Brief Article Cite This: J. Med. Chem. 2018, 61, 3231−3236
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Intrinsic Property Forecast Index (iPFI) as a Rule of Thumb for Medicinal Chemists to Remove a Phototoxicity Liability Jean-François Fournier,* Claire Bouix-Peter, Denis Duvert, Anne-Pascale Luzy, and Gilles Ouvry Nestlé Skin Health R&D, 2400 Route des Colles, BP 87, 06902 Sophia-Antipolis Cedex, France S Supporting Information *
ABSTRACT: Phototoxicity occurs when UV irradiation causes otherwise benign compounds to become irritant, sensitizers, or even genotoxic. This toxicity is particularly a concern after topical application and in dermatological programs where skin irritation can be incompatible with the desired therapeutic outcome. This brief article establishes that the intrinsic property forecast index (iPFI) can be used to evaluate the probability of a compound being phototoxic and gives medicinal chemists a practical tool to handle this liability.
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INTRODUCTION Phototoxicity, photoallergy, or drug-induced photosensitivity, hereby referenced as phototoxicity, occurs when UV irradiation, for example by the sun, causes otherwise benign compounds to become irritant or even toxic. This would typically occur if said compound absorbs light in the UV spectrum to reach an excited state. From there, a number of processes could occur (ROS generation, transfer of energy, drug decomposition,...) to account for the difference in skin toxicity vs the non-UV irradiated compound.1 Many common drugs such as NSAID ketoprofen and antibiotic lomefloxacin are phototoxic,1 although sometimes only a fraction of the patient population develops symptoms. Novel candidate drugs must therefore be screened for phototoxicity. In particular, in dermatology, skin irritation is often incompatible with the desired therapeutic effect (e.g., skin inflammation in acne or atopic dermatitis) and should be screened for early on during the discovery stage, especially if the route of administration is topical where skin concentration in the upper layers is high. However, a better approach for a medicinal chemist would be to understand the physicochemical basis of phototoxicity in order to design molecules with lower risk. Furthermore, whereas in silico models can help selecting the most promising candidates, they tend to be black-box models that offer little practical help in the design phase and have been elaborated from limited data sets.2 We therefore embarked on a systematic analysis of our early phase phototoxicity results in an in-house test (∼1000 results © 2018 American Chemical Society
produced under identical conditions) vs descriptors easily understood and manipulated at the molecular level by medicinal chemists.
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METHODOLOGY Photocytotoxicity potential was assessed in a keratinocytes NRU assay adapted from the 3T3 NRU assay described in OECD guideline 432. Cells were irradiated with daylight UV simulation at 6 J/cm2. Cell viability was determined after 24 h exposure with chemicals, and a phototoxicity irritation factor (PIF) value was determined by the ratio of LC50 value with and without UV. Chemicals were classified as follow: PIF < 2 nonphototoxic, 2 < PIF < 5 low phototoxic potential, and PIF > 5 phototoxic. The sensitivity of the 3T3 NRU-PT is high, and if a compound is negative in this assay, it would have a very low probability of being phototoxic in humans. However, a positive result in the 3T3 NRU-PT should not be regarded as indicative of a likely clinical phototoxic risk but rather a flag for follow-up assessment.3 The 76 compounds (∼8% of the data set) with a low phototoxic potential were removed from the analysis presented in this article as it did not seem relevant to predict an inconclusive results and for better visual clarity. However, the curious reader will find a similar analysis including these results in the Supporting Information. The aim of this study was to provide easily Received: January 16, 2018 Published: March 16, 2018 3231
DOI: 10.1021/acs.jmedchem.8b00075 J. Med. Chem. 2018, 61, 3231−3236
Journal of Medicinal Chemistry
Brief Article
This trend reversal was at first surprising. However, it was noted that 30 of these 31 nonphototoxic compounds were of the same chemical series. Furthermore, it was also noted that they had low ChromLogDs (21 below 2; all below 3).6 Although the possibility that phototoxicity might be linked to lipophilicity can be met with skepticism, it was realized that the latter is linked to toxicity in general because compounds are then more prone to binding any and all targets.7 We thus examined our data to assess whether such a link did indeed exist. While Figure 2 shows that no clear correlation can be made between the proportion of phototoxic compounds and solely
understandable rules for medicinal chemists. As such, the analysis presented here gives for each descriptor (physicochemical property) the proportion of phototoxic (red) to nonphototoxic (green) compounds along a binned continuum of values. With the notable exception of Figure 5, bins with fewer than 10 results were either removed or merged/adjusted to prevent outliers from skewing analysis. It is assumed that the proportions of phototoxic compounds can be qualitatively assimilated to the probability of future compounds being phototoxic.
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RESULTS AND DISCUSSION The number of conjugated π electrons has an impact on different light absorption parameters and consequently on phototoxicity.2b We were therefore not surprised to observe a clear trend in the proportion of phototoxic compounds depending on the fraction of sp3 atoms (fsp3) across our data set involving multiple chemical series. This trend was mirrored by another one with the number of aromatic groups (N Arom), albeit with the notable exception of compounds where N Arom was equal to 5.4,5
Figure 2. Proportion of phototoxic compound in function of only ChromLogP indicates no clear correlation. The number of data points used in each bin is given above the bars.
lipophilicity as measured with ChromLogP,8,9 Figure 3a shows that when combined with the number of aromatic rings, a twodimensional trend is observed. Indeed, not only does the proportion of phototoxic compound increase with the number of aromatic rings for each range of ChromLogP (across columns) but also generally with ChromLogP for any fixed number of rings (across rows). This situation corresponds to what has already been described by Young and co-workers regarding multiple other properties in their seminal paper describing the intrinsic property forecast index (iPFI) as a relevant marker equal to the sum of ChromLogP and number of aromatic rings.6b Briefly, the authors bring evidence supporting the notions that aromatic groups have an impact beyond their simple contribution to overall hydrophobicity (flat structure, π-stacking, ...) on multiple key parameters (solubility, protein binding, metabolism, promiscuity, ...) and that ChromLogD is more reliable than traditional shake-flask LogD. They then propose the use of the composite descriptor PFI and iPFI as a measure of compound quality and design tool. Indeed, Figure 3b shows a better correlation with iPFI than that with N Arom alone (Figure 1b). Correcting the number of aromatic rings by normalizing over the number of aromatic atoms in the case of fused rings did not have a significant effect and thus the simpler N Arom was used thereafter.10 Notably, because of differences between shake flask LogP and ChromLogP, it is not standard practice to use cLogP to calculate PFI. We nonetheless took the liberty of examining whether
Figure 1. Proportion of phototoxic compound in function of (a) the fraction of sp3 atoms (fsp3) or (b) the number of aromatic rings (N Arom). The number of data points used in each bin is given above the bars. 3232
DOI: 10.1021/acs.jmedchem.8b00075 J. Med. Chem. 2018, 61, 3231−3236
Journal of Medicinal Chemistry
Brief Article
Table 1. Number of Matched Pairs with iPFI Reductions Per Given Impact on Photoxicity Potential
a
Number of matched pairs resulting in an increase (e.g., from low phototoxic potential to phototoxic), no change, or a reduction (e.g., from phototoxic to non phototoxic) in phototoxicity potential. bA matched pair analysis with nine atoms maximum fragment size, eight atom minimum core size, and including any single atom changes and nonring fragmentations gave a total of 4789 matched pairs with negative ΔiPFI values and 1715 matched pairs with ΔiPFI values below or equal to −1.
Figure 3. Proportion of phototoxic compound in function of ChromLogP and the number of aromatic rings indicates a correlation for both factors with (a) a bidimensional plot and (b) the intrinsic property forecast index. The number of data points used in each bin is given above the pies and bars. Most pies with N Arom equal to 0, 1, or 5 had fewer than 10 data points and were thus combined with the more ubiquitous N Arom equal to 2 or 4.
iPFI could be substituted with the sum of a calculated LogP (Simulation Plus) and the number of aromatic rings. Figure 4 shows this can be done, although results may differ depending on which calculation software is used. As an example of how this rule of thumb can be used, we show in Figure 5a the analysis for the early part of a project with a 6-amino-pyrazolopyrimidine scaffold. Initially a significant proportion of the compounds were phototoxic. Consequently, a choice was made at the design stage to only synthesize compounds whose expected iPFI values were lower than 7. Gratifyingly, the strategy proved to be successful as the “faulty” bin height was reduced and a similar phototoxicity distribution per bins was found for the new compounds (Figure 5b). The molecular matched pairs shown in Table 1 exemplify cases where structural transformations were accompanied by a reduction in iPFI and the loss of phototoxicity. It should be noted that
an iPFI reduction is only likely to produce a phototoxicity potential reduction if at least a low risk exists, it occurs between iPFI values where the proportion of phototoxic compounds changes significantly and if no specific phototoxicity-causing substructural elements are involved. For example, of the three pyridine/ oxetane matched pairs resulting in no change in phototoxicity potential, two have starting points that are already nonphototoxic, while the last one, which is phototoxic, bears a phototoxicophore.12 Furthermore, of the 4789 matched pairs giving a negative ΔiPFI, only 335 give rise to an increase in phototoxicity potential while almost four times as much (1311) instead give rise to a decrease (or 10 times as much fold-difference with ΔiPFI ≤ −1). This emphasizes the importance of structural elements in addition, and perhaps even orthogonally, to the physicochemical properties of the molecules when assessing the risk of phototoxicity 3233
DOI: 10.1021/acs.jmedchem.8b00075 J. Med. Chem. 2018, 61, 3231−3236
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Brief Article
Figure 4. Sum of a calculated (Simulation Plus) logP and number of aromatic rings also correlates the proportion of phototoxic compounds. The number of data points used in each bin is given above the bars.
of a compound. This simple rule of thumb should only be used as a guide to the medicinal chemist as opposed to a fixed rule with a threshold iPFI value of, for example, 9, beyond which compounds would be predicted phototoxic. Indeed, we have observed a strong dependency on chemical structure which can shift this overall tendency to the right or left (Figure 6). For example, in a caspase 1 inhibitor program, phototoxicity of inhibitors with a uracil-based scaffold had a strong dependency on iPFI within the typical design range of that project.13 However, the phototoxicity of indazole-based RORγ inverse agonists14 and uracil-based antagonists of CGRP15 was seemingly insensitive to iPFI, in the former case, because the indazole-based scaffold shifts the phototoxicity proportion to the left (higher proportion for the same iPFI),16,17 and in the latter case because the uracil-based scaffold (different configuration vs the caspase 1 uracils) shifts it to the right. Nonetheless, the results strongly suggest that when faced with a chemical series with a high proportion of phototoxic compounds, medicinal chemists can address this issue by lowering the iPFI of their structures. This can be done at the design stage either by lowering the number of aromatic rings (various well-known strategies can be utilized, for example complete or partial saturation, bioisosteres,18 opening ring with or without the use of intramolecular H-bonding, ...) or lowering lipophilicity (removing lipophilic substituents or adding hydrophilic ones).
Figure 5. Case study of how the iPFI rule of thumb strategy was used with a 6-amino-pyrazolopyri(mi)dine scaffold. (a) Early in project, compounds with iPFI > 7 tend to be phototoxic. (b) Late in project, fewer compounds with iPFI > 7 were made resulted in fewer phototoxic compounds.11
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CONCLUSION In conclusion, we have demonstrated the relevance of physicochemical properties such as the fraction of sp3 atoms, the number of aromatic rings, and the lipophilicity with regard to the outcome of an in vitro phototoxicity test. By assimilating past proportions of phototoxic compounds within binned iPFI values as a probability of future compounds being phototoxic, we established an easily remembered rule-of-thumb way of predicting phototoxicity and more importantly a chemical handle for the medicinal chemist to use to remove a potential phototoxicity liability. This work again stresses the importance of keeping iPFI (lipophilicity and the number of aromatic rings) within a reasonable range.
The astute reader will realize that although we present in this article rules based on over 25 projects and twice as many chemical series, we do not recommend using them universally and blindly for phototoxicity prediction as more subtle structural factors are then ignored. For quantitative predictions, we either use a formally built model or re-evaluate the proportion of phototoxic compounds within the same chemical series.
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EXPERIMENTAL SECTION
The relative purity ≥95% and the mass of the products were confirmed by LC/MS (220−420 nm) on a Waters acquity UPLC photodiode array detector system using the following conditions: Column, BEH C18 50 mm ×2.1 mm, 1.8 μm; solvent A, water 0.1% formic acid or water 3234
DOI: 10.1021/acs.jmedchem.8b00075 J. Med. Chem. 2018, 61, 3231−3236
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Figure 6. Proportion of phototoxic compound within the project design iPFI varies with the chemical series concerned, as shown by (a) caspase 1 uracils (strong dependency), (b) RORγ indazole (little dependency due to an intrinsically highly phototoxic scaffold), (c) CGRP uracils (little dependency due to an intrinsically highly nonphototoxic scaffold). The number of data points used in each bin is given above the bars.
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ammonium carbonate 2 g/L; solvent B, CH3CN; flow rate, 0.8 mL/min; run time, 2.2 min; gradient, from 5 to 95% solvent B; mass detector, Waters SQ detector. Phototoxicity Test. Human keratinocyte neonatal cells were maintained in culture for 24 h for formation of monolayers. Then 96-well plates were preincubated with serially diluted solutions of the test compound for 30 min at 37 °C and 5% CO2. One plate was exposed to a dose of 5J/cm2 during 15 min (19.6W/m2 UVB and 90.8W/m2 UVA), whereas the other plate was kept in the dark (−UV experiment). The treatment medium was replaced with culture medium after 24 h. Cell viability was determined by Neutral Red after 3 h at 37 °C, 5% CO2. Cytotoxicity was measured as an inhibition of the capacity of the cell cultures to take up vital dye 1 day after treatment. The photoirritancy factor (PIF) was calculated by comparing the two equally effective cytotoxic chemical concentrations (EC50 values) in the dark (−UV) and light experiments (+UV).
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ACKNOWLEDGMENTS We thank Franck Tran for a script which calculates the corrected number of aromatic rings of fused rings. ABBREVIATIONS USED 3T3, 3-day transfer, inoculum 3 × 105 cells; CGRP, calcitonin gene-related peptide; fsp3, fraction of sp3 atoms; iPFI, intrinsic property forecast index; N Arom, number of aromatic rings; NRU, neutral red uptake; PIF, phototoxicity irritation factor; RORγ, retinoid orphan receptor gamma; ROS, radical oxygen species; UV, ultraviolet.
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ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jmedchem.8b00075. Additional figures (PDF) Descriptors and phototoxicity results (CSV) Jython script to calculate atom normalized N Arom (TXT)
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REFERENCES
(1) Arimoto-Kobayashi, S. Phototoxicity and photomutagenicity of medicines, carcinogens and endogenous compounds. Genes Environ. 2014, 36, 103−110. (2) (a) Ringeissen, S.; Marrot, L.; Note, R.; Labarussiat, A.; Imbert, S.; Todorov, M.; Mekenyan, O.; Meunier, J. R. Development of a mechanistic SAR model for the detection of phototoxic chemicals and use in an integrated testing strategy. Toxicol. In Vitro 2011, 25, 324−334. (b) Haranosono, Y.; Kurata, M.; Sakaki, H. Establishment of an in silico phototoxicity prediction method by combining descriptors related to photo-absorption and photo-reaction. J. Toxicol. Sci. 2014, 39, 655−664. (3) For more details, see: OECD, Test No. 432: In Vitro 3T3 NRU Phototoxicity Test; OECD Publishing: Paris, 2004. (4) For a discussion on the importance of the number of aromatic rings on compound developability, see: (a) Ritchie, T. J.; Macdonald, S. J. F. The impact of aromatic ring count on compound developability − are too many aromatic rings a liability in drug design? Drug Discovery Today 2009, 14, 1011−1020. (b) Ritchie, T. J.; Macdonald, S. J.; Young, R. J.; Pickett, S. D. The impact of aromatic ring count on compound developability: further insights by examining carbo- and hetero-aromatic and -aliphatic ring types. Drug Discovery Today 2011, 16, 164−171. (5) Fused aromatic rings such as naphthalene were counted as two aromatic rings. (6) Compound lipophilicity is evaluated at pH 6.5 (a pH intermediate of that of skin and blood), with the notable exception of 28 neutral
AUTHOR INFORMATION
Corresponding Author
*Phone: +33 4 92 38 68 84. E-mail: jean-francois.fournier@ umontreal.ca. ORCID
Jean-François Fournier: 0000-0003-4958-1478 Notes
The authors declare the following competing financial interest(s): All authors were Nestle Skin Health R and D full-time employees at the time this work was carried out. 3235
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compounds for which pH 3.0 was used, by the chromatographic method described by Valko and then expressed as ChromLogD using the equation described by Young: ChromLogD = CHI*0.0857 − 2. (a) Valko, K.; Bevan, C.; Reynolds, D. Chromatographic hydrophobicity index by fast-gradient RP-HPLC: A high-throughput alternative to logP/logD. Anal. Chem. 1997, 69, 2022−2029. (b) Young, R. J.; Green, D. V. S.; Luscombe, C. N.; Hill, A. P. Getting physical in drug discovery II: the impact of chromatographic hydrophobicity measurements and aromaticity. Drug Discovery Today 2011, 16, 822−830. (7) Waring, M. J. Lipophilicity in drug discovery. Expert Opin. Drug Discovery 2010, 5, 235−248. (8) Here and elsewhere in this article, ChromLogD gives, at best, similar trends vs ChromLogP (9) For acids and bases, ChromLogP is extrapolated from ChromLogD using the pKa calculated using ChemAxon and the adapted Henderson− Hasselbalch equations: ChromLogD + log[1 + 10(pH−pKa)] and ChromLogD + log[1 + 10(pKa−pH)] respectively. (10) Data shown in the Supporting Information. For a discussion on the difference between fused vs nonfused aromatic rings, see reference.4b (11) The results used in Figure 5b are not part of the main data set and have not been used to establish any of the other trends. (12) Ouvry, G.; Atrux-Tallau, N.; Bihl, F.; Bondu, A.; Bouix-Peter, C.; Carlavan, I.; Christin, O.; Cuadrado, M. J.; Defoin-Platel, C.; Deret, S.; Duvert, D.; Feret, C.; Forissier, M.; Fournier, J.-F.; Froude, D.; HaciniRachinel, F.; Harris, C. S.; Hervouet, C.; Huguet, H.; Lafitte, G.; Luzy, A.-P.; Musicki, B.; Orfila, D.; Ozello, B.; Pascau, C.; Pascau, J.; Parnet, V.; Peluchon, G.; Pierre, R.; Piwnica, D.; Raffin, C.; Rossio, P.; Spiesse, D.; Taquet, N.; Thoreau, E.; Vatinel, R.; Vial, E.; Hennequin, L. F. Discovery and characterization of CD12681, a potent RORγ inverse agonist, preclinical candidate for the topical treatment of psoriasis. ChemMedChem 2018, 13, 321. (13) In this chemical series, the phototoxicity risk was removed with a small chemical structure modification which did not decrease the iPFI. See Fournier, J.-F.; Clary, L.; Chambon, S.; Dumais, L.; Harris, C. S.; Millois, C.; Pierre, R.; Talano, S.; Thoreau, É.; Aubert, J.; Aurelly, M.; Bouix-Peter, C.; Brethon, A.; Chantalat, L.; Christin, O.; Comino, C.; ElBazbouz, G.; Ghilini, A.-L.; Isabet, T.; Lardy, C.; Luzy, A.-P.; Mathieu, C.; Mebrouk, K.; Orfila, D.; Pascau, J.; Reverse, K.; Roche, D.; Rodeschini, V.; Hennequin, L. F. Rational drug design of topically administered caspase 1 inhibitors for the treatment of inflammatory acne. Manuscript submitted for publication. (14) Ouvry, G.; Bouix-Peter, C.; Ciesielski, F.; Chantalat, L.; Christin, O.; Comino, C.; Duvert, D.; Feret, C.; Harris, C. S.; Lamy, L.; Luzy, A.P.; Musicki, B.; Orfila, D.; Pascau, J.; Parnet, V.; Perrin, A.; Pierre, R.; Polge, G.; Raffin, C.; Rival, Y.; Taquet, N.; Thoreau, E.; Hennequin, L. F. Discovery of phenoxyindazoles and phenylthioindazoles as RORγ inverse agonists. Bioorg. Med. Chem. Lett. 2016, 26, 5802−5808. (15) Clary, L.; Fournier, J.-F.; Thoreau, E. Preparation of Heterocyclic Compounds as CGRP Receptor Antagonist and their use in Medicine and in Cosmetics. PCT Int. Appl. WO2016102882A1, 2016; 407pp. (16) For another example of the indazole scaffold being linked with a high probability of phototoxicity, see Ritzén, A.; Sørensen, M. D.; Dack, K. N.; Greve, D. R.; Jerre, A.; Carnerup, M. A.; Rytved, K. A.; BaggerBahnsen, J. Fragment-based discovery of 6-arylindazole JAK inhibitors. ACS Med. Chem. Lett. 2016, 7, 641−646. (17) The two nonphototoxic indazole-based RORγ inverse agonists are arguably false negative because they were both highly cytotoxic even without UV. (18) Meanwell, N. A. Synopsis of some recent tactical application of bioisosteres in drug design. J. Med. Chem. 2011, 54, 2529−2591.
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