Design strategies to address kinetics of drug binding and residence time

Quantitative Prediction of Dissociation Rates of PYK2 Ligands Using Umbrella Sampling and Milestoning

We used umbrella sampling and the milestoning simulation method to study the dissociation of multiple ligands from protein kinase PYK2. The activation barriers obtained from the potential of mean force of the umbrella sampling simulations correlated well with the experimental dissociation rates. Using the zero-temperature string method, we obtained optimized paths along the free-energy surfaces for milestoning simulations of three ligands with a similar structure. The milestoning simulations gave an absolute dissociation rate within 2 orders of magnitude of the experimental value for two ligands but at least 3 orders of magnitude too high for the third. Despite the similarity in their structures, the ligands took different pathways to exit from the binding site of PYK2, making contact with different sets of residues. In addition, the protein experienced different conformational changes for dissociation of the three ligands.

Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A3 Receptor

A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol-1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand's unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol-1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times.

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.

Unbinding Kinetics of Muscarinic M3 Receptor Antagonists Explained by Metadynamics Simulations

The residence time (RT), the time for which a drug remains bound to its biological target, is a critical parameter for drug design. The prediction of this key kinetic property has been proven to be challenging and computationally demanding in the framework of atomistic simulations. In the present work, we setup and applied two distinct metadynamics protocols to estimate the RTs of muscarinic M3 receptor antagonists. In the first method, derived from the conformational flooding approach, the kinetics of unbinding is retrieved from a physics-based parameter known as the acceleration factor α (i.e., the running average over time of the potential deposited in the bound state). Such an approach is expected to recover the absolute RT value for a compound of interest. In the second method, known as the t_META-D approach, a qualitative estimation of the RT is given by the time of simulation required to drive the ligand from the binding site to the solvent bulk. This approach has been developed to reproduce the change of experimental RTs for compounds targeting the same target. Our analysis shows that both computational protocols are able to rank compounds in agreement with their experimental RTs. Quantitative structure-kinetics relationship (SKR) models can be identified and employed to predict the impact of a chemical modification on the experimental RT once a calibration study has been performed.

Qualitative Estimation of Protein-Ligand Complex Stability through Thermal Titration Molecular Dynamics Simulations

The prediction of ligand efficacy has long been linked to thermodynamic properties such as the equilibrium dissociation constant, which considers both the association and the dissociation rates of a defined protein-ligand complex. In the last 15 years, there has been a paradigm shift, with an increased interest in the determination of kinetic properties such as the drug-target residence time since they better correlate with ligand efficacy compared to other parameters. In this article, we present thermal titration molecular dynamics (TTMD), an alternative computational method that combines a series of molecular dynamics simulations performed at progressively increasing temperatures with a scoring function based on protein-ligand interaction fingerprints for the qualitative estimation of protein-ligand-binding stability. The protocol has been applied to four different pharmaceutically relevant test cases, including protein kinase CK1δ, protein kinase CK2, pyruvate dehydrogenase kinase 2, and SARS-CoV-2 main protease, on a variety of ligands with different sizes, structures, and experimentally determined affinity values. In all four cases, TTMD was successfully able to distinguish between high-affinity compounds (low nanomolar range) and low-affinity ones (micromolar), proving to be a useful screening tool for the prioritization of compounds in a drug discovery campaign.

Simulation of ligand dissociation kinetics from the protein kinase PYK2

Early-stage drug discovery projects often focus on equilibrium binding affinity to the target alongside selectivity and other pharmaceutical properties. The kinetics of drug binding are ignored but can have significant influence on drug efficacy. Therefore, increasing attention has been paid on evaluating drug-binding kinetics early in a drug discovery process. Simulating drug-binding kinetics at the atomic level is challenging for the long time scale involved. Here, we used the transition-based reweighting analysis method (TRAM) with the Markov state model to study the dissociation of a ligand from the protein kinase PYK2. TRAM combines biased and unbiased simulations to reduce computational costs. This work used the umbrella sampling technique for the biased simulations. Although using the potential of mean force from umbrella sampling simulations with the transition-state theory over-estimated the dissociation rate by three orders of magnitude, TRAM gave a dissociation rate within an order of magnitude of the experimental value.

Insight into Thermodynamic and Kinetic Profiles in Small-Molecule Optimization

Structure-activity relationships (SARs) and structure-property relationships (SPRs) have been considered the most important factors during the drug optimization process. For medicinal chemists, improvements in the potencies and druglike properties of small molecules are regarded as their major goals. Among them, the binding affinity and selectivity of small molecules on their targets are the most important indicators. In recent years, there has been growing interest in using thermodynamic and kinetic profiles to analyze ligand-receptor interactions, which could provide not only binding affinities but also detailed binding parameters for small-molecule optimization. In this perspective, we are trying to provide an insight into thermodynamic and kinetic profiles in small-molecule optimization. Through a highlight of strategies on the small-molecule optimization with specific cases, we aim to put forward the importance of structure-thermodynamic relationships (STRs) and structure-kinetic relationships (SKRs), which could provide more guidance to find safe and effective small-molecule drugs.

Design, Synthesis, and Biological Characterization of Inhaled p38α/β MAPK Inhibitors for the Treatment of Lung Inflammatory Diseases

The identification of novel inhaled p38α/β mitogen-activated protein kinases (MAPK) (MAPK14/11) inhibitors suitable for the treatment of pulmonary inflammatory conditions has been described. A rational drug design approach started from the identification of a novel tetrahydronaphthalene series, characterized by nanomolar inhibition of p38α with selectivity over p38γ and p38δ isoforms. SAR optimization of 1c is outlined, where improvements in potency against p38α and ligand-enzyme dissociation kinetics led to several compounds showing pronounced anti-inflammatory effects in vitro (inhibition of TNFα release). Targeting of the defined physicochemical properties allowed the identification of compounds 3h, 4e, and 4f, which showed, upon intratracheal instillation, low plasma levels, prolonged lung retention, and anti-inflammatory effects in a rat acute model of a bacterial endotoxin-induced pulmonary inflammation. Compound 4e, in particular, displayed remarkable efficacy and duration of action and was selected for progression in disease models of asthma and chronic obstructive pulmonary disease (COPD).

A guide to enzyme kinetics in early drug discovery

Drugs interact with their target of interest to bring about the desired phenotypic outcome that results in disease alleviation. Traditionally, most lead optimization exercises were driven by affinity measures (like IC₅₀ ) to inform structure-activity relationship (SAR)-guided medicinal chemistry. However, an IC₅₀ value is a thermodynamic estimate measured under equilibrium conditions that can vary as a function of substrate concentration and/or time (the latter especially for nonequilibrium modalities). Further, like other thermodynamic estimates, it is a state-function that is indifferent to the path traversed from the initial state to the final state. This can be a cause for concern in drug discovery given the predominance of nonequilibrium interactions and the open thermodynamic nature of the human system. Under such situations, employing rates along with equilibrium constants (or IC₅₀ values) would be far more relevant to capture the time evolution of the small molecule's interaction with the target of interest. These rates are generally typified by the rate of association, rate of dissociation and the residence time of the small molecule on the target (target occupancy). These parameters, when combined with the concept of target vulnerability, therapeutic window, pharmacokinetic profile of the small molecule, estimates of endogenous ligand and target turnover, will shed critical insights into the kinetics and dynamics of a small molecule's interaction with the protein, and allow realistic modelling of the system to enable optimizations and dosing decisions. With that aim, this guide will attempt to introduce the traditional role of mechanistic enzymology within drug discovery and emphasize the importance of kinetics in guiding SAR-based optimizations. It will also present initial ideas on how kinetic investigation should be positioned relative to the temporal span of a drug-discovery pipeline to leverage maximal utility from the investment in time and effort.

Atomistic description of molecular binding processes based on returning probability theory

The efficiency of molecular binding such as host-guest binding is commonly evaluated in terms of kinetics, such as rate coefficients. In general, to compute the coefficient of the overall binding process, we need to consider both the diffusion of reactants and barrier crossing to reach the bound state. Here, we develop a methodology of quantifying the rate coefficient of binding based on molecular dynamics simulation and returning probability (RP) theory proposed by Kim and Lee [J. Chem. Phys. 131, 014503 (2009)]. RP theory provides a tractable formula of the rate coefficient in terms of the thermodynamic stability and kinetics of the intermediate state on a predefined reaction coordinate. In this study, the interaction energy between reactants is utilized as the reaction coordinate, enabling us to effectively describe the reactants' relative position and orientation on one-dimensional space. Application of this method to the host-guest binding systems, which consist of β-cyclodextrin and small guest molecules, yields the rate coefficients consistent with the experimental results.

The prediction of protein-ligand unbinding for modern drug discovery

INTRODUCTION

Drug-target thermodynamic and kinetic information have perennially important roles in drug design. The prediction of protein-ligand unbinding, which can provide important kinetic information, in experiments continues to face great challenges. Uncovering protein-ligand unbinding through molecular dynamics simulations has become efficient and inexpensive with the progress and enhancement of computing power and sampling methods.

AREAS COVERED

In this review, various sampling methods for protein-ligand unbinding and their basic principles are firstly briefly introduced. Then, their applications in predicting aspects of protein-ligand unbinding, including unbinding pathways, dissociation rate constants, residence time and binding affinity, are discussed.

EXPERT OPINION

Although various sampling methods have been successfully applied in numerous systems, they still have shortcomings and deficiencies. Most enhanced sampling methods require researchers to possess a wealth of prior knowledge of collective variables or reaction coordinates. In addition, most systems studied at present are relatively simple, and the study of complex systems in real drug research remains greatly challenging. Through the combination of machine learning and enhanced sampling methods, prediction accuracy can be further improved, and some problems encountered in complex systems also may be solved.

A Long Residence Time Enoyl-Reductase Inhibitor Explores an Extended Binding Region with Isoenzyme-Dependent Tautomer Adaptation and Differential Substrate-Binding Loop Closure

The enoyl-acyl carrier protein (ACP) reductase (ENR) is a key enzyme within the bacterial fatty-acid synthesis pathway. It has been demonstrated that small-molecule inhibitors carrying the diphenylether (DPE) scaffold bear a great potential for the development of highly specific and effective drugs against this enzyme class. Interestingly, different substitution patterns of the DPE scaffold have been shown to lead to varying effects on the kinetic and thermodynamic behavior toward ENRs from different organisms. Here, we investigated the effect of a 4'-pyridone substituent in the context of the slow tight-binding inhibitor SKTS1 on the inhibition of the Staphylococcus aureus enoyl-ACP-reductase saFabI and the closely related isoenzyme from Mycobacterium tuberculosis, InhA, and explored a new interaction site of DPE inhibitors within the substrate-binding pocket. Using high-resolution crystal structures of both complexes in combination with molecular dynamics (MD) simulations, kinetic measurements, and quantum mechanical (QM) calculations, we provide evidence that the 4'-pyridone substituent adopts different tautomeric forms when bound to the two ENRs. We furthermore elucidate the structural determinants leading to significant differences in the residence time of SKTS1 on both enzymes.

Qualitative Prediction of Ligand Dissociation Kinetics from Focal Adhesion Kinase Using Steered Molecular Dynamics

Most early-stage drug discovery projects focus on equilibrium binding affinity to the target alongside selectivity and other pharmaceutical properties. Since many approved drugs have nonequilibrium binding characteristics, there has been increasing interest in optimizing binding kinetics early in the drug discovery process. As focal adhesion kinase (FAK) is an important drug target, we examine whether steered molecular dynamics (SMD) can be useful for identifying drug candidates with the desired drug-binding kinetics. In simulating the dissociation of 14 ligands from FAK, we find an empirical power–law relationship between the simulated time needed for ligand unbinding and the experimental rate constant for dissociation, with a strong correlation depending on the SMD force used. To improve predictions, we further develop regression models connecting experimental dissociation rate with various structural and energetic quantities derived from the simulations. These models can be used to predict dissociation rates from FAK for related compounds.

Probing the CB1 Cannabinoid Receptor Binding Pocket with AM6538, a High-Affinity Irreversible Antagonist

Cannabinoid receptor 1 (CB₁) is a potential therapeutic target for the treatment of pain, obesity and obesity-related metabolic disorders, and addiction. The crystal structure of human CB₁ has been determined in complex with the stabilizing antagonist AM6538. In the present study, we characterize AM6538 as a tight-binding/irreversible antagonist of CB₁, as well as two derivatives of AM6538 (AM4112 and AM6542) as slowly dissociating CB₁ antagonists across binding simulations and cellular signaling assays. The long-lasting nature of AM6538 was explored in vivo wherein AM6538 continues to block CP55,940-mediated behaviors in mice up to 5 days after a single injection. In contrast, the effects of SR141716A abate in mice 2 days after injection. These studies demonstrate the functional outcome of CB₁ antagonist modification and open the path for development of long-lasting CB₁ antagonists.

Molecular Dynamics Simulations of Adenosine Receptors: Advances, Applications and Trends

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Adenosine receptors (ARs) are transmembrane proteins that belong to the G protein-coupled receptors (GPCRs) superfamily and mediate the biological functions of adenosine. To date, four AR subtypes are known, namely A1, A2A, A2B and A3 that exhibit different signaling pathways, tissue localization, and mechanisms of activation. Moreover, the widespread ARs and their implication in numerous physiological and pathophysiological conditions had made them pivotal therapeutic targets for developing clinically effective agents.

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The crystallographic success in identifying the 3D crystal structures of A2A and A1 ARs has dramatically enriched our understanding of their structural and functional properties such as ligand binding and signal transduction. This, in turn, has provided a structural basis for a larger contribution of computational methods, particularly molecular dynamics (MD) simulations, toward further investigation of their molecular properties and designing bioactive ligands with therapeutic potential. MD simulation has been proved to be an invaluable tool in investigating ARs and providing answers to some critical questions. For example, MD has been applied in studying ARs in terms of ligand-receptor interactions, molecular recognition, allosteric modulations, dimerization, and mechanisms of activation, collectively aiding in the design of subtype selective ligands.

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In this review, we focused on the advances and different applications of MD simulations utilized to study the structural and functional aspects of ARs that can foster the structure-based design of drug candidates. In addition, relevant literature was briefly discussed which establishes a starting point for future advances in the field of drug discovery to this pivotal group of drug targets.

Kinetics of Drug Binding and Residence Time

The kinetics of drug binding and unbinding is assuming an increasingly crucial role in the long, costly process of bringing a new medicine to patients. For example, the time a drug spends in contact with its biological target is known as residence time (the inverse of the kinetic constant of the drug-target unbinding, 1/ koff). Recent reports suggest that residence time could predict drug efficacy in vivo, perhaps even more effectively than conventional thermodynamic parameters (free energy, enthalpy, entropy). There are many experimental and computational methods for predicting drug-target residence time at an early stage of drug discovery programs. Here, we review and discuss the methodological approaches to estimating drug binding kinetics and residence time. We first introduce the theoretical background of drug binding kinetics from a physicochemical standpoint. We then analyze the recent literature in the field, starting from the experimental methodologies and applications thereof and moving to theoretical and computational approaches to the kinetics of drug binding and unbinding. We acknowledge the central role of molecular dynamics and related methods, which comprise a great number of the computational methods and applications reviewed here. However, we also consider kinetic Monte Carlo. We conclude with the outlook that drug (un)binding kinetics may soon become a go/no go step in the discovery and development of new medicines.

Overview of Recent Strategic Advances in Medicinal Chemistry

Introducing novel strategies, concepts, and technologies that speed up drug discovery and the drug development cycle is of great importance both in the highly competitive pharmaceutical industry as well as in academia. This Perspective aims to present a "big-picture" overview of recent strategic innovations in medicinal chemistry and drug discovery.

Binding kinetics of ligands acting at GPCRs

The influence of drug-receptor binding kinetics has often been overlooked during the development of new therapeutics that target G protein-coupled receptors (GPCRs). Over the last decade there has been a growing understanding that an in-depth knowledge of binding kinetics at GPCRs is required to successfully target this class of proteins. Ligand binding to a GPCR is often not a simple single step process with ligand freely diffusing in solution. This review will discuss the experiments and equations that are commonly used to measure binding kinetics and how factors such as allosteric regulation, rebinding and ligand interaction with the plasma membrane may influence these measurements. We will then consider the molecular characteristics of a ligand and if these can be linked to association and dissociation rates.

Protein-ligand interaction fingerprints for accurate prediction of dissociation rates of p38 MAPK Type II inhibitors

Binding/unbinding kinetics are key determinants of drug potencies. However, there are still a lot of challenges in predicting kinetic properties during early-stage drug development. In this work, position-restrained molecular dynamics simulations combined with energy decomposition were applied to extract protein-ligand interaction (PLI) fingerprints along the unbinding pathway of 20 p38 mitogen-activated protein kinase (p38 MAPK) Type II inhibitors. The results showed that the electrostatic and/or van der Waals interaction fingerprints at three key positions can be used for accurate prediction of the dissociation rate constants (koff) of p38 MAPK Type II inhibitors. The strategy proposed in this paper can provide not only an efficient method of predicting the dissociation rates of the p38 MAPK Type II inhibitors, but also the atom-level mechanism of enthalpy-driven unbinding process.

Structural insights reveal a recognition feature for tailoring hydrocarbon stapled-peptides against the eukaryotic translation initiation factor 4E protein

Stapled-peptides have emerged as an exciting class of molecules which can modulate protein-protein interactions. We have used a structure-guided approach to rationally develop a set of hydrocarbon stapled-peptides with high binding affinities and residence times against the oncogenic eukaryotic translation initiation factor 4E (eIF4E) protein. Crystal structures of these peptides in complex with eIF4E show that they form specific interactions with a region on the protein-binding interface of eIF4E which is distinct from the other well-established canonical interactions. This recognition element is a major molecular determinant underlying the improved binding kinetics of these peptides with eIF4E. The interactions were further exploited by designing features in the peptides to attenuate disorder and increase helicity which collectively resulted in the generation of a distinct class of hydrocarbon stapled-peptides targeting eIF4E. This study details new insights into the molecular basis of stapled-peptide: eIF4E interactions and their exploitation to enhance promising lead molecules for the development of stapled-peptide compounds for oncology.

Surface Binding Energy Landscapes Affect Phosphodiesterase Isoform-Specific Inhibitor Selectivity

As human phosphodiesterase (PDE) proteins are attractive drug targets, a large number of selective PDE inhibitors have been developed. However, since the catalytic sites of PDE isoforms are conserved in sequence and structure, it remains unclear how these inhibitors discriminate PDE isoforms in a selective manner. Here we perform long-time scale molecular dynamics (MD) simulations to investigate the spontaneous association processes of a highly selective PDE2A inhibitor (BAY60–7550) with the catalytic pockets of six PDE isoforms. We found that the free-energy landscapes of PDE:BAY60–7550 interactions on the PDE surfaces are very different between various PDE isoforms; and the free-energy landscape of PDE2A forms a favorable low-energy pathway that not only drives BAY60–7550 toward the target binding site, but also guides BAY60–7750 to adopt its native binding conformation known from crystal structure. Thus, this study reveals that the inhibitor interactions with the PDE surface residues play an important role in its high selectivity for PDE2A, and thereby provides new fundamental insights into the PDE isoform-specific inhibitor selectivity.

Chaperome heterogeneity and its implications for cancer study and treatment

The chaperome is the collection of proteins in the cell that carry out molecular chaperoning functions. Changes in the interaction strength between chaperome proteins lead to an assembly that is functionally and structurally distinct from each constituent member. In this review, we discuss the epichaperome, the cellular network that forms when the chaperome components of distinct chaperome machineries come together as stable, functionally integrated, multimeric complexes. In tumors, maintenance of the epichaperome network is vital for tumor survival, rendering them vulnerable to therapeutic interventions that target critical epichaperome network components. We discuss how the epichaperome empowers an approach for precision medicine cancer trials where a new target, biomarker, and relevant drug candidates can be correlated and integrated. We introduce chemical biology methods to investigate the heterogeneity of the chaperome in a given cellular context. Lastly, we discuss how ligand-protein binding kinetics are more appropriate than equilibrium binding parameters to characterize and unravel chaperome targeting in cancer and to gauge the selectivity of ligands for specific tumor-associated chaperome pools.

Link between a high k on for drug binding and a fast clinical action: to be or not to be?

Review articles on binding kinetics essentially focus on drugs that dissociate slowly from their target since this is required for the successful treatment of many pathophysiological conditions. Recently, the therapeutic benefit of a high k on (i.e. the second order association rate constant) has also been linked to fast association and to a fast clinical action. Other studies, however, called this assertion into question since additional factors, like the dosing paradigm and the binding mechanism, are important as well. The still ongoing reticence about integrating binding kinetics in lead optimization programs motivated us to critically review the link between the drug's kinetic rate constants and their in vitro and in vivo target occupancy profile, with special focus on k on. The presented simulations tally with a positive link between a drug's effective/observed association rate (which is quite easy to determine in vitro) and the swiftness of its clinical action. On the other hand, the simulations show that the k on-concept should not be confounded with the effective association process since increasing this parameter only enhances the drug's in vitro and in vivo association under certain conditions: the binding mechanism should be suitable, rebinding (and thus the factors within the target's micro-environment that favour this mechanism) should not be too prominent and the dosage should not be kept in par with the drug's affinity. Otherwise, increasing k on could be ineffective or even be counter-productive.

Kinetic operational models of agonism for G-protein-coupled receptors

The application of kinetics to research and therapeutic development of G-protein-coupled receptors has become increasingly valuable. Pharmacological models provide the foundation of pharmacology, providing concepts and measurable parameters such as efficacy and potency that have underlain decades of successful drug discovery. Currently there are few pharmacological models that incorporate kinetic activity in such a way as to yield experimentally-accessible drug parameters. In this study, a kinetic model of pharmacological response was developed that provides a kinetic descriptor of efficacy (the transduction rate constant, k_τ) and allows measurement of receptor-ligand binding kinetics from functional data. The model assumes: (1) receptor interacts with a precursor of the response ("Transduction potential") and converts it to the response. (2) The response can decay. Familiar response vs time plots emerge, depending on whether transduction potential is depleted and/or response decays. These are the straight line, the "association" exponential curve, and the rise-and-fall curve. Convenient, familiar methods are described for measuring the model parameters and files are provided for the curve-fitting program Prism (GraphPad Software) that can be used as a guide. The efficacy parameter k_τ is straightforward to measure and accounts for receptor reserve; all that is required is measurement of response over time at a maximally-stimulating concentration of agonist. The modular nature of the model framework allows it to be extended. Here this is done to incorporate antagonist-receptor binding kinetics and slow agonist-receptor equilibration. In principle, the modular framework can incorporate other cellular processes, such as receptor desensitization. The kinetic response model described here can be applied to measure kinetic pharmacological parameters than can be used to advance the understanding of GPCR pharmacology and optimize new and improved therapeutics.

Binding Thermodynamics and Kinetics Calculations Using Chemical Host and Guest: A Comprehensive Picture of Molecular Recognition

Understanding the fine balance between changes of entropy and enthalpy and the competition between a guest and water molecules in molecular binding is crucial in fundamental studies and practical applications. Experiments provide measurements. However, illustrating the binding/unbinding processes gives a complete picture of molecular recognition not directly available from experiments, and computational methods bridge the gaps. Here, we investigated guest association/dissociation with β-cyclodextrin (β-CD) by using microsecond-time-scale molecular dynamics (MD) simulations, postanalysis and numerical calculations. We computed association and dissociation rate constants, enthalpy, and solvent and solute entropy of binding. All the computed values of kon, koff, ΔH, ΔS, and ΔG using GAFF-CD and q4MD-CD force fields for β-CD could be compared with experimental data directly and agreed reasonably with experiment findings. In addition, our study further interprets experiments. Both force fields resulted in similar computed ΔG from independently computed kinetics rates, ΔG = -RT ln(kon·C0/koff), and thermodynamics properties, ΔG = ΔH - TΔS. The water entropy calculations show that the entropy gain of desolvating water molecules are a major driving force, and both force fields have the same strength of nonpolar attractions between solutes and β-CD as well. Water molecules play a crucial role in guest binding to β-CD. However, collective water/β-CD motions could contribute to different computed kon and ΔH values by different force fields, mainly because the parameters of β-CD provide different motions of β-CD, hydrogen-bond networks of water molecules in the cavity of free β-CD, and strength of desolvation penalty. As a result, q4MD-CD suggests that guest binding is mostly driven by enthalpy, while GAFF-CD shows that gaining entropy is the major driving force of binding. The study deepens our understanding of ligand-receptor recognition and suggests strategies for force field parametrization for accurately modeling molecular systems.

A binding kinetics study of human adenosine A3 receptor agonists

The human adenosine A₃ (hA₃) receptor has been suggested as a viable drug target in inflammatory diseases and in cancer. So far, a number of selective hA₃ receptor agonists (e.g. IB-MECA and 2-Cl-IB-MECA) inducing anti-inflammatory or anticancer effects are under clinical investigation. Drug-target binding kinetics is increasingly recognized as another pharmacological parameter, next to affinity, for compound triage in the early phases of drug discovery. However, such a kinetics-driven analysis has not yet been performed for the hA₃ receptor. In this study, we first validated a competition association assay for adenosine A₃ receptor agonists to determine the target interaction kinetics. Affinities and Kinetic Rate Index (KRI) values of 11 ribofurano and 10 methanocarba nucleosides were determined in radioligand binding assays. Afterwards, 15 analogues were further selected (KRI <0.70 or KRI >1.35) for full kinetics characterization. The structure-kinetics relationships (SKR) were derived and longer residence times were associated with methanocarba and enlarged adenine N⁶ and C2 substitutions. In addition, from a k_on-k_off-K_D kinetic map we divided the agonists into three subgroups. A residence time "cliff" was observed, which might be relevant to (N)-methanocarba derivatives' rigid C2-arylalkynyl substitutions. Our findings provide substantial evidence that, next to affinity, additional knowledge of binding kinetics is useful for developing and selecting new hA₃R agonists in the early phase of the drug discovery process.

Distinct in vivo target occupancy by bivalent- and induced-fit-like binding drugs

BACKGROUND AND PURPOSE

Optimal drug therapy often requires long-lasting target occupancy While this attribute was usually linked to the drug's pharmacokinetic properties, the dissociation rate is now increasingly recognized to contribute as well. Nearly all the earlier pharmacokinetic-pharmacodynamic (PK-PD) simulations encompassed single-step binding drugs and focused on koff . However, 'micro'-PK mechanisms and more complex binding mechanisms like bivalent- and induced-fit binding may contribute as well. Corresponding binding models are presently explored.

EXPERIMENTAL APPROACH

We compared the 24 h in vivo occupancy over time profiles of prototype bivalent- and induced-fit-like binding drugs (A and B) after one or repeated daily dosings, both without and with rebinding. Special attention was focused on the effect of each of the microscopic rate constants on the occupancy profiles and on the metrics to represent those profiles.

KEY RESULTS

Although both models can be represented by the same mathematical formulation, drugs A and B display quite different occupancy profiles, even though they have the same potency. These differences can be attributed to the different effects of their microscopic rate constants on their composite koff and also on their susceptibility to experience rebinding. This also affects how the occupancy profiles of bivalent- and induced-fit-like binders progress when repeating the dosings and by changing the dosage.

CONCLUSIONS AND IMPLICATIONS

Closer attention should be paid to more complex binding models in PK-PD simulations. This may help pharmacologists and medicinal chemists to improve the translation of in vitro kinetic measurements from preclinical screening programmes into clinical efficiency.

Discovery and Optimization of Potent, Cell-Active Pyrazole-Based Inhibitors of Lactate Dehydrogenase (LDH)

We report the discovery and medicinal chemistry optimization of a novel series of pyrazole-based inhibitors of human lactate dehydrogenase (LDH). Utilization of a quantitative high-throughput screening paradigm facilitated hit identification, while structure-based design and multiparameter optimization enabled the development of compounds with potent enzymatic and cell-based inhibition of LDH enzymatic activity. Lead compounds such as 63 exhibit low nM inhibition of both LDHA and LDHB, submicromolar inhibition of lactate production, and inhibition of glycolysis in MiaPaCa2 pancreatic cancer and A673 sarcoma cells. Moreover, robust target engagement of LDHA by lead compounds was demonstrated using the cellular thermal shift assay (CETSA), and drug-target residence time was determined via SPR. Analysis of these data suggests that drug-target residence time (off-rate) may be an important attribute to consider for obtaining potent cell-based inhibition of this cancer metabolism target.

Modulation of Glycine-Mediated Spinal Neurotransmission for the Treatment of Chronic Pain

Chronic pain constitutes a significant and expanding worldwide health crisis. Currently available analgesics poorly serve individuals suffering from chronic pain, and new therapeutic agents that are more effective, safer, and devoid of abuse liabilities are desperately needed. Among the myriad of cellular and molecular processes contributing to chronic pain, spinal disinhibition of pain signaling to higher cortical centers plays a critical role. Accumulating evidence shows that glycinergic inhibitory neurotransmission in the spinal cord dorsal horn gates nociceptive signaling, is essential in maintaining physiological pain sensitivity, and is diminished in pathological pain states. Thus, it is hypothesized that agents capable of enhancing glycinergic tone within the dorsal horn could obtund nociceptor signaling to the brain and serve as analgesics for persistent pain. This Perspective highlights the potential that pharmacotherapies capable of increasing inhibitory spinal glycinergic neurotransmission hold in providing new and transformative analgesic therapies for the treatment of chronic pain.

Design, Synthesis, and Biological Evaluation of Novel Type I1/2 p38α MAP Kinase Inhibitors with Excellent Selectivity, High Potency, and Prolonged Target Residence Time by Interfering with the R-Spine

We recently reported 1a (skepinone-L) as a type I p38α MAP kinase inhibitor with high potency and excellent selectivity in vitro and in vivo. However, as a type I inhibitor, it is entirely ATP-competitive and shows just a moderate residence time. Thus, the scope was to develop a new class of advanced compounds maintaining the structural binding features of skepinone-L scaffold like inducing a glycine flip at the hinge region and occupying both hydrophobic regions I and II. Extending this scaffold with suitable residues resulted in an interference with the kinase's R-Spine. By synthesizing 69 compounds, we could significantly prolong the target residence time with one example to 3663 s, along with an excellent selectivity score of 0.006 and an outstanding potency of 1.0 nM. This new binding mode was validated by cocrystallization, showing all binding interactions typifying type I¹/₂ binding. Moreover, microsomal studies showed convenient metabolic stability of the most potent, herein reported representatives.

Structure-Affinity Relationships and Structure-Kinetics Relationships of Pyrido[2,1-f]purine-2,4-dione Derivatives as Human Adenosine A3 Receptor Antagonists

We expanded on a series of pyrido[2,1-f]purine-2,4-dione derivatives as human adenosine A₃ receptor (hA₃R) antagonists to determine their kinetic profiles and affinities. Many compounds showed high affinities and a diverse range of kinetic profiles. We found hA₃R antagonists with very short residence time (RT) at the receptor (2.2 min for 5) and much longer RTs (e.g., 376 min for 27 or 391 min for 31). Two representative antagonists (5 and 27) were tested in [³⁵S]GTPγS binding assays, and their RTs appeared correlated to their (in)surmountable antagonism. From a k_on–k_off–K_D kinetic map, we divided the antagonists into three subgroups, providing a possible direction for the further development of hA₃R antagonists. Additionally, we performed a computational modeling study that sheds light on the crucial receptor interactions, dictating the compounds’ binding kinetics. Knowledge of target binding kinetics appears useful for developing and triaging new hA₃R antagonists in the early phase of drug discovery.

Conformational energy range of ligands in protein crystal structures: The difficult quest for accurate understanding

In this review, we address a fundamental question: What is the range of conformational energies seen in ligands in protein-ligand crystal structures? This value is important biophysically, for better understanding the protein-ligand binding process; and practically, for providing a parameter to be used in many computational drug design methods such as docking and pharmacophore searches. We synthesize a selection of previously reported conflicting results from computational studies of this issue and conclude that high ligand conformational energies really are present in some crystal structures. The main source of disagreement between different analyses appears to be due to divergent treatments of electrostatics and solvation. At the same time, however, for many ligands, a high conformational energy is in error, due to either crystal structure inaccuracies or incorrect determination of the reference state. Aside from simple chemistry mistakes, we argue that crystal structure error may mainly be because of the heuristic weighting of ligand stereochemical restraints relative to the fit of the structure to the electron density. This problem cannot be fixed with improvements to electron density fitting or with simple ligand geometry checks, though better metrics are needed for evaluating ligand and binding site chemistry in addition to geometry during structure refinement. The ultimate solution for accurately determining ligand conformational energies lies in ultrahigh-resolution crystal structures that can be refined without restraints.

Binding Kinetics and Pathways of Ligands to GPCRs

Previously, drugs were developed focusing on target affinity and selectivity. However, it is becoming evident that the drug-target residence time, related to the off-rate, is an important parameter for successful drug development. The residence time influences both the on-rate and overall effectiveness of drugs. Furthermore, ligand binding is now appreciated to be a multistep process because metastable and/or intermediate binding sites in the extracellular region have been identified. In this review, we summarize experimental ligand-binding data for G-protein-coupled receptors (GPCRs), and their binding pathways, analyzed by molecular dynamics (MD). The kinetics of drug binding to GPCRs are complex and depend on several factors, including charge distribution on the receptor surface, ligand-receptor interactions in the binding channel and the binding site, or solvation.

Systematic Dissociation Pathway Searches Guided by Principal Component Modes

We introduce a novel method, Pathway Search guided by Internal Motions (PSIM), that efficiently finds molecular dissociation pathways of a ligand-receptor system with guidance from principal component (PC) modes obtained from molecular dynamics (MD) simulations. Modeling ligand-receptor dissociation pathways can provide insights into molecular recognition and has practical applications, including understanding kinetic mechanisms and barriers to binding/unbinding as well as design of drugs with desired kinetic properties. PSIM uses PC modes in multilayer internal coordinates to identify natural molecular motions that guide the search for conformational switches and unbinding pathways. The new multilayer internal coordinates overcome problems with Cartesian and classical internal coordinates that fail to smoothly present dihedral rotation or generate nonphysical distortions. We used HIV-1 protease, which has large-scale flap motions, as an example protein to demonstrate use of the multilayer internal coordinates. We provide examples of algorithms and implementation of PSIM with alanine dipeptide and chemical host-guest systems, 2-naphthyl ethanol-β-cyclodextrin and tetramethylammonium-cryptophane complexes. Tetramethylammonium-cryptophane has slow binding/unbinding kinetics. Its residence time, the length to dissociate tetramethylammonium from the host, is ∼14 s from experiments, and PSIM revealed 4 dissociation pathways in approximately 150 CPU h. We also searched the releasing pathways for the product glyceraldehyde-3-phosphate from tryptophan synthase, and one complete dissociation pathway was constructed after running multiple search iterations in approximately 300 CPU h. With guidance by internal PC modes from MD simulations, the PSIM method has advantages over simulation-based methods to search for dissociation pathways of molecular systems with slow noncovalent kinetic behavior.

Pharmacological property optimization for allosteric ligands: A medicinal chemistry perspective

New strategies to potentially improve drug safety and efficacy emerge with allosteric programs. Biased allosteric modulators can be designed with high subtype selectivity and defined receptor signaling endpoints, however, selecting the most meaningful parameters for optimization can be perplexing. Historically, "potency hunting" at the expense of physicochemical and pharmacokinetic optimization has led to numerous tool compounds with excellent pharmacological properties but no path to drug development. Conversely, extensive physicochemical and pharmacokinetic screening with only post hoc bias and allosteric characterization has led to inefficacious compounds or compounds with on-target toxicities. This field is rapidly evolving with new mechanistic understanding, changes in terminology, and novel opportunities. The intent of this digest is to summarize current understanding and debates within the field. We aim to discuss, from a medicinal chemistry perspective, the parameter choices available to drive SAR.

A novel CCR2 antagonist inhibits atherogenesis in apoE deficient mice by achieving high receptor occupancy

CC Chemokine Receptor 2 (CCR2) and its endogenous ligand CCL2 are involved in a number of diseases, including atherosclerosis. Several CCR2 antagonists have been developed as potential therapeutic agents, however their in vivo clinical efficacy was limited. In this report, we aimed to determine whether 15a, an antagonist with a long residence time on the human CCR2, is effective in inhibiting the development of atherosclerosis in a mouse disease model. First, radioligand binding assays were performed to determine affinity and binding kinetics of 15a on murine CCR2. To assess the in vivo efficacy, western-type diet fed apoE-/- mice were treated daily with 15a or vehicle as control. Treatment with 15a reduced the amount of circulating CCR2+ monocytes and the size of the atherosclerotic plaques in both the carotid artery and the aortic root. We then showed that the long pharmacokinetic half-life of 15a combined with the high drug concentrations ensured prolonged CCR2 occupancy. These data render 15a a promising compound for drug development and confirms high receptor occupancy as a key parameter when targeting chemokine receptors.

Protein-ligand (un)binding kinetics as a new paradigm for drug discovery at the crossroad between experiments and modelling

In the last three decades, protein and nucleic acid structure determination and comprehension of the mechanisms, leading to their physiological and pathological functions, have become a cornerstone of biomedical sciences. A deep understanding of the principles governing the fates of cells and tissue at the molecular level has been gained over the years, offering a solid basis for the rational design of drugs aimed at the pharmacological treatment of numerous diseases. Historically, affinity indicators (i.e. Kd and IC50/EC50) have been assumed to be valid indicators of the in vivo efficacy of a drug. However, recent studies pointed out that the kinetics of the drug-receptor binding process could be as important or even more important than affinity in determining the drug efficacy. This eventually led to a growing interest in the characterisation and prediction of the rate constants of protein-ligand association and dissociation. For instance, a drug with a longer residence time can kinetically select a given receptor over another, even if the affinity for both receptors is comparable, thus increasing its therapeutic index. Therefore, understanding the molecular features underlying binding and unbinding processes is of central interest towards the rational control of drug binding kinetics. In this review, we report the theoretical framework behind protein-ligand association and highlight the latest advances in the experimental and computational approaches exploited to investigate the binding kinetics.

Evaluating the Contribution of Transition-State Destabilization to Changes in the Residence Time of Triazole-Based InhA Inhibitors

A critical goal of lead compound selection and optimization is to maximize target engagement while minimizing off-target binding. Since target engagement is a function of both the thermodynamics and kinetics of drug-target interactions, it follows that the structures of both the ground states and transition states on the binding reaction coordinate are needed to rationally modulate the lifetime of the drug-target complex. Previously, we predicted the structure of the rate-limiting transition state that controlled the time-dependent inhibition of the enoyl-ACP reductase InhA. This led to the discovery of a triazole-containing diphenyl ether with an increased residence time on InhA due to transition-state destabilization rather than ground-state stabilization. In the present work, we evaluate the inhibition of InhA by 14 triazole-based diphenyl ethers and use a combination of enzyme kinetics and X-ray crystallography to generate a structure-kinetic relationship for time-dependent binding. We show that the triazole motif slows the rate of formation for the final drug-target complex by up to 3 orders of magnitude. In addition, we identify a novel inhibitor with a residence time on InhA of 220 min, which is 3.5-fold longer than that of the INH-NAD adduct formed by the tuberculosis drug, isoniazid. This study provides a clear example in which the lifetime of the drug-target complex is controlled by interactions in the transition state for inhibitor binding rather than the ground state of the enzyme-inhibitor complex, and demonstrates the important role that on-rates can play in drug-target residence time.

A High-Throughput Method for Measuring Drug Residence Time Using the Transcreener ADP Assay

Analysis of drug-target residence times during drug development can result in improved efficacy, increased therapeutic window, and reduced side effects. Residence time can be estimated as the reciprocal of the dissociation rate ( k_off) of an inhibitor from its target. The traditional methods for measuring k_off require synthesis of labeled ligands or low-throughput label-free methods. To provide an alternative that is better suited to an automated high-throughput screening (HTS) environment, we adapted a classic "jump dilution" catalytic assay method for determination of k_off values for kinase inhibitor drugs. We used the Transcreener ADP² Kinase assay as a universal, homogenous method to monitor the recovery of kinase activity as the drugs dissociated from preformed inhibitor-kinase complexes. We measured residence times for several drugs that bind the epidermal growth factor receptor (EGFR), ABL1, and Aurora kinases and found that the rank ordering of inhibitor k_off values correlated with literature values determined using ligand binding assays. Moreover, very similar results were obtained using the Transcreener assay with fluorescence polarization (FP), fluorescence intensity (FI), and time-resolved Förster resonance energy transfer (TR-FRET) detection modes. This HTS-compatible, generic assay method should facilitate the use of residence time as a parameter for compound prioritization and optimization early in kinase drug discovery programs.

Biophysics in drug discovery: impact, challenges and opportunities

Over the past 25 years, biophysical technologies such as X-ray crystallography, nuclear magnetic resonance spectroscopy, surface plasmon resonance spectroscopy and isothermal titration calorimetry have become key components of drug discovery platforms in many pharmaceutical companies and academic laboratories. There have been great improvements in the speed, sensitivity and range of possible measurements, providing high-resolution mechanistic, kinetic, thermodynamic and structural information on compound-target interactions. This Review provides a framework to understand this evolution by describing the key biophysical methods, the information they can provide and the ways in which they can be applied at different stages of the drug discovery process. We also discuss the challenges for current technologies and future opportunities to use biophysical methods to solve drug discovery problems.

Comparative Analysis of Binding Kinetics and Thermodynamics of Dipeptidyl Peptidase-4 Inhibitors and Their Relationship to Structure

The binding kinetics and thermodynamics of dipeptidyl peptidase (DPP)-4 inhibitors (gliptins) were investigated using surface plasmon resonance and isothermal titration calorimetry. Binding of gliptins to DPP-4 is a rapid electrostatically driven process. Off-rates were generally slow partly because of reversible covalent bond formation by some gliptins, and partly because of strong and extensive interactions. Binding of all gliptins is enthalpy-dominated due to strong ionic interactions and strong solvent-shielded hydrogen bonds. Using a congeneric series of molecules which represented the intermediates in the lead optimization program of linagliptin, the onset of slow binding kinetics and development of the thermodynamic repertoire were analyzed in the context of incremental changes of the chemical structures. All compounds rapidly associated, and therefore the optimization of affinity and residence time is highly correlated. The major contributor to the increasing free energy of binding was a strong increase of binding enthalpy, whereas entropic contributions remained low and constant despite significant addition of lipophilicity.

Effects of target binding kinetics on in vivo drug efficacy: koff , kon and rebinding

BACKGROUND AND PURPOSE

Optimal drug therapy often requires continuing high levels of target occupancy. Besides the traditional pharmacokinetic contribution, target binding kinetics is increasingly considered to play an important role as well. While most attention has been focused on the dissociation rate of the complex, recent reports expressed doubt about the unreserved translatability of this pharmacodynamic property into clinical efficacy. 'Micro'-pharmacokinetic mechanisms like drug rebinding and partitioning into the cell membrane may constitute a potential fix.

EXPERIMENTAL APPROACH

Simulations were based on solving differential equations.

KEY RESULTS

Based on a selected range of association and dissociation rate constants, kon and koff , and rebinding potencies of the drugs as variables, their effects on the temporal in vivo occupancy profile of their targets, after one or multiple repetitive dosings, have here been simulated.

CONCLUSIONS AND IMPLICATIONS

Most strikingly, the simulations show that, when rebinding is also taken into account, increasing kon may produce closely the same outcome as decreasing koff when dosing is performed in accordance with the therapeutically most relevant constant [Lmax ]/KD ratio paradigm. Also, under certain conditions, rebinding may produce closely the same outcome as invoking slow diffusion of the drug between the plasma compartment and a target-containing 'effect' compartment. Although the present simulations should only be regarded as a 'proof of principle', these findings may help pharmacologists and medicinal chemists to devise ex vivo and in vitro binding kinetic assays that are more relevant and translatable to in vivo settings.

Impact, determination and prediction of drug-receptor residence times for GPCRs

The residence time of a ligand on a GPCR of interest has become an optimization parameter in many examples in drug design. Long residence times can counterbalance unfavorable pharmacokinetic parameters, contributing to compound safety, and short residence times can be a tool to avoid target related side effects. Unlike the prediction and interpretation of the structure-activity relationship (SAR) of a ligand class on a receptor, the understanding and prediction of the structure-kinetics relationship (SKR) is much more demanding. Experimental and computational approaches are described, which serve to either rationalize SKR or to predict the kinetic parameters such as on-rates and off-rates.

Conformational Adaption May Explain the Slow Dissociation Kinetics of Roniciclib (BAY 1000394), a Type I CDK Inhibitor with Kinetic Selectivity for CDK2 and CDK9

Roniciclib (BAY 1000394) is a type I pan-CDK (cyclin-dependent kinase) inhibitor which has revealed potent efficacy in xenograft cancer models. Here, we show that roniciclib displays prolonged residence times on CDK2 and CDK9, whereas residence times on other CDKs are transient, thus giving rise to a kinetic selectivity of roniciclib. Surprisingly, variation of the substituent at the 5-position of the pyrimidine scaffold results in changes of up to 3 orders of magnitude of the drug-target residence time. CDK2 X-ray cocrystal structures have revealed a DFG-loop adaption for the 5-(trifluoromethyl) substituent, while for hydrogen and bromo substituents the DFG loop remains in its characteristic type I inhibitor position. In tumor cells, the prolonged residence times of roniciclib on CDK2 and CDK9 are reflected in a sustained inhibitory effect on retinoblastoma protein (RB) phosphorylation, indicating that the target residence time on CDK2 may contribute to sustained target engagement and antitumor efficacy.