Drug-Target Residence Time Affects in Vivo Target Occupancy through Multiple Pathways

The translational value of ligand-receptor binding kinetics in drug discovery

The translation of in vitro potency of a candidate drug, as determined by traditional pharmacology metrics (such as EC50/IC50 and KD/Ki values), to in vivo efficacy and safety is challenging. Residence time, which represents the duration of drug-target interaction, can be part of a more comprehensive understanding of the dynamic nature of drug-target interactions in vivo, thereby enabling better prediction of drug efficacy and safety. As a consequence, a prolonged residence time may help in achieving sustained pharmacological activity, while transient interactions with shorter residence times may be favourable for targets associated with side effects. Therefore, integration of residence time into the early stages of drug discovery and development has yielded a number of clinical candidates with promising in vivo efficacy and safety profiles. Insights from residence time research thus contribute to the translation of in vitro potency to in vivo efficacy and safety. Further research and advances in measuring and optimizing residence time will bring a much-needed addition to the drug discovery process and the development of safer and more effective drugs. In this review, we summarize recent research progress on residence time, highlighting its importance from a translational perspective.

Long-term residence and efficacy of adenovirus-mimetic nanoparticles in renal target tissue

A major shortcoming in the treatment of mesangial cell-associated diseases such as IgA nephropathy, diabetic nephropathy, or lupus nephritis, which frequently progress to end-stage renal disease, is poor drug availability in the glomerular mesangium. Drug delivery via active targeting of nanoparticles, using ligands attached to the particle surface for target cell recognition to increase the biodistribution to the mesangium, is a promising strategy to overcome this hurdle. However, although several glomerular tissue targeting approaches have been described, so far no study has demonstrated the particles' ability to deliver sufficient drug amounts combined with an appropriate nanoparticle target retention time to trigger relevant biological effects in the mesangium. In our study, we encapsulated erastin, a ferroptosis-inducing model compound, into adenovirus-mimetic, mesangial cell-targeting nanoparticles, enabling the direct visualisation of biological effects through ferroptosis-dependent histological changes. By intravital microscopy and analysis of histological sections, we were not only able to localise the injected particles over 10 days within the target cells but also to demonstrate biological activity in the renal glomeruli. In conclusion, we have characterised adenovirus-mimetic nanoparticles as a highly suitable drug delivery platform for the treatment of mesangial cell-associated diseases and additionally provided the basis for a potential renal disease model.

Overcoming Secondary Mutations of Type II Kinase Inhibitors

Type II kinase inhibitors bind in the "DFG-out" kinase conformation and are generally considered to be more potent and selective than type I inhibitors, which target a DFG-in conformation. Nine type II inhibitors are currently clinically approved, with more undergoing clinical development. Resistance-conferring secondary mutations emerged with the first series of type II inhibitors, most commonly at residues within the kinase activation loop and at the "gatekeeper" position. Recently, new inhibitors have been developed to overcome such mutations; however, mutations activating other pathways (and/or other targets) have subsequently emerged on occasion. Here, we systematically summarize the secondary mutations that confer resistance to type II inhibitors, the structural basis for resistance, newer inhibitors designed to overcome resistance, as well as the challenges and opportunities for the development of new inhibitors to overcome secondary kinase domain mutations.

Endovascular Applications for the Management of High-Grade Gliomas in the Modern Era

High-grade gliomas (HGGs) have a poor prognosis and are difficult to treat. This review examines the evolving landscape of endovascular therapies for HGGs. Recent advances in endovascular catheter technology and delivery methods allow for super-selective intra-arterial cerebral infusion (SSIACI) with increasing precision. This treatment modality may offer the ability to deliver anti-tumoral therapies directly to tumor regions while minimizing systemic toxicity. However, challenges persist, including blood-brain barrier (BBB) penetration, hemodynamic complexities, and drug-tumor residence time. Innovative adjunct techniques, such as focused ultrasound (FUS) and hyperosmotic disruption, may facilitate BBB disruption and enhance drug penetration. However, hemodynamic factors that limit drug residence time remain a limitation. Expanding therapeutic options beyond chemotherapy, including radiotherapy and immunobiologics, may motivate future investigations. While preclinical and clinical studies demonstrate moderate efficacy, larger randomized trials are needed to validate the clinical benefits. Additionally, future directions may involve endovascular sampling for peri-tumoral surveillance; changes in drug formulations to prolong residence time; and the exploration of non-pharmaceutical therapies, like radioembolization and photodynamic therapy. Endovascular strategies hold immense potential in reshaping HGG treatment paradigms, offering targeted and minimally invasive approaches. However, overcoming technical challenges and validating clinical efficacy remain paramount for translating these advancements into clinical care.

Exploring inter-ethnic and inter-patient variability and optimal dosing of osimertinib: a physiologically based pharmacokinetic modeling approach

Purpose: This study aimed to develop and validate a physiologically based pharmacokinetic (PBPK) model for osimertinib (OSI) to predict plasma trough concentration (Ctrough) and pulmonary EGFRm+ (T790M and L858R mutants) inhibition in Caucasian, Japanese, and Chinese populations. The PBPK model was also utilized to investigate inter-ethnic and inter-patient differences in OSI pharmacokinetics (PK) and determine optimal dosing regimens. Methods: Population PBPK models of OSI for healthy and disease populations were developed using physicochemical and biochemical properties of OSI and physiological parameters of different groups. And then the PBPK models were validated using the multiple clinical PK and drug-drug interaction (DDI) study data. Results: The model demonstrated good consistency with the observed data, with most of prediction-to-observation ratios of 0.8-1.25 for AUC, Cmax, and Ctrough. The PBPK model revealed that plasma exposure of OSI was approximately 2-fold higher in patients compared to healthy individuals, and higher exposure observed in Caucasians compared to other ethnic groups. This was primarily attributed to a lower CL/F of OSI in patients and Caucasian. The PBPK model displayed that key factors influencing PK and EGFRm+ inhibition differences included genetic polymorphism of CYP3A4, CYP1A2 expression, plasma free concentration (fup), albumin level, and auto-inhibition/induction on CYP3A4. Inter-patient PK variability was most influenced by CYP3A4 variants, fup, and albumin level. The PBPK simulations indicated that the optimal dosing regimen for patients across the three populations of European, Japanese, and Chinese ancestry was OSI 80 mg once daily (OD) to achieve the desired range of plasma Ctrough (328-677 nmol/L), as well as 80 mg and 160 mg OD for desirable pulmonary EGFRm+ inhibition (>80%). Conclusion: In conclusion, this study's PBPK simulations highlighted potential ethnic and inter-patient variability in OSI PK and EGFRm+ inhibition between Caucasian, Japanese, and Chinese populations, while also providing insights into optimal dosing regimens of OSI.

Covalent inhibitors: An ambitious approach for the discovery of newer oncotherapeutics

Covalent inhibitors have been used to treat several diseases for over a century. However, strategic approaches for the rational design of covalent drugs have taken a definitive shape in recent times. Since the first appearance of covalent inhibitors in the late 18th century, the field has grown tremendously and around 30% of marketed drugs are covalent inhibitors especially, for oncology indications. However, the off-target toxicity and safety concerns can be significant issues related to the covalent drugs. Covalent kinase inhibitor (CKI) targeted oncotherapeutics has advanced dramatically over the last two decades since the discovery of afatinib (Gilotrif®), an EGFR inhibitor. Since then, US FDA has approved 10 CKIs for diverse cancer targets. The present review broadly summarizes the ongoing development in the discovery of newer CKIs from 2016 till the end of 2022. We believe that these efforts will assist the modern medicinal chemist actively working in the field of CKI discovery for varied indications.

How Robust Is the Ligand Binding Transition State?

For many drug targets, it has been shown that the kinetics of drug binding (e.g., on rate and off rate) is more predictive of drug efficacy than thermodynamic quantities alone. This motivates the development of predictive computational models that can be used to optimize compounds on the basis of their kinetics. The structural details underpinning these computational models are found not only in the bound state but also in the short-lived ligand binding transition states. Although transition states cannot be directly observed experimentally due to their extremely short lifetimes, recent successes have demonstrated that modeling the ligand binding transition state is possible with the help of enhanced sampling molecular dynamics methods. Previously, we generated unbinding paths for an inhibitor of soluble epoxide hydrolase (sEH) with a residence time of 11 min. Here, we computationally modeled unbinding events with the weighted ensemble method REVO (resampling of ensembles by variation optimization) for five additional inhibitors of sEH with residence times ranging from 14.25 to 31.75 min, with average prediction accuracy within an order of magnitude. The unbinding ensembles are analyzed in detail, focusing on features of the ligand binding transition state ensembles (TSEs). We find that ligands with similar bound poses can show significant differences in their ligand binding TSEs, in terms of their spatial distribution and protein-ligand interactions. However, we also find similarities across the TSEs when examining more general features such as ligand degrees of freedom. Together these findings show significant challenges for rational, kinetics-based drug design.

Unraveling the Mechanism of Epichaperome Modulation by Zelavespib: Biochemical Insights on Target Occupancy and Extended Residence Time at the Site of Action

Drugs with a long residence time at their target sites are often more efficacious in disease treatment. The mechanism, however, behind prolonged retention at the site of action is often difficult to understand for non-covalent agents. In this context, we focus on epichaperome agents, such as zelavespib and icapamespib, which maintain target binding for days despite rapid plasma clearance, minimal retention in non-diseased tissues, and rapid metabolism. They have shown significant therapeutic value in cancer and neurodegenerative diseases by disassembling epichaperomes, which are assemblies of tightly bound chaperones and other factors that serve as scaffolding platforms to pathologically rewire protein-protein interactions. To investigate their impact on epichaperomes in vivo, we conducted pharmacokinetic and target occupancy measurements for zelavespib and monitored epichaperome assemblies biochemically in a mouse model. Our findings provide evidence of the intricate mechanism through which zelavespib modulates epichaperomes in vivo. Initially, zelavespib becomes trapped when epichaperomes bound, a mechanism that results in epichaperome disassembly, with no change in the expression level of epichaperome constituents. We propose that the initial trapping stage of epichaperomes is a main contributing factor to the extended on-target residence time observed for this agent in clinical settings. Zelavespib's residence time in tumors seems to be dictated by target disassembly kinetics rather than by frank drug-target unbinding kinetics. The off-rate of zelavespib from epichaperomes is, therefore, much slower than anticipated from the recorded tumor pharmacokinetic profile or as determined in vitro using diluted systems. This research sheds light on the underlying processes that make epichaperome agents effective in the treatment of certain diseases.

Evolution of Slow-Binding Inhibitors Targeting Histone Deacetylase Isoforms

Because the overexpression of histone deacetylase enzymes (HDACs) has been linked to numerous diseases, including various cancers and neurodegenerative disorders, HDAC inhibitors have emerged as promising therapeutic agents. However, most HDAC inhibitors lack both subclass and isoform selectivity, which leads to potential toxicity. Unlike classical hydroxamate HDAC inhibitors, slow-binding HDAC inhibitors form tight and prolonged bonds with HDAC enzymes. This distinct mechanism of action improves both selectivity and toxicity profiles, which makes slow-binding HDAC inhibitors a promising class of therapeutic agents for various diseases. Therefore, the development of slow-binding HDAC inhibitors that can effectively target a wide range of HDAC isoforms is crucial. This Perspective provides valuable insights into the potential and progress of slow-binding HDAC inhibitors as promising drug candidates for the treatment of various diseases.

Development of Long-Acting Dipeptidyl Peptidase-4 Inhibitors: Structural Evolution and Long-Acting Determinants

Considerable effort has been made to achieve less frequent dosing in the development of DPP-4 inhibitors. Enthusiasm for long-acting DPP-4 inhibitors is based on the promise that such agents with less frequent dosing regimens are associated with improved patient adherence, but the rational design of long-acting DPP-4 inhibitors remains a major challenge. In this Perspective, the development of long-acting DPP-4 inhibitors is comprehensively summarized to highlight the evolution of initial lead compounds on the path toward developing long-acting DPP-4 inhibitors over nearly three decades. The determinants for long duration of action are then examined, including the nature of the target, potency, binding kinetics, crystal structures, selectivity, and preclinical and clinical pharmacokinetic and pharmacodynamic profiles. More importantly, several possible approaches for the rational design of long-acting drugs are discussed. We hope that this information will facilitate the design and development of safer and more effective long-acting DPP-4 inhibitors and other oral drugs.

Zebrafish as model system for the biological characterization of CK1 inhibitors

Introduction: The CK1 family is involved in a variety of physiological processes by regulating different signaling pathways, including the Wnt/β-catenin, the Hedgehog and the p53 signaling pathways. Mutations or dysregulation of kinases in general and of CK1 in particular are known to promote the development of cancer, neurodegenerative diseases and inflammation. There is increasing evidence that CK1 isoform specific small molecule inhibitors, including CK1δ- and CK1ε-specific inhibitors of Wnt production (IWP)-based small molecules with structural similarity to benzimidazole compounds, have promising therapeutic potential. Methods: In this study, we investigated the suitability of the zebrafish model system for the evaluation of such CK1 inhibitors. To this end, the kinetic parameters of human CK1 isoforms were compared with those of zebrafish orthologues. Furthermore, the effects of selective CK1δ inhibition during zebrafish embryonic development were analyzed in vivo. Results: The results revealed that zebrafish CK1δA and CK1δB were inhibited as effectively as human CK1δ by compounds G2-2 with IC50 values of 345 and 270 nM for CK1δA and CK1δB versus 503 nM for human CK1δ and G2-3 exhibiting IC50 values of 514 and 561 nM for zebrafish CK1δA and B, and 562 nM for human CK1δ. Furthermore, the effects of selective CK1δ inhibition on zebrafish embryonic development in vivo revealed phenotypic abnormalities indicative of downregulation of CK1δ. Treatment of zebrafish embryos with selected inhibitors resulted in marked phenotypic changes including blood stasis, heart failure, and tail malformations. Conclusion: The results suggest that the zebrafish is a suitable in vivo assay model system for initial studies of the biological relevance of CK1δ inhibition.

Optical-Controlled Kinetic Switch: Fine-Tuning of the Residence Time of an Antagonist Binding to the Vasopressin V2 Receptor in In Vitro, Ex Vivo, and In Vivo Models of ADPKD

The pharmacological activity of a small-molecule ligand is linked to its receptor residence time. Therefore, precise control of the duration for which a ligand binds to its receptor is highly desirable. Herein, we designed photoswitchable ligands targeting the vasopressin V₂ receptor (V₂R), a validated target for autosomal dominant polycystic kidney disease (ADPKD). We adapted the photoswitching trait of azobenzene to the parent V₂R antagonist lixivaptan (LP) to generate azobenzene lixivaptan derivatives (aLPs). Among them, aLPs-5g was a potential optical-controlled kinetic switch. Upon irradiation, cis-aLPs-5g displayed a 4.3-fold prolonged V₂R residence time compared to its thermally stable trans configuration. The optical-controlled kinetic variations led to distinct inhibitory effects on cellular functional readout. Furthermore, conversion of the cis/trans isomer of aLPs-5g resulted in different efficacies of inhibiting renal cystogenesis ex vivo and in vivo. Overall, aLPs-5g represents a photoswitch for precise control of ligand-receptor residence time and, consequently, the pharmacological activity.

Advances in computational methods for ligand binding kinetics

Binding kinetic parameters can be correlated with drug efficacy, which in recent years led to the development of various computational methods for predicting binding kinetic rates and gaining insight into protein-drug binding paths and mechanisms. In this review, we introduce and compare computational methods recently developed and applied to two systems, trypsin-benzamidine and kinase-inhibitor complexes. Methods involving enhanced sampling in molecular dynamics simulations or machine learning can be used not only to predict kinetic rates, but also to reveal factors modulating the duration of residence times, selectivity, and drug resistance to mutations. Methods which require less computational time to make predictions are highlighted, and suggestions to reduce the error of computed kinetic rates are presented.

Importance of Target-Mediated Drug Disposition (TMDD) of Small-Molecule Compounds and Its Impact on Drug Development-Example of the Class Effect of HSD-1 Inhibitors

With more potent drug candidates being developed, the incidence of target-mediated drug disposition (TMDD) in small-molecule compounds has significantly increased in the past decade. Moreover, TMDD appears to apply to some small-molecule compound classes. The main purpose of the current review is to increase the awareness of TMDD in a series of small-molecule inhibitors of 11β-hydroxysteroid dehydrogenase type 1 (HSD-1) using ABT-384, SPI-62, MK-0916, BMS-823778, and BI-187004 as case examples. Although developed independently by different pharmaceutical companies, these HSD-1 inhibitors demonstrated strikingly similar nonlinear pharmacokinetic behaviors when wide dose ranges were evaluated in first-in-human (FIH) single ascending dose (SAD) and multiple ascending dose (MAD) studies. Recognizing TMDD in small-molecule compounds is important, as the information can be leveraged to select the appropriate dose regimen, improve clinical trial design, as well as predict pharmacological target occupancy. In this review, we summarize the general pharmacokinetic features that facilitate the recognition of small-molecule TMDD, provide case examples of specific HSD-1 inhibitors, highlight the importance of recognizing TMDD of small-molecule compounds during clinical development, and comment on the importance of utilizing pharmacometric modeling to facilitate the quantitative understanding of small-molecule compounds exhibiting TMDD.

High-throughput mechanistic screening of non-equilibrium inhibitors by a fully automated data analysis pipeline in early drug-discovery

Recent efforts for increasing the success in drug discovery focus on an early, massive, and routine mechanistic and/or kinetic characterization of drug-target engagement as part of a design-make-test-analyze strategy. From an experimental perspective, many mechanistic assays can be translated into a scalable format on automation platforms and thereby enable routine characterization of hundreds or thousands of compounds. However, now the limiting factor to achieve such in-depth characterization at high-throughput becomes the quality-driven data analysis, the sheer scale of which outweighs the time available to the scientific staff of most labs. Therefore, automated analytical workflows are needed to enable such experimental scale-up. We have implemented such a fully automated workflow in Genedata Screener for time-dependent ligand-target binding analysis to characterize non-equilibrium inhibitors. The workflow automates Quality Control (QC) / data modelling and decision-making process in a staged analysis: (1) quality control of raw input data-fluorescence signal-based progress curves - featuring automated rejection of unsuitable measurements; (2) automated model selection - one-step versus two-step binding model - using statistical methods and biological validity rules; (3) result visualization in specific plots and annotated result tables, enabling the scientist to review large result sets efficiently and, at the same time, to rapidly identify and focus on interesting or unusual results; (4) an interactive user interface for immediate adjustment of automated decisions, where necessary. Applying this workflow to first-pass, high-throughput kinetic studies on kinase projects has allowed us to surmount previously rate-limiting manual analysis steps and boost productivity; and is now routinely embedded in a biopharma discovery research process.

Estimation of Drug-Target Residence Time by Targeted Molecular Dynamics Simulations

Drug-target residence time has emerged as a key selection factor in drug discovery since the binding duration of a drug molecule to its protein target can significantly impact its in vivo efficacy. The challenge in studying the residence time, in early drug discovery stages, lies in how to cost-effectively determine the residence time for the systematic assessment of compounds. Currently, there is still a lack of computational protocols to quickly estimate such a measure, particularly for large and flexible protein targets and drugs. Here, we report an efficient computational protocol, based on targeted molecular dynamics, to rank drug candidates by their residence time and to obtain insights into ligand-target dissociation mechanisms. The method was assessed on a dataset of 10 arylpyrazole inhibitors of CDK8, a large, flexible, and clinically important target, for which the experimental residence time of the inhibitors ranges from minutes to hours. The compounds were correctly ranked according to their estimated residence time scores compared to their experimental values. The analysis of protein-ligand interactions along the dissociation trajectories highlighted the favorable contribution of hydrophobic contacts to residence time and revealed key residues that strongly affect compound residence time.

Design, Synthesis, and Pharmacological Evaluation of Second-Generation Soluble Adenylyl Cyclase (sAC, ADCY10) Inhibitors with Slow Dissociation Rates

Soluble adenylyl cyclase (sAC: ADCY10) is an enzyme involved in intracellular signaling. Inhibition of sAC has potential therapeutic utility in a number of areas. For example, sAC is integral to successful male fertility: sAC activation is required for sperm motility and ability to undergo the acrosome reaction, two processes central to oocyte fertilization. Pharmacologic evaluation of existing sAC inhibitors for utility as on-demand, nonhormonal male contraceptives suggested that both high intrinsic potency, fast on and slow dissociation rates are essential design elements for successful male contraceptive applications. During the course of the medicinal chemistry campaign described here, we identified sAC inhibitors that fulfill these criteria and are suitable for in vivo evaluation of diverse sAC pharmacology.

Physiologically based pharmacokinetic combined JAK2 occupancy modelling to simulate PK and PD of baricitinib with kidney transporter inhibitors and in patients with hepatic/renal impairment

PURPOSE

Our aim is to build a physiologically based pharmacokinetic and JAK2 occupancy model (PBPK-JO) to simultaneously predict pharmacokinetic (PK) and pharmacodynamic (PD) changes of baricitinib (BAR) in healthy humans when co-administrated with kidney transporters OAT3 and MATE2-K inhibitors, and in patients with hepatic and renal impairment.

METHODS

Probenecid and vandetanib were selected as OAT3 and MATE2-K competitive inhibitors, respectively. The PBPK-JO model was built using physicochemical and biochemical properties of BAR, and then verified by observed clinical PK. Finally, the model was applied to determine optimal dosing regimens in various clinical situations.

RESULTS

Here, we have successfully simulated PK and JAK2 occupancy profiles in humans by PBPK-JO model. Moreover, this modelling reproduced every observed PK data, and every mean relative deviation (MRD) was below 2. The simulation suggested that PK of BAR had a significant change (2.22-fold increase), however PD only had a slight increase of 1.14-fold. Additionally, the simulation also suggested that vandetanib was almost unlikely to affect the PK and PD of BAR. In simulations of hepatic and renal impairment patients, the predictions suggested that significant changes in the PK and PD of BAR occurred. However, there was a lower fold increase in JAK2 occupancy than in PK in patients relative to healthy individuals.

CONCLUSION

Administration dose adjustment of BAR when co-administrated with OAT3 inhibitors or in patients with hepatic or renal impairment should combine PK and PD changes of BAR, instead of only considering PK alteration.

Enhanced-Sampling Simulations for the Estimation of Ligand Binding Kinetics: Current Status and Perspective

The dissociation rate (k off) associated with ligand unbinding events from proteins is a parameter of fundamental importance in drug design. Here we review recent major advancements in molecular simulation methodologies for the prediction of k off. Next, we discuss the impact of the potential energy function models on the accuracy of calculated k off values. Finally, we provide a perspective from high-performance computing and machine learning which might help improve such predictions.

Computer-aided engineering of staphylokinase toward enhanced affinity and selectivity for plasmin

Cardio- and cerebrovascular diseases are leading causes of death and disability, resulting in one of the highest socio-economic burdens of any disease type. The discovery of bacterial and human plasminogen activators and their use as thrombolytic drugs have revolutionized treatment of these pathologies. Fibrin-specific agents have an advantage over non-specific factors because of lower rates of deleterious side effects. Specifically, staphylokinase (SAK) is a pharmacologically attractive indirect plasminogen activator protein of bacterial origin that forms stoichiometric noncovalent complexes with plasmin, promoting the conversion of plasminogen into plasmin. Here we report a computer-assisted re-design of the molecular surface of SAK to increase its affinity for plasmin. A set of computationally designed SAK mutants was produced recombinantly and biochemically characterized. Screening revealed a pharmacologically interesting SAK mutant with ∼7-fold enhanced affinity toward plasmin, ∼10-fold improved plasmin selectivity and moderately higher plasmin-generating efficiency in vitro. Collectively, the results obtained provide a framework for SAK engineering using computational affinity-design that could pave the way to next-generation of effective, highly selective, and less toxic thrombolytics.

Development of an intracellular quantitative assay to measure compound binding kinetics

Contemporary drug discovery typically quantifies the effect of a molecule on a biological target using the equilibrium-derived measurements of IC50, EC50, or KD. Kinetic descriptors of drug binding are frequently linked with the effectiveness of a molecule in modulating a disease phenotype; however, these parameters are yet to be fully adopted in early drug discovery. Nanoluciferase bioluminescence resonance energy transfer (NanoBRET) can be used to measure interactions between fluorophore-conjugated probes and luciferase fused target proteins. Here, we describe an intracellular NanoBRET competition assay that can be used to quantify cellular kinetic rates of compound binding to nanoluciferase-fused bromodomain and extra-terminal (BET) proteins. Comparative rates are generated using a cell-free NanoBRET assay and by utilizing orthogonal recombinant protein-based methodologies. A screen of known pan-BET inhibitors is used to demonstrate the value of this approach in the investigation of kinetic selectivity between closely related proteins.

Enhanced Sampling Approach to the Induced-Fit Docking Problem in Protein-Ligand Binding: The Case of Mono-ADP-Ribosylation Hydrolase Inhibitors

Enhanced sampling methods can predict free-energy landscapes associated with protein/ligand binding, characterizing the involved intermolecular interactions in a precise way. However, these in silico approaches can be challenged by induced-fit effects. Here, we present a variant of volume-based metadynamics tailored to tackle this problem in a general and efficient way. The validity of the approach is established by applying it to substrate/enzyme complexes of pharmacological relevance: mono-ADP-ribose (ADPr) in complex with mono-ADP-ribosylation hydrolases (MacroD1 and MacroD2), where induced-fit phenomena are known to be significant. The calculated binding free energies are consistent with experiments, with an absolute error smaller than 0.5 kcal/mol. Our simulations reveal that in all circumstances, the active loops, delimiting the boundaries of the binding site, undergo significant conformation rearrangements upon ligand binding. The calculations further provide, for the first time, the molecular basis of ADPr specificity and the relative changes in its experimental binding affinity on passing from MacroD1 to MacroD2 and all its mutants. Our study paves the way to the quantitative description of induced-fit events in molecular recognition.

Evolution of the drug-target residence time model

IntroductionThe pharmacological action of a drug is linked to its affinity for a specific molecular target as quantified by in vitro equilibrium measurements. However, it is clear that for many highly effective drugs, interactions with their molecular targets do not conform to simple, equilibrium conditions in vivo and this results in a temporal discordance between pharmacokinetics and pharmacodynamics. The drug-target residence time model was developed to provide a theoretical framework with which to understand cases in which very slow dissociation of the drug-target complex in vivo results in durable PD effects even after systemic concentrations of drug have waned.Area coveredIn this article, the author provides a brief description of the drug-target residence time model and focuses on the refinements that have been made to the original model to incorporate the influences of compound rebinding in cells and pharmacokinetic properties of drug molecules.Expert opinionThere is now overwhelming evidence for the utility of the drug-target residence time model as a framework for understanding in vivo drug action. The in vitro measured residence time (τ_R) must be used in concert with equilibrium measures of drug-target affinity (e.g. IC₅₀) and with in vivo measures of pharmacokinetic half-life, to afford the researcher a powerful approach to compound optimization for clinical effect. Despite the significant use and refinement of this model, continued studies are required to better understand the dynamic interplay between residence time, target pathobiology, drug distribution and drug pharmacokinetics.

A Novel High-Throughput FLIPR Tetra-Based Method for Capturing Highly Confluent Kinetic Data for Structure-Kinetic Relationship Guided Early Drug Discovery

Target engagement by small molecules is necessary for producing a physiological outcome. In the past, a lot of emphasis was placed on understanding the thermodynamics of such interactions to guide structure-activity relationships. It is becoming clearer, however, that understanding the kinetics of the interaction between a small-molecule inhibitor and the biological target [structure-kinetic relationship (SKR)] is critical for selection of the optimum candidate drug molecule for clinical trial. However, the acquisition of kinetic data in a high-throughput manner using traditional methods can be labor intensive, limiting the number of molecules that can be tested. As a result, in-depth kinetic studies are often carried out on only a small number of compounds, and usually at a later stage in the drug discovery process. Fundamentally, kinetic data should be used to drive key decisions much earlier in the drug discovery process, but the throughput limitations of traditional methods preclude this. A major limitation that hampers acquisition of high-throughput kinetic data is the technical challenge in collecting substantially confluent data points for accurate parameter estimation from time course analysis. Here, we describe the use of the fluorescent imaging plate reader (FLIPR), a charge-coupled device (CCD) camera technology, as a potential high-throughput tool for generating biochemical kinetic data with smaller time intervals. Subsequent to the design and optimization of the assay, we demonstrate the collection of highly confluent time-course data for various kinase protein targets with reasonable throughput to enable SKR-guided medicinal chemistry. We select kinase target 1 as a special case study with covalent inhibition, and demonstrate methods for rapid and detailed analysis of the resultant kinetic data for parameter estimation. In conclusion, this approach has the potential to enable rapid kinetic studies to be carried out on hundreds of compounds per week and drive project decisions with kinetic data at an early stage in drug discovery.

Relative Importance of Soluble and Microsomal Epoxide Hydrolases for the Hydrolysis of Epoxy-Fatty Acids in Human Tissues

Epoxy-fatty acids (EpFAs) are endogenous lipid mediators that have a large breadth of biological activities, including the regulation of blood pressure, inflammation, angiogenesis, and pain perception. For the past 20 years, soluble epoxide hydrolase (sEH) has been recognized as the primary enzyme for degrading EpFAs in vivo. The sEH converts EpFAs to the generally less biologically active 1,2-diols, which are quickly eliminated from the body. Thus, inhibitors of sEH are being developed as potential drug therapeutics for various diseases including neuropathic pain. Recent findings suggest that other epoxide hydrolases (EHs) such as microsomal epoxide hydrolase (mEH) and epoxide hydrolase-3 (EH3) can contribute significantly to the in vivo metabolism of EpFAs. In this study, we used two complementary approaches to probe the relative importance of sEH, mEH, and EH3 in 15 human tissue extracts: hydrolysis of 14,15-EET and 13,14-EDP using selective inhibitors and protein quantification. The sEH hydrolyzed the majority of EpFAs in all of the tissues investigated, mEH hydrolyzed a significant portion of EpFAs in several tissues, whereas no significant role in EpFAs metabolism was observed for EH3. Our findings indicate that residual mEH activity could limit the therapeutic efficacy of sEH inhibition in certain organs.

Movement to the Clinic of Soluble Epoxide Hydrolase Inhibitor EC5026 as an Analgesic for Neuropathic Pain and for Use as a Nonaddictive Opioid Alternative

This report describes the development of an orally active analgesic that resolves inflammation and neuropathic pain without the addictive potential of opioids. EC5026 acts on the cytochrome P450 branch of the arachidonate cascade to stabilize epoxides of polyunsaturated fatty acids (EpFA), which are natural mediators that reduce pain, resolve inflammation, and maintain normal blood pressure. EC5026 is a slow-tight binding transition-state mimic that inhibits the soluble epoxide hydrolase (sEH) at picomolar concentrations. The sEH rapidly degrades EpFA; thus, inhibiting sEH increases EpFA in vivo and confers beneficial effects. This mechanism addresses disease states by shifting endoplasmic reticulum stress from promoting cellular senescence and inflammation toward cell survival and homeostasis. We describe the synthesis and optimization of EC5026 and its development through human Phase 1a trials with no drug-related adverse events. Additionally, we outline fundamental work leading to discovery of the analgesic and inflammation-resolving CYP450 branch of the arachidonate cascade.

Discovery and characterization of small molecule SIRT3-specific inhibitors as revealed by mass spectrometry

Sirtuins play a prominent role in several cellular processes and are implicated in various diseases. The understanding of biological roles of sirtuins is limited because of the non-availability of small molecule inhibitors, particularly the specific inhibitors directed against a particular SIRT. We performed a high-throughput screening of pharmacologically active compounds to discover novel, specific, and selective sirtuin inhibitor. Several unique in vitro sirtuin inhibitor pharmacophores were discovered. Here, we present the discovery of novel chemical scaffolds specific for SIRT3. We have demonstrated the in vitro activity of these compounds using label-free mass spectroscopy. We have further validated our results using biochemical, biophysical, and computational studies. Determination of kinetic parameters shows that the SIRT3 specific inhibitors have a moderately longer residence time, possibly implying high in vivo efficacy. The molecular docking results revealed the differential selectivity pattern of these inhibitors against sirtuins. The discovery of specific inhibitors will improve the understanding of ligand selectivity in sirtuins, and the binding mechanism as revealed by docking studies can be further exploited for discovering selective and potent ligands targeting sirtuins.

Into the Fray! A Beginner's Guide to Medicinal Chemistry

Modern medicinal chemistry is a complex, multidimensional discipline that operates at the interface of the chemical and biological sciences. The medicinal chemistry contribution to drug discovery is typically described in the context of the well-recited linear progression of the drug discovery pipeline. However, compound optimization is idiosyncratic to each project, and clear definitions of hit and lead molecules and the subsequent progress along the pipeline becomes easily blurred. In addition, this description lacks insight into the entangled relationship between chemical and pharmacological properties, and thus provides limited guidance on how innovative medicinal chemistry strategies can be applied to solve optimization problems, regardless of the stage in the pipeline. Through discussion and illustrative examples, this article seeks to provide insights into the finesse of medicinal chemistry and the subtlety of balancing chemical properties pharmacology. In so doing, it aims to serve as an accessible and simple-to-digest guide for anyone who wishes to learn about the underlying principles of medicinal chemistry, in a context that has been decoupled from the pipeline description.

Target-Mediated Drug Disposition-A Class Effect of Soluble Epoxide Hydrolase Inhibitors

Pharmacological target-mediated drug disposition (TMDD) represents a special source of nonlinear pharmacokinetics, and its occurrence in large-molecule compounds has been well recognized because numerous protein drugs have been reported to have TMDD due to specific binding to their pharmacological targets. Although TMDD can also happen in small-molecule compounds, it has been largely overlooked. In this mini-review, we summarize the occurrence of TMDD that we discovered recently in a series of small-molecule soluble epoxide hydrolase (sEH) inhibitors. Our journey started with an accidental discovery of target-mediated kinetics of 1-(1-propanoylpiperidin-4-yl)-3-[4-(trifluoromethoxy)phenyl]urea (TPPU), a potent sEH inhibitor, in a pilot clinical study. To confirm what we observed in humans, we conducted a series of mechanism experiments in animals, including pharmacokinetic experiments using sEH knockout mice as well as in vivo displacement experiments with co-administration of another potent sEH inhibitor. Our mechanism studies confirmed that the TMDD of TPPU is due to its pharmacological target sEH. We further expanded our evaluation to various other sEH inhibitors and found that TMDD is a class effect of this group of small-molecule sEH inhibitors. In addition to summarizing the occurrence of TMDD in sEH inhibitors, in this mini-review we also highlighted the importance of recognizing TMDD of small-molecule compounds and its impact in clinical development as well as using pharmacometric modeling in facilitating quantitative understanding of TMDD.

Preparation and evaluation of soluble epoxide hydrolase inhibitors with improved physical properties and potencies for treating diabetic neuropathic pain

Soluble epoxide hydrolase (sEH), a novel therapeutic target for neuropathic pain, is a largely cytosolic enzyme that degrades epoxy-fatty acids (EpFAs), an important class of lipid signaling molecules. Many inhibitors of sEH have been reported, and to date, the 1,3-disubstituted urea has the highest affinity reported for the sEH among the central pharmacophores evaluated. An earlier somewhat water soluble sEH inhibitor taken to the clinic for blood pressure control had mediocre potency (both affinity and kinetics) and a short in vivo half-life. We undertook a study to overcome these difficulties, but the sEH inhibitors carrying a 1,3-disubstituted urea often suffer poor physical properties that hinder their formulation. In this report, we described new strategies to improve the physical properties of sEH inhibitors with a 1,3-disubstituted urea while maintaining their potency and drug-target residence time (a complementary in vitro parameter) against sEH. To our surprise, we identified two structural modifications that substantially improve the potency and physical properties of sEH inhibitors carrying a 1,3-disubstituted urea pharmacophore. Such improvements will greatly facilitate the movement of sEH inhibitors to the clinic.

On Calculating Free Energy Differences Using Ensembles of Transition Paths

The free energy of a process is the fundamental quantity that determines its spontaneity or propensity at a given temperature. In particular, the binding free energy of a drug candidate to its biomolecular target is used as an objective quantity in drug design. Recently, binding kinetics—rates of association (k_on) and dissociation (k_off)—have also demonstrated utility for their ability to predict efficacy and in some cases have been shown to be more predictive than the binding free energy alone. Some methods exist to calculate binding kinetics from molecular simulations, although these are typically more difficult to calculate than the binding affinity as they depend on details of the transition path ensemble. Assessing these rate constants can be difficult, due to uncertainty in the definition of the bound and unbound states, large error bars and the lack of experimental data. As an additional consistency check, rate constants from simulation can be used to calculate free energies (using the log of their ratio) which can then be compared to free energies obtained experimentally or using alchemical free energy perturbation. However, in this calculation it is not straightforward to account for common, practical details such as the finite simulation volume or the particular definition of the “bound” and “unbound” states. Here we derive a set of correction terms that can be applied to calculations of binding free energies using full reactive trajectories. We apply these correction terms to revisit the calculation of binding free energies from rate constants for a host-guest system that was part of a blind prediction challenge, where significant deviations were observed between free energies calculated with rate ratios and those calculated from alchemical perturbation. The correction terms combine to significantly decrease the error with respect to computational benchmarks, from 3.4 to 0.76 kcal/mol. Although these terms were derived with weighted ensemble simulations in mind, some of the correction terms are generally applicable to free energies calculated using physical pathways via methods such as Markov state modeling, metadynamics, milestoning, or umbrella sampling.

Development of Improved Double-Nanobody Sandwich ELISAs for Human Soluble Epoxide Hydrolase Detection in Peripheral Blood Mononuclear Cells of Diabetic Patients and the Prefrontal Cortex of Multiple Sclerosis Patients

Nanobodies have been progressively replacing traditional antibodies in various immunological methods. However, the use of nanobodies as capture antibodies is greatly hampered by their poor performance after passive adsorption to polystyrene microplates, and this restricts the full use of double nanobodies in sandwich enzyme-linked immunosorbent assays (ELISAs). Herein, using the human soluble epoxide hydrolase (sEH) as a model analyte, we found that both the immobilization format and the blocking agent have a significant influence on the performance of capture nanobodies immobilized on polystyrene and the subsequent development of double-nanobody sandwich ELISAs. We first conducted epitope mapping for pairing nanobodies and then prepared a horseradish-peroxidase-labeled nanobody using a mild conjugation procedure as a detection antibody throughout the work. The resulting sandwich ELISA using a capture nanobody (A9, 1.25 μg/mL) after passive adsorption and bovine serum albumin (BSA) as a blocking agent generated a moderate sensitivity of 0.0164 OD·mL/ng and a limit of detection (LOD) of 0.74 ng/mL. However, the introduction of streptavidin as a linker to the capture nanobody at the same working concentration demonstrated a dramatic 16-fold increase in sensitivity (0.262 OD·mL/ng) and a 25-fold decrease in the LOD for sEH (0.03 ng/mL). The streptavidin-bridged double-nanobody ELISA was then successfully applied to tests for recovery, cross-reactivity, and real samples. Meanwhile, we accidentally found that blocking with skim milk could severely damage the performance of the capture nanobody by an order of magnitude compared with BSA. This work provides guidelines to retain the high effectiveness of the capture nanobody and thus to further develop the double-nanobody ELISA for various analytes.

Simultaneous Target-Mediated Drug Disposition Model for Two Small-Molecule Compounds Competing for Their Pharmacological Target: Soluble Epoxide Hydrolase

1-(1-propanoylpiperidin-4-yl)-3-[4-(trifluoromethoxy)phenyl]urea (TPPU) and 1-(4-trifluoro-methoxy-phenyl)-3-(1-cyclopropanecarbonyl-piperidin-4-yl)-urea (TCPU) are potent inhibitors of soluble epoxide hydrolase (sEH) that have much better efficacy in relieving nociceptive response than the Food and Drug Administration-approved drug gabapentin in a rodent model of diabetic neuropathy. Experiments conducted in sEH knockout mice or with coadministration of a potent sEH displacer demonstrated that the pharmacokinetics of TPPU and TCPU were influenced by the specific binding to their pharmacologic target sEH, a phenomenon known as target-mediated drug disposition (TMDD). To quantitatively characterize the complex pharmacokinetics of TPPU and TCPU and gain better understanding on their target occupancy, population pharmacokinetics analysis using a nonlinear mixed-effect modeling approach was performed in the current study. The final model was a novel simultaneous TMDD interaction model, in which TPPU and TCPU compete for sEH, with TCPU binding to an additional unknown target pool with larger capacity that we refer to as a refractory pool. The total amount of sEH enzyme in mice was predicted to be 16.2 nmol, which is consistent with the experimental value of 10 nmol. The dissociate rate constants of TPPU and TCPU were predicted to be 2.24 and 2.67 hours^-1, respectively, which is close to the values obtained from in vitro experiments. Our simulation result predicted that 90% of the sEH will be occupied shortly after a low dose of 0.3 mg/kg TPPU administration, with ≥40% of sEH remaining to be bound with TPPU for at least 7 days. Further efficacy experiments are warranted to confirm the predicted target occupancy. SIGNIFICANCE STATEMENT: Although target-mediated drug disposition (TMDD) models have been well documented, most of them were established in a single compound scenario. Our novel model represents the first TMDD interaction model for two small-molecule compounds competing for the same pharmacological target.

Concept of Pharmacologic Target-Mediated Drug Disposition in Large-Molecule and Small-Molecule Compounds

Target-mediated drug disposition (TMDD) is a term to describe a nonlinear pharmacokinetic (PK) phenomenon that is caused by high-affinity binding of a compound to its pharmacologic targets. As the interaction between a drug and its pharmacologic target belongs to the process of pharmacodynamics (PD), TMDD can be viewed as a consequence of "PD affecting PK." Although there are numerous TMDD-related articles in the literature, most of them focus on characterizing TMDD using various mathematical models, which may not be suitable for those readers who have little interest in mathematical modeling and only want to have an understanding of the basic concept. The goal of this review is to serve as a "primer" on TMDD. This review explains (1) how TMDD happens; (2) why large-molecule and small-molecule compounds exhibiting TMDD demonstrate substantially different nonlinear PK behaviors; (3) what nonlinear PK profiles look like in large-molecule and small-molecule compounds exhibiting TMDD, using pegfilgrastim, erythropoietin, ABT-384, and linagliptin as case examples; and (4) how to identify whether the nonlinear PK of a compound is because of TMDD.