate primary amines and Fmoc-protected amino acids (Scheme S1). 9505
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library (194 in 400) exceeded 1 × 10−6 cm/s; orally bioavailable small molecule drugs propranolol and warfarin have been reported to display Papp values of 7.9 × 10−6 and 1.3 × 10−6 cm/s, respectively, under the same conditions.24 We used propranolol as a positive control, which showed a Papp of 9.1 × 10−6 cm/s in our experiment. In the side-chain-based analyses, the scatter plots of LogPapp versus ALogP described similar binomial distributions (Figure 2B and Figures S6 and S7). This suggested that side chain lipophilicity was roughly additive and was the major permeability determining factor in these compounds. The highest overall permeability values were for compounds in the ALogP range from 2 to 4. Of the 179 compounds within this ALogP range, 154 compounds had permeabilities greater than 1 × 10−6 cm/s. By contrast, out of 221 compounds outside of this ALogP range, only 40 compounds had permeability greater than 1 × 10−6 cm/s. However, none of the compounds had a Papp value greater than 16 × 10−6 cm/s (LogPapp −4.8), which was close to the aqueous boundary layer (ABL) limit25 of our PAMPA conditions (LogPapp −4.5, estimated from in-house unpublished data). Compounds with ALogP values above 4 showed low % recovery due to sequestration into the membrane or to the walls of the apparatus (or both). Beyond ALogP ∼5, the % recovery appeared to increase again, possibly due to the formation of colloidal aggregates26 that are not only membrane impermeable but also (because of their size) incapable of adsorption or sequestration into the lipid compartment. If these aggregates do not settle during the course of the experiment, an increase in recovery would be seen. These types of suspensions have been observed for very lipophilic compounds and are known to give rise to anomalous bioactivity results such as bell-shaped dose− response curves. The PAMPA results also showed a correlation between permeability and MW. We sorted the 400 compounds by MW and divided the library into five groups of 80 compounds each. For each MW group, the compounds were sorted by permeability, and a box plot was generated of compounds in the top 20th percentile within each group (Figure 2C). Also, the scatter plot of LogPapp versus ALogP was colored by MW groups (Figure 2D), in which only 3 out of 5 MW group were shown for simplicity. The mean permeability of the top 20th percentile decreased with increasing MW. However, even in the high MW category (MW 851.1−944.2), most compounds in the top 20th percentile had Papp values greater than 1 × 10−6 cm/s. Most of these permeable compounds have ALogP values between 2 and 4, while their median values increased with increasing MW (low MW, 2.81; mid-low MW, 2.88; medium MW, 3.27; mid-high MW, 3.57; high MW, 3.73). As shown in Figure 2D, the highest permeability coefficients decreased and permeable ALogP range shifted to the lipophilic region along with increasing MW. Design of Library 2: Permuting Backbone Stereochemistry and N-Methylation. To investigate the effect of backbone stereochemistry and N-methylation on membrane permeability in the context of side chain variation, we designed Library 2 (Figure 3) in which three of the four stereogenic centers were permuted, generating eight diastereomeric sublibraries (2.1−2.8). The amide at Leu3 was also varied (NMe or NH). Peptoid side chains R2 (A12, A14, A15) and R6 (A01, A04, A08) and amino acid side chain R1 (Ala, Phe) were permuted, yielding 36 compounds for each diastereomeric sublibrary (18 for Leu3[NMe] and 18 for Leu3[NH]) (Scheme
Figure 3. Design of Library 2. Library 2 was designed by permuting scaffold stereochemistry, N-methylation at Leu3, and side chain functional groups. The table represents the stereoconfiguration of amino acids in each sublibrary.
S2). The scaffold 2.2 (Leu3[NMe]) in this library has the same backbone configuration as the scaffold used in Library 1. These compounds spanned an ALogP range from 0.46 to 5.00 and a MW range from 606.8 to 831.0, with each compound having a unique accurate mass within its sublibrary to facilitate analysis. Membrane Permeability of Library 2. For seven out of the eight sublibraries from Library 2, each of the 36 expected products showed a single peak in the extracted ion chromatogram corresponding to its accurate mass. For sublibrary 2.3, many of the products showed multiple peaks, which we attributed to a combination of epimerization during cyclization and the presence of multiple conformers. Based on previous studies, we tentatively attribute the non-epimeric side products as cis−trans amide rotamers, which can be separable on the HPLC time scale in cyclic peptomers and N-methylated peptides (Figure S5). Thus, we calculated permeability parameters for members in sublibrary 2.3 based on only the main peaks, ruling out the contribution of minor peaks. Experimental PAMPA LogPapp versus calculated ALogP values were plotted separately for each sublibrary based on N-methylation at the Leu3 amide (Figure 4A). As with Library 1, each sublibrary of Library 2 described a binominal distribution. Contrary to the well-established strong dependence of permeability on N-methylation and stereochemistry in cyclic peptides, we were somewhat surprised to find a significant number of permeable compounds in both NMe and NH series for all eight sublibraries. However, there were 9506
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conformational effects or more directly by orienting side chains to shield polar groups in the molecule.23 To investigate the degree of IMHB in these cyclic peptomers and determine whether the differences observed between sublibraries in Library 2 could be corroborated with pure compounds, we synthesized NH and NMe variants of diastereomeric scaffolds 2.2 and 2.4, with the stereochemistry of 2.2 being the same as that of Library 1 (Figure 5A). The 1H NMR spectrum of 11a (2.2−02Me) in CDCl3 showed four amide protons, suggesting two conformations in a ratio of approximately 1:1. 12a (2.4− 02Me) showed only two amide protons in a single conformation. 11b (2.2−02H) and 12b (2.4−02H) also
Figure 4. PAMPA results of Library 2. (A) LogPapp are plotted against AlogP in each sublibrary. Red bubbles represent X = Me groups, and gray bubbles represent X = H groups, sized by % recovery. The purple lines represent the Papp = 1 × 10−6 cm/s. Three compounds with large variation (average of Papp < standard deviation of Papp) were removed from the analysis. (B) Permeability coefficients of sublibraries 2.2 and 2.4, split into X = Me and X = H, are displayed in the box plots, which split the distribution of data into five values; minimum, first quartile, median, third quartile, and maximum.
still differences among the sublibraries in terms of overall permeability and the optimal ALogP range within which the most permeable species were found. In sublibraries 2.1, 2.2, 2.3, 2.5, and 2.6, the permeability curves of the NMe series were shifted toward lower ALogP values compared to their NH congeners. In contrast, for sublibraries 2.4, 2.7, and 2.8, the NMe and NH curves overlapped, peaking at close to the same ALogP value (∼4). Sublibrary 2.4 had the lowest overall permeability of all the sublibraries. Both the NH and NMe versions of sublibrary 2.4 had lower permeabilities than the same sequences in sublibrary 2.2, which differed in configuration by a single stereocenter (Figure 4B). H−D Exchange Experiments. Stereochemical configuration in cyclic peptides can have a profound effect on permeability,4a,8,9 either by influencing IMHB through global
Figure 5. H−D exchange experiments. (A) These four compounds were individually synthesized and tested in H−D exchange experiments. (B) Amide N−H resonances were monitored as a function of time. Each amide was normalized to the corresponding amide at 0 min. The left graph represents 11a (red circle, 8.53 ppm; red triangle, 7.58 ppm; red square, 7.49 ppm; red asterisk, 7.30 ppm), which showed two conformations in an approximate 1:1 ratio, and 11b (gray circle, 7.77 ppm; gray triangle, 7.46 ppm). The right graph represent 12a (red circle, 7.75 ppm; red triangle, 7.54 ppm) and 12b (gray circle, 7.82 ppm; gray triangle, 7.48 ppm). The third amide protons (6.26 ppm for 11b and 6.04 ppm for 12b) disappeared immediately after adding the mixture of acetic acid-d4 and methanol-d4. (C) Heat map represents the time required for more than 50% protons exchanged to deuteriums, which were calculated by linear approximation between each two data points across the 50% line of the normalized intensity. 9507
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Figure 6. Caco-2 cell permeability. (A) These eight compounds were individually synthesized and tested in Caco-2 permeability. (B) Blue bars represent the membrane permeability coefficients calculated from PAMPA on Library 1 experiment (n = 3). The green bars represent Caco-2 cell permeability coefficients (apical to basal) using individual compounds (n = 2). The orange bars represent Caco-2 cell permeability coefficients (apical to basal) using individual compounds (n = 2) in the presence of verapamil as a P-gp inhibitor. The error bars represent the standard deviations. (C) Caco-2 cell permeability coefficients are plotted against PAMPA permeability coefficients. The green triangles represent the Caco-2 assay performed without P-gp inhibitor. The orange triangles represent the Caco-2 assay performed with P-gp inhibitor. The asterisks represent propranolol, whose Caco-2 permeabilities were measured with P-gp inhibitor (orange) and without P-gp inhibitor (green). The green dotted line represents a regression line for permeability data set (ruling out propranolol) without P-gp inhibitor. The orange dotted line represents a regression line for permeability data set (including propranolol) with P-gp inhibitor.
phase column chromatography. They exhibited Caco-2 permeability coefficients from 0.67 × 10−6 to 3.9 × 10−6 cm/ s (Figure 6B, Table S3), which showed a linear correlation with PAMPA permeability coefficients (slope = 1.01, R2 = 0.90) (Figure 6C). However, the values were smaller than expected based on propranolol (Caco-2, 27 × 10−6 cm/s; PAMPA, 9.1 × 10−6 cm/s). Suspecting the involvement of efflux proteins, we conducted the Caco-2 in the presence of the P-glycoprotein (Pgp) inhibitor verapamil. The Caco-2 permeabilities were significantly improved (Papp = 6.4 × 10−6 to 21.1 × 10−6 cm/ s) in the presence of verapamil, with a linear correlation between Caco-2 and PAMPA that now included propranolol (slope = 0.79, R2 = 0.77) (Figure 6C). These results revealed cyclic peptomers were not only membrane permeable but also cell permeable with a potential risk as P-gp substrates. However, it is noteworthy that all eight compounds showed higher Caco-2 permeability than the orally bioavailable atenolol (Papp = 0.22 × 10−6 cm/s) without P-gp inhibitor.
showed three amide protons, indicating a single conformation for each of these compounds. We investigated the H−D exchange rates of the four compounds in CDCl3, upon addition of 1:9 acetic acid-d4 in methanol-d4 (5%) (Figure 5B). All four amide protons of 11a remained unexchanged over 120 min. In contrast, both amide protons of 12a exchanged to deuterium rapidly, disappearing nearly completely within 30 min. Two of the amide protons of 11b and 12b exchanged moderately quickly, while one amide proton in each of these compounds disappeared completely within 1 min. Between the two X = H compounds, on average, the NH protons of 11b were more protected from exchange than those of 12b. These results suggest that N-methylation decreases solvent exposure of NH groups in the more permeable scaffold 2.2, most likely by enhancing IMHB. At the same time, N-methylation appears to increase NH solvent exposure in the less permeable scaffold 2.4, possibly by destabilizing IMHB relative to the non-N-methylated parent compound. Cell Permeability. We synthesized a selection of compounds from Library 1 and evaluated their cell permeabilities in Caco-2 cells.27 We chose eight compounds (Figure 6A) with diverse functional side chains, MW, and ALogP values, which were all successfully synthesized by the same method used for library synthesis and purified by reverse-
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DISCUSSION We measured passive membrane permeabilities of complex library mixtures using high-resolution mass spectrometry and UHPLC. This allowed accurate quantitation down to subnanomolar concentrations, while the mass accuracy allowed unambiguous identification of all 40 members of each 9508
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LogPapp/ALogP curve for scaffold 2.4 (Leu3NMe) virtually overlapped with that of 2.4 (Leu3NH). Most of the cyclic peptomers in this study were quite permeable as long as their overall lipophilicities fell within the appropriate ALogP range, regardless of their specific side chain compositions. This range will likely shift for different scaffolds or with compounds that include hydrogen bond donors on the side chains. Nonetheless, among scaffolds with some degree of favorable IMHB, permeability can be controlled essentially by tuning lipophilicity at one or more side chains. For small molecules, much is known about how structural changes impact permeability, clearance, toxicity, and so on, and the challenge of medicinal chemistry is manifesting those changes while maintaining or improving biological activity. Here, we show that passive permeability in cyclic peptomers generally tracks with overall lipophilicity, and that inherent permeability at the scaffold (i.e., conformational) level widens the lipophilicity window within which good permeability can be achieved. Additional studies aimed at, for example, metabolic clearance, should help further define the potential of this chemical space with respect to drug design.
sublibrary. We were thus able to examine the permeabilities of all library members without the need to deconvolute by resynthesis of individual compounds. In principle, one could analyze libraries of even greater complexity, for example, using longer HPLC gradients or additional mass spectrometric separation strategies (e.g., by adding separation by ion mobility). PAMPA permeabilities fit a binomial distribution with respect to the lipophilic descriptor ALogP. The positive correlation on the left side of this curve follows the classical Overton model 28 that relates permeation rate to the equilibrium constant of partitioning into the bilayer times the diffusion coefficient through the bilayer. Beyond ALogP ∼ 3, increasing lipophilicity in Library 1 led to a decrease in effective permeability. The decrease in Papp for compounds with lipophilicities above ALogP ∼ 3 is not unique to cyclic peptomers and has been seen in cyclic peptides4b and small molecule drugs.29 Although theoretically intrinsic permeability (P0) will continue to increase with increasing lipophilicity,30 the observed apparent permeability (Papp) can be skewed downward by factors such as membrane sequestration and decreasing aqueous solubility. In a drug discovery setting, membrane retention can often be attenuated by plasma protein binding,31 while poor solubility can be tackled using alternative formulation strategies. Contrary to previous results,4b,6 hydrophilic side chains did not necessarily abrogate permeability, which suggests that substituent effects are roughly additive and that hydrophobic side chains can compensate for hydrophilic side chains and vice versa. For example, most of the compounds that contained the morpholine side chain (sublibrary 1.5) had ALogP values below the favorable range ( 1 × 10−6 cm/s) because they contained other side chains with enough lipophilicity to compensate for the polar morpholine group, thus bringing these compounds into the favorable ALogP range. A caveat is that we did not include side chains with hydrogen bond donors or highly charged groups although Leu3[NH] compounds in Library 2 had at least one exposed backbone amide. Based on previous observations,4b,6 there may be a limit to which highly polar functionality can be offset by increasing the lipophilicity of substituents elsewhere in the molecule. The LogPapp versus ALogP curves for the different scaffolds of Library 2 provide a unique window into the effect of stereochemistry and N-methylation on permeability. Because ALogP is a two-dimensional descriptor, diastereomers with the same ALogP values have different permeabilities due to conformational effects. Indeed, the relative displacement of the LogPapp versus ALogP curves for the different scaffolds provides information about the degree to which their backbones are either shielded or solvent exposed. The very slow H−D exchange observed for 11a compared to 11b is consistent with the leftward displacement of the LogPapp/ ALogP curve for scaffold 2.2 (Leu3NMe) compared to 2.2 (Leu3NH). In this scaffold, N-methylation at Leu3 enhanced permeability by not only masking an exposed amide NH, but also by stabilizing IMHB in the backbone. On the other hand, while N-methylation of Leu3 in scaffold 2.4 removed an exposed NH, it also increased solvent exposure of the remaining NH groups, evidenced by an increase in H−D exchange rates in 12a compared to 12b. Consequently, the
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CONCLUSION Here, we report progress in the use of split-pool libraries and analytical tools to study membrane permeability en masse. The PAMPA results of two libraries revealed that the hexameric cyclic peptomers were inherently permeable irrespective of the functional groups on side chains, provided that they remain within an optimal ALogP range. However, in compounds of the same overall lipophilicity, MW was a rate-limiting factor for membrane permeability. Stereochemical configuration and Nmethylation affected the maximum Papp values as well as the optimal ALogP range for a given scaffold. However, some side chain combinations were still permeable even when they were part of less permeable scaffolds. These results indicate that achieving an appropriate ALogP window is more important for the permeability of hexameric cyclic peptomers than the specific stereochemical configuration, N-methylation patterns, and aliphatic side chains (which are among the factors that play a key role in passive permeability in cyclic peptides). We believe these insights apply to other macrocycles, which means the chemical space of bRo5 macrocycles is more extensive than had been previously considered.
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EXPERIMENTAL SECTION
General. All chemicals were commercially available and used without further purification. For reverse-phase column chromatography, a SNAP Ultra C18 cartridge (30 g, Biotage) was employed. All NMR spectra were recorded in CDCl3 on a Varian 500 MHz NMR instrument with Unity Plus console and 5 mm broad-band probe at 25 °C. Chemical shifts were referenced to residual solvent proton signals (1H 7.26 ppm for chloroform). The purity of each single compound was tested by HPLC (Waters 1525) with an attached mass spectrometer (Micromass ZQ, waters) and PDA detector (Waters 2998) through a 3.5 μm C18 column (XBridge BEH C18 4.6 × 50 mm). The mixture of water (0.1% formic acid) and ACN (0.1% formic acid) was used as an eluent, of which ACN percentage was increased stepwise (0−2 min, 20%; 2−10 min, linear gradient from 20 to 100%; 10−12 min, 100%) with a flow rate of 1.2 mL/min. The absorbance at 220 nm wavelength was used to calculate the purity and retention factor k′ by MassLynx ver.4.1. All compounds were at least 95% pure. LC-MS analyses for PAMPA were performed on an UHPLC (UltiMate 3000, Dionex) with attached mass spectrometer (Orbitrap Velos Pro, Thermo Scientific) through a 1.9 μm C18 column 9509
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tube was removed from the instrument, and a solution of 39 μL of MeOH-d4 containing 10% AcOH-d4 was added by syringe. Upon addition of the deuterated solvents and quick agitation, the NMR tube was returned to the spectrometer. Spectra were recorded using 16 free induction decay transients for each time point at increasing intervals over a period of 2 h. H−D exchange rates were measured by integrating each exchangeable amide resonance separately and recording the ratio of its peak area versus the peak area for downfield non-exchangeable N-methyl protons or α protons.
(Hypersil GOLD 30 × 2.1 mm, Thermo Scientific). The mixture of water (0.1% formic acid) and ACN (0.1% formic acid) was used as an eluent, of which ACN percentage was increased stepwise (0−0.5 min, 10%; 0.5−3.5 min, linear gradient from 10 to 100%; 3.5−5 min, 100%) with a flow rate of 0.6 mL/min. Cyclic Peptomer Synthesis. Linear peptomers were synthesized on 2-chlorotrityl resin (0.3−0.5 mmol/g) using standard Fmoc coupling (Fmoc amino acid/HATU/DIPEA in DMF, 1.5 h) and peptoid synthesis conditions (bromoacetic acid/DIC in DMF, 30 min, then 1 mol/L amine in NMP, 1.5 h). The linear peptomers were cleaved from resin with 30% HFIP in DCM. Cyclization was performed in dilute conditions (