Physicochemical drug properties associated within vivotoxicological outcomes: a review

Safety Implications of Modulating Nuclear Receptors: A Comprehensive Analysis from Non-Clinical and Clinical Perspectives

The unintended modulation of nuclear receptor (NR) activity by drugs can lead to toxicities amongst the endocrine, gastrointestinal, hepatic cardiovascular, and central nervous systems. While secondary pharmacology screening assays include NRs, safety risks due to unintended interactions of small molecule drugs with NRs remain poorly understood. To identify potential nonclinical and clinical safety effects resulting from functional interactions with 44 of the 48 human-expressed NRs, we conducted a systematic narrative review of the scientific literature, tissue expression data, and used curated databases (OFF-X™) (Off-X, Clarivate) to organize reported toxicities linked to the functional modulation of NRs in a tabular and machine-readable format. The top five NRs associated with the highest number of safety alerts from peer-reviewed journals, regulatory agency communications, congresses/conferences, clinical trial registries, and company communications were the Glucocorticoid Receptor (GR, 18,328), Androgen Receptor (AR, 18,219), Estrogen Receptor (ER, 12,028), Retinoic acid receptors (RAR, 10,450), and Pregnane X receptor (PXR, 8044). Toxicities associated with NR modulation include hepatotoxicity, cardiotoxicity, endocrine disruption, carcinogenicity, metabolic disorders, and neurotoxicity. These toxicities often arise from the dysregulation of receptors like Peroxisome proliferator-activated receptors (PPARα, PPARγ), the ER, PXR, AR, and GR. This dysregulation leads to various health issues, including liver enlargement, hepatocellular carcinoma, heart-related problems, hormonal imbalances, tumor growth, metabolic syndromes, and brain function impairment. Gene expression analysis using heatmaps for human and rat tissues complemented the functional modulation of NRs associated with the reported toxicities. Interestingly, certain NRs showed ubiquitous expression in tissues not previously linked to toxicities, suggesting the potential utilization of organ-specific NR interactions for therapeutic purposes.

Electrophysiological Changes in the Rabbit Ventricular Wedge and Human-Induced Pluripotent Stem-Cell Derived (IPSC) Cardiomyocytes Translate to Severe Arrhythmia Observed in a Canine Toxicology Study, Not Predicted by Standard In Vitro Ion Channel Assays

During drug discovery, small molecules are typically assayed in vitro for secondary pharmacology effects, which include ion channels relevant to cardiac electrophysiology. Compound A was an irreversible inhibitor of myeloperoxidase investigated for the treatment of peripheral artery disease. Oral doses in dogs at ≥5 mg/kg resulted in cardiac arrhythmias in a dose-dependent manner (at Cmax, free ≥1.53 μM) that progressed in severity with time. Nevertheless, a panel of 13 different cardiac ion channel (K, Na, and Ca) assays, including hERG, failed to identify pharmacologic risks of the molecule. Compound A and a related Compound B were evaluated for electrophysiological effects in the isolated rabbit ventricular wedge assay. Compounds A and B prolonged QT and Tp-e intervals at ≥1 and ≥.3 μM, respectively, and both prolonged QRS at ≥5 μM. Compound A produced early after depolarizations and premature ventricular complexes at ≥5 μM. These data indicate both compounds may be modulating hERG (Ikr) and Nav1.5 ion channels. In human IPSC cardiomyocytes, Compounds A and B prolonged field potential duration at ≥3 μM and induced cellular dysrhythmia at ≥10 and ≥3 μM, respectively. In a rat toxicology study, heart tissue: plasma concentration ratios for Compound A were ≥19X at 24 hours post-dose, indicating significant tissue distribution. In conclusion, in vitro ion channel assays may not always identify cardiovascular electrophysiological risks observed in vivo, which can be affected by tissue drug distribution. Risk for arrhythmia may increase with a "trappable" ion channel inhibitor, particularly if cardiac tissue drug levels achieve a critical threshold for pharmacologic effects.

Discovery and Optimization of Selective Brain-Penetrant EBP Inhibitors that Enhance Oligodendrocyte Formation

The inhibition of emopamil binding protein (EBP), a sterol isomerase within the cholesterol biosynthesis pathway, promotes oligodendrocyte formation, which has been proposed as a potential therapeutic approach for treating multiple sclerosis. Herein, we describe the discovery and optimization of brain-penetrant, orally bioavailable inhibitors of EBP. A structure-based drug design approach from literature compound 1 led to the discovery of a hydantoin-based scaffold, which provided balanced physicochemical properties and potency and an improved in vitro safety profile. The long half-lives of early hydantoin-based EBP inhibitors in rodents prompted an unconventional optimization strategy, focused on increasing metabolic turnover while maintaining potency and a brain-penetrant profile. The resulting EBP inhibitor 11 demonstrated strong in vivo target engagement in the brain, as illustrated by the accumulation of EBP substrate zymostenol after repeated dosing. Furthermore, compound 11 enhanced the formation of oligodendrocytes in human cortical organoids, providing additional support for our therapeutic hypothesis.

Computer-Aided Drug Discovery and Design: Recent Advances and Future Prospects

Computer-aided drug discovery and design involve the use of information technologies to identify and develop, on a rational ground, chemical compounds that align a set of desired physicochemical and biological properties. In its most common form, it involves the identification and/or modification of an active scaffold (or the combination of known active scaffolds), although de novo drug design from scratch is also possible. Traditionally, the drug discovery and design processes have focused on the molecular determinants of the interactions between drug candidates and their known or intended pharmacological target(s). Nevertheless, in modern times, drug discovery and design are conceived as a particularly complex multiparameter optimization task, due to the complicated, often conflicting, property requirements.This chapter provides an updated overview of in silico approaches for identifying active scaffolds and guiding the subsequent optimization process. Recent groundbreaking advances in the field have also analyzed the integration of state-of-the-art machine learning approaches in every step of the drug discovery process (from prediction of target structure to customized molecular docking scoring functions), integration of multilevel omics data, and the use of a diversity of computational approaches to assist target validation and assess plausible binding pockets.

Drug Self-Aggregation into Nano-Entities Has the Potential to Induce Immune Responses

The free-state solution behaviors of small molecules profoundly affect their respective properties. It is becoming more obvious that compounds can adopt a three-phase equilibrium when placed in an aqueous solution, among soluble-lone molecule form, self-assembled aggregate form (nano-entities), and solid precipitate form. Recently, correlations have emerged between the existence of self-assemblies into drug nano-entities and unintended side effects. This report describes our pilot study involving a selection of drugs and dyes to explore if there may be a correlation between the existence of drug nano-entities and immune responses. We first implement practical strategies for detecting the drug self-assemblies using a combination of nuclear magnetic resonance (NMR), dynamic light scattering (DLS), transmission electron microscopy (TEM), and confocal microscopy. We then used enzyme-linked immunosorbent assays (ELISA) to monitor the modulation of immune responses on two cellular models, murine macrophage and human neutrophils, upon exposure to the drugs and dyes. The results suggest that exposure to some aggregates correlated with an increase in IL-8 and TNF-α in these model systems. Given this pilot study, further correlations merit pursuing on a larger scale given the importance and potential impact of drug-induced immune-related side effects.

Deep Annotation of Donated Chemical Probes (DCP) in Organotypic Human Liver Cultures and Patient-Derived Organoids from Tumor and Normal Colorectum

Well-characterized small molecules are essential tools for studying the biology and therapeutic relevance of a target protein. However, many compounds reported in the literature and routinely studied in biomedical research lack the potency and selectivity required for mechanistic cellular studies on the function of a given protein. Furthermore, commercially available compounds often do not include useful tools developed by industry as part of their research and development efforts, as they frequently remain proprietary. The freely available donated chemical probe (DCP) library, fueled by generous donations of compounds from industry and academia, enables easy access to a steadily growing collection of these valuable and well-characterized tools. Here, we provide a systematic description of the current DCP library collection and their associated comprehensive characterization data, including a variety of in vitro and cellular assays. Of note, we characterized the set in relevant human primary models by employing hepatotoxicity screening in primary human liver spheroids and viability screening in patient-derived colorectal cancer organoids and matched normal-adjacent epithelium. Taken together, the DCP library represents a well-annotated, openly available collection of tool compounds for studying a wide range of targets, including kinases, G-protein-coupled receptors, and ion channels. As such, it represents a unique resource for the biomedical research community.

Discovery of Benzo[d]imidazole-6-sulfonamides as Bromodomain and Extra-Terminal Domain (BET) Inhibitors with Selectivity for the First Bromodomain

The bromodomain and extra-terminal (BET) family of proteins includes BRD2, BRD3, BRD4, and the testis-specific protein, BRDT, each containing two N-terminal tandem bromodomain (BRD) modules. Potent and selective inhibitors targeting the two bromodomains are required to elucidate their biological role(s), with potential clinical applications. In this study, we designed and synthesized a series of benzimidazole-6-sulfonamides starting from the azobenzene compounds MS436 (7 a) and MS611 (7 b) that exhibited preference for the first (BD1) over the second (BD2) BRD of BET family members. The most-promising compound (9 a) showed good binding potency and improved metabolic stability and selectivity towards BD1 with respect to the parent compounds.

Searching for Novel Anaplastic Lymphoma Kinase Inhibitors: Structure-Guided Screening of Natural Compounds for a Tyrosine Kinase Therapeutic Target in Cancers

Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase molecular target with broad importance for drug discovery, especially in the field of cancer therapeutics. ALK belongs to the insulin receptor superfamily that is involved in various malignancies, including non-small cell lung cancer, anaplastic large cell lymphoma, and neuroblastoma. ALK has been shown to play a role in cancer progression and metastasis, making it one of the prime targets to develop novel anticancer therapeutics. In this context, natural compounds can be an important resource to unravel novel ALK inhibitors. In this study, we report a structure-based virtual screening of natural compounds from the ZINC database, with an eye to potential inhibitors of ALK. Molecular docking was performed on a natural compound library, and top hits holding good binding affinity, docking score, and specificity toward ALK were selected. The hits were further evaluated based on the PAINS (pan-assay interference compounds) filter, ADMET (absorption, distribution, metabolism, excretion, toxicity) properties, PASS (prediction of activity spectra for substances) analysis, and two-dimensional interaction of protein-ligand complexes. Importantly, two natural compounds (ZINC03845566 and ZINC03999625) were identified as potential candidates for ALK, having appreciable affinity and specificity toward the ALK binding pocket and depicting drug-like properties as predicted from ADMET analysis and their physicochemical parameters. An all-atom molecular dynamics simulation for 100 ns on ALK promised stable ALK-ligand complexes. Hence, we conclude that ZINC03845566 and ZINC03999625 can act as potential ALK inhibitors against cancers where ALK plays a role, for example, in lung cancer, among others. All in all, these findings inform future discovery and translational research for ALK inhibitors as anticancer drugs.

Moringa oleifera Seed at the Interface of Food and Medicine: Effect of Extracts on Some Reproductive Parameters, Hepatic and Renal Histology

The lipid-rich Seed of Moringa oleifera has been promoted as an effective water clarifier. Aside its vital nutritional application as an emerging food additive, the seed has continued to gain a wider acceptance in various global ethnomedicines for managing several communicable and lifestyle diseases, howbeit, its potential toxic effect, particularly on fertility and pregnancy outcomes has remained uninvestigated; the effect of Moringa oleifera seed (MOSE) aqueous-methanol extracts on fertility and pregnancy outcome, was investigated in vivo using female Wistar rats that were divided into 50, 100, 300 and 500 mg per kilogram body weight. Group six was given Moringa oleifera seed treated water ad-libitum (ad-libitum group). Organs harvested for histological assessment included ovary, uterus, liver and kidney. In addition to HPLC fingerprint and a preliminary peptide detection, we determined the physico-chemical characteristics and mineral content of MOSE using standard methods. Data were analyzed with significance at p ≤ 0.05. There was no significant difference in the estrus cycle, mating index, gestation survival index, gestation index, fertility index and sex ratio among all groups. Gestation length was reduced in some groups. While the male pup birth weight was comparable among the different groups, female pups birth weights were significantly reduced in 50 and 100 mg groups. Anogenital distance indices of female pups in ad libitum group were significantly increased. Pathologies were observed in liver and kidneys of dams while kidneys of pups presented a dose dependent reduction in the number of glomeruli. There were no observed pathological changes in the ovary and uterus. This study showed for the first time in rodents, that the lipid-rich MOSE is unsafe to the kidney of rodents while the lipid-free MOSE appears to be safe at doses up to 300 mg/kg body weight. Findings from this study suggested that the female pups were masculinized. In conclusion, the lipid-rich seed extracts of MOSE appear to be unsafe during pregnancy, induce hepatic and renal toxicity while the lipid-free MOSE excludes inherent toxicity as the hydrophobic part has been linked to toxicity as observed in this study due to the developmental programming effect on female offspring in rodents.

Design of a Stable Coamorphous System Using Lactose as an Antiplasticizing Agent for Diphenhydramine Hydrochloride with a Low Glass Transition Temperature

Coamorphous systems comprising small molecules are emerging as counterparts to polymeric solid dispersions. However, the glass transition temperatures (T_gs) of coamorphous materials are relatively low because of the lack of polymeric carriers with higher T_gs. This study aimed to investigate the applicability of lactose (LAC) as an antiplasticizing coformer to a coamorphous system. Diphenhydramine hydrochloride (DPH) was selected as a model drug (T_g = 16 °C). Differential scanning calorimetry showed a comelting point in addition to a decrease in the neat melting points depending on the composition of the physical mixtures, suggesting that the mixture of DPH-LAC was eutectic. The melting point of the eutectic mixture was calculated according to the Schröder-van Laar equation. The heat of fusion of the eutectic mixture was maximized at a 70:30 molar ratio of DPH to LAC; at this point, the melting peaks of the pure components disappeared. The heat flow profiles following the melting and cooling of DPH-LAC physical mixtures at the ratios from 10:90 to 90:10 showed a single T_g, suggesting the formation of a coamorphous system. Lactose showed a T_g of over 100 °C, and the T_g of DPH increased with the molar ratio of LAC; it was 84 °C at a 10:90 molar ratio of DPH to LAC. The Raman image indicated the formation of a homogeneous dispersion of DPH and LAC in the coamorphous system. Peak shifts in the infrared spectra indicated the presence of intermolecular interactions between the amino group of DPH and the hydroxyl group of LAC. Principal component analysis of the infrared spectra revealed a significant change at the 70:30 molar ratio of DPH to LAC, which was in agreement with the results of the thermal analysis. A stability test at 40 °C revealed rapid crystallization of the supercooled liquid DPH. The coamorphous samples containing 10-50% of LAC remained in an amorphous state for 21 days, and no crystallization was observed for the samples containing >60% of LAC for 28 days. The relatively lower T_g (less than 40 °C) of the coamorphous system containing 10-50% of LAC might have caused crystallization during storage. These findings indicate that LAC, which is a safe and widely used pharmaceutical excipient, can be applied to coamorphous systems as an antiplasticizing coformer.

Discovery of Brain-Penetrant Glucosylceramide Synthase Inhibitors with a Novel Pharmacophore

Inhibition of glucosylceramide synthase (GCS) is a major therapeutic strategy for Gaucher's disease and has been suggested as a potential target for treating Parkinson's disease. Herein, we report the discovery of novel brain-penetrant GCS inhibitors. Assessment of the structure-activity relationship revealed a unique pharmacophore in this series. The lipophilic ortho-substituent of aromatic ring A and the appropriate directionality of aromatic ring B were key for potency. Optimization of the absorption, distribution, metabolism, elimination, toxicity (ADMETox) profile resulted in the discovery of T-036, a potent GCS inhibitor in vivo. Pharmacophore-based scaffold hopping was performed to mitigate safety concerns associated with T-036. The ring opening of T-036 resulted in another potent GCS inhibitor with a lower toxicological risk, T-690, which reduced glucosylceramide in a dose-dependent manner in the plasma and cortex of mice. Finally, we discuss the structural aspects of the compounds that impart a unique inhibition mode and lower the cardiovascular risk.

The Synthesis of 12β-Methyl-18-nor-Avicholic Acid Analogues as Potential TGR5 Agonists†

In the quest for new modulators of the Farnesoid-X (FXR) and Takeda G-protein-coupled (TGR5) receptors, bile acids are a popular candidate for drug development. Recently, bile acids endowed with a...

Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein-Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein-protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.

A probable means to an end: exploring P131 pharmacophoric scaffold to identify potential inhibitors of Cryptosporidium parvum inosine monophosphate dehydrogenase

Compound P131 has been established to inhibit Cryptosporidium parvum's inosine monophosphate dehydrogenase (CpIMPDH). Its inhibitory activity supersedes that of paromomycin, which is extensively used in treating cryptosporidiosis. Through the per-residue energy decomposition approach, crucial moieties of P131 were identified and subsequently adopted to create a pharmacophore model for virtual screening in the ZINC database. This search generated eight ADMET-compliant hits that were examined thoroughly to fit into the active site of CpIMPDH via molecular docking. Three compounds ZINC46542062, ZINC58646829, and ZINC89780094, with favorable docking scores of - 8.3 kcal/mol, - 8.2 kcal/mol, and - 7.5 kcal/mol, were selected. The potential inhibitory mechanism of these compounds was probed using molecular dynamics simulation and Molecular Mechanics Generalized Poisson Boltzmann Surface Area (MM/PBSA) analyses. Results revealed that one of the hits (ZINC46542062) exhibited a lower binding free energy of - 39.52 kcal/mol than P131, which had - 34.6 kcal/mol. Conformational perturbation induced by the binding of the identified hits to CpIMPDH was similar to P131, suggesting a similarity in inhibitory mechanisms. Also, in silico investigation of the properties of the hit compounds implied superior physicochemical properties with regards to their synthetic accessibility, lipophilicity, and number of hydrogen bond donors and acceptors in comparison with P131. ZINC46542062 was identified as a promising hit compound with the highest binding affinity to the target protein and favorable physicochemical and pharmacokinetic properties relative to P131. The identified compounds can serve as a basis for conducting further experimental investigations toward the development of anticryptosporidials, which can overcome the challenges of existing therapeutic options. Graphical abstract P131 and the identified compounds docked in the NAD⁺ binding site of Cryptosporidium parvum IMPDH.

Physicochemical Properties, Biotransformation, and Transport Pathways of Established and Newly Approved Medications: A Systematic Review of the Top 200 Most Prescribed Drugs vs. the FDA-Approved Drugs Between 2005 and 2016

BACKGROUND

Enzyme-mediated biotransformation of pharmacological agents is a crucial step in xenobiotic detoxification and drug disposition. Herein, we investigated the metabolism and physicochemical properties of the top 200 most prescribed drugs (established) as well as drugs approved by the US Food and Drug Administration (FDA) between 2005 and 2016 (newly approved).

OBJECTIVE

Our objective was to capture the changing trends in the routes of administration, physicochemical properties, and prodrug medications, as well as the contributions of drug-metabolizing enzymes and transporters to drug clearance.

METHODS

The University of Washington Drug Interaction Database (DIDB^®) as well as other online resources (e.g., CenterWatch.com, Drugs.com, DrugBank.ca, and PubChem.ncbi.nlm.nih.gov) was used to collect and stratify the dataset required for exploring the above-mentioned trends.

RESULTS

Analyses revealed that ~ 90% of all drugs in the established and newly approved drug lists were administered systemically (oral or intravenous). Meanwhile, the portion of biologics (molecular weight > 1 kDa) was 15 times greater in the newly approved list than established drugs. Additionally, there was a 4.5-fold increase in the number of compounds with a high calculated partition coefficient (cLogP > 3) and a high total polar surface area (> 75 Å²) in the newly approved drug vs. the established category. Further, prodrugs in established or newly approved lists were found to be converted to active compounds via hydrolysis, demethylases, and kinases. The contribution of cytochrome P450 (CYP) 3A4, as the major biotransformation pathway, has increased from 40% in the established drug list to 64% in the newly approved drug list. Moreover, the role of CYP1A2, CYP2C19, and CYP2D6 were decreased as major metabolizing enzymes among the newly approved medications. Among non-CYP major metabolizers, the contribution of alcohol dehydrogenases/aldehyde dehydrogenases (ADH/ALDH) and sulfotransferases decreased in the newly approved drugs compared with the established list. Furthermore, the highest contribution among uptake and efflux transporters was found for Organic Anion Transporting Polypeptide 1B1 (OATP1B1) and P-glycoprotein (P-gp), respectively.

CONCLUSIONS

The higher portion of biologics in the newly approved drugs compared with the established list confirmed the growing demands for protein- and antibody-based therapies. Moreover, the larger number of hydrophilic drugs found in the newly approved list suggests that the probability of toxicity is likely to decrease. With regard to CYP-mediated major metabolism, CYP3A5 showed an increased involvement owing to the identification of unique probe substrates to differentiate CYP3As. Furthermore, the contribution of OATP1B1 and P-gp did not show a significant shift in the newly approved drugs as compared to the established list because of their broad substrate specificity.

Drug Induced Liver Injury (DILI). Mechanisms and Medicinal Chemistry Avoidance/Mitigation Strategies

Adverse drug reactions (ADRs) are a common cause of attrition in drug discovery and development and drug-induced liver injury (DILI) is a leading cause of preclinical and clinical drug terminations. This perspective outlines many of the known DILI mechanisms and assessment methods used to evaluate and mitigate DILI risk. Literature assessments and retrospective analyses using verified DILI-associated drugs from the Liver Tox Knowledge Base (LTKB) have been used to derive the predictive value of each end point, along with combination approaches of multiple methods. In vitro assays to assess inhibition of the bile salt export pump (BSEP), mitotoxicity, reactive metabolite (RM) formation, and hepatocyte cytolethality, along with physicochemical properties and clinical dose provide useful DILI predictivity. This Perspective also highlights some of the strategies used by medicinal chemists to reduce DILI risk during the optimization of drug candidates.

Most Influential Physicochemical and In Vitro Assay Descriptors for Hepatotoxicity and Nephrotoxicity Prediction

Drug-induced organ injury is a major reason for drug candidate attrition in preclinical and clinical drug development. The liver, kidneys, and heart have been recognized as the most common organ systems affected in safety-related attrition or the subject of black box warnings and postmarket drug withdrawals. In silico physicochemical property calculations and in vitro assays have been utilized separately in the early stages of the drug discovery and development process to predict drug safety. In this study, we combined physicochemical properties and in vitro cytotoxicity assays including mitochondrial dysfunction to build organ-specific univariate and multivariable logistic regression models to achieve odds ratios for the prediction of clinical hepatotoxicity, nephrotoxicity, and cardiotoxicity using 215 marketed drugs. The multivariable hepatotoxic predictive model showed an odds ratio of 6.2 (95% confidence interval (CI) 1.7-22.8) or 7.5 (95% CI 3.2-17.8) for mitochondrial inhibition or drug plasma C_max >1 μM for drugs associated with liver injury, respectively. The multivariable nephrotoxicity predictive model showed an odds ratio of 5.8 (95% CI 2.0-16.9), 6.4 (95% CI 1.1-39.3), or 15.9 (95% CI 2.8-89.0) for drug plasma C_max >1 μM, mitochondrial inhibition, or hydrogen-bond-acceptor atoms >7 for drugs associated with kidney injury, respectively. Conversely, drugs with a total polar surface area ≥75 Å were 79% (odds ratio 0.21, 95% CI 0.061-0.74) less likely to be associated with kidney injury. Drugs belonging to the extended clearance classification system (ECCS) class 4, where renal secretion is the primary clearance mechanism (low permeability drugs that are bases/neutrals), were 4 (95% CI 1.8-9.5) times more likely to to be associated with kidney injury with this data set. Alternatively, ECCS class 2 drugs, where hepatic metabolism is the primary clearance (high permeability drugs that are bases/neutrals) were 77% less likely (odds ratio 0.23 95% CI 0.095-0.54) to to be associated with kidney injury. A cardiotoxicity model was poorly defined using any of these drug physicochemical attributes. Combining in silico physicochemical properties descriptors along with in vitro toxicity assays can be used to build predictive toxicity models to select small molecule therapeutics with less potential to cause liver and kidney organ toxicity.

Utility of Physicochemical Properties for the Prediction of Toxicological Outcomes: Takeda Perspective

The role that physicochemical properties play toward increasing the likelihood of toxicity findings in in vivo studies has been well reported, albeit sometimes with different conclusions. We decided to understand the role that physicochemical properties play toward the prediction of in vivo toxicological outcomes for Takeda chemistry using 284 internal compounds. In support of the previously reported "3/75 rule", reducing lipophilicity of molecules decreases toxicity odds noticeably; however, we also found that the trend of toxicity odds is different between compounds classified by their ionization state. For basic molecules, the odds of in vivo toxicity outcomes were significantly impacted by both lipophilicity and polar surface area, whereas neutral molecules were impacted less so. Through an analysis of several project-related compounds, we herein demonstrate that the utilization of the 3/75 rule coupled with consideration of ionization state is a rational strategy for medicinal chemistry design of safer drugs.

Promiscuity of in Vitro Secondary Pharmacology Assays and Implications for Lead Optimization Strategies

We conducted an analysis on screening data generated from 1445 compounds against a panel of 130 enzymes, ion channels, and receptors to assess secondary pharmacological risks. Hit rates of these targets as well as physicochemical properties for those hits were evaluated. A majority of targets yielded hits with higher clogP, molecular weight, and more basic character than inactive compounds. Although most targets favored lipophilic hits, the average clogP of hits at a given target did not correlate with its hit rate. Furthermore, a matched pair analysis was completed to determine structural changes that impacted off-target activities. A correlation of binding assays used in this analysis illustrated that some pharmacologically related binding assays are highly correlative and may be substituted for a smaller set of surrogate assays.

Exploring the Chemical Space of Cytochrome P450 Inhibitors Using Integrated Physicochemical Parameters, Drug Efficiency Metrics and Decision Tree Models

The cytochrome P450s (CYPs) play a central role in the metabolism of various endogenous and exogenous compounds including drugs. CYPs are vulnerable to inhibition and induction which can lead to adverse drug reactions. Therefore, insights into the underlying mechanism of CYP450 inhibition and the estimation of overall CYP inhibitor properties might serve as valuable tools during the early phases of drug discovery. Herein, we present a large data set of inhibitors against five major metabolic CYPs (CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) for the evaluation of important physicochemical properties and ligand efficiency metrics to define property trends across various activity levels (active, efficient and inactive). Decision tree models for CYP inhibition were developed with an accuracy >90% for both the training set and 10-folds cross validation. Overall, molecular weight (MW), hydrogen bond acceptors/donors (HBA/HBD) and lipophilicity (clogP/logPo/w) represent important physicochemical descriptors for CYP450 inhibitors. However, highly efficient CYP inhibitors show mean MW, HBA, HBD and logP values between 294.18–482.40,5.0–8.2,1–7.29 and 1.68–2.57, respectively. Our results might help in optimization of toxicological profiles associated with new chemical entities (NCEs), through a better understanding of inhibitor properties leading to CYP-mediated interactions.

Overcoming the Blood-Brain Barrier: The Role of Nanomaterials in Treating Neurological Diseases

Therapies directed toward the central nervous system remain difficult to translate into improved clinical outcomes. This is largely due to the blood-brain barrier (BBB), arguably the most tightly regulated interface in the human body, which routinely excludes most therapeutics. Advances in the engineering of nanomaterials and their application in biomedicine (i.e., nanomedicine) are enabling new strategies that have the potential to help improve our understanding and treatment of neurological diseases. Herein, the various mechanisms by which therapeutics can be delivered to the brain are examined and key challenges facing translation of this research from benchtop to bedside are highlighted. Following a contextual overview of the BBB anatomy and physiology in both healthy and diseased states, relevant therapeutic strategies for bypassing and crossing the BBB are discussed. The focus here is especially on nanomaterial-based drug delivery systems and the potential of these to overcome the biological challenges imposed by the BBB. Finally, disease-targeting strategies and clearance mechanisms are explored. The objective is to provide the diverse range of researchers active in the field (e.g., material scientists, chemists, engineers, neuroscientists, and clinicians) with an easily accessible guide to the key opportunities and challenges currently facing the nanomaterial-mediated treatment of neurological diseases.

Rapid experimental measurements of physicochemical properties to inform models and testing

The structures and physicochemical properties of chemicals are important for determining their potential toxicological effects, toxicokinetics, and route(s) of exposure. These data are needed to prioritize the risk for thousands of environmental chemicals, but experimental values are often lacking. In an attempt to efficiently fill data gaps in physicochemical property information, we generated new data for 200 structurally diverse compounds, which were rigorously selected from the USEPA ToxCast chemical library, and whose structures are available within the Distributed Structure-Searchable Toxicity Database (DSSTox). This pilot study evaluated rapid experimental methods to determine five physicochemical properties, including the log of the octanol:water partition coefficient (known as log(Kow) or logP), vapor pressure, water solubility, Henry's law constant, and the acid dissociation constant (pKa). For most compounds, experiments were successful for at least one property; log(Kow) yielded the largest return (176 values). It was determined that 77 ToxPrint structural features were enriched in chemicals with at least one measurement failure, indicating which features may have played a role in rapid method failures. To gauge consistency with traditional measurement methods, the new measurements were compared with previous measurements (where available). Since quantitative structure-activity/property relationship (QSAR/QSPR) models are used to fill gaps in physicochemical property information, 5 suites of QSPRs were evaluated for their predictive ability and chemical coverage or applicability domain of new experimental measurements. The ability to have accurate measurements of these properties will facilitate better exposure predictions in two ways: 1) direct input of these experimental measurements into exposure models; and 2) construction of QSPRs with a wider applicability domain, as their predicted physicochemical values can be used to parameterize exposure models in the absence of experimental data.

Computer-Aided Drug Design: An Overview

The term drug design describes the search of novel compounds with biological activity, on a systematic basis. In its most common form, it involves modification of a known active scaffold or linking known active scaffolds, although de novo drug design (i.e., from scratch) is also possible. Though highly interrelated, identification of active scaffolds should be conceptually separated from drug design. Traditionally, the drug design process has focused on the molecular determinants of the interactions between the drug and its known or intended molecular target. Nevertheless, current drug design also takes into consideration other relevant processes than influence drug efficacy and safety (e.g., bioavailability, metabolic stability, interaction with antitargets).This chapter provides an overview on possible approaches to identify active scaffolds (including in silico approximations to approach that task) and computational methods to guide the subsequent optimization process. It also discusses in which situations each of the overviewed techniques is more appropriate.

Computational Toxicology Methods in Chemical Library Design and High-Throughput Screening Hit Validation

The discovery of molecular toxicity in a clinical drug candidate can have a significant impact on both the cost and timeline of the drug discovery process. Early identification of potentially toxic compounds during screening library preparation or, alternatively, during the hit validation process, is critical to ensure that valuable time and resources are not spent pursuing compounds that may possess a high propensity for human toxicity. This chapter focuses on the application of computational molecular filters, applied either prescreening or postscreening, to identify and remove known reactive and/or potentially toxic compounds from consideration in drug discovery campaigns.

Carcinogenic potential of sanguinarine, a phytochemical used in 'therapeutic' black salve and mouthwash

Black salves are escharotic skin cancer therapies in clinical use since the mid 19th century. Sanguinaria canadensis, a major ingredient of black salve formulations, contains a number of bioactive phytochemicals including the alkaloid sanguinarine. Despite its prolonged history of clinical use, conflicting experimental results have prevented the carcinogenic potential of sanguinarine from being definitively determined. Sanguinarine has a molecular structure similar to known polyaromatic hydrocarbon carcinogens and is a DNA intercalator. Sanguinarine also generates oxidative and endoplasmic reticulum stress resulting in the unfolded protein response and the formation of 8-hydroxyguanine genetic lesions. Sanguinarine has been the subject of contradictory in vitro and in vivo genotoxicity and murine carcinogenesis test results that have delayed its carcinogenic classification. Despite this, epidemiological studies have linked mouthwash that contains sanguinarine with the development of oral leukoplakia. Sanguinarine is also proposed as an aetiological agent in gallbladder carcinoma. This literature review investigates the carcinogenic potential of sanguinarine. Reasons for contradictory genotoxicity and carcinogenesis results are explored, knowledge gaps identified and a strategy for determining the carcinogenic potential of sanguinarine especialy relating to black salve are discussed. As patients continue to apply black salve, especially to skin regions suffering from field cancerization and skin malignancies, an understanding of the genotoxic and carcinogenic potential of sanguinarine is of urgent clinical relevance.

Medicinal and Biological Chemistry (MBC) Library: An Efficient Source of New Hits

Identification of new hits is one of the biggest challenges in drug discovery. Creating a library of well-characterized drug-like compounds is a key step in this process. Our group has developed an in-house chemical library called the Medicinal and Biological Chemistry (MBC) library. This collection has been successfully used to start several medicinal chemistry programs and developed in an accumulation of more than 30 years of experience in drug design and discovery of new drugs for unmet diseases. It contains over 1000 compounds, mainly heterocyclic scaffolds. In this work, analysis of drug-like properties and comparative study with well-known libraries by using different computer software are presented here.

Development of 2-aminooxazoline 3-azaxanthene β-amyloid cleaving enzyme (BACE) inhibitors with improved selectivity against Cathepsin D

As part of an ongoing effort at Amgen to develop a disease-modifying therapy for Alzheimer's disease, we have previously used the aminooxazoline xanthene (AOX) scaffold to generate potent and orally efficacious BACE1 inhibitors. While AOX-BACE1 inhibitors demonstrated acceptable cardiovascular safety margins, a retinal pathological finding in rat toxicological studies demanded further investigation. It has been widely postulated that such retinal toxicity might be related to off-target inhibition of Cathepsin D (CatD), a closely related aspartyl protease. We report the development of AOX-BACE1 inhibitors with improved selectivity against CatD by following a structure- and property-based approach. Our efforts culminated in the discovery of a picolinamide-substituted 3-aza-AOX-BACE1 inhibitor absent of retinal effects in an early screening rat toxicology study.

Designing safer oral drugs

Designing an oral drug such that its estimated dose to humans is both efficacious and safe is challenging. During the early design stage, where in vitro or preclinical species in vivo safety data are limited, heuristic-based criteria often related to physicochemical properties are used for guidance. The causal relationship between a compound's log P and its human in vivo toxicity is considered. With respect to designing efficacious oral drugs that potentially have reduced toxicity liabilities, an alternative heuristic-based criterion is proposed based on the amount of compound in the body at steady state. In humans, a threshold for the amount of compound in the body at steady state of 0.5 mg kg-1 is suggested. The criterion is based on the minimum toxic blood-plasma concentration that produces clinically relevant side effects or symptoms in humans for 242 oral drugs. It can be used to estimate a therapeutic window against which a compound's estimated in vivo plasma levels for a particular dose size and frequency can be assessed. The relationship between this criterion and acceptable oral dose sizes for different charge types with different in vivo plasma clearances is discussed.

Selectivity Determination of a Small Molecule Chemical Probe Using Protein Microarray and Affinity Capture Techniques

Small molecule selectivity is an essential component of candidate drug selection and target validation. New technologies are required to better understand off-target effects, with particular emphasis needed on broad protein profiling. Here, we describe the use of a tritiated chemical probe and a 9000 human protein microarray to discern the binding selectivity of an inhibitor of the mRNA decapping scavenger enzyme DcpS. An immobilized m⁷GTP resin was also used to assess the selectivity of a DcpS inhibitor against mRNA cap-associated proteins in whole cell extracts. These studies confirm the exquisite selectivity of diaminoquinazoline DcpS inhibitors, and highlight the utility of relatively simple protein microarray and affinity enrichment technologies in drug discovery and chemical biology.

On the translocation of bacteria and their lipopolysaccharides between blood and peripheral locations in chronic, inflammatory diseases: the central roles of LPS and LPS-induced cell death

We have recently highlighted (and added to) the considerable evidence that blood can contain dormant bacteria. By definition, such bacteria may be resuscitated (and thus proliferate). This may occur under conditions that lead to or exacerbate chronic, inflammatory diseases that are normally considered to lack a microbial component. Bacterial cell wall components, such as the endotoxin lipopolysaccharide (LPS) of Gram-negative strains, are well known as potent inflammatory agents, but should normally be cleared. Thus, their continuing production and replenishment from dormant bacterial reservoirs provides an easy explanation for the continuing, low-grade inflammation (and inflammatory cytokine production) that is characteristic of many such diseases. Although experimental conditions and determinants have varied considerably between investigators, we summarise the evidence that in a great many circumstances LPS can play a central role in all of these processes, including in particular cell death processes that permit translocation between the gut, blood and other tissues. Such localised cell death processes might also contribute strongly to the specific diseases of interest. The bacterial requirement for free iron explains the strong co-existence in these diseases of iron dysregulation, LPS production, and inflammation. Overall this analysis provides an integrative picture, with significant predictive power, that is able to link these processes via the centrality of a dormant blood microbiome that can resuscitate and shed cell wall components.

Plate-based diversity subset screening generation 2: an improved paradigm for high-throughput screening of large compound files

High-throughput screening (HTS) is an effective method for lead and probe discovery that is widely used in industry and academia to identify novel chemical matter and to initiate the drug discovery process. However, HTS can be time consuming and costly and the use of subsets as an efficient alternative to screening entire compound collections has been investigated. Subsets may be selected on the basis of chemical diversity, molecular properties, biological activity diversity or biological target focus. Previously, we described a novel form of subset screening: plate-based diversity subset (PBDS) screening, in which the screening subset is constructed by plate selection (rather than individual compound cherry-picking), using algorithms that select for compound quality and chemical diversity on a plate basis. In this paper, we describe a second-generation approach to the construction of an updated subset: PBDS2, using both plate and individual compound selection, that has an improved coverage of the chemical space of the screening file, whilst only selecting the same number of plates for screening. We describe the validation of PBDS2 and its successful use in hit and lead discovery. PBDS2 screening became the default mode of singleton (one compound per well) HTS for lead discovery in Pfizer.

Development of a Novel Quantitative Structure-Activity Relationship Model to Accurately Predict Pulmonary Absorption and Replace Routine Use of the Isolated Perfused Respiring Rat Lung Model

Purpose

We developed and tested a novel Quantitative Structure-Activity Relationship (QSAR) model to better understand the physicochemical drivers of pulmonary absorption, and to facilitate compound design through improved prediction of absorption. The model was tested using a large array of both existing and newly designed compounds.

Methods

Pulmonary absorption data was generated using the isolated perfused respiring rat lung (IPRLu) model for 82 drug discovery compounds and 17 marketed drugs. This dataset was used to build a novel QSAR model based on calculated physicochemical properties. A further 9 compounds were used to test the model’s predictive capability.

Results

The QSAR model performed well on the 9 compounds in the “Test set” with a predicted versus observed correlation of R² = 0.85, and >65% of compounds correctly categorised. Calculated descriptors associated with permeability and hydrophobicity positively correlated with pulmonary absorption, whereas those associated with charge, ionisation and size negatively correlated.

Conclusions

The novel QSAR model described here can replace routine generation of IPRLu model data for ranking and classifying compounds prior to synthesis. It will also provide scientists working in the field of inhaled drug discovery with a deeper understanding of the physicochemical drivers of pulmonary absorption based on a relevant respiratory compound dataset.

IDAAPM: integrated database of ADMET and adverse effects of predictive modeling based on FDA approved drug data

Background

The disposition of a pharmaceutical compound within an organism, i.e. its Absorption, Distribution, Metabolism, Excretion, Toxicity (ADMET) properties and adverse effects, critically affects late stage failure of drug candidates and has led to the withdrawal of approved drugs. Computational methods are effective approaches to reduce the number of safety issues by analyzing possible links between chemical structures and ADMET or adverse effects, but this is limited by the size, quality, and heterogeneity of the data available from individual sources. Thus, large, clean and integrated databases of approved drug data, associated with fast and efficient predictive tools are desirable early in the drug discovery process.

Description

We have built a relational database (IDAAPM) to integrate available approved drug data such as drug approval information, ADMET and adverse effects, chemical structures and molecular descriptors, targets, bioactivity and related references. The database has been coupled with a searchable web interface and modern data analytics platform (KNIME) to allow data access, data transformation, initial analysis and further predictive modeling. Data were extracted from FDA resources and supplemented from other publicly available databases. Currently, the database contains information regarding about 19,226 FDA approval applications for 31,815 products (small molecules and biologics) with their approval history, 2505 active ingredients, together with as many ADMET properties, 1629 molecular structures, 2.5 million adverse effects and 36,963 experimental drug-target bioactivity data.

Conclusion

IDAAPM is a unique resource that, in a single relational database, provides detailed information on FDA approved drugs including their ADMET properties and adverse effects, the corresponding targets with bioactivity data, coupled with a data analytics platform. It can be used to perform basic to complex drug-target ADMET or adverse effects analysis and predictive modeling. IDAAPM is freely accessible at http://idaapm.helsinki.fi and can be exploited through a KNIME workflow connected to the database.Graphical abstract

Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices

Needs for fast, yet reliable means of assessing the lipophilicities of diverse compounds resulted in the development of various in silico and chromatographic approaches that are faster, cheaper, and greener compared to the traditional shake-flask method. However, at present no accepted "standard" approach exists for their comparison and selection of the most appropriate one(s). This is of utmost importance when it comes to the development of new lipophilicity indices, or the assessment of the lipophilicity of newly synthesized compounds. In this study, 50 well-known, diverse compounds of significant pharmaceutical and environmental importance have been selected and examined. Octanol-water partition coefficients have been measured with the shake-flask method for most of them. Their retentions have been studied in typical reversed thin-layer chromatographic systems, involving the most frequently employed stationary phases (octadecyl- and cyano-modified silica), and acetonitrile and methanol as mobile phase constituents. Twelve computationally estimated logP-s and twenty chromatographic indices together with the shake-flask octanol-water partition coefficient have been investigated with classical chemometric approaches-such as principal component analysis (PCA), hierarchical cluster analysis (HCA), Pearson's and Spearman's correlation matrices, as well as novel non-parametric methods: sum of ranking differences (SRD) and generalized pairwise correlation method (GPCM). Novel SRD and GPCM methods have been introduced based on the Comparisons with One VAriable (lipophilicity metric) at a Time (COVAT). For the visualization of COVAT results, a heatmap format was introduced. Analysis of variance (ANOVA) was applied to reveal the dominant factors between computational logPs and various chromatographic measures. In consensus-based comparisons, the shake-flask method performed the best, closely followed by computational estimates, while the chromatographic estimates often overlap with in silico assessments, mostly with methods involving octadecyl-modified silica stationary phases. The ones that employ cyano-modified silica perform generally worse. The introduction of alternative coloring schemes for the covariance matrices and SRD/GPCM heatmaps enables the discovery of intrinsic relationships among lipophilicity scales and the selection of best/worst measures. Closest to the recommended logKOW values are ClogP and the first principal component scores obtained on octadecyl-silica stationary phase in combination with methanol-water mobile phase, while the usage of slopes derived from Soczewinski-Matyisik equation should be avoided.

Current and Future Perspectives on the Development, Evaluation, and Application of in Silico Approaches for Predicting Toxicity

Exploiting non-testing approaches to predict toxicity early in the drug discovery development cycle is a helpful component in minimizing expensive drug failures due to toxicity being identified in late development or even during clinical trials. Changes in regulations in the industrial chemicals and cosmetics sectors in recent years have prompted a significant number of advances in the development, application, and assessment of non-testing approaches, such as (Q)SARs. Many efforts have also been undertaken to establish guiding principles for performing read-across within category and analogue approaches. This review offers a perspective, as taken from these sectors, of the current status of non-testing approaches, their evolution in light of the advances in high-throughput approaches and constructs such as adverse outcome pathways, and their potential relevance for drug discovery. It also proposes a workflow for how non-testing approaches could be practically integrated within testing and assessment strategies.

Profiling the estimated plasma concentrations of 215 marketed oral drugs

The human pharmacokinetic parameters of 215 marketed oral drugs have been collated and their estimated plasma concentrations (following repeat dosing) profiled against time using a one-compartment model.

Computational toxicology

Predictive toxicology plays a critical role in reducing the failure rate of new drugs in pharmaceutical research and development. Despite recent gains in our understanding of drug-induced toxicity, however, it is urgent that the utility and limitations of our current predictive tools be determined in order to identify gaps in our understanding of mechanistic and chemical toxicology. Using recently published computational regression analyses of in vitro and in vivo toxicology data, it will be demonstrated that significant gaps remain in early safety screening paradigms. More strategic analyses of these data sets will allow for a better understanding of their domain of applicability and help identify those compounds that cause significant in vivo toxicity but which are currently mis-predicted by in silico and in vitro models. These ‘outliers’ and falsely predicted compounds are metaphorical lighthouses that shine light on existing toxicological knowledge gaps, and it is essential that these compounds are investigated if attrition is to be reduced significantly in the future. As such, the modern computational toxicologist is more productively engaged in understanding these gaps and driving investigative toxicology towards addressing them.

In silico ADME/T modelling for rational drug design

In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.

A novel drug discovery strategy: mechanistic investigation of an enantiomeric antitumor agent targeting dual p53 and NF-κB pathways

The p53 and nuclear factor κB (NF-κB) pathways play crucial roles in human cancer development. Simultaneous targeting of both pathways is an attractive therapeutic strategy against cancer. In this study, we report an antitumor molecule that bears a pyrrolo[3,4-c]pyrazole scaffold and functions as an enantiomeric inhibitor against both the p53-MDM2 interaction and the NF-κB activation. It is a first-in-class enantiomeric inhibitor with dual efficacy for cancer therapy. Synergistic effect was observed in vitro and in vivo. Docking and molecular dynamics simulation studies further provided insights into the nature of stereoselectivity.