Phototoxicity─Medicinal Chemistry Strategies for Risk Mitigation in Drug Discovery

Phototoxicity is a common safety concern encountered by project teams in pharmaceutical research and has the potential to stop progression of an otherwise promising candidate molecule. This perspective aims to provide an overview of the approaches toward mitigation of phototoxicity that medicinal chemists have taken during the lead optimization phase in the context of regulatory standards for photosafety evaluation. Various strategies are laid out based on available literature examples in order to highlight how structural modification can be utilized toward successful mitigation of a phototoxicity liability. A proposed flowchart is presented as a guidance tool to be used by the practicing medicinal chemist when facing a phototoxicity risk. The description of available tools to consider in the drug design process will include an overview of the evolution of in silico methods and their application as well as structure alerts for consideration as potential phototoxicophores.

DFT study of sertraline hydrochloride antidepressant drug

CONTEXT

The global reactivity and molecular stability of sertraline hydrochloride (SHCl) are predicted for chemical and photo-biological applications. SHCl has a wide indirect HOMO-LUMO gap of about 4.77 eV. The p orbital states of nitrogen and chlorine atoms play the main role in HOMO and LUMO energy levels. Maximum optical transitions are observed at the energy range of 4.96 to 5.64 eV. The main reflectivity occurs at the ultraviolet energy range of 5.51 to 6.16 eV. Obtained high absorption in the ultraviolet region is in good agreement with experiments. It is found that SHCl can be used in new antidepressant drugs.

METHODS

Optoelectronic properties of SHCl was performed using density functional theory (DFT) calculations as implemented in WIEN2k package. The generalized gradient approximation (GGA) and the Modified Becke and Johnson (mBJ) potential are used for calculation of the exchange-correlation potentials.

Machine learning prediction of UV-Vis spectra features of organic compounds related to photoreactive potential

Machine learning (ML) algorithms were explored for the classification of the UV-Vis absorption spectrum of organic molecules based on molecular descriptors and fingerprints generated from 2D chemical structures. Training and test data (~ 75 k molecules and associated UV-Vis data) were assembled from a database with lists of experimental absorption maxima. They were labeled with positive class (related to photoreactive potential) if an absorption maximum is reported in the range between 290 and 700 nm (UV/Vis) with molar extinction coefficient (MEC) above 1000 Lmol^-1 cm^-1, and as negative if no such a peak is in the list. Random forests were selected among several algorithms. The models were validated with two external test sets comprising 998 organic molecules, obtaining a global accuracy up to 0.89, sensitivity of 0.90 and specificity of 0.88. The ML output (UV-Vis spectrum class) was explored as a predictor of the 3T3 NRU phototoxicity in vitro assay for a set of 43 molecules. Comparable results were observed with the classification directly based on experimental UV-Vis data in the same format.

Computational Study on the Mechanism of the Photouncaging Reaction of Vemurafenib: Toward an Enhanced Photoprotection Approach for Photosensitive Drugs

The photochemical behavior of the photosensitive first-line anticancer drug vemurafenib (VFB) is of great interest due to the impact of such behavior on its pharmacological activity. In this work, we computationally elucidated the mechanism of the photoinduced release of VFB from the 4,5-dimethoxy-2-nitrobenzene (DMNB) photoprotecting group by employing various density functional theory (DFT)/time-dependent DFT (TD-DFT) approaches. The computational investigations included a comparative assessment of the influence of the position of the photoprotecting group as a substituent on the thermodynamics and kinetics of the photouncaging reactions of two VFB-DMNB prodrugs, namely pyrrole (N_P) and sulfonamide (N_S). With the aid of the DFT calculations concerning the activation energy barrier (∆G^‡), the obtained results suggest that the step of the photoinduced intramolecular proton transfer of the DMNB moiety is not detrimental concerning the overall reaction profile of the photouncaging reaction of both prodrugs. However, the obtained results suggested that the position of the substitution position of the DMNB photoprotecting group within the prodrug structure has a substantial impact on the photouncaging reaction. In particular, the DMNB-N_s-VFB prodrug exhibited a notable increase in ∆G^‡ for the key step of ring opining within the DMNB moiety indicative of potentially hindered kinetics of the photouncaging process compared with DMNB-N_p-VFB. Such an increase in ∆G^‡ may be attributed to the electronic influence of the N_P fragment of the prodrug. The results reported herein elaborate on the mechanism of the photoinduced release of an important anticancer drug from photoprotecting groups with the aim of enhancing our understanding of the photochemical behavior of such photosensitive pharmaceutical materials at the molecular level.

Metabolic and Pharmaceutical Aspects of Fluorinated Compounds

The applications of fluorine in drug design continue to expand, facilitated by an improved understanding of its effects on physicochemical properties and the development of synthetic methodologies that are providing access to new fluorinated motifs. In turn, studies of fluorinated molecules are providing deeper insights into the effects of fluorine on metabolic pathways, distribution, and disposition. Despite the high strength of the C-F bond, the departure of fluoride from metabolic intermediates can be facile. This reactivity has been leveraged in the design of mechanism-based enzyme inhibitors and has influenced the metabolic fate of fluorinated compounds. In this Perspective, we summarize the literature associated with the metabolism of fluorinated molecules, focusing on examples where the presence of fluorine influences the metabolic profile. These studies have revealed potentially problematic outcomes with some fluorinated motifs and are enhancing our understanding of how fluorine should be deployed.

Computational Investigation of Drug Phototoxicity: Photosafety Assessment, Photo-Toxophore Identification, and Machine Learning

One of the most appreciated capabilities of computational toxicology is to support the design of pharmaceuticals with reduced toxicological hazard. To this end, we have strengthened our drug photosafety assessments by applying novel computer models for the anticipation of in vitro phototoxicity and human photosensitization. These models are typically used in pharmaceutical discovery projects as part of the compound toxicity assessments and compound optimization methods. To ensure good data quality and aiming at models with global applicability we separately compiled and curated highly chemically diverse data sets from 3T3 NRU phototoxicity reports (450 compounds) and clinical photosensitization alerts (1419 compounds) which are provided as supplements. The latter data gives rise to a comprehensive list of explanatory fragments for visual guidance, termed phototoxophores, by application of a Bayesian statistics approach. To extend beyond the domain of well sampled fragments we applied machine learning techniques based on explanatory descriptors such as pharmacophoric fingerprints or, more important, accurate electronic energy descriptors. Electronic descriptors were extracted from quantum chemical computations at the density functional theory (DFT) level. Accurate UV/vis spectral absorption descriptors and pharmacophoric fingerprints turned out to be necessary for predictive computer models, which were both derived from Deep Neural Networks but also the simpler Random Decision Forests approach. Model accuracies of 83-85% could typically be reached for diverse test data sets and other company in-house data, while model sensitivity (the capability of correctly detecting toxicants) was even better, reaching 86%-90%. Importantly, a computer model-triggered response-map allowed for graphical/chemical interpretability also in the case of previously unknown phototoxophores. The photosafety models described here are currently applied in a prospective manner for the hazard identification, prioritization, and optimization of newly designed molecules.

Successful Strategies for Mitigation of a Preclinical Signal for Phototoxicity in a DGAT1 Inhibitor

Diacylglycerol O-acyltransferase 1 (DGAT1) inhibitor Pradigastat (1) was shown to be effective at decreasing postprandial triglyceride levels in a patient population with familial chylomicronemia syndrome (FCS). Although pradigastat does not cause photosensitization in humans at the high clinical dose of 40 mg, a positive signal was observed in preclinical models of phototoxicity. Herein, we describe a preclinical phototoxicity mitigation strategy for diarylamine containing molecules utilizing the introduction of an amide or suitable heterocyclic function. This strategy led to the development of two second-generation compounds with low risk of phototoxicity, disparate exposure profiles, and comparable efficacy to 1 in a rodent lipid bolus model for post-prandial plasma triglycerides.

Analysis of phototoxin taste closely correlates nucleophilicity to type 1 phototoxicity

Pigments often inflict tissue-damaging and proaging toxicity on light illumination by generating free radicals and reactive oxygen species (ROS). However, the molecular mechanism by which organisms sense phototoxic pigments is unknown. Here, we discover that Transient Receptor Potential Ankyrin 1-A isoform [TRPA1(A)], previously shown to serve as a receptor for free radicals and ROS induced by photochemical reactions, enables Drosophila melanogaster to aphotically sense phototoxic pigments for feeding deterrence. Thus, TRPA1(A) detects both cause (phototoxins) and effect (free radicals and ROS) of photochemical reactions. A group of pigment molecules not only activates TRPA1(A) in darkness but also generates free radicals on light illumination. Such aphotic detection of phototoxins harboring the type 1 (radical-generating) photochemical potential requires the nucleophile-sensing ability of TRPA1. In addition, agTRPA1(A) from malaria-transmitting mosquitoes Anopheles gambiae heterologously produces larger current responses to phototoxins than Drosophila TRPA1(A), similar to their disparate nucleophile responsiveness. Along with TRPA1(A)-stimulating capabilities, type 1 phototoxins exhibit relatively strong photo-absorbance and low energy gaps between the highest occupied molecular orbital and the lowest unoccupied molecular orbital. However, TRPA1(A) activation is more highly concordant to type 1 phototoxicity than are those photochemical parameters. Collectively, nucleophile sensitivity of TRPA1(A) allows flies to taste potential phototoxins for feeding deterrence, preventing postingestive photo-injury. Conversely, pigments need to bear high nucleophilicity (electron-donating propensity) to act as type 1 phototoxins, which is consistent with the fact that transferring photoexcited electrons from phototoxins to other molecules causes free radicals. Thus, identification of a sensory mechanism in Drosophila reveals a property fundamental to type 1 phototoxins.

Discovery of a Novel Series of Pyrazolo[1,5-a]pyrimidine-Based Phosphodiesterase 2A Inhibitors Structurally Different from N-((1S)-1-(3-Fluoro-4-(trifluoromethoxy)phenyl)-2-methoxyethyl)-7-methoxy-2-oxo-2,3-dihydropyrido[2,3-b]pyrazine-4(1H)-carboxamide (TAK-915), for the Treatment of Cognitive Disorders

It has been hypothesized that selective inhibition of phosphodiesterase (PDE) 2A could potentially be a novel approach to treat cognitive impairment in neuropsychiatric and neurodegenerative disorders through augmentation of cyclic nucleotide signaling pathways in brain regions associated with learning and memory. Following our earlier work, this article describes a drug design strategy for a new series of lead compounds structurally distinct from our clinical candidate 2 (TAK-915), and subsequent medicinal chemistry efforts to optimize potency, selectivity over other PDE families, and other preclinical properties including in vitro phototoxicity and in vivo rat plasma clearance. These efforts resulted in the discovery of N-((1S)-2-hydroxy-2-methyl-1-(4-(trifluoromethoxy)phenyl)propyl)-6-methyl-5-(3-methyl-1H-1,2,4-triazol-1-yl)pyrazolo[1,5-a]pyrimidine-3-carboxamide (20), which robustly increased 3',5'-cyclic guanosine monophosphate (cGMP) levels in the rat brain following an oral dose, and moreover, attenuated MK-801-induced episodic memory deficits in a passive avoidance task in rats. These data provide further support to the potential therapeutic utility of PDE2A inhibitors in enhancing cognitive performance.

Discovery of Antimalarial Azetidine-2-carbonitriles That Inhibit P. falciparum Dihydroorotate Dehydrogenase

Dihydroorotate dehydrogenase (DHODH) is an enzyme necessary for pyrimidine biosynthesis in protozoan parasites of the genus Plasmodium, the causative agents of malaria. We recently reported the identification of novel compounds derived from diversity-oriented synthesis with activity in multiple stages of the malaria parasite life cycle. Here, we report the optimization of a potent series of antimalarial inhibitors consisting of azetidine-2-carbonitriles, which we had previously shown to target P. falciparum DHODH in a biochemical assay. Optimized compound BRD9185 (27) has in vitro activity against multidrug-resistant blood-stage parasites (EC₅₀ = 0.016 μM) and is curative after just three doses in a P. berghei mouse model. BRD9185 has a long half-life (15 h) and low clearance in mice and represents a new structural class of DHODH inhibitors with potential as antimalarial drugs.

Discovery of phenoxyindazoles and phenylthioindazoles as RORγ inverse agonists

Targeting the IL17 pathway and more specifically the nuclear receptor RORγ is thought to be beneficial in multiple skin disorders. The Letter describes the discovery of phenoxyindazoles and thiophenoxy indazoles as potent RORγ inverse agonists. Optimization of the potency and efforts to mitigate the phototoxic liability of the series are presented. Finally, crystallization of the lead compound revealed that the series bound to an allosteric site of the nuclear receptor. Such compounds could be useful as tool compounds for understanding the impact of topical treatment on skin disease models.