1 / 16

Chapter 3. Basic Principles of Drug Design III Designing drug molecules to fit receptors

Chapter 3. Basic Principles of Drug Design III Designing drug molecules to fit receptors 3.1 Overall strategy: The multiphore method of drug design - drug designing to fit into receptor --- multiphore method [biosphores] (1) receptor-based functional groups

kueng
Download Presentation

Chapter 3. Basic Principles of Drug Design III Designing drug molecules to fit receptors

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Chapter 3. Basic Principles of Drug Design III Designing drug molecules to fit receptors 3.1 Overall strategy: The multiphore method of drug design - drug designing to fit into receptor --- multiphore method [biosphores] (1) receptor-based functional groups (2) complementary functional groups [pharmacophore & contact points] (3) molecular baggage (4) toxicophore [designing out the toxicity] - multiphore method [bioisostere & iterative method] - drug optimization 1. design or identification of a lead (prototype) compound 2. synthesis and initial biological evaluation of the lead compound 3. optimization of the lead compound for the pharmacodynamic phase 4. optimization for the pharmacokinetic and pharmaceutical phases 5. pre-clinical and clinical evaluation of the optimized lead compound analog 3.2. Identification of a lead compound - serendipity, endogenous source, exogenous source, rational drug design, high throughput screening programs, genomics/proteomics

  2. 3.2.1 Lead compound identification - Epilepsy 3.2.2 Lead compound identification by serendipity 3.2.2.1 The benzodiazepines: Diazepam and serendipity - phenothiazines as antipsychotic agents - tricyclic benzheptoxdiazine compounds --- quinazoline 3-oxides --- chlordiazepoxide --- diazepam (valium) --- benzodiazepine 3.2.2.2 Alipathic carboxylates: Valproic acid and serendipity - Eymard’s khelin and coumarin dissolved in valproic acid [kidney stone treatment] - anticonvulsant and antiepileptic action 3.2.3 Lead compound identification from endogenous sources - exploiting endogenous molecules 3.2.3.1 Peptidomimetic chemistry as a source of lead compounds - failings of peptides as drugs [too big / too flexible / hydrolyzable amide bonds / no oral / no BBB] - attractive points [numerous stereogenic centers / functional groups / easy synthesis / conformation / bioactive molecules] - peptidomimetic chemistry 1. alanine scanning : minimal bioactive segment / conformation restriction rebuilt by isosteric fragment

  3. 2. three-dim structure of peptide --- pharmacophore --- organic molecules non-peptidic but bioactive organic molecule drug 3.2.3.2 Other endogenous drug lead platforms - nucleic acids, lipids, CHO --- organic molecules as mimetics 3.2.4. Lead compound identification from exogenous sources (1) exogenous from the perspective of drug design for humans [digitalis / penicillin / taxol] (2) molecular diversity (3) ethnopharmacology (4) biochemical information from metabolic pathways, enzyme mechanisms, cell physiology

  4. 3.2.5 Lead compound identification by rational drug design - 10200 small organic molecules ---- 1052 drug-like molecules 3.2.5.1 Bromides for epilepsy - anaphrodisiac bromides ---- phenobarbital (1912) 3.2.5.2 A modern definition of rational drug design - iterative process [feedback loops and new information] - cimetidine: H2 antagonist drug for peptic ulcer treatment - amprenavir, indinavir, melfinavir, ritonavir, saquinavir, lopinavir: HIV-1/PR - structural chemistry and molecular modeling 3.2.5.3 Role of quantum pharmacology in rational drug design - Einstein / Schrodinger / Heisenberg / Dirac - For large molecules semi-empirical molecular orbital calculations and density functional theory molecular mechanics supercomputer - CAMD - de novo design of lead compounds 3.2.6 Lead compound identification by combinatorial chemistry with HTS - random screening

  5. 3.2.6.1 Drug discovery by screening: diphenylhydantoin - 5-ethyl-5-phenylhydantoin (nirvanol): less toxic hypnotic - 5,5-diphenylhydantoin (phenytoin): worthless hypnotic - anticonvulsant - antiepileptic drug discovery [hydantoin analogs / pentaatomic heterocyclic compounds] 3.2.6.2 Drug discovery by screening : a modern definition - the library of compounds: combinatorial chemistry library - the screening bioassay: HTS methods 3.2.6.3 Combinatorial chemistry and drug discovery by screening (1) libraries of oligomers of naturally occurring monomers a) oligopeptide libraries; b) oligonucleotide libraries (2) libraries of oligomers of non-naturally occurring monomers a) oligocarbamate; b) oligourea; c) oligosulfone; d) oligosulfoxide (3) libraries of monomers with multiple sites for substituents a) synthetic ease privileged structure [dioxapiperazines] b) pharmacological activity privileged structure [benzodiazopines / dihydropyridines / hydantoins] c) novel template structures [dihydrobenzopyrans] - solid phase peptide synthesis: makes byproduct removal and final compound purification easier

  6. 3.2.6.4 High throughput screening and drug discovery - biological evaluation assay [microplate activity assay / gel diffusion assay / affinity selection assay] - pooling strategy and combinatorial synthesis 3.2.7 Lead compound identification through genomics and proteomics - > 4000 human diseases: druggable genetic factors 3.2.7.1 Genomics and lead compound discovery - human genome project: 2000. 6. 26. - genomics: human biochemistry / linking specific genes to specific diseases - post-genomic tech: linking specific proteins to specific genes 3.2.7.2 Proteomics and lead compound discovery - elucidation of the structure and function profiles of all proteins - DNA microarray tech: mRNA and protein relationship [structural proteomics] - interaction proteomics [complexity and integrated network] - from genomics to proteomics to disease cascade 3.2.7.3 Bioinformatics and cheminformatics in lead compound discovery - predict the phenomenology of cellular physiology and pharmacology at a molecular level using computational methods - identify novel molecules to alter the function of various proteins - chemogenomics: multiple drugs to target multiple-gene families

  7. Transcription Translation • Posttranslationally • modified proteins • Protein-ligand • interactions DNA RNA Protein Reverse Transcription Information Function Information Function Biological phenomena Central Dogma in Biological System

  8. Postgenomic era Proteomics (St./Fn.) Functional Genomics Genomics (Structural) 단백질의 특성 및 기능 파악 조직별 5,000 - 20,000 추정 DNA 염기서열 약 30억개 (2-3% 유전자) 유전자 및 기능파악 총 4 만 유전자 추정 현재까지 9,000여종 파악

  9. Proteomics [1] Biological Perturbation [2] High-throughput Screening two-dimensional gel electrophoresis in-gel protein digestion MALDI-TOF mass spectrometry peptide mass mapping [3] Bioinformatics [4] Conventional Protein Chemistry

  10. 3.2.8 Pharmacogenomics and the future of lead compound discovery - design individualized drugs [tailor-made design of chemotherapies] - single nucleotide polymorphism maps - pharmacogenomics 3.3 Synthesis of a lead compound - organic synthesis [take advantage of carbon atoms] - starting material to target molecule [linear vs. convergent process] - correct positioning of functional groups in three-dimensional space - ten general classes of reactions - two fundamental construction activities a) creation of C-C / C=C / C-H bonds (structural framework) b) creation of functional groups (functionality to the framework)

  11. 3.3.1 Synthon approach to drug molecular synthesis - synthon approach: organized & systematic approach [backward thinking process] - target molecule --- disconnection --- fragments [synthons] - synthetic equivalents: functional group interconversion (FGI) 3.3.2 Need for efficient synthetic methods - successful drugs: a) large quantities in an industrial setting b) scalable, efficient, environmentally friendly c) fewer steps d) water as a solvent

  12. 3.3.3 Need for a robust biological model for compound evaluation - biological assay: rapid, cost-effective, efficient, and easy to implement - biological model ------ human disease - in silico (computing simulation) / in vitro / in vivo 3.3.4 Deciding to optimize a lead compound - optimization of the lead compound - drug action: prediction on toxicity, side effects, transport characteristics, metabolic fate in vivo - molecular modifications a) physicochemical consequences and molecular action mechanism ---- structural change in an organic molecule b) new pharmacological effects: discontinuous jump - experience / serendipity / luck - drug discovery --- biomedical research

More Related