A practical guide to secondary pharmacology in drug discovery

Recapitulating the potential contribution of protein S-palmitoylation in cancer

Protein S-palmitoylation is a reversible form of protein lipidation in which the formation of a thioester bond occurs between a cysteine (Cys) residue of a protein and a 16-carbon fatty acid chain. This modification is catalyzed by a family of palmitoyl acyl transferases, the DHHC enzymes, so called because of their Asp-His-His-Cys (DHHC) catalytic motif. Deregulation of DHHC enzymes has been linked to various diseases, including cancer and infections. Cancer, a major cause of global mortality, is characterized by features like uncontrolled cell growth, resistance to cell death, angiogenesis, invasion, and metastasis. Several of these processes are controlled by DHHC-mediated S-palmitoylation of oncogenes or tumor suppressors, including growth factor receptors (e.g., EGFR), kinases (e.g., AKT), and transcription factors (e.g., β-catenin). Dynamic regulation of S-palmitoylation is also governed by protein depalmitoylases. These enzymes balance the cycling of palmitoylation and regulate cellular signaling, cell growth, and its organization. Given the significance of S-palmitoylation in cancer, the DHHCs and protein depalmitoylases are promising targets for cancer therapy. Here we summarize the catalytic mechanisms of DHHC enzymes and depalmitoylases, their role in cancer progression and prevention, as well as the crosstalk of palmitoylation with other post-translational modifications. Additionally, we discuss the methods to detect S-palmitoylation, the limitations of available DHHC-targeting inhibitors, and ongoing research efforts to address these obstacles.

DFT, Molecular Docking, ADME, and Cardiotoxicity Studies of Persuasive Thiazoles as Potential Inhibitors of the Main Protease of SARS-CoV-2

This study explores the capability of thiazoles as potent inhibitors of SARS-CoV-2 Mpro. Seventeen thiazoles (1-17) were screened for their linking affinity with the active site of SARS-CoV-2 Mpro and compared with the FDA-recommended antiviral drugs, Remdesivir and Baricitinib. Density Functional Theory (DFT) calculations provided electronic and energetic properties of these ligands, shedding light on their stability and reactivity. Molecular docking analysis revealed that thiazole derivatives exhibited favorable linking affinities with various functional sites of SARS-CoV-2 proteins, including spike receptor-linking zone, nucleocapsid protein N-terminal RNA linking zone, and Mpro. Notably, compounds 3, 10, and 12 displayed the best interaction with 6LZG as compared to FDA-approved antiviral drugs Remdesivir and Baricitinib, while compounds 1, 10, and 8 exhibited strong linking with 6 M3 M and also better than Remdesivir and Baricitinib. Additionally, compounds 3, 1, and 6 showed promising interactions with 6LU7 but only compound 3 performed better than Baricitinib. An ADME (Absorption, Distribution, Metabolism, and Excretion) study provided insights into the pharmacokinetics and drug-likeness of these compounds, with all ligands demonstrating good physicochemical characteristics, lipophilicity, water solubility, pharmacokinetics, drug-likeness, and medicinal chemistry attributes. The results suggest that these selected thiazole derivatives hold promise as potential candidates for further drug development.

Importance of tailored non-clinical safety testing of novel antimalarial drugs: Industry best-practice

Malaria is an acute, debilitating parasitic illness. There were 249 million cases of malaria in 2022, resulting in 608,000 deaths globally, 76% of which were children ≤5 years. The unique nature of this disease (recurrences leading to re-treatments and numerous organ systems affected), specific clinical treatment regimens, poor compliance, and diversity of affected populations (predominantly pediatrics, women of childbearing potential, pregnant and lactating women), often makes standard testing approaches inadequate, and tailor-made safety assessments are more appropriate. We provide best practice recommendations based on company experience for the non-clinical safety assessment of antimalarial drugs, with a focus on small molecules since they represent the majority of drug candidates for this illness. We focus on specific testing considerations for repeat dose toxicity studies, including combination toxicity assessments, since new drug treatment regimens typically foresee short treatment durations to improve compliance (i.e., 1 day) with combinations of compounds to improve efficacy and limit potential resistance. Due to the target population, the timing of reproductive, developmental, and juvenile toxicity studies may be earlier than general testing roadmaps for other small molecule drugs. In conclusion, key recommendations presented should enable a more effective and efficient development path whilst protecting clinical trial participants and patients.

Predicting clinical outcomes from off-target receptor interactions using Secondary Intelligence™

Adverse effects due to off-target activity can be predicted by careful comparison of the relationship between expected plasma concentration and off-target activity of the test compound with that of reference drugs targeting that receptor for their therapeutic efficacy. The ratio between plasma concentration (unbound) and the Ki at the receptor is a surrogate measure reflecting receptor occupancy. Where data are available for reference drugs, we have curated and evaluated this at 100 receptors, 72 of which can involve both negative and positive modulations by drugs: a total of 172 'receptor modulations'. This provides a quantitative framework upon which to achieve consistent risk assessment of off-target interactions across receptors, across compounds and between assessors. It therefore represents a significant departure from an opinion-based to an evidence-based approach to secondary pharmacology. Demonstration of proof-of-principle was achieved for one of the receptor interactions (α1A-adrenoceptor antagonism leading to postural hypotension in clinical use) due to the availability of high-quality off-target Ki data for >30 drugs at this receptor.

In vitro pharmacologic profiling aids systemic toxicity assessment of chemicals

An adapted in vitro pharmacology profiling panel (APPP) was developed that included targets used in the pharmaceutical industry alongside additional targets whose cellular functions have been linked to systemic toxicities. This panel of 83 target assays was used to profile the activities of 129 cosmetic relevant chemicals with diverse chemical structures, physiochemical properties and cosmetic use types. Internal data consistency was proved robust, as evidenced by the reproducibility between single concentration and concentration-response data and showed good concordance with data reported in the ToxCast and drug excipient datasets. We discuss how the data can be analyzed and multiple potential contexts of use illustrated by case studies, alongside other new approach methodologies, to support cosmetic chemical risk assessments that do not require data from new animal studies.

Assessing the interplay between off-target promiscuity, cytotoxicity, and tolerability in rodents to improve the safety profile of novel anti-malarial plasmepsin X inhibitors

Within drug development, high off-target promiscuity as well as potent cytotoxicity, are associated with a high attrition rate. We investigated the safety profile of novel plasmepsin X (PMX) inhibitors for the treatment of malaria. In our screening cascade, a total of 249 PMX compounds were profiled in a panel of in vitro secondary pharmacology assays containing 44 targets (SafetyScreen44 panel) and in a cytotoxicity assay in HepG2 cells using ATP as an endpoint. Six of the lead compounds were subsequently tested in a 7-d rat toxicology study, and/or in a cardiovascular study in guinea pigs. Overall, compounds with high cytotoxicity in HepG2 cells correlated with high promiscuity (off-target hit rate >20%) in the SafetyScreen44 panel and were associated with poor tolerability in vivo (decedents, morbidity, adverse clinical signs, or severe cardiovascular effects). Some side effects observed in rats or guinea pigs could putatively be linked with hits in the secondary pharmacological profiling, such as the M1 or M2 muscarinic acetylcholine receptor, opioid µ and/or κ receptors or hERG/CaV1.2/Na+ channels, which were common to >50% the compounds tested in vivo. In summary, compounds showing high cytotoxicity and high promiscuity are likely to be poorly tolerated in vivo. However, such associations do not necessarily imply a causal relationship. Identifying the targets that cause these undesirable effects is key for early safety risk assessment. A tiered approach, based on a set of in vitro assays, helps selecting the compounds with highest likelihood of success to proceed to in vivo toxicology studies.

The state of the art in secondary pharmacology and its impact on the safety of new medicines

Secondary pharmacology screening of investigational small-molecule drugs for potentially adverse off-target activities has become standard practice in pharmaceutical research and development, and regulatory agencies are increasingly requesting data on activity against targets with recognized adverse effect relationships. However, the screening strategies and target panels used by pharmaceutical companies may vary substantially. To help identify commonalities and differences, as well as to highlight opportunities for further optimization of secondary pharmacology assessment, we conducted a broad-ranging survey across 18 companies under the auspices of the DruSafe leadership group of the International Consortium for Innovation and Quality in Pharmaceutical Development. Based on our analysis of this survey and discussions and additional research within the group, we present here an overview of the current state of the art in secondary pharmacology screening. We discuss best practices, including additional safety-associated targets not covered by most current screening panels, and present approaches for interpreting and reporting off-target activities. We also provide an assessment of the safety impact of secondary pharmacology screening, and a perspective on opportunities and challenges in this rapidly developing field.

Preclinical mitigation of 5-HT2B agonism-related cardiac valvulopathy revisited

Cardiac valvulopathy (Cardiac Valve Disease; CVD) associated with off-target activation of the 5-hydroxytryptamine (5-HT) 2B receptor has been well recognized, but is still poorly predicted during drug development. The regulatory guidance proposes the use of 5-HT2B binding data (i.e., Ki values) and free maximum therapeutic exposure (Cmax) to calculate safety margins as a threshold of detection (>10) for eliminating the risk of drug-induced cardiac valvulopathy. In this paper, we provide additional recommendations for preclinical prediction of CVD risk based on clinical pharmacodynamic and pharmacokinetic data obtained from drugs with or without 5-HT2B receptor activation. Our investigations showed that 5-HT2B agonist affinity of molecules tested in an in vitro 5-HT2B cell-based functional assay, placed in perspective to their sustained plasma exposure (AUCs) and not to their peak plasma exposure, Cmax (i.e., maximum therapeutic exposure) provide a solid basis for interpreting 5-HT2B data, for calculating safety margins and then, accurately differentiate drugs associated with a clinical risk of CVD from those which are not (despite having some agonist 5-HT2B activity). In addition, we discuss the risk of multi-organ fibrosis linked to 5-HT2B receptor activation, often underestimated, however well reported in FAERS for 5-HT2B agonists. We believe that our recommendations have the potential to mitigate the risk for the clinical development of CVD and fibrosis.

ICH S1 prospective evaluation study and weight of evidence assessments: commentary from industry representatives

Industry representatives on the ICH S1B(R1) Expert Working Group (EWG) worked closely with colleagues from the Drug Regulatory Authorities to develop an addendum to the ICH S1B guideline on carcinogenicity studies that allows for a weight-of-evidence (WoE) carcinogenicity assessment in some cases, rather than conducting a 2-year rat carcinogenicity study. A subgroup of the EWG composed of regulators have published in this issue a detailed analysis of the Prospective Evaluation Study (PES) conducted under the auspices of the ICH S1B(R1) EWG. Based on the experience gained through the Prospective Evaluation Study (PES) process, industry members of the EWG have prepared the following commentary to aid sponsors in assessing the standard WoE factors, considering how novel investigative approaches may be used to support a WoE assessment, and preparing appropriate documentation of the WoE assessment for presentation to regulatory authorities. The commentary also reviews some of the implementation challenges sponsors must consider in developing a carcinogenicity assessment strategy. Finally, case examples drawn from previously marketed products are provided as a supplement to this commentary to provide additional examples of how WoE criteria may be applied. The information and opinions expressed in this commentary are aimed at increasing the quality of WoE assessments to ensure the successful implementation of this approach.

Developing a pragmatic consensus procedure supporting the ICH S1B(R1) weight of evidence carcinogenicity assessment

The ICH S1B carcinogenicity global testing guideline has been recently revised with a novel addendum that describes a comprehensive integrated Weight of Evidence (WoE) approach to determine the need for a 2-year rat carcinogenicity study. In the present work, experts from different organizations have joined efforts to standardize as much as possible a procedural framework for the integration of evidence associated with the different ICH S1B(R1) WoE criteria. The framework uses a pragmatic consensus procedure for carcinogenicity hazard assessment to facilitate transparent, consistent, and documented decision-making and it discusses best-practices both for the organization of studies and presentation of data in a format suitable for regulatory review. First, it is acknowledged that the six WoE factors described in the addendum form an integrated network of evidence within a holistic assessment framework that is used synergistically to analyze and explain safety signals. Second, the proposed standardized procedure builds upon different considerations related to the primary sources of evidence, mechanistic analysis, alternative methodologies and novel investigative approaches, metabolites, and reliability of the data and other acquired information. Each of the six WoE factors is described highlighting how they can contribute evidence for the overall WoE assessment. A suggested reporting format to summarize the cross-integration of evidence from the different WoE factors is also presented. This work also notes that even if a 2-year rat study is ultimately required, creating a WoE assessment is valuable in understanding the specific factors and levels of human carcinogenic risk better than have been identified previously with the 2-year rat bioassay alone.

LCK-SafeScreen-Model: An Advanced Ensemble Machine Learning Approach for Estimating the Binding Affinity between Compounds and LCK Target

The lymphocyte-specific protein tyrosine kinase (LCK) is a critical target in leukemia treatment. However, potential off-target interactions involving LCK can lead to unintended consequences. This underscores the importance of accurately predicting the inhibitory reactions of drug molecules with LCK during the research and development stage. To address this, we introduce an advanced ensemble machine learning technique designed to estimate the binding affinity between molecules and LCK. This comprehensive method includes the generation and selection of molecular fingerprints, the design of the machine learning model, hyperparameter tuning, and a model ensemble. Through rigorous optimization, the predictive capabilities of our model have been significantly enhanced, raising test R2 values from 0.644 to 0.730 and reducing test RMSE values from 0.841 to 0.732. Utilizing these advancements, our refined ensemble model was employed to screen an MCE -like drug library. Through screening, we selected the top ten scoring compounds, and tested them using the ADP-Glo bioactivity assay. Subsequently, we employed molecular docking techniques to further validate the binding mode analysis of these compounds with LCK. The exceptional predictive accuracy of our model in identifying LCK inhibitors not only emphasizes its effectiveness in projecting LCK-related safety panel predictions but also in discovering new LCK inhibitors. For added user convenience, we have also established a webserver, and a GitHub repository to share the project.

Predicting binding between 55 cannabinoids and 4,799 biological targets by in silico methods

Recently, there has been an increase in cannabis-derived products being marketed as foods, dietary supplements, and other consumer products. Cannabis contains over a hundred cannabinoids, many of which have unknown physiological effects. Since there are large numbers of cannabinoids, and many are not commercially available for in vitro testing, an in silico tool (Chemotargets Clarity software) was used to predict binding between 55 cannabinoids and 4,799 biological targets (enzymes, ion channels, receptors, and transporters). This tool relied on quantitative structure activity relationships (QSAR), structural similarity, and other approaches to predict binding. From this screening, 827 cannabinoid-target binding pairs were predicted, which included 143 unique targets. Many cannabinoids sharing core structures (cannabinoid "types") had similar binding profiles, whereas most cannabinoids containing carboxylic acid groups were similar without regards to their core structure. For some of the binding predictions (43), in vitro binding data were available, and they agreed well with in silico binding data (median fourfold difference in binding concentrations). Finally, clinical adverse effects associated with 22 predicted targets were identified from an online database (Clarivate Off-X), providing important insights on potential human health hazards. Overall, in silico biological target predictions are a rapid means to identify potential hazards due to cannabinoid-target interactions, and the data can be used to prioritize subsequent in vitro and in vivo testing.

"Appraisal of state-of-the-art" The 2021 Distinguished Service Award of the Safety Pharmacology Society: Reflecting on the past to tackle challenges ahead

This appraisal of state-of-the-art manuscript highlights and expands upon the thoughts conveyed in the lecture of Dr. Jean-Pierre Valentin, recipient of the 2021 Distinguished Service Award of the Safety Pharmacology Society, given on the 2nd December 2021. The article reflects on the strengths, weaknesses, opportunities, and threats that surrounded the evolution of safety and secondary pharmacology over the last 3 decades with a particular emphasis on pharmaceutical drug development delivery, scientific and technological innovation, complexities of regulatory framework and people leadership and development. The article further built on learnings from past experiences to tackle constantly emerging issues and evolving landscape whilst being cognizant of the challenges facing these disciplines in the broader drug development and societal context.

A Molecular Toolbox of Positron Emission Tomography Tracers for General Anesthesia Mechanism Research

With appropriate radiotracers, positron emission tomography (PET) allows direct or indirect monitoring of the spatial and temporal distribution of anesthetics, neurotransmitters, and biomarkers, making it an indispensable tool for studying the general anesthesia mechanism. In this Perspective, PET tracers that have been recruited in general anesthesia research are introduced in the following order: 1) ¹¹C/¹⁸F-labeled anesthetics, i.e., PET tracers made from inhaled and intravenous anesthetics; 2) PET tracers targeting anesthesia-related receptors, e.g., neurotransmitters and voltage-gated ion channels; and 3) PET tracers for studying anesthesia-related neurophysiological effects and neurotoxicity. The radiosynthesis, pharmacodynamics, and pharmacokinetics of the above PET tracers are mainly discussed to provide a practical molecular toolbox for radiochemists, anesthesiologists, and those who are interested in general anesthesia.

The evolving role of investigative toxicology in the pharmaceutical industry

For decades, preclinical toxicology was essentially a descriptive discipline in which treatment-related effects were carefully reported and used as a basis to calculate safety margins for drug candidates. In recent years, however, technological advances have increasingly enabled researchers to gain insights into toxicity mechanisms, supporting greater understanding of species relevance and translatability to humans, prediction of safety events, mitigation of side effects and development of safety biomarkers. Consequently, investigative (or mechanistic) toxicology has been gaining momentum and is now a key capability in the pharmaceutical industry. Here, we provide an overview of the current status of the field using case studies and discuss the potential impact of ongoing technological developments, based on a survey of investigative toxicologists from 14 European-based medium-sized to large pharmaceutical companies.

Target identification by structure-based computational approaches: Recent advances and perspectives

The use of computational techniques in the early stages of drug discovery has recently experienced a boost, especially in the target identification step. Finding the biological partner(s) for new or existing synthetic and/or natural compounds by "wet" approaches may be challenging; therefore, preliminary in silico screening is even more recommended. After a brief overview of some of the most known target identification techniques, recent advances in structure-based computational approaches for target identification are reported in this digest, focusing on Inverse Virtual Screening and its recent applications. Moreover, future perspectives concerning the use of such methodologies, coupled or not with other approaches, are analyzed.

Are Non-animal Systemic Safety Assessments Protective? A Toolbox and Workflow

An important question in toxicological risk assessment is whether non-animal new approach methodologies (NAMs) can be used to make safety decisions that are protective of human health, without being overly conservative. In this work, we propose a core NAM toolbox and workflow for conducting systemic safety assessments for adult consumers. We also present an approach for evaluating how protective and useful the toolbox and workflow are by benchmarking against historical safety decisions. The toolbox includes physiologically based kinetic (PBK) models to estimate systemic Cmax levels in humans, and 3 bioactivity platforms, comprising high-throughput transcriptomics, a cell stress panel, and in vitro pharmacological profiling, from which points of departure are estimated. A Bayesian model was developed to quantify the uncertainty in the Cmax estimates depending on how the PBK models were parameterized. The feasibility of the evaluation approach was tested using 24 exposure scenarios from 10 chemicals, some of which would be considered high risk from a consumer goods perspective (eg, drugs that are systemically bioactive) and some low risk (eg, existing food or cosmetic ingredients). Using novel protectiveness and utility metrics, it was shown that up to 69% (9/13) of the low risk scenarios could be identified as such using the toolbox, whilst being protective against all (5/5) the high-risk ones. The results demonstrated how robust safety decisions could be made without using animal data. This work will enable a full evaluation to assess how protective and useful the toolbox and workflow are across a broader range of chemical-exposure scenarios.

Matrix Thermal Shift Assay for Fast Construction of Multidimensional Ligand-Target Space

Existing thermal shift-based mass spectrometry approaches are able to identify target proteins without chemical modification of the ligand, but they are suffering from complicated workflows with limited throughput. Herein, we present a new thermal shift-based method, termed matrix thermal shift assay (mTSA), for fast deconvolution of ligand-binding targets and binding affinities at the proteome level. In mTSA, a sample matrix, treated horizontally with five different compound concentrations and vertically with five technical replicates of each condition, was denatured at a single temperature to induce protein precipitation, and then, data-independent acquisition was employed for quick protein quantification. Compared with previous thermal shift assays, the analysis throughput of mTSA was significantly improved, but the costs as well as efforts were reduced. More importantly, the matrix experiment design allowed simultaneous computation of the statistical significance and fitting of the dose-response profiles, which can be combined to enable a more accurate identification of target proteins, as well as reporting binding affinities between the ligand and individual targets. Using a pan-specific kinase inhibitor, staurosporine, we demonstrated a 36% improvement in screening sensitivity over the traditional thermal proteome profiling (TPP) and a comparable sensitivity with a latest two-dimensional TPP. Finally, mTSA was successfully applied to delineate the target landscape of perfluorooctanesulfonic acid (PFOS), a persistent organic pollutant that is hard to perform modification on, and revealed several potential targets that might account for the toxicities of PFOS.

Use of Lhasa Limited Products for the In Silico Prediction of Drug Toxicity

Lhasa Limited have had a role in the in silico prediction of drug and other chemical toxicity for over 30 years. This role has always been multifaceted, both as a provider of predictive software such as Derek Nexus, and as an honest broker for the sharing of proprietary chemical and toxicity data. A changing regulatory environment and the drive for the Replacement, Reduction and Refinement (the 3Rs) of animal testing have led both to increased acceptance of in silico predictions and a desire for the sharing of data to reduce duplicate testing. The combination of these factors has led to Lhasa Limited providing a suite of products and coordinating numerous data-sharing consortia that do indeed facilitate a significant reduction in the testing burden that companies would otherwise be laboring under. Many of these products and consortia can be organized into workflows for specific regulatory use cases, and it is these that will be used to frame the narrative in this chapter.

Characterizing the pharmacokinetics and biodistribution of therapeutic proteins: an industry white paper

Characterization of the pharmacokinetics (PK) and biodistribution of therapeutic proteins (TPs) is a hot topic within the pharmaceutical industry, particularly with an ever-increasing catalog of novel modality TPs. Here, we review the current practices, and provide a summary of extensive cross-company discussions as well as a survey completed by International Consortium for Innovation and Quality (IQ consortium) members on this theme. A wide variety of in vitro, in vivo and in silico techniques are currently used to assess PK and biodistribution of TPs, and we discuss the relevance of these from an industry perspective, focusing on PK/PD understanding at the preclinical stage of development, and translation to human. We consider that the 'traditional in vivo biodistribution study' is becoming insufficient as a standalone tool, and thorough characterization of the interaction of the TP with its target(s), target biology, and off-target interactions at a microscopic scale are key to understand the overall biodistribution at a full-body scale. Our summary of the current challenges and our recommendations to address these issues could provide insight into the implementation of best practices in this area of drug development, and continued cross-company collaboration will be of tremendous value. Significance Statement The Innovation & Quality Consortium (IQ) Translational and ADME Sciences Leadership Group (TALG) working group for the ADME of therapeutic proteins evaluates the current practices, recent advances, and challenges in characterizing the PK and biodistribution of therapeutic proteins during drug development, and proposes recommendations to address these issues. Incorporating the in vitro, in vivo and in silico approaches discussed herein may provide a pragmatic framework to increase early understanding of PK/PD relationships, and aid translational modelling for first-in-human dose predictions.

High-throughput screening for identifying acetylcholinesterase inhibitors: Insights on novel inhibitors and the use of liver microsomes

Rapid, higher throughput, and predictive toxicological methods are needed to assess vast numbers of chemicals with unknown safety profiles. A current effort towards this goal is Toxicology in the 21st Century (Tox21), a United States government consortium using a battery of in vitro assays to screen a library of 10,000 compounds relevant to food, drug, and environmental safety. Recently, we implemented in vitro assays for measuring acetylcholinesterase (AChE) inhibition, a mechanism of toxicity, into Tox21's high-throughput screening campaign (Li S., et al. Environ Health Persp 2021;129:047008, doi:10.1289/EHP6993). In this Commentary, we provide detailed insights on two topics related to our article: (1) prioritizing recently discovered AChE inhibitors from our screening based upon physiological relevance and (2) incorporating human liver microsomes into the AChE inhibition assay to identify metabolically active AChE inhibitors.

Rational Design of Highly Potent, Selective, and Bioavailable SGK1 Protein Kinase Inhibitors for the Treatment of Osteoarthritis

The serine/threonine kinase SGK1 is an activator of the β-catenin pathway and a powerful stimulator of cartilage degradation that is found to be upregulated under genomic control in diseased osteoarthritic cartilage. Today, no oral disease-modifying treatments are available and chronic treatment in this indication sets high requirements for the drug selectivity, pharmacokinetic, and safety profile. We describe the identification of a highly selective druglike 1H-pyrazolo[3,4-d]pyrimidine SGK1 inhibitor 17a that matches both safety and pharmacokinetic requirements for oral dosing. Rational compound design was facilitated by a novel hSGK1 co-crystal structure, and multiple ligand-based computer models were applied to guide the chemical optimization of the compound ADMET and selectivity profiles. Compounds were selected for subchronic proof of mechanism studies in the mouse femoral head cartilage explant model, and compound 17a emerged as a druglike SGK1 inhibitor, with a highly optimized profile suitable for oral dosing as a novel, potentially disease-modifying agent for osteoarthritis.

CNS pharmacology of NKCC1 inhibitors

The Na-K-2Cl cotransporter NKCC1 and the neuron-specific K-Cl cotransporter KCC2 are considered attractive CNS drug targets because altered neuronal chloride regulation and consequent effects on GABAergic signaling have been implicated in numerous CNS disorders. While KCC2 modulators are not yet clinically available, the loop diuretic bumetanide has been used off-label in attempts to treat brain disorders and as a tool for NKCC1 inhibition in preclinical models. Bumetanide is known to have anticonvulsant and neuroprotective effects under some pathophysiological conditions. However, as shown in several species from neonates to adults (mice, rats, dogs, and by extrapolation in humans), at the low clinical doses of bumetanide approved for diuresis, this drug has negligible access into the CNS, reaching levels that are much lower than what is needed to inhibit NKCC1 in cells within the brain parenchyma. Several drug discovery strategies have been initiated over the last ∼15 years to develop brain-permeant compounds that, ideally, should be selective for NKCC1 to eliminate the diuresis mediated by inhibition of renal NKCC2. The strategies employed to improve the pharmacokinetic and pharmacodynamic properties of NKCC1 blockers include evaluation of other clinically approved loop diuretics; development of lipophilic prodrugs of bumetanide; development of side-chain derivatives of bumetanide; and unbiased high-throughput screening approaches of drug discovery based on large chemical compound libraries. The main outcomes are that (1), non-acidic loop diuretics such as azosemide and torasemide may have advantages as NKCC1 inhibitors vs. bumetanide; (2), bumetanide prodrugs lead to significantly higher brain levels than the parent drug and have lower diuretic activity; (3), the novel bumetanide side-chain derivatives do not exhibit any functionally relevant improvement of CNS accessibility or NKCC1 selectivity vs. bumetanide; (4) novel compounds discovered by high-throughput screening may resolve some of the inherent problems of bumetanide, but as yet this has not been achieved. Thus, further research is needed to optimize the design of brain-permeant NKCC1 inhibitors. In parallel, a major challenge is to identify the mechanisms whereby various NKCC1-expressing cellular targets of these drugs within (e.g., neurons, oligodendrocytes or astrocytes) and outside the brain parenchyma (e.g., the blood-brain barrier, the choroid plexus, and the endocrine system), as well as molecular off-target effects, might contribute to their reported therapeutic and adverse effects.

Unexpected similarity between HIV-1 reverse transcriptase and tumor necrosis factor binding sites revealed by computer vision

Rationalizing the identification of hidden similarities across the repertoire of druggable protein cavities remains a major hurdle to a true proteome-wide structure-based discovery of novel drug candidates. We recently described a new computational approach (ProCare), inspired by numerical image processing, to identify local similarities in fragment-based subpockets. During the validation of the method, we unexpectedly identified a possible similarity in the binding pockets of two unrelated targets, human tumor necrosis factor alpha (TNF-α) and HIV-1 reverse transcriptase (HIV-1 RT). Microscale thermophoresis experiments confirmed the ProCare prediction as two of the three tested and FDA-approved HIV-1 RT inhibitors indeed bind to soluble human TNF-α trimer. Interestingly, the herein disclosed similarity could be revealed neither by state-of-the-art binding sites comparison methods nor by ligand-based pairwise similarity searches, suggesting that the point cloud registration approach implemented in ProCare, is uniquely suited to identify local and unobvious similarities among totally unrelated targets.

In silico approaches in organ toxicity hazard assessment: current status and future needs in predicting liver toxicity

Hepatotoxicity is one of the most frequently observed adverse effects resulting from exposure to a xenobiotic. For example, in pharmaceutical research and development it is one of the major reasons for drug withdrawals, clinical failures, and discontinuation of drug candidates. The development of faster and cheaper methods to assess hepatotoxicity that are both more sustainable and more informative is critically needed. The biological mechanisms and processes underpinning hepatotoxicity are summarized and experimental approaches to support the prediction of hepatotoxicity are described, including toxicokinetic considerations. The paper describes the increasingly important role of in silico approaches and highlights challenges to the adoption of these methods including the lack of a commonly agreed upon protocol for performing such an assessment and the need for in silico solutions that take dose into consideration. A proposed framework for the integration of in silico and experimental information is provided along with a case study describing how computational methods have been used to successfully respond to a regulatory question concerning non-genotoxic impurities in chemically synthesized pharmaceuticals.

In silico approaches in organ toxicity hazard assessment: Current status and future needs for predicting heart, kidney and lung toxicities

The kidneys, heart and lungs are vital organ systems evaluated as part of acute or chronic toxicity assessments. New methodologies are being developed to predict these adverse effects based on in vitro and in silico approaches. This paper reviews the current state of the art in predicting these organ toxicities. It outlines the biological basis, processes and endpoints for kidney toxicity, pulmonary toxicity, respiratory irritation and sensitization as well as functional and structural cardiac toxicities. The review also covers current experimental approaches, including off-target panels from secondary pharmacology batteries. Current in silico approaches for prediction of these effects and mechanisms are described as well as obstacles to the use of in silico methods. Ultimately, a commonly accepted protocol for performing such assessment would be a valuable resource to expand the use of such approaches across different regulatory and industrial applications. However, a number of factors impede their widespread deployment including a lack of a comprehensive mechanistic understanding, limited in vitro testing approaches and limited in vivo databases suitable for modeling, a limited understanding of how to incorporate absorption, distribution, metabolism, and excretion (ADME) considerations into the overall process, a lack of in silico models designed to predict a safe dose and an accepted framework for organizing the key characteristics of these organ toxicants.

Aggregation and analysis of secondary pharmacology data from investigational new drug submissions at the US Food and Drug Administration

Secondary pharmacology studies are utilized by the pharmaceutical industry as a cost-efficient tool to identify potential safety liabilities of drugs before entering Phase 1 clinical trials. These studies are recommended by the Food and Drug Administration (FDA) as a part of the Investigational New Drug (IND) application. However, despite the utility of these assays, there is little guidance on which targets should be screened and which format should be used. Here, we evaluated 226 secondary pharmacology profiles obtained from close to 90 unique sponsors. The results indicated that the most tested target in our set was the GABA benzodiazepine receptor (tested 168 times), the most hit target was adenosine 3 (hit 24 times), and the target with the highest hit percentage was the quinone reductase 2 (NQO2) receptor (hit 29% of the time). The overall results were largely consistent with those observed in previous publications. However, this study also identified the need for improvement in the submission process of secondary pharmacology studies by industry, which could enhance their utility for regulatory purpose. FDA-industry collaborative working groups will utilize this data to determine the best methods for regulatory submission of these studies and evaluate the need for a standard target panel.

A property-response perspective on modern toxicity assessment and drug toxicity index (DTI)

Toxicity related failures in drug discovery and clinical development have motivated scientists and regulators to develop a wide range of in-vitro, in-silico tools coupled with data science methods. Older drug discovery rules are being constantly modified to churn out any hidden predictive value. Nonetheless, the dose-response concepts remain central to all these methods. Over the last 2 decades medicinal chemists, and pharmacologists have observed that different physicochemical, and pharmacological properties capture trends in toxic responses. We propose that these observations should be viewed in a comprehensive property-response framework where dose is only a factor that modifies the inherent toxicity potential. We then introduce the recently proposed "Drug Toxicity Index (DTI)" and briefly summarize its applications. A webserver is available to calculate DTI values (https://all-tool-kit.github.io/Web-Tool.html).

Systematic Analysis of Protein Targets Associated with Adverse Events of Drugs from Clinical Trials and Postmarketing Reports

Adverse drug reactions (ADRs) are undesired effects of medicines that can harm patients and are a significant source of attrition in drug development. ADRs are anticipated by routinely screening drugs against secondary pharmacology protein panels. However, there is still a lack of quantitative information on the links between these off-target proteins and the reporting of ADRs in humans. Here, we present a systematic analysis of associations between measured and predicted in vitro bioactivities of drugs and adverse events (AEs) in humans from two sources of data: the Side Effect Resource, derived from clinical trials, and the Food and Drug Administration Adverse Event Reporting System, derived from postmarketing surveillance. The ratio of a drug's therapeutic unbound plasma concentration over the drug's in vitro potency against a given protein was used to select proteins most likely to be relevant to in vivo effects. In examining individual target bioactivities as predictors of AEs, we found a trade-off between the positive predictive value and the fraction of drugs with AEs that can be detected. However, considering sets of multiple targets for the same AE can help identify a greater fraction of AE-associated drugs. Of the 45 targets with statistically significant associations to AEs, 30 are included on existing safety target panels. The remaining 15 targets include 9 carbonic anhydrases, of which CA5B is significantly associated with cholestatic jaundice. We include the full quantitative data on associations between measured and predicted in vitro bioactivities and AEs in humans in this work, which can be used to make a more informed selection of safety profiling targets.