1
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Liu H, Zhang H, IJzerman AP, Guo D. The translational value of ligand-receptor binding kinetics in drug discovery. Br J Pharmacol 2023. [PMID: 37705429 DOI: 10.1111/bph.16241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/27/2023] [Accepted: 09/01/2023] [Indexed: 09/15/2023] Open
Abstract
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.
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Affiliation(s)
- Hongli Liu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Haoran Zhang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Adriaan P IJzerman
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, The Netherlands
| | - Dong Guo
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
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2
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Galvani F, Pala D, Cuzzolin A, Scalvini L, Lodola A, Mor M, Rizzi A. Unbinding Kinetics of Muscarinic M3 Receptor Antagonists Explained by Metadynamics Simulations. J Chem Inf Model 2023; 63:2842-2856. [PMID: 37053454 PMCID: PMC10170513 DOI: 10.1021/acs.jcim.3c00042] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/15/2023]
Abstract
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 tMETA-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.
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Affiliation(s)
- Francesca Galvani
- Dipartimento di Scienze degli Alimenti e del Farmaco, Università degli Studi di Parma, Parco Area delle Scienze 27/A, I-43124 Parma, Italy
| | - Daniele Pala
- Chemistry Research and Drug Design Department, Chiesi Farmaceutici S.p.A., Largo F. Belloli 11/A, 43122 Parma, Italy
| | - Alberto Cuzzolin
- Chemistry Research and Drug Design Department, Chiesi Farmaceutici S.p.A., Largo F. Belloli 11/A, 43122 Parma, Italy
| | - Laura Scalvini
- Dipartimento di Scienze degli Alimenti e del Farmaco, Università degli Studi di Parma, Parco Area delle Scienze 27/A, I-43124 Parma, Italy
| | - Alessio Lodola
- Dipartimento di Scienze degli Alimenti e del Farmaco, Università degli Studi di Parma, Parco Area delle Scienze 27/A, I-43124 Parma, Italy
| | - Marco Mor
- Dipartimento di Scienze degli Alimenti e del Farmaco, Università degli Studi di Parma, Parco Area delle Scienze 27/A, I-43124 Parma, Italy
- Microbiome Research Hub, University of Parma, Parco Area delle Scienze 11/A, I-43124 Parma, Italy
| | - Andrea Rizzi
- Chemistry Research and Drug Design Department, Chiesi Farmaceutici S.p.A., Largo F. Belloli 11/A, 43122 Parma, Italy
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3
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Srinivasan B. A guide to enzyme kinetics in early drug discovery. FEBS J 2022; 290:2292-2305. [PMID: 35175693 DOI: 10.1111/febs.16404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 02/10/2022] [Accepted: 02/15/2022] [Indexed: 12/28/2022]
Abstract
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.
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Affiliation(s)
- Bharath Srinivasan
- Mechanistic and Structural Biology Discovery Sciences R&D AstraZeneca Cambridge UK
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4
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Potterton A, Heifetz A, Townsend-Nicholson A. Predicting Residence Time of GPCR Ligands with Machine Learning. Methods Mol Biol 2022; 2390:191-205. [PMID: 34731470 DOI: 10.1007/978-1-0716-1787-8_8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Drug-target residence time, the duration of binding at a given protein target, has been shown in some protein families to be more significant for conferring efficacy than binding affinity. To carry out efficient optimization of residence time in drug discovery, machine learning models that can predict that value need to be developed. One of the main challenges with predicting residence time is the paucity of data. This chapter outlines all of the currently available ligand kinetic data, providing a repository that contains the largest publicly available source of GPCR-ligand kinetic data to date. To help decipher the features of kinetic data that might be beneficial to include in computational models for the prediction of residence time, the experimental evidence for properties that influence residence time are summarized. Finally, two different workflows for predicting residence time with machine learning are outlined. The first is a single-target model trained on ligand features; the second is a multi-target model trained on features generated from molecular dynamics simulations.
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Affiliation(s)
- Andrew Potterton
- Structural and Molecular Biology, University College London, London, UK
- Evotec (U.K.) Ltd., Abingdon, Oxfordshire, UK
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5
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Wan S, Potterton A, Husseini FS, Wright DW, Heifetz A, Malawski M, Townsend-Nicholson A, Coveney PV. Hit-to-lead and lead optimization binding free energy calculations for G protein-coupled receptors. Interface Focus 2020; 10:20190128. [PMID: 33178414 PMCID: PMC7653344 DOI: 10.1098/rsfs.2019.0128] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/06/2020] [Indexed: 12/13/2022] Open
Abstract
We apply the hit-to-lead ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and lead-optimization TIES (thermodynamic integration with enhanced sampling) methods to compute the binding free energies of a series of ligands at the A1 and A2A adenosine receptors, members of a subclass of the GPCR (G protein-coupled receptor) superfamily. Our predicted binding free energies, calculated using ESMACS, show a good correlation with previously reported experimental values of the ligands studied. Relative binding free energies, calculated using TIES, accurately predict experimentally determined values within a mean absolute error of approximately 1 kcal mol-1. Our methodology may be applied widely within the GPCR superfamily and to other small molecule-receptor protein systems.
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Affiliation(s)
- Shunzhou Wan
- Centre for Computational Science, Department of Chemistry, University College London, London WC1H 0AJ, UK
| | - Andrew Potterton
- Institute of Structural and Molecular Biology, Research Department of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, UK
| | - Fouad S. Husseini
- Centre for Computational Science, Department of Chemistry, University College London, London WC1H 0AJ, UK
| | - David W. Wright
- Centre for Computational Science, Department of Chemistry, University College London, London WC1H 0AJ, UK
| | - Alexander Heifetz
- Institute of Structural and Molecular Biology, Research Department of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, UK
- Evotec (UK) Ltd, 114 Innovation Drive, Milton Park, Abingdon OX14 4RZ, UK
| | - Maciej Malawski
- ACK Cyfronet, AGH University of Science and Technology, Nawojki 11, 30-950, Kraków, Poland
| | - Andrea Townsend-Nicholson
- Institute of Structural and Molecular Biology, Research Department of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, UK
| | - Peter V. Coveney
- Centre for Computational Science, Department of Chemistry, University College London, London WC1H 0AJ, UK
- Computational Science Laboratory, Institute for Informatics, Faculty of Science, University of Amsterdam, 1098XH Amsterdam, The Netherlands
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6
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Borisov DV, Veselovsky AV. [Ligand-receptor binding kinetics in drug design]. BIOMEDITSINSKAIA KHIMIIA 2020; 66:42-53. [PMID: 32116225 DOI: 10.18097/pbmc20206601042] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Traditionally, the thermodynamic values of affinity are considered as the main criterion for the development of new drugs. Usually, these values for drugs are measured <i>in vitro</i> at steady concentrations of the receptor and ligand, which are differed from <i>in vivo</i> environment. Recent studies have shown that the kinetics of the process of drug binding to its receptor make significant contribution in the drug effectiveness. This has increased attention in characterizing and predicting the rate constants of association and dissociation of the receptor ligand at the stage of preclinical studies of drug candidates. A drug with a long residence time can determine ligand-receptor selectivity (kinetic selectivity), maintain pharmacological activity of the drug at its low concentration in vivo. The paper discusses the theoretical basis of protein-ligand binding, molecular determinants that control the kinetics of the drug-receptor binding. Understanding the molecular features underlying the kinetics of receptor-ligand binding will contribute to the rational design of drugs with desired properties.
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Affiliation(s)
- D V Borisov
- Institute of Biomedical Chemistry, Moscow, Russia
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7
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Long residence time adenosine A1 receptor agonists produce sustained wash-resistant antilipolytic effect in rat adipocytes. Biochem Pharmacol 2019; 164:45-52. [DOI: 10.1016/j.bcp.2019.03.032] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2019] [Accepted: 03/20/2019] [Indexed: 02/06/2023]
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8
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Potterton A, Husseini FS, Southey MWY, Bodkin MJ, Heifetz A, Coveney PV, Townsend-Nicholson A. Ensemble-Based Steered Molecular Dynamics Predicts Relative Residence Time of A 2A Receptor Binders. J Chem Theory Comput 2019; 15:3316-3330. [PMID: 30893556 DOI: 10.1021/acs.jctc.8b01270] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Drug-target residence time, the length of time for which a small molecule stays bound to its receptor target, has increasingly become a key property for optimization in drug discovery programs. However, its in silico prediction has proven difficult. Here we describe a method, using atomistic ensemble-based steered molecular dynamics (SMD), to observe the dissociation of ligands from their target G protein-coupled receptor in a time scale suitable for drug discovery. These dissociation simulations accurately, precisely, and reproducibly identify ligand-residue interactions and quantify the change in ligand energy values for both protein and water. The method has been applied to 17 ligands of the A2A adenosine receptor, all with published experimental kinetic binding data. The residues that interact with the ligand as it dissociates are known experimentally to have an effect on binding affinities and residence times. There is a good correlation ( R2 = 0.79) between the computationally calculated change in water-ligand interaction energy and experimentally determined residence time. Our results indicate that ensemble-based SMD is a rapid, novel, and accurate semi-empirical method for the determination of drug-target relative residence time.
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Affiliation(s)
- Andrew Potterton
- Institute of Structural & Molecular Biology, Research Department of Structural & Molecular Biology, Division of Biosciences , University College London , London WC1E 6BT , United Kingdom
| | - Fouad S Husseini
- Centre for Computational Science, Department of Chemistry , University College London , London WC1H 0AJ , United Kingdom
| | - Michelle W Y Southey
- Evotec (U.K.) Ltd., 114 Innovation Drive, Milton Park , Abingdon , Oxfordshire OX14 4RZ , United Kingdom
| | - Mike J Bodkin
- Evotec (U.K.) Ltd., 114 Innovation Drive, Milton Park , Abingdon , Oxfordshire OX14 4RZ , United Kingdom
| | - Alexander Heifetz
- Institute of Structural & Molecular Biology, Research Department of Structural & Molecular Biology, Division of Biosciences , University College London , London WC1E 6BT , United Kingdom.,Evotec (U.K.) Ltd., 114 Innovation Drive, Milton Park , Abingdon , Oxfordshire OX14 4RZ , United Kingdom
| | - Peter V Coveney
- Centre for Computational Science, Department of Chemistry , University College London , London WC1H 0AJ , United Kingdom.,Computational Science Laboratory, Institute for Informatics, Faculty of Science , University of Amsterdam , Amsterdam 1098XH , The Netherlands
| | - Andrea Townsend-Nicholson
- Institute of Structural & Molecular Biology, Research Department of Structural & Molecular Biology, Division of Biosciences , University College London , London WC1E 6BT , United Kingdom
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9
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Mocking TAM, Verweij EWE, Vischer HF, Leurs R. Homogeneous, Real-Time NanoBRET Binding Assays for the Histamine H 3 and H 4 Receptors on Living Cells. Mol Pharmacol 2018; 94:1371-1381. [PMID: 30249614 DOI: 10.1124/mol.118.113373] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 09/19/2018] [Indexed: 11/22/2022] Open
Abstract
Receptor-binding affinity and ligand-receptor residence time are key parameters for the selection of drug candidates and are routinely determined using radioligand competition-binding assays. Recently, a novel bioluminescence resonance energy transfer (BRET) method utilizing a NanoLuc-fused receptor was introduced to detect fluorescent ligand binding. Moreover, this NanoBRET method gives the opportunity to follow fluorescent ligand binding on intact cells in real time, and therefore, results might better reflect in vivo conditions as compared with the routinely used cell homogenates or purified membrane fractions. In this study, a real-time NanoBRET-based binding assay was established and validated to detect binding of unlabeled ligands to the histamine H3 receptor (H3R) and histamine H4 receptor on intact cells. Obtained residence times of clinically tested H3R antagonists were reflected by their duration of H3R antagonism in a functional receptor recovery assay.
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Affiliation(s)
- Tamara A M Mocking
- Amsterdam Institute for Molecules, Medicines and Systems, Division of Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eléonore W E Verweij
- Amsterdam Institute for Molecules, Medicines and Systems, Division of Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Henry F Vischer
- Amsterdam Institute for Molecules, Medicines and Systems, Division of Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rob Leurs
- Amsterdam Institute for Molecules, Medicines and Systems, Division of Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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10
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Vlot AHC, de Witte WEA, Danhof M, van der Graaf PH, van Westen GJP, de Lange ECM. Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling. AAPS JOURNAL 2017; 20:11. [PMID: 29204742 DOI: 10.1208/s12248-017-0172-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2017] [Accepted: 11/20/2017] [Indexed: 12/31/2022]
Abstract
Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (K D) and the target dissociation rate constant on target and tissue selectivity. The K D values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ8-tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the K D and k off for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal K D value is often not the lowest K D value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.
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Affiliation(s)
- Anna H C Vlot
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333, CC, Leiden, The Netherlands
| | - Wilhelmus E A de Witte
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333, CC, Leiden, The Netherlands
| | - Meindert Danhof
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333, CC, Leiden, The Netherlands
| | - Piet H van der Graaf
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333, CC, Leiden, The Netherlands.,Certara Quantitative Systems Pharmacology, Canterbury Innovation Centre, Canterbury, CT2 7FG, UK
| | - Gerard J P van Westen
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333, CC, Leiden, The Netherlands
| | - Elizabeth C M de Lange
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333, CC, Leiden, The Netherlands.
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11
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Nederpelt I, Kuzikov M, de Witte WEA, Schnider P, Tuijt B, Gul S, IJzerman AP, de Lange ECM, Heitman LH. From receptor binding kinetics to signal transduction; a missing link in predicting in vivo drug-action. Sci Rep 2017; 7:14169. [PMID: 29075004 PMCID: PMC5658448 DOI: 10.1038/s41598-017-14257-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 10/09/2017] [Indexed: 11/12/2022] Open
Abstract
An important question in drug discovery is how to overcome the significant challenge of high drug attrition rates due to lack of efficacy and safety. A missing link in the understanding of determinants for drug efficacy is the relation between drug-target binding kinetics and signal transduction, particularly in the physiological context of (multiple) endogenous ligands. We hypothesized that the kinetic binding parameters of both drug and endogenous ligand play a crucial role in determining cellular responses, using the NK1 receptor as a model system. We demonstrated that the binding kinetics of both antagonists (DFA and aprepitant) and endogenous agonists (NKA and SP) have significantly different effects on signal transduction profiles, i.e. potency values, in vitro efficacy values and onset rate of signal transduction. The antagonistic effects were most efficacious with slowly dissociating aprepitant and slowly associating NKA while the combination of rapidly dissociating DFA and rapidly associating SP had less significant effects on the signal transduction profiles. These results were consistent throughout different kinetic assays and cellular backgrounds. We conclude that knowledge of the relationship between in vitro drug-target binding kinetics and cellular responses is important to ultimately improve the understanding of drug efficacy in vivo.
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Affiliation(s)
- Indira Nederpelt
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands
| | - Maria Kuzikov
- Fraunhofer IME Screening Port, Schnackenburgallee 114, D-22525, Hamburg, Germany
| | - Wilbert E A de Witte
- Division of Pharmacology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands
| | - Patrick Schnider
- Roche Pharmaceutical Research and Early Development, Small Molecule Research, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Bruno Tuijt
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands
| | - Sheraz Gul
- Fraunhofer IME Screening Port, Schnackenburgallee 114, D-22525, Hamburg, Germany
| | - Adriaan P IJzerman
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands
| | - Elizabeth C M de Lange
- Division of Pharmacology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands
| | - Laura H Heitman
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands.
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12
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Callegari D, Lodola A, Pala D, Rivara S, Mor M, Rizzi A, Capelli AM. Metadynamics Simulations Distinguish Short- and Long-Residence-Time Inhibitors of Cyclin-Dependent Kinase 8. J Chem Inf Model 2017; 57:159-169. [DOI: 10.1021/acs.jcim.6b00679] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Donatella Callegari
- Dipartimento
di Farmacia, Università degli Studi di Parma, Viale delle
scienze 27/A, 43124 Parma, Italy
| | - Alessio Lodola
- Dipartimento
di Farmacia, Università degli Studi di Parma, Viale delle
scienze 27/A, 43124 Parma, Italy
| | - Daniele Pala
- Dipartimento
di Farmacia, Università degli Studi di Parma, Viale delle
scienze 27/A, 43124 Parma, Italy
| | - Silvia Rivara
- Dipartimento
di Farmacia, Università degli Studi di Parma, Viale delle
scienze 27/A, 43124 Parma, Italy
| | - Marco Mor
- Dipartimento
di Farmacia, Università degli Studi di Parma, Viale delle
scienze 27/A, 43124 Parma, Italy
| | - Andrea Rizzi
- Chemistry
Research and Drug Design Department, Chiesi Farmaceutici S.p.A., Largo F. Belloli 11/A, 43122 Parma, Italy
| | - Anna Maria Capelli
- Chemistry
Research and Drug Design Department, Chiesi Farmaceutici S.p.A., Largo F. Belloli 11/A, 43122 Parma, Italy
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13
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de Witte WE, Danhof M, van der Graaf PH, de Lange EC. In vivo Target Residence Time and Kinetic Selectivity: The Association Rate Constant as Determinant. Trends Pharmacol Sci 2016; 37:831-842. [DOI: 10.1016/j.tips.2016.06.008] [Citation(s) in RCA: 85] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 06/13/2016] [Accepted: 06/15/2016] [Indexed: 12/16/2022]
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14
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Costa-Neto CM, Parreiras-E-Silva LT, Bouvier M. A Pluridimensional View of Biased Agonism. Mol Pharmacol 2016; 90:587-595. [PMID: 27638872 DOI: 10.1124/mol.116.105940] [Citation(s) in RCA: 85] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2016] [Accepted: 09/14/2016] [Indexed: 12/17/2022] Open
Abstract
When studying G protein-coupled receptor (GPCR) signaling and ligand-biased agonism, at least three dimensional spaces must be considered, as follows: 1) the distinct conformations that can be stabilized by different ligands promoting the engagement of different signaling effectors and accessory regulators; 2) the distinct subcellular trafficking that can be conferred by different ligands, which results in spatially distinct signals; and 3) the differential binding kinetics that maintain the receptor in specific conformation and/or subcellular localization for different periods of time, allowing for the engagement of distinct signaling effector subsets. These three pluridimensional aspects of signaling contribute to different faces of functional selectivity and provide a complex, interconnected way to define the signaling profile of each individual ligand acting at GPCRs. In this review, we discuss how each of these aspects may contribute to the diversity of signaling, but also how they shed light on the complexity of data analyses and interpretation. The impact of phenotype variability as a source of signaling diversity, and the influence of novel and more sensitive assays in the detection and analysis of signaling pluridimensionality, is also discussed. Finally, we discuss perspectives for the use of the concept of pluridimensional signaling in drug discovery, in which we highlight future predictive tools that may facilitate the identification of compounds with optimal therapeutic and safety properties based on the signaling signatures of drug candidates.
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Affiliation(s)
- Claudio M Costa-Neto
- Department of Biochemistry and Immunology, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, Brazil (C.M.C.-N., L.T.P.-S.); and Department of Biochemistry and Molecular Medicine and Institute for Research in Immunology and Cancer, University of Montréal, Montréal, Canada (L.T.P.-S., M.B.)
| | - Lucas T Parreiras-E-Silva
- Department of Biochemistry and Immunology, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, Brazil (C.M.C.-N., L.T.P.-S.); and Department of Biochemistry and Molecular Medicine and Institute for Research in Immunology and Cancer, University of Montréal, Montréal, Canada (L.T.P.-S., M.B.)
| | - Michel Bouvier
- Department of Biochemistry and Immunology, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, Brazil (C.M.C.-N., L.T.P.-S.); and Department of Biochemistry and Molecular Medicine and Institute for Research in Immunology and Cancer, University of Montréal, Montréal, Canada (L.T.P.-S., M.B.)
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Guo D, Heitman LH, IJzerman AP. The Added Value of Assessing Ligand-Receptor Binding Kinetics in Drug Discovery. ACS Med Chem Lett 2016; 7:819-21. [PMID: 27660682 DOI: 10.1021/acsmedchemlett.6b00273] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
In the past decade drug research community has started to appreciate the indispensable role of ligand-receptor binding kinetics (BK) in drug discovery. Next to the classical equilibrium-based drug evaluation process with affinity and potency values as outcomes, kinetic investigation of the ligand-receptor interaction can aid compound triage in the hit-to-lead campaign and provide additional information to understand the molecular mechanism of drug action. Translational models incorporating BK are emerging as well, which represent powerful tools for the prediction of in vivo effects. In this viewpoint we will summarize some recent findings and discuss and emphasize the added value of ligand-receptor binding kinetics in drug research.
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Affiliation(s)
- Dong Guo
- Jiangsu
Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, 209 Tongshan Road, Xuzhou 221004, Jiangsu, China
| | - Laura H. Heitman
- Division
of Medicinal Chemistry, Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O.
Box 9502, 2300 RA Leiden, The Netherlands
| | - Adriaan P. IJzerman
- Division
of Medicinal Chemistry, Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O.
Box 9502, 2300 RA Leiden, The Netherlands
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16
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Guo D, Heitman LH, IJzerman AP. Kinetic Aspects of the Interaction between Ligand and G Protein-Coupled Receptor: The Case of the Adenosine Receptors. Chem Rev 2016; 117:38-66. [DOI: 10.1021/acs.chemrev.6b00025] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Dong Guo
- Division of Medicinal Chemistry,
Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O. Box 9502, 2300 RA Leiden, The Netherlands
| | - Laura H. Heitman
- Division of Medicinal Chemistry,
Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O. Box 9502, 2300 RA Leiden, The Netherlands
| | - Adriaan P. IJzerman
- Division of Medicinal Chemistry,
Leiden Academic Centre for Drug Research (LACDR), Leiden University, P.O. Box 9502, 2300 RA Leiden, The Netherlands
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