Enzyme-mediated drug-drug interactions: a review of in vivo and in vitro methodologies, regulatory guidance, and translation to the clinic.

Enzyme-mediated pharmacokinetic drug-drug interactions can be caused by altered activity of drug metabolizing enzymes in the presence of a perpetrator drug, mostly via inhibition or induction. We identified a gap in the literature for a state-of-the art detailed overview assessing this type of DDI risk in the context of drug development. This manuscript discusses in vitro and in vivo methodologies employed during the drug discovery and development process to predict clinical enzyme-mediated DDIs, including the determination of clearance pathways, metabolic enzyme contribution, and the mechanisms and kinetics of enzyme inhibition and induction. We discuss regulatory guidance and highlight the utility of in silico physiologically-based pharmacokinetic modeling, an approach that continues to gain application and traction in support of regulatory filings. Looking to the future, we consider DDI risk assessment for targeted protein degraders, an emerging small molecule modality, which does not have recommended guidelines for DDI evaluation. Our goal in writing this report was to provide early-career researchers with a comprehensive view of the enzyme-mediated pharmacokinetic DDI landscape to aid their drug development efforts.

Considerations and recommendations for assessment of plasma protein binding and drug-drug interactions for siRNA therapeutics.

At the time of writing, although siRNA therapeutics are approved for human use, no official regulatory guidance specific to this modality is available. In the absence of guidance, preclinical development for siRNA followed a hybrid of the small molecule and biologics guidance documents. However, siRNA differs significantly from small molecules and protein-based biologics in its physicochemical, absorption, distribution, metabolism and excretion properties, and its mechanism of action. Consequently, certain reports typically included in filing packages for small molecule or biologics may benefit from adaption, or even omission, from an siRNA filing. In this white paper, members of the 'siRNA working group' in the IQ Consortium compile a list of reports included in approved siRNA filing packages and discuss the relevance of two in vitro reports-the plasma protein binding evaluation and the drug-drug interaction risk assessment-to support siRNA regulatory filings. Publicly available siRNA approval packages and the literature were systematically reviewed to examine the role of siRNA plasma protein binding and drug-drug interactions in understanding pharmacokinetic/pharmacodynamic relationships, safety and translation. The findings are summarized into two decision trees to help guide industry decide when in vitro siRNA plasma protein binding and drug-drug interaction studies are warranted.

Modeling the CRL4A ligase complex to predict target protein ubiquitination induced by cereblon-recruiting PROTACs.

PROteolysis TArgeting Chimeras (PROTACs) are hetero-bifunctional small molecules that can simultaneously recruit target proteins and E3 ligases to form a ternary complex, promoting target protein ubiquitination and degradation via the Ubiquitin-Proteasome System (UPS). PROTACs have gained increasing attention in recent years due to certain advantages over traditional therapeutic modalities and enabling targeting of previously "undruggable" proteins. To better understand the mechanism of PROTAC-induced Target Protein Degradation (TPD), several computational approaches have recently been developed to study and predict ternary complex formation. However, mounting evidence suggests that ubiquitination can also be a rate-limiting step in PROTAC-induced TPD. Here, we propose a structure-based computational approach to predict target protein ubiquitination induced by cereblon (CRBN)-based PROTACs by leveraging available structural information of the CRL4A ligase complex (CRBN/DDB1/CUL4A/Rbx1/NEDD8/E2/Ub). We generated ternary complex ensembles with Rosetta, modeled multiple CRL4A ligase complex conformations, and predicted ubiquitination efficiency by separating the ternary ensemble into productive and unproductive complexes based on the proximity of the ubiquitin to accessible lysines on the target protein. We validated our CRL4A ligase complex models with published ternary complex structures and additionally employed our modeling workflow to predict ubiquitination efficiencies and sites of a series of cyclin-dependent kinases (CDKs) after treatment with TL12-186, a pan-kinase PROTAC. Our predictions are consistent with CDK ubiquitination and site-directed mutagenesis of specific CDK lysine residues as measured using a NanoBRET ubiquitination assay in HEK293 cells. This work structurally links PROTAC-induced ternary formation and ubiquitination, representing an important step toward prediction of target "degradability."

Industry Perspective on the Pharmacokinetic and Absorption, Distribution, Metabolism, and Excretion Characterization of Heterobifunctional Protein Degraders.

Targeted protein degraders (TPDs), specifically the bifunctional protein degraders discussed in this manuscript, consist of two linked ligands for a protein of interest and an E3 ligase, resulting in molecules that largely violate accepted physicochemical limits (e.g., Lipinski's Rule of Five) for oral bioavailability. In 2021, the IQ Consortium Degrader DMPK/ADME Working Group undertook a survey of 18 IQ member and nonmember companies working on degraders to understand whether the characterization and optimization of these molecules were different from any other beyond the Rule of Five (bRo5) compounds. Additionally, the working group sought to identify pharmacokinetic (PK)/absorption, distribution, metabolism, and excretion (ADME) areas in need of further evaluation and where additional tools could aid in more rapid advancement of TPDs to patients. The survey revealed that although TPDs reside in a challenging bRo5 physicochemical space, most respondents focus their efforts on oral delivery. Physicochemical properties required for oral bioavailability were generally consistent across the companies surveyed. Many of the member companies used modified assays to address challenging degrader properties (e.g., solubility, nonspecific binding), but only half indicated that they modified their drug discovery workflows. The survey also suggested the need for further scientific investigation in the areas of central nervous system penetration, active transport, renal elimination, lymphatic absorption, in silico/machine learning, and human pharmacokinetic prediction. Based on the survey results, the Degrader DMPK/ADME Working Group concluded that TPD evaluation does not fundamentally differ from other bRo5 compounds but requires some modification compared with traditional small molecules and proposes a generic workflow for PK/ADME evaluation of bifunctional TPDs. SIGNIFICANCE STATEMENT: Based on an industry survey, this article provides an understanding of the current state of absorption, distribution, metabolism, and excretion science pertaining to characterizing and optimizing targeted protein degraders, specifically bifunctional protein degraders, based upon responses by 18 IQ consortium members and non-members developing targeted protein degraders. Additionally, this article puts into context the differences / similarities in methods and strategies utilized for heterobifunctional protein degraders compared to other beyond Rule of Five molecules and conventional small molecule drugs.

Half-life extension of peptidic APJ agonists by N-terminal lipid conjugation.

Agonism of the endothelial receptor APJ (putative receptor protein related to AT1; AT1: angiotensin II receptor type 1) has the potential to ameliorate congestive heart failure by increasing cardiac output without inducing hypertrophy. Although the endogenous agonist, pyr-apelin-13 (1), has shown beneficial APJ-mediated inotropic effects in rats and humans, such effects are short-lived given its extremely short half-life. Here, we report the conjugation of 1 to a fatty acid, providing a lipidated peptide (2) with increased stability that retains inotropic activity in an anesthetized rat myocardial infarction (MI) model. We also report the preparation of a library of 15-mer APJ agonist peptide-lipid conjugates, including adipoyl-γGlu-OEG-OEG-hArg-r-Q-hArg-P-r-NMeLeuSHK-G-Oic-pIPhe-P-DBip-OH (17), a potent APJ agonist with high plasma protein binding and a half-life suitable for once-daily subcutaneous dosing in rats. A correlation between subcutaneous absorption rate and lipid length/type of these conjugates is also reported.

Plasma and Liver Protein Binding of N-Acetylgalactosamine-Conjugated Small Interfering RNA.

Understanding small interfering RNA (siRNA) fraction unbound (f u) in relevant physiologic compartments is critical for establishing pharmacokinetic-pharmacodynamic relationships for this emerging modality. In our attempts to isolate the equilibrium free fraction of N-acetylgalactosamine-conjugated siRNA using classic small-molecule in vitro techniques, we found that the hydrodynamic radius was critical in determining the size exclusion limit requirements for f u isolation, largely validating the siRNA "rigid rod" hypothesis. With this knowledge, we developed an orthogonally validated 50 kDa molecular-mass cutoff ultrafiltration assay to quantify f u in biologic matrices including human, nonhuman primate, rat, and mouse plasma, and human liver homogenate. To enhance understanding of the siRNA-plasma interaction landscape, we examined the effects of various common oligonucleotide therapeutic modifications to the ribose and helix backbone on siRNA f u in plasma (f u,plasma) and found that chemical modifications can alter plasma protein binding by at least 20%. Finally, to gain insight into which specific plasma proteins bind to siRNA, we developed a qualitative screen to identify binding "hits" across a panel of select purified human plasma proteins.

The Role of Protein-Protein and Protein-Membrane Interactions on P450 Function.

This symposium summary, sponsored by the ASPET, was held at Experimental Biology 2015 on March 29, 2015, in Boston, Massachusetts. The symposium focused on: 1) the interactions of cytochrome P450s (P450s) with their redox partners; and 2) the role of the lipid membrane in their orientation and stabilization. Two presentations discussed the interactions of P450s with NADPH-P450 reductase (CPR) and cytochrome b5. First, solution nuclear magnetic resonance was used to compare the protein interactions that facilitated either the hydroxylase or lyase activities of CYP17A1. The lyase interaction was stimulated by the presence of b5 and 17α-hydroxypregnenolone, whereas the hydroxylase reaction was predominant in the absence of b5. The role of b5 was also shown in vivo by selective hepatic knockout of b5 from mice expressing CYP3A4 and CYP2D6; the lack of b5 caused a decrease in the clearance of several substrates. The role of the membrane on P450 orientation was examined using computational methods, showing that the proximal region of the P450 molecule faced the aqueous phase. The distal region, containing the substrate-access channel, was associated with the membrane. The interaction of NADPH-P450 reductase (CPR) with the membrane was also described, showing the ability of CPR to "helicopter" above the membrane. Finally, the endoplasmic reticulum (ER) was shown to be heterogeneous, having ordered membrane regions containing cholesterol and more disordered regions. Interestingly, two closely related P450s, CYP1A1 and CYP1A2, resided in different regions of the ER. The structural characteristics of their localization were examined. These studies emphasize the importance of P450 protein organization to their function.

Microphysiological endothelial models to characterize subcutaneous drug absorption.

The high variability in subcutaneous bioavailability of protein therapeutics is poorly understood, contributing to critical delays in patient access to new therapies. Preclinical animal and in vitro models fail to provide a physiologically relevant testbed to parse potential contributors to human bioavailability, therefore new strategies are necessary. Here, we present a microphysiological model of the human hypodermal vasculature at the injection site to study the interactions of administered protein therapeutics within the microenvironment that influence subcutaneous bioavailability. Our model combines human dermal endothelial cells, fibroblasts, and adipocytes, self-assembled into three-dimensional, perfusable microvessels that express relevant extracellular matrix. We demonstrate the utility of the model for measurement of biophysical parameters within the hypodermal microenvironment that putatively impact protein kinetics and distribution at the injection site. We propose that microphysiological models of the subcutaneous space have applications in preclinical development of protein therapeutics intended for subcutaneous administration with optimal bioavailability.

Utility of physiologically based pharmacokinetic modeling to predict inter-antibody variability in monoclonal antibody pharmacokinetics in mice.

In this investigation, we tested the hypothesis that a physiologically based pharmacokinetic (PBPK) model incorporating measured in vitro metrics of off-target binding can largely explain the inter-antibody variability in monoclonal antibody (mAb) pharmacokinetics (PK). A diverse panel of 83 mAbs was evaluated for PK in wild-type mice and subjected to 10 in vitro assays to measure major physiochemical attributes. After excluding for target-mediated elimination and immunogenicity, 56 of the remaining mAbs with an eight-fold variability in the area under the curve (AUC0-672h: 1.74 × 106 -1.38 × 107 ng∙h/mL) and 10-fold difference in clearance (2.55-26.4 mL/day/kg) formed the training set for this investigation. Using a PBPK framework, mAb-dependent coefficients F1 and F2 modulating pinocytosis rate and convective transport, respectively, were estimated for each mAb with mostly good precision (coefficient of variation (CV%) <30%). F1 was estimated to be the mean and standard deviation of 0.961 ± 0.593, and F2 was estimated to be 2.13 ± 2.62. Using principal component analysis to correlate the regressed values of F1/F2 versus the multidimensional dataset composed of our panel of in vitro assays, we found that heparin chromatography retention time emerged as the predictive covariate to the mAb-specific F1, whereas F2 variability cannot be well explained by these assays. A sigmoidal relationship between F1 and the identified covariate was incorporated within the PBPK framework. A sensitivity analysis suggested plasma concentrations to be most sensitive to F1 when F1 > 1. The predictive utility of the developed PBPK model was evaluated against a separate panel of 14 mAbs biased toward high clearance, among which area under the curve of PK data of 12 mAbs was predicted within 2.5-fold error, and the positive and negative predictive values for clearance prediction were 85% and 100%, respectively. MAb heparin chromatography assay output allowed a priori identification of mAb candidates with unfavorable PK.

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies.

Biologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration-time curve (AUC0-672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL.