Rational Drug Discovery

Slides:



Advertisements
Similar presentations
The Drug Discovery Process
Advertisements

Combinatorial computational method gives new picomolar ligands for a known enzyme Bartosz A. Grzybowski, Alexey V. Ishchenko, Chu- Young Kim, George Topalov,
Case Study: Dopamine D 3 Receptor Anthagonists Chapter 3 – Molecular Modeling 1.
1 Sequential Screening S. Stanley Young NISS HTS Workshop October 25, 2002.
Jürgen Sühnel Institute of Molecular Biotechnology, Jena Centre for Bioinformatics Jena / Germany Supplementary Material:
Lipinski’s rule of five
S TRUCTURAL B IOINFORMATICS. A subset of Bioinformatics concerned with the of biological structures - proteins, DNA, RNA, ligands etc. It is the first.
Summary Molecular surfaces QM properties presented on surface Compound screening Pattern matching on surfaces Martin Swain Critical features Dave Whitley.
Enhancing the C-48 STAT3 Inhibitor
THE BUILDING BLOCKS OF LIFE. BUILT FOR YOU Putting Engineering back into Protein Engineering Jun Liao, UC Santa Cruz Manfred K. Warmuth, UC Santa Cruz.
Organic Chemistry 4 th Edition Paula Yurkanis Bruice Irene Lee Case Western Reserve University Cleveland, OH ©2004, Prentice Hall Chapter 30 The Organic.
1111 Discovery Novel Allosteric Fragment Inhibitors of HIV-1 Reverse Transcriptase for HIV Prevention A/Prof Gilda Tachedjian Retroviral Biology and Antivirals.
OMICS Group Contact us at: OMICS Group International through its Open Access Initiative is committed to make genuine and.
RAPID: Randomized Pharmacophore Identification for Drug Design PW Finn, LE Kavraki, JC Latombe, R Motwani, C Shelton, S Venkatasubramanian, A Yao Presented.
Structure Based Drug Design
Pharmacophore and FTrees
Cédric Notredame (30/08/2015) Chemoinformatics And Bioinformatics Cédric Notredame Molecular Biology Bioinformatics Chemoinformatics Chemistry.
Asia’s Largest Global Software & Services Company Genomes to Drugs: A Bioinformatics Perspective Sharmila Mande Bioinformatics Division Advanced Technology.
PHC 222 Medicinal Chemistry-1- Part(I) Dr. Huda Al Salem Lecture (1)
1 Biological Discovery High Volume Screening Combinatorial Diversity Structure, Design, Informatics Lead Series Biodisposition Toxicity Efficacy Pharmacokinetics.
QSAR Study of HIV Protease Inhibitors Using Neural Network and Genetic Algorithm Akmal Aulia, 1 Sunil Kumar, 2 Rajni Garg, * 3 A. Srinivas Reddy, 4 1 Computational.
1 © Patrick An Introduction to Medicinal Chemistry 3/e Chapter 10 DRUG DESIGN: OPTIMIZING TARGET INTERACTIONS Part 2: Section 10.2.
MECHANISTIC PHARMACOKINETICS: COMPARTMENTAL MODELS
Hierarchical Database Screenings for HIV-1 Reverse Transcriptase Using a Pharmacophore Model, Rigid Docking, Solvation Docking, and MM-PB/SA Junmei Wang,
Pharmacophores Chapter 13 Part 2.
Computer-aided drug discovery (CADD)/design methods have played a major role in the development of therapeutically important small molecules for several.
1 © 2. Structure Activity Relationships (SAR) Alter, remove or mask a functional groupAlter, remove or mask a functional group Test the analogue for activityTest.
Modeling Protein Flexibility with Spatial and Energetic Constraints Yi-Chieh Wu 1, Amarda Shehu 2, Lydia Kavraki 2,3  Provided an approach to generating.
1 DRUG DISCOVERY Random Search e.g., buying paintbrush, mop, hammer, gluestick, nail, etc. etc. for hanging a picture frame on the wall Rational Design.
MEDC 603 Fall Measuring Drug Action  Dose – Response Curves Response  fraction bound (fb) = Fraction bound [D] [D] = K D R + D R:D.
Biochemical Reaction Rate: Enzyme Kinetics What affect do enzymes and enzyme inhibitors have on enzyme catalysis on a quantitative level? Lipitor inhibits.
Computational Approach for Combinatorial Library Design Journal club-1 Sushil Kumar Singh IBAB, Bangalore.
Dr. Laila M. Matalqah Ph.D. Pharmacology Pharmacodynamics 2 General Pharmacology M212.
Principles of Drug Design
Pharmaceutical Approaches to Antiviral Drug Discovery
Molecular Modeling in Drug Discovery: an Overview
TIDEA Target (and Lead) Independent Drug Enhancement Algorithm.
(Quantitative) Structure- Activity Relationships (Q)SAR.
Structural Bioinformatics in Drug Discovery Melissa Passino.
Page 1 Computer-aided Drug Design —Profacgen. Page 2 The most fundamental goal in the drug design process is to determine whether a given compound will.
Opiates.
Lipinski’s rule of five
Dr. George Geromichalos, Ph.D.
Homology Modeling and Docking to Potential Novel Inhibitor for
Serine Proteases A large group of enzymes that cleave amide bond
Computational Tools Seminar
2AXA (brown) & 1Z95 (green) superimposed
Receptor Theory & Toxicant-Receptor Interactions
APPLICATIONS OF BIOINFORMATICS IN DRUG DISCOVERY
Important Points in Drug Design based on Bioinformatics Tools
Drug Affinity Responsive Target Stability (DARTS).
Molecular Docking Profacgen. The interactions between proteins and other molecules play important roles in various biological processes, including gene.
Coagulation and Anti-coagulation
Structural Bioinformatics in Drug Discovery
Anti-Coagulants Physical Process of Clotting
Rational Drug Design Dr SANTOSH MOKALE. Professor,
Process of Drug Discovery
A Primer on Opioids/Opiates
Università degli Studi di Milano
Anti-Coagulants Physical Process of Clotting
INTRODUCTION to Pharmacology
Narcotic analgesic Drugs
Important Points in Drug Design based on Bioinformatics Tools
Drug Design and Drug Discovery
Anti-Coagulants Physical Process of Clotting
School of Pharmacy, University of Nizwa
DRUG DESIGN: OPTIMIZING TARGET INTERACTIONS
Patrick: An Introduction to Medicinal Chemistry 6e
Translational research involves an iterative process of forward and back translation to use and refine procedures that optimize sensitivity and selectivity.
Research Rational Drug Design: A process for drug design which bases the design of the drug upon the structure of its protein target. Structural mapping.
Presentation transcript:

Rational Drug Discovery Full Toolbox Required to Compete Successfully Biological Discovery High Volume Screening Combinatorial Diversity Rational [Structure, Design, Informatics] Lead Discovery Research Biodisposition Toxicity Efficacy Pharmacokinetics Preclinical R&D IND Lead Series Iterative Process MEDC 607 & MEDC 603

Rational Drug Discovery Definition Rational – Reason-based Not based on chance alone May not involve computers Types of Drug Discovery Searches Structure – based Drug Design (structure of the receptor, binding site, AA residues, thermodynamics) Pharmacophore – based Drug Design (structure of the ligand, SAR, QSAR) Mechanism – based Drug Design (molecular mechanism of action, transition state) MEDC 607 & MEDC 603

Receptor-based Drug Design Design of Antithrombin Activators MEDC 607 & MEDC 603

Receptor-based Drug Design Binding Site Information Lys114 Arg47 Lys125 Arg129 Arg46 _ Asn45 Arg13 Lys11 MEDC 607 & MEDC 603

Receptor-based Drug Design Thermodynamics -DGO (kcal/mol) MEDC 607 & MEDC 603

Receptor-based Drug Design Computerized Modeling MEDC 607 & MEDC 603

Receptor-based Drug Design Design of New Structures A) B) ECS = (2S,3S) (+)CS = (2S,3R) MoS :: R = H, R’ = OSO3- QS :: R = OSO3-, R’ = H 2 3 Pentasaccharide Binding Site Residues HINT Score DEF = ECS = MEDC 607 & MEDC 603

Pharmacophore-based Drug Design Natural Product Derivatization and Pharmacophore Elucidation Morphine R = R’ = H Codeine R = Me, R’ = H Heroin R = R’ = COCH3 (Analgesic + additive) Levorphanol (a morphinan) (3 – 4X morphine analgesic + retains additive property) Pentazocine (less potent than morphine + reduced additive property) Methadone (equipotent as morphine analgesic + almost no additive) Meperidine (10-12% of morphine analgesic + much lowered additive) (less potent than morphine + reduced additive property) MEDC 607 & MEDC 603

Mechanism of Aspartic Proteinases Mechanism-based Drug Design Design of HIV Protease Inhibitor _ _ + _ _ Mechanism of Aspartic Proteinases _ _ _ MEDC 607 & MEDC 603

Mechanism-based Drug Design IC50 (nM) Inhibitor Structure HIV-1 HIV-2 Z.Phe[CH(OH)CH2N]Pro.OtBu 6,500 Z.Asn.Phe[CH(OH)CH2N]Pro.OtBu 140 330 Z.Asn.Phe[CH(OH)CH2N]Pro.OtBu 300 MEDC 607 & MEDC 603

Rational Design of HIV-1/2 Proteinase Inhibitors IC50 (nM) Inhibitor Structure HIV-1 HIV-2 Z.Leu.Asn.Phe[CH(OH)CH2N]Pro.Ile.NHiBu 750 Z.Asn.Phe[CH(OH)CH2N]Pro.NHiBu 210 Z.Asn.Phe[CH(OH)CH2N]PIC.NHiBu 18 MEDC 607 & MEDC 603

Rational Design of HIV-1/2 Proteinase Inhibitors IC50 (nM) Inhibitor Structure HIV-1 HIV-2 QC.Asn.Phe[CH(OH)CH2N]PIC.NHiBu 2 9.5 QC.Asn.Phe[CH(OH)CH2N]DIQ.NHiBu <0.4 <0.8 MEDC 607 & MEDC 603