Principles of Pharmacology Dr
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Principle of Pharmacodynamics
Principle of pharmacodynamics Dr. M. Emamghoreishi Full Professor Department of Pharmacology Medical School Shiraz University of Medical Sciences Email:[email protected] Reference: Basic & Clinical Pharmacology: Bertrum G. Katzung and Anthony J. Treveror, 13th edition, 2015, chapter 20, p. 336-351 Learning Objectives: At the end of sessions, students should be able to: 1. Define pharmacology and explain its importance for a clinician. 2. Define ―drug receptor‖. 3. Explain the nature of drug receptors. 4. Describe other sites of drug actions. 5. Explain the drug-receptor interaction. 6. Define the terms ―affinity‖, ―intrinsic activity‖ and ―Kd‖. 7. Explain the terms ―agonist‖ and ―antagonist‖ and their different types. 8. Explain chemical and physiological antagonists. 9. Explain the differences in drug responsiveness. 10. Explain tolerance, tachyphylaxis, and overshoot. 11. Define different dose-response curves. 12. Explain the information that can be obtained from a graded dose-response curve. 13. Describe the potency and efficacy of drugs. 14. Explain shift of dose-response curves in the presence of competitive and irreversible antagonists and its importance in clinical application of antagonists. 15. Explain the information that can be obtained from a quantal dose-response curve. 16. Define the terms ED50, TD50, LD50, therapeutic index and certain safety factor. What is Pharmacology?It is defined as the study of drugs (substances used to prevent, diagnose, and treat disease). Pharmacology is the science that deals with the interactions betweena drug and the bodyor living systems. The interactions between a drug and the body are conveniently divided into two classes. The actions of the drug on the body are termed pharmacodynamicprocesses.These properties determine the group in which the drug is classified, and they play the major role in deciding whether that group is appropriate therapy for a particular symptom or disease. -
Pharmacodynamics Drug Receptor Interactions Part-2
Pharmacodynamics: (Drug Receptor Interactions, Part 2) ………………………………………………………………………………………………………………………………………………………………………………………………………………… VPT: Unit I; Lecture-22 (Dated 03.12.2020) Dr. Nirbhay Kumar Asstt. Professor & Head Deptt. of Veterinary Pharmacology & Toxicology Bihar Veterinary College, Bihar Animal Sciences University, Patna Drug Receptor Interactions Agonist It is a drug that possesses affinity for a particular receptor and causes a change in the receptor that result in an observable effect. Full agonist: Produces a maximal response by occupying all or a fraction of receptors. (Affinity=1, Efficacy=1) Partial agonist: Produces less than a maximal response even when the drug occupies all of the receptors. (Affinity=1, Efficacy= 0 to 1) Inverse agonist: Activates a receptor to produce an effect in the opposite direction to that of the well recognized agonist. (Affinity=1, Efficacy= –1 to 0). Source: Rang & Dale’s Pharmacology, Elsevier Source: Good & Gilman’s The Pharmacological Basis of Therapeutics, 13th Edn. Antagonist An antagonist is a drug that blocks the response produced by an agonist. Antagonists interact with the receptor or other components of the effector mechanism, but antagonists are devoid of intrinsic activity (Affinity=1, Efficacy=0). Antagonist contd… Competitive Antagonism: It is completely reversible; an increase in the concentration of the agonist in the bio-phase will overcome the effect of the antagonist. Example: Atropine (Antimuscarinic agent) Diphenhydramine (H1 receptor blocker) Non-competitive antagonism: The agonist has no influence upon the degree of antagonism or its reversibility. Example: Platelet inhibiting action of aspirin (The thromboxane synthase enzyme of platelets is irreversibly inhibited by aspirin, a process that is reversed only by production of new platelets). -
Measuring Ligand Efficacy at the Mu- Opioid Receptor Using A
RESEARCH ARTICLE Measuring ligand efficacy at the mu- opioid receptor using a conformational biosensor Kathryn E Livingston1,2, Jacob P Mahoney1,2, Aashish Manglik3, Roger K Sunahara4, John R Traynor1,2* 1Department of Pharmacology, University of Michigan Medical School, Ann Arbor, United States; 2Edward F Domino Research Center, University of Michigan, Ann Arbor, United States; 3Department of Pharmaceutical Chemistry, School of Pharmacy, University of California San Francisco, San Francisco, United States; 4Department of Pharmacology, University of California San Diego School of Medicine, La Jolla, United States Abstract The intrinsic efficacy of orthosteric ligands acting at G-protein-coupled receptors (GPCRs) reflects their ability to stabilize active receptor states (R*) and is a major determinant of their physiological effects. Here, we present a direct way to quantify the efficacy of ligands by measuring the binding of a R*-specific biosensor to purified receptor employing interferometry. As an example, we use the mu-opioid receptor (m-OR), a prototypic class A GPCR, and its active state sensor, nanobody-39 (Nb39). We demonstrate that ligands vary in their ability to recruit Nb39 to m- OR and describe methadone, loperamide, and PZM21 as ligands that support unique R* conformation(s) of m-OR. We further show that positive allosteric modulators of m-OR promote formation of R* in addition to enhancing promotion by orthosteric agonists. Finally, we demonstrate that the technique can be utilized with heterotrimeric G protein. The method is cell- free, signal transduction-independent and is generally applicable to GPCRs. DOI: https://doi.org/10.7554/eLife.32499.001 *For correspondence: [email protected] Competing interests: The authors declare that no Introduction competing interests exist. -
Response Vs. Log [L] - Full Agonist
DavidsonX – D001x – Medicinal Chemistry Chapter 5 – Receptors Part 2 – Ligands Video Clip – Ligand Types Ligands can have different effects on a receptor. Each type of ligand can be readily classified according to its behavior. A type of ligand is the full agonist. The term agonist refers to a compound that binds a receptor and elicits a response (E). Full agonists elicit the same level of full response (E = Emax = 100%) as the endogenous ligand of the receptor. Graphically, a receptor-ligand interaction is plotted as response (E/Emax) vs. log [L]. The relationship is sigmoidal. A full agonist approaches full response (E/Emax = 1.0) as log [L] reaches relatively high levels. response vs. log [L] - full agonist 1 0.9 0.8 0.7 x a 0.6 m E 0.5 / E 0.4 0.3 0.2 0.1 0 log [L] Two ligands can achieve a full response without being equivalent. Ligands can differ with respect to the concentration required to trigger a response. A ligand that affects a response at a lower concentration has a higher potency. Potencies are measured as the effective ligand concentration required to reach a 50% response – EC50 or, in these graphs, log [EC50]. A more potent ligand has a lower EC50 value. full agonist comparison 1 0.9 full agonist 1 0.8 (more potent) full agonist 2 0.7 (less potent) x a 0.6 log EC m 50 E 0.5 / E 0.4 0.3 log EC 0.2 50 0.1 0 log [L] Partial agonists also cause a response, but they cannot reach the same, 100% response level of the endogenous ligand. -
Anew Drug Design Strategy in the Liht of Molecular Hybridization Concept
www.ijcrt.org © 2020 IJCRT | Volume 8, Issue 12 December 2020 | ISSN: 2320-2882 “Drug Design strategy and chemical process maximization in the light of Molecular Hybridization Concept.” Subhasis Basu, Ph D Registration No: VB 1198 of 2018-2019. Department Of Chemistry, Visva-Bharati University A Draft Thesis is submitted for the partial fulfilment of PhD in Chemistry Thesis/Degree proceeding. DECLARATION I Certify that a. The Work contained in this thesis is original and has been done by me under the guidance of my supervisor. b. The work has not been submitted to any other Institute for any degree or diploma. c. I have followed the guidelines provided by the Institute in preparing the thesis. d. I have conformed to the norms and guidelines given in the Ethical Code of Conduct of the Institute. e. Whenever I have used materials (data, theoretical analysis, figures and text) from other sources, I have given due credit to them by citing them in the text of the thesis and giving their details in the references. Further, I have taken permission from the copyright owners of the sources, whenever necessary. IJCRT2012039 International Journal of Creative Research Thoughts (IJCRT) www.ijcrt.org 284 www.ijcrt.org © 2020 IJCRT | Volume 8, Issue 12 December 2020 | ISSN: 2320-2882 f. Whenever I have quoted written materials from other sources I have put them under quotation marks and given due credit to the sources by citing them and giving required details in the references. (Subhasis Basu) ACKNOWLEDGEMENT This preface is to extend an appreciation to all those individuals who with their generous co- operation guided us in every aspect to make this design and drawing successful. -
Investigating the Influence of Tracer Kinetics
Molecular Pharmacology Fast Forward. Published on July 10, 2019 as DOI: 10.1124/mol.119.116764 This article has not been copyedited and formatted. The final version may differ from this version. MOL # 116764 Investigating the influence of tracer kinetics on competition-kinetic association binding assays; identifying the optimal conditions for assessing the kinetics of low affinity compounds. David A Sykes1,2, Palash Jain1,2 & Steven J Charlton1,2,3 1School of Life Sciences, Queen’s Medical Centre, University of Nottingham, Nottingham NG7 2UH, UK Downloaded from 2Centre of Membrane and Protein and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK. 3 Excellerate Bioscience Ltd, Discovery Building, BioCity, Pennyfoot Street, molpharm.aspetjournals.org Nottingham, NG1 1GF, UK at ASPET Journals on October 1, 2021 1 Molecular Pharmacology Fast Forward. Published on July 10, 2019 as DOI: 10.1124/mol.119.116764 This article has not been copyedited and formatted. The final version may differ from this version. MOL # 116764 Running title: Optimizing the design of competition association assays. Addresses for correspondence: Prof Steven Charlton School of Life Sciences Queen's Medical Centre University of Nottingham Nottingham NG7 2UH Downloaded from E-mail: [email protected] molpharm.aspetjournals.org David Sykes School of Life Sciences Queen's Medical Centre University of Nottingham at ASPET Journals on October 1, 2021 Nottingham NG7 2UH E-mail: [email protected] 2 Molecular Pharmacology Fast Forward. Published on July 10, 2019 as DOI: 10.1124/mol.119.116764 This article has not been copyedited and formatted. The final version may differ from this version. -
Analyzing Binding Data UNIT 7.5 Harvey J
Analyzing Binding Data UNIT 7.5 Harvey J. Motulsky1 and Richard R. Neubig2 1GraphPad Software, La Jolla, California 2University of Michigan, Ann Arbor, Michigan ABSTRACT Measuring the rate and extent of radioligand binding provides information on the number of binding sites, and their afÞnity and accessibility of these binding sites for various drugs. This unit explains how to design and analyze such experiments. Curr. Protoc. Neurosci. 52:7.5.1-7.5.65. C 2010 by John Wiley & Sons, Inc. Keywords: binding r radioligand r radioligand binding r Scatchard plot r r r r r r receptor binding competitive binding curve IC50 Kd Bmax nonlinear regression r curve Þtting r ßuorescence INTRODUCTION A radioligand is a radioactively labeled drug that can associate with a receptor, trans- porter, enzyme, or any protein of interest. The term ligand derives from the Latin word ligo, which means to bind or tie. Measuring the rate and extent of binding provides information on the number, afÞnity, and accessibility of these binding sites for various drugs. While physiological or biochemical measurements of tissue responses to drugs can prove the existence of receptors, only ligand binding studies (or possibly quantitative immunochemical studies) can determine the actual receptor concentration. Radioligand binding experiments are easy to perform, and provide useful data in many Þelds. For example, radioligand binding studies are used to: 1. Study receptor regulation, for example during development, in diseases, or in response to a drug treatment. 2. Discover new drugs by screening for compounds that compete with high afÞnity for radioligand binding to a particular receptor. -
Volume C, Module 2 Opioids: Basics of Addiction; Treatment with Agonists, Partial Agonists, and Antagonists
VolumeVolume C,C, ModuleModule 22 Opioids:Opioids: BasicsBasics ofof Addiction;Addiction; TreatmentTreatment withwith Agonists,Agonists, PartialPartial Agonists,Agonists, andand AntagonistsAntagonists Treatnet Training Volume C: Module 2 – Updated 18 October 2007 ModuleModule 2:2: TrainingTraining goalsgoals ToTo describedescribe the:the: ¾ KeyKey componentscomponents ofof opiateopiate addictionaddiction andand itsits medicalmedical // psychiatricpsychiatric consequencesconsequences ¾ BenefitsBenefits andand limitationslimitations ofof methadonemethadone asas aa pharmacotherapypharmacotherapy forfor opiateopiate dependencedependence ¾ BenefitsBenefits andand limitationslimitations ofof buprenorphinebuprenorphine asas aa pharmacotherapypharmacotherapy forfor opiateopiate dependencedependence ¾ BenefitsBenefits andand limitationslimitations ofof narcoticnarcotic antagonistsantagonists forfor overdoseoverdose (naloxone)(naloxone) andand relapserelapse preventionprevention (naltrexone)(naltrexone) forfor opiateopiate dependencedependence ModuleModule 2:2: WorkshopsWorkshops WorkshopWorkshop 1:1: Opiates:Opiates: WhatWhat theythey are,are, problemsproblems associatedassociated withwith theirtheir use,use, andand medicalmedical treatmenttreatment implicationsimplications WorkshopWorkshop 2:2: OpiateOpiate addictionaddiction treatmenttreatment withwith methadonemethadone WorkshopWorkshop 3:3: OpiateOpiate addictionaddiction treatmenttreatment withwith buprenorphinebuprenorphine WorkshopWorkshop 4:4: OpiateOpiate AntagonistAntagonist Treatment:Treatment: -
International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification
0031-6997/03/5504-597–606$7.00 PHARMACOLOGICAL REVIEWS Vol. 55, No. 4 Copyright © 2003 by The American Society for Pharmacology and Experimental Therapeutics 30404/1114803 Pharmacol Rev 55:597–606, 2003 Printed in U.S.A International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification. XXXVIII. Update on Terms and Symbols in Quantitative Pharmacology RICHARD R. NEUBIG, MICHAEL SPEDDING, TERRY KENAKIN, AND ARTHUR CHRISTOPOULOS Department of Pharmacology, University of Michigan, Ann Arbor, Michigan (R.R.N.); Institute de Recherches Internationales Servier, Neuilly sur Seine, France (M.S.); Systems Research, GlaxoSmithKline Research and Development, Research Triangle Park, North Carolina (T.K.); and Department of Pharmacology, University of Melbourne, Parkville, Australia (A.C.) Abstract ............................................................................... 597 I. Introduction............................................................................ 597 II. Working definition of a receptor .......................................................... 598 III. Use of drugs in definition of receptors or of signaling pathways ............................. 598 A. The expression of amount of drug: concentration and dose ............................... 598 1. Concentration..................................................................... 598 2. Dose. ............................................................................ 598 B. General terms used to describe drug action ........................................... -
First Principles and Their Application to Drug Discovery
REVIEWS Drug Discovery Today Volume 17, Numbers 1/2 January 2012 The utilization of the kinetic and thermodynamic signatures of preclinical leads is proving pivotal in their triage and rational optimization towards clinical candidates with maximal in vivo efficacy devoid of adverse events. Reviews KEYNOTE REVIEW Target–drug interactions: first principles and their application to drug discovery 1 1 Sara Nu´n˜ez studied organic Sara Nu´n˜ ez , Jennifer Venhorst and Chris G. Kruse chemistry at the University of Barcelona (Spain) and the Abbott Healthcare Products, 1381 CP Weesp, The Netherlands University of London (UK). She received her Ph.D. in 2003 from the University of Manchester (UK), and thereafter did a In this review, we begin by introducing the basic principles of kinetics postdoc in Biophysics at the and thermodynamics of target–drug binding within the context of Albert Einstein College of Medicine (USA). In 2005, she drug discovery. In addition, we present a meta-analysis of the recent joined Solvay Pharmaceuticals (now Abbott Healthcare) in The Netherlands as a postdoctoral fellow; and in 2008, she literature describing the kinetic and thermodynamic resolution of was promoted to Sr. Computational Medicinal Chemist. At Abbott, she has supported the medicinal chemistry efforts successful clinical candidates with diverse mechanisms of action. for neuroscience drug discovery programs, from target We finish by discussing the best practices in the triage and chemical discovery up to and including clinical proof of principle studies. She has supported more than 15 programs optimization towards clinical candidates with maximal in vivo internationally, and was project manager of the D2-103 Top Institute Pharma innitiative. -
A Regularized Full Reference Tissue Model for PET Neuroreceptor Mapping
NeuroImage 139 (2016) 405–414 Contents lists available at ScienceDirect NeuroImage journal homepage: www.elsevier.com/locate/ynimg A regularized full reference tissue model for PET neuroreceptor mapping Joseph B. Mandeville a,⁎, Christin Y.M. Sander a, Hsiao-Ying Wey a, Jacob M. Hooker a, Hanne D. Hansen b, Claus Svarer b, Gitte M. Knudsen b, Bruce R. Rosen a a Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States b Neurobiology Research Unit, Rigshospitalet and University of Copenhagen, DK-2100 Copenhagen, Denmark article info abstract Article history: The full reference tissue model (FRTM) is a PET analysis framework that includes both free and specifically Received 15 January 2016 bound compartments within tissues, together with rate constants defining association and dissociation Accepted 24 June 2016 from the specifically bound compartment. The simplified reference tissue model (SRTM) assumes instanta- Available online 27 June 2016 neous exchange between tissue compartments, and this “1-tissue” approximation reduces the number of parameters and enables more robust mapping of non-displaceable binding potentials. Simulations based upon FRTM have shown that SRTM exhibits biases that are spatially dependent, because biases depend upon binding potentials. In this work, we describe a regularized model (rFRTM) that employs a global esti- mate of the dissociation rate constant from the specifically bound compartment (k4). The model provides an internal calibration for optimizing k4 through the reference-region outflow rate k2′, a model parameter that should be a global constant but varies regionally in SRTM. Estimates of k4 by rFRTM are presented for four PET radioligands. -
Protein Conformational Dynamics Dictate the Binding Affinity for a Ligand
ARTICLE Received 26 Dec 2013 | Accepted 24 Mar 2014 | Published 24 Apr 2014 DOI: 10.1038/ncomms4724 Protein conformational dynamics dictate the binding affinity for a ligand Moon-Hyeong Seo1, Jeongbin Park2, Eunkyung Kim1, Sungchul Hohng2,3,4 & Hak-Sung Kim1 Interactions between a protein and a ligand are essential to all biological processes. Binding and dissociation are the two fundamental steps of ligand–protein interactions, and determine the binding affinity. Intrinsic conformational dynamics of proteins have been suggested to play crucial roles in ligand binding and dissociation. Here, we demonstrate how protein dynamics dictate the binding and dissociation of a ligand through a single-molecule kinetic analysis for a series of maltose-binding protein mutants that have different intrinsic conformational dynamics and dissociation constants for maltose. Our results provide direct evidence that the ligand dissociation is determined by the intrinsic opening rate of the protein. 1 Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 305-701, Korea. 2 Department of Physics and Astronomy, Seoul National University, Seoul 151-747, Korea. 3 Department of Biophysics and Chemical Biology, Seoul National University, Seoul 151-747, Korea. 4 National Center for Creative Research Initiatives, Seoul National University, Seoul 151-747, Korea. Correspondence and requests for materials should be addressed to H.-S.K. (email: [email protected]). NATURE COMMUNICATIONS | 5:3724 | DOI: 10.1038/ncomms4724 | www.nature.com/naturecommunications 1 & 2014 Macmillan Publishers Limited. All rights reserved. ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms4724 ransient interactions between a protein and a ligand are central to all biological processes including signal trans- K34C Tduction, cellular regulation and enzyme catalysis.