Drug Pract2

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Molecular Conceptor - Table of Contents

Structural BioinformaticsLast updated on September 2012

A - DRUG DISCOVERY

1. Introduction to Drug Discovery

2. Principles of Rational Drug Design

B - PROTEIN STRUCTURE AND MODELING

1. Structural Bioinformatics (in progress)

2. Protein Structure

3. Molecular Dynamics

C - STRUCTURE-BASED DESIGN

1. Introduction to Protein-Ligand Binding

2. Principles of Structure-Based Design

3. Molecular Docking: Principles and Methods

4. Case Studies in Structure-Based Design

5. Case Studies of Docking in Drug Discovery

6. Analyses of Protein-Ligand Complexes

D - MOLECULAR BASIS OF DRUGS

1. Molecular Geometry

2. Molecular Properties 3. Stereochemistry

4. Molecular Energies

5. Conformational Analysis

6. Molecular Graphics

7. Selected Examples in 3D Analysis

E - GENERAL TOPICS

1. General Introduction to Drugs

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2. Drug Discovery

3. Drug Development

A. DRUG DISCOVERY

A1. INTRODUCTION TO DRUG DISCOVERY

A1.1 From the Origin of Medicines to Today

A1.1.1 Attempts to Cure Diseases in Antiquity

A1.1.2 Medicines Used in Ancient Civilizations

A1.1.3 5th-4th BC Centuries: The Greek Period

A1.1.4 2nd Century: The Roman Period

A1.1.5 13th Century: The Arab School

A1.1.6 13th Century: First Apothecary Shops

A1.1.7 16th Century: Pharmaceutical Science

A1.1.8 16th Century: Maritime Routes to India and America

A1.1.9 18th Century: First Vaccine

A1.1.10 19th Century: Drug Administration

A1.1.11 19th Century: Isolation of Compounds

A1.1.12 19th Century: Relief of Pain in Surgical Operations

A1.1.13 19th Century: New Classes of Drugs

A1.1.14 20th Century: Pioneer Work of Paul Ehrlich

A1.1.15 20th Century: Sulfonamide Antibacterial Dyes

A1.1.16 20th Century: Recognition of Vitamins

A1.1.17 20th Century: The Antibiotic Era

A1.1.18 20th Century: Pfizer Management Decision

A1.1.19 20th Century: Large Scale Production of Penicillin

A1.1.20 20th Century: Antibacterial Agents Isolated from Plants

A1.1.21 20th Century: Discovery of Adrenal Cortex Hormones

A1.1.22 20th Century: NSAIDs

A1.1.23 20th Century: Key Transition Discoveries

A1.1.24 20th Century: Some Drug Discovery Projects

A1.1.25 Example-1 of Project: Factor Xa

A1.1.26 Example-2 of Project: Motilin Antagonists

A1.1.27 Example-3 of Project: COX-2 Inhibitors

A1.1.28 Example-4 of Project: Rotamase Inhibitors

A1.1.29 20th Century: From Apothecaries to Factories

A1.2 Revolutions that Changed Drug Discovery

A1.2.1 Major Achievements

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A1.2.2 Understanding Drug-Receptor Recognition

A1.2.3 Consolidation of Concept of Biological Targets

A1.2.4 Recombinant Technologies and Cloning of Genes

A1.2.5 Deciphering the Sequences of Genomes

A1.2.6 Determination of Proteins 3D Architectures A1.2.7 Automated Methods in Synthetic Chemistry

A1.2.8 HTS Screening

A1.2.9 Automation in Drug Discovery

A1.2.10 In-Silico Modeling becomes Mature

A1.3 In-Silico Technologies

A1.3.1 The Explosion of In-Silico Technologies

A1.3.2 Encoding Molecules: 2D and 3D Databases

A1.3.3 Development of Molecule Encoding

A1.3.4 3D Searching is not Trivial A1.3.5 Encoding Molecular Properties

A1.3.6 Development of Models for Data Analysis

A1.3.7 Molecular Modeling

A1.3.8 Development of Computer Graphics

A1.3.9 Development of Models for Data Visualization

A1.3.10 In-Silico Molecular Mechanics

A1.3.11 In-Silico Molecular Dynamics

A1.3.12 In-Silico Docking

A1.3.13 In-Silico Virtual Screening

A1.3.14 3D Searching and Bioisosterism A1.3.15 Pharmacophore Elucidation and Mapping

A1.3.16 Structure-Activity Relationships - SAR

A1.3.17 Chemometrics

A1.3.18 Development of QSAR

A1.3.19 3D-QSAR

A1.3.20 In-Silico Library Design

A1.3.21 In-Silico Homology Modeling

A1.3.22 In-Silico Free Energy Simulations

A1.3.23 Cheminformatics

A1.3.24 Structural Bioinformatics A1.3.25 Reaction Searching

A1.3.26 Computer-Assisted Structure Elucidation

A1.3.27 In-Silico Prediction of ADME/Tox Properties

A1.3.28 Quantum Chemical Calculations

A1.4 The Drug Discovery Process

A1.4.1 Outline of Drug Discovery

A1.4.2 Starting Idea in a Project

A1.4.3 Importance of Assay Validation

A1.4.4 The Drug Discovery Process

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A1.4.5 Starting Molecule in a Project

A1.4.6 Optimization of the Lead

A1.4.7 Potency and Selectivity

A1.4.8 Beyond Potency and Selectivity in Lead Optimization

A1.4.9 Drugability A1.4.10 Resistance

A1.4.11 Pharmacodynamics

A1.4.12 Drug Delivery

A1.4.13 Metabolism

A1.4.14 Bioavailability

A1.4.15 Toxicity

A1.4.16 Patentability

A1.4.17 Protection of Drug Discovery Achievements

A1.4.18 Lifetime and Effective Lifetime of a Patent

A1.4.19 Assessing Patentability: The Viagra-Levitra Example

A1.4.20 Drug Discovery before and after 1980

A1.4.21 Intelligent Management Strategy

A1.5 Rational Drug Design Strategy

A1.5.1 Two Major Approaches

A1.5.2 Underlying Principles

A1.5.3 Contribution of Molecular Modeling

A1.5.4 The Molecular Similarity Principle

A1.5.5 The Molecular Complementarity

A1.5.6 The Concept of 2D and 3D Pharmacophores A1.5.7 Structure-Based Drug Discovery: The Aliskiren Example

A1.5.8 Therapeutic Risk in a Project

A1.6 The Major Players in Drug Research

A1.6.1 Role of Each Scientist

A1.6.2 Organic Chemist

A1.6.3 Prepare new Molecules

A1.6.4 Analyze SAR Data

A1.6.5 Order new Molecules and Libraries

A1.6.6 Design of a Library of Molecules

A1.6.7 Scale Up a Chemical Synthesis

A1.6.8 Biologist

A1.6.9 Develop Biological Assays

A1.6.10 Develop in-vivo Models for Testing new Molecules

A1.6.11 Test New Molecules

A1.6.12 Compare Results Obtained by Other Groups

A1.6.13 Develop Models for Early Assessment of Toxicity

A1.6.14 Implement Platform for High Throughput Screening

A1.6.15 Molecular Modeler

A1.6.16 Provide Structural Models of Good Quality

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A1.6.17 Analyze and Suggest Candidate Molecules

A1.6.18 Assess Molecules Submitted the Team

A1.6.19 Explore Ways for 3D Alignment of Molecules

A1.6.20 Biotechnologist

A1.6.21 Cloning DNA Sequences A1.6.22 Isolation of Enzyme

A1.6.23 Identify Disease-Relevant Target

A1.6.24 Validate a New Assay

A1.6.25 Computational Chemist

A1.6.26 Search for a Predictive 3D-QSAR Model

A1.6.27 Launch High Throughput Docking Simulations

A1.6.28 Estimate the Binding Energies of New Molecules

A1.6.29 Assess the Quality of QSAR Models

A1.6.30 Structural Bioinformatician

A1.6.31 Encoding and Visualizing Biomolecules

A1.6.32 Understand Protein Flexibility

A1.6.33 Create 3D Models of new Proteins

A1.6.34 Decode the Function of a Protein from its 3D Structure

A1.6.35 Reveal Key Residues in a Protein

A1.6.36 Cheminformatician

A1.6.37 Calculate Molecular Properties

A1.6.38 Find Similar Molecules

A1.6.39 Analyze HTS Results

A1.6.40 Contribute to Virtual Screening and Library Design

A1.6.41 Update and Maintain Databases

A1.6.42 Biophysicist

A1.6.43 X-Ray Crystallographer

A1.6.44 Prepare Crystals of a Protein or a Complex

A1.6.45 Diffraction Pattern and Density Map

A1.6.46 Fit the Electron Density Map

A1.6.47 Refine the 3D Atomic Model

A1.6.48 NMR Spectroscopist

A1.7 Chemistry in Drug Discovery

A1.7.1 Chemistry in Drug Discovery A1.7.2 Synthesis of Complicated Molecules

A1.7.3 Three Methods in Synthetic Chemistry

A1.7.4 Classical Drug Discovery

A1.7.5 Parallel Drug Discovery

A1.7.6 Combinatorial Drug Discovery

A1.7.7 Chemistry in Lead Discovery

A1.7.8 Protein Kinase Example

A1.7.9 Lead Optimization

A1.7.10 Example: Optimization of the Gleevec Series

A1.7.11 Chemistry in Drug Development

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A1.8 The Present and Future Face of Drug Discovery

A1.8.1 Outsourcing: an Important Cultural Shift

A1.8.2 Why Outsourcing Develops so Well?

A1.8.3 Management Response to Challenging Situations A1.8.4 Management Challenges

A1.8.5 Mergers and Mega-Mergers

A1.8.6 Drug Discovery and Mergers

A1.8.7 Massive Cut of Jobs Following Mergers

A1.8.8 Headcount are not always Reduced

A1.8.9 Creation and Development of Startup Companies

A1.8.10 Startup Example-1: Amgen

A1.8.11 Startup Example-2: Actelion

A1.8.12 Startup Example-3: Speedel

A1.8.13 Increasing Importance of Generics

A1.8.14 Economical Implications of Generics

A1.8.15 Emergence of New Industrial Players

A1.8.16 Pharmaceutical Industry in India and China

A1.8.17 Personalized Medicines

A1.8.18 Pharmacogenomics Example

A1.8.19 Stem Cell Therapy

A1.8.20 Some Facts and Figures

A1.8.21 The Cost of Developing a New Drug

A1.8.22 The R&D Process

A1.8.23 Innovation of Drug Discovery (1997-2007)

A1.8.24 Improvements in Life Expectancy

A1.8.25 Drug Discovery in the Industry

A1.8.26 Success of Drug Discovery (in 2008)

A1.8.27 60 Years of Drug Discovery Achievements

A1.8.28 Concluding Remarks

A2. PRINCIPLES OF RATIONAL DRUG DESIGN

A2.1 Rational Drug Design

A2.1.1 Drug Design Basis: Molecular Recognition

A2.1.2 Lock-and-Key Model

A2.1.3 Induced-Fit Model

A2.1.4 Rational Drug Design

A2.1.5 Rational Drug Design Process

A2.1.6 Receptor-Based Drug Design

A2.1.7 Pharmacophore-Based Drug Design

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A2.2 Pharmacophore-Based Design

A2.2.1 Pharmacophore-Based Drug Design Approach

A2.2.2 Similarity Concepts and Molecular Mimicry

A2.2.3 Examples of Molecular Mimicry A2.2.4 ATP

A2.2.5 Dopamine

A2.2.6 Histamine

A2.2.7 Estradiol

A2.2.8 Peptidomimetics

A2.2.9 Strengths of Pharmacophore-Based Drug Design

A2.3 Receptor-Based Design

A2.3.1 Design by Direct Interaction with Receptor Sites

A2.3.2 Exploiting the Receptor Recognition Concepts A2.3.3 Initial Data in Receptor-Based Drug Design

A2.3.4 Strengths of Receptor Based Drug Design

A2.4 Integration in a Global Perspective

A2.4.1 Typical Projects

A2.4.2 Exploit the Two Methods, Independently

A2.4.3 Synergy Between the Two Approaches

A2.4.4 Example of Synergy Between the Two Approaches

A2.4.5 Good Binding Models, the Synergy Condition

A2.4.6 Ideal Situation

A2.4.7 Example 1

A2.4.8 Example 2

A2.4.9 Integration in a Global Perspective

A2.4.10 Pharmacophore-Based Drug Design

A2.4.11 Receptor-Based Drug Design

A2.4.12 Integrated Global Approach

A2.5 Challenge of the Genomics Era

A2.5.1 The Genomic Era A2.5.2 A New Challenge in Drug Design

A2.6 Typical Projects

A2.6.1 Typical Pharmacophore-Based Project

A2.6.2 Design Based on 3D Mimicry

A2.6.3 Typical Receptor-Based Project

A2.6.4 Design Based in Making Favorable 3D Interactions

A2.6.5 Typical Genomic Project

A2.7 Perspectives

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A2.7.1 Drug Discovery of the 1970's



A2.7.4 The Present Situation

A2.7.5 Initial Skepticism Towards Rational Drug Design A2.7.6 Success Stories in Rational Drug Design

A2.7.7 Future Perspectives

A2.8 CHAPTER QUIZZES (Available only in Academic License)

B. PROTEIN STRUCTURE AND MODELING

B1. STRUCTURAL BIOINFORMATICS

B1.1 Introduction to Structural Bioinformatics

B1.1.1 Challenges in the Post Genomic Era

B1.1.2 The Informational Chaos

B1.1.3 Integration through Computational Science

B1.1.4 Structural Bioinformatics

B1.1.5 Grouping Fields into One Discipline

B1.1.6 3D Basis of Structural Bioinformatics

B1.1.7 The Structural Genomics Effort

B1.1.8 The Protein Structure Initiative

B1.1.9 Strategy of the Protein Structure Initiative

B1.1.10 The Structural Genomics Consortium

B1.1.11 Global Planning of Structural Genomics

B1.1.12 The Impact of Structural Genomics

B1.1.13 The Relationship between Structure and Function

B1.1.14 Example of a Structure-Function Relationship

B1.1.15 Learning from Evolution

B1.1.16 Learning from Structural Folds

B1.1.17 Learning from Molecular Shape

B1.1.18 Example of Knowledge Derived from 3D Structure

B1.1.19 Is Structure Sufficient to Predict Function?

B1.1.20 Exploiting Knowledge to Design New Drugs

B1.1.21 Bridge between Genomics and Drug Discovery

B1.1.22 Tools Developed by Structural Bioinformatics

B1.2 Architecture of Biomolecules

B1.2.1 Biomolecules in the Cell

B1.2.2 DNA/RNA Structure

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B1.2.3 DNA is the Genetic Material

B1.2.4 DNA Variability

B1.2.5 Importance of the DNA 3D Structure

B1.2.6 The Building Blocks

B1.2.7 Base B1.2.8 Sugar

B1.2.9 Phosphate

B1.2.10 Putting the Building Blocks Together

B1.2.11 Nomenclature of Nucleotides and Nucleosides

B1.2.12 Nucleotides of Nucleic Acids

B1.2.13 The Double Helix Structure

B1.2.14 DNA Helices are Antiparallel

B1.2.15 Hydrogen Bonding Pattern

B1.2.16 Aromatic Base Stacking

B1.2.17 Major and Minor Grooves

B1.2.18 DNA forms

B1.2.19 G-Quadruplex Conformation

B1.2.20 DNA versus RNA

B1.2.21 3D Folds of RNA

B1.2.22 Protein Structure

B1.2.23 Proteins are Fundamental to Life

B1.2.24 Structural Diversity of Proteins

B1.2.25 Importance of Protein 3D Structures

B1.2.26 Chemical Nature of Proteins

B1.2.27 Challenges in Understanding Protein Structure

B1.2.28 Protein Structure Complexity

B1.2.29 The Four Levels of Protein Architecture

B1.2.30 Primary Structure

B1.2.31 Secondary Structure

B1.2.32 Tertiary Structure

B1.2.33 Quaternary Structure

B1.3 Biomolecular Properties

B1.3.1 Protein Flexibility and Motion

B1.3.2 Importance of Dynamic Motions in Biological Processes B1.3.3 Example of Function: ATP Synthase

B1.3.4 Example of Function: DNA Biosynthesis

B1.3.5 Example of Function: Molecular Switch

B1.3.6 Example of Induced-Fit: RNA-Protein Recognition

B1.3.7 Example of Induced-Fit: Ubiquitous Proteins

B1.3.8 Types of Molecular Motions

B1.3.9 Time Scale of Protein Motion

B1.3.10 Methods to Study Protein Motions

B1.3.11 Experimental Techniques to Study Protein Motions

B1.3.12 Simulation Methods to Study Protein Motions B1.3.13 Normal Mode Analyses (NMA)

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B1.3.14 Molecular Dynamics vs Normal Mode Analyses

B1.3.15 Database of Macromolecular Movements

B1.4 Assembly of Biomolecules

B1.4.1 Biological Molecule Association

B1.4.2 Molecular Recognition

B1.4.3 The Recognition Process

B1.4.4 Complementary Features Upon Binding

B1.4.5 Role of Native Protein Configuration

B1.4.6 Tolerance Upon Binding

B1.4.7 The "Induced-Fit" Theory

B1.4.8 Example of Enzyme Adaptation to Inhibitor Binding

B1.4.9 Example of Ligand Adaptation upon Binding

B1.4.10 Maximizing Surface Contacts

B1.4.11 Motions Associated to Induced-Fit B1.4.12 Experimental Evidence of the Induced-Fit Model

B1.4.13 Large Rearrangements

B1.4.14 Role of Large Rearrangements

B1.4.15 The Domino Effect

B1.4.16 Proteins Described as Ensemble of Conformations

B1.4.17 Energy Landscape of a Protein

B1.4.18 Conformational Selection Operated by a Ligand

B1.4.19 Energetic Induction Upon Binding

B1.4.20 Forces Involved in Molecular Recognition

B1.4.21 Van der Waals Forces B1.4.22 Electrostatic Interactions

B1.4.23 Hydrogen Bonds

B1.4.24 Solvent Effect

B1.4.25 The Role of the Solvent

B1.4.26 The Hydrophobic Effect

B1.4.27 The Entropic Effects

B1.4.28 Enthalpy-Entropy Compensation

B1.4.29 Assessing Binding Interactions

B1.4.30 Free Energy of Binding

B1.4.31 Importance of Free Energy of Binding B1.4.32 Experimental Measures of Binding Affinities

B1.4.33 Titration Curve to Measure Kd

B1.4.34 Scatchard-Rosenthal Plots

B1.4.35 Conversion of Kd into Energies

B1.4.36 Theoretical Prediction of Binding Energies

B1.4.37 Solving the Schrodinger Equation

B1.4.38 Molecular Mechanics

B1.4.39 Force-Field

B1.4.40 Example of Force-Fields

B1.4.41 Other Methods B1.4.42 Incorporation of the Solvent

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B1.5 Obtaining Macromolecular 3D-Structures

B1.5.1 Experimental Methods

B1.5.2 X-ray Crystallography

B1.5.3 Protein Production and Purification B1.5.4 Growing of Single Crystal

B1.5.5 The Single Crystal

B1.5.6 Collecting the Diffraction Data

B1.5.7 Recovering the Phase Angle

B1.5.8 Structure Determination and Refinement

B1.5.9 Atomic Coordinates

B1.5.10 The Advantages of X-ray Crystallography

B1.5.11 The Limitations of X-ray Crystallography

B1.5.12 NMR Spectroscopy

B1.5.13 NMR Concepts

B1.5.14 Spin-Spin Coupling

B1.5.15 Data Collection

B1.5.16 Structure Determination

B1.5.17 Analysis

B1.5.18 The Advantages of NMR

B1.5.19 The Limitations of NMR

B1.5.20 Electron Microscopy

B1.5.21 Basic Concept

B1.5.22 The Advantages of Electron Microscopy

B1.5.23 The Limitations of Electron Microscopy

B2. PROTEIN STRUCTURE

B2.1 Structural and Functional Diversity of Proteins

B2.1.1 Proteins are Fundamental to Life

B2.1.2 Great Diversity of Protein Biological Functions

B2.1.3 Chemical Nature of Proteins

B2.1.4 Structural Diversity of Proteins

B2.2 Link between Protein Sequence, Folding and Function

B2.2.1 Importance of Protein 3D Structures

B2.2.2 Protein Folding

B2.2.3 Anfinsen's Dogma

B2.2.4 Anfinsen's Dogma and Levinthal's Paradox

B2.2.5 The Pathway Theory and Energy Funnels

B2.2.6 Mechanisms of Protein Folding

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B2.2.7 The Protein Misfolding Problem

B2.2.8 Challenge in Understanding Protein Structure

B2.3 Amino Acids: Building Blocks of Proteins

B2.3.1 Amino acids: Building Blocks of Proteins

B2.3.2 α-Amino Acids

B2.3.3 α-Amino Acid Stereoisomers

B2.3.4 Diversity of the Properties of Amino Acids

B2.3.5 Amino Acids Properties

B2.3.6 Classification of Amino Acids Properties

B2.3.7 Non-Standard Amino Acids

B2.4 From Amino Acids to Proteins

B2.4.1 Amino Acids are Linked by Peptide Bonds

B2.4.2 Peptide Biosynthesis

B2.4.3 Polymer Amino-Acids

B2.4.4 Length of Proteins

B2.4.5 More than One Polypeptide Chain

B2.4.6 Conjugated Proteins

B2.4.7 Examples of Conjugated Proteins

B2.4.8 Cross-Linked Polypeptide Chains

B2.5 Geometry of Proteins and Peptides

B2.5.1 Peptide Bonds are Planar B2.5.2 Why the Peptide Bond is Planar?

B2.5.3 Cis and Trans Isomers of the Peptide Bond

B2.5.4 Trans Isomer Favored

B2.5.5 Isomers of Proline

B2.5.6 Peptide Torsion Angles

B2.5.7 Conformational Freedom

B2.5.8 Conformational Complexity of Polypeptide Chains

B2.5.9 Not All φ / ψ Torsion Angles are Possible

B2.5.10 The Ramachandran Plot

B2.5.11 φ and ψ Distribution B2.5.12 Interactive Ramachandran Plot

B2.5.13 Torsion Angles Observed in Proteins

B2.5.14 Glycine Residue Torsion Angles

B2.5.15 Side Chain Conformations

B2.5.16 Side Chain Atomic and 3D Nomenclature

B2.5.17 Side Chain Conformations

B2.5.18 Non-Rotameric Side Chain Conformations

B2.6 Protein Structure Overview

B2.6.1 Protein Structure Complexity

B2.6.2 The Four Levels of Protein Architecture

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B2.6.7 Forces Involved in Protein Stability B2.6.8 Proteins are not Static

B2.6.9 Representing Protein Structures

B2.6.10 Wireframe Representation

B2.6.11 Ball and Stick Representation

B2.6.12 Cα Trace Representation

B2.6.13 Ribbon Representation

B2.6.14 Cartoon Representation

B2.6.15 Space Filling - CPK Representation

B2.6.16 Surface Representation

B2.7 Primary Structure


B2.7.2 Unique Primary Structure for Each Protein

B2.7.3 Primary Sequence and Protein Properties

B2.8 Secondary Structure


B2.8.2 Periodic and Non Periodic Secondary Structure Elements

B2.8.3 Hydrogen Bonds in Secondary Structure Elements

B2.8.4 The α-Helix

B2.8.5 Packing of the α-Helix

B2.8.6 φ and ψ Torsion Angles of the α-Helix

B2.8.7 Two Enantiomeric α-Helices

B2.8.8 Geometry Described with Pitch and Rise

B2.8.9 Helix Macro-Dipole

B2.8.10 Amphipathic Character of the α Helix

B2.8.11 3(10)-Helix and π-Helix

B2.8.12 Helices Geometrical Parameters

B2.8.13 Occurrence of Helices in Proteins

B2.8.14 The β-Sheet

B2.8.15 The β-Strand Unit

B2.8.16 φ and ψ Torsion Angles in β-Sheets

B2.8.17 Stability of the β-Sheet

B2.8.18 Parallel and Anti-Parallel β-Sheets

B2.8.19 Occurrence of β-Sheets in Proteins

B2.8.20 Twist of the β-sheet

B2.8.21 Turns

B2.8.22 β-Turns

B2.8.23 φ and ψ Torsion Angles of β Turns

B2.8.24 Non-Regular Coil and Loops

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B2.8.25 Coil

B2.8.26 Loops

B2.9 Super-Secondary Structure (Motifs)

B2.9.1 Super-Secondary Structures and Motifs

B2.9.2 Classification of Super-Secondary Structures

B2.9.3 All β super-secondary structures

B2.9.4 β-Hairpin

B2.9.5 β-Meander

B2.9.6 Greek-Key

B2.9.7 All α Super-Secondary Structures

B2.9.8 αα-Hairpin

B2.9.9 αα-Corners

B2.9.10 EF Hand

B2.9.11 Helix-Turn-Helix B2.9.12 Four-Helix Bundle

B2.9.13 Mixed α & β Super-Secondary Structures

B2.9.14 β-α-β Motif

B2.9.15 Rossmann Fold

B2.10 Tertiary Structure


B2.10.2 Domains in the Tertiary Structure

B2.10.3 Domains and Sequence

B2.10.4 Domains and Function

B2.10.5 New Look on Proteins Levels of Architecture

B2.10.6 Blurred Boundaries

B2.10.7 Tertiary Structure Patterns: Folds

B2.10.8 Fold Diversity

B2.10.9 Protein Folds and Function

B2.10.10 Classification of Protein Folds

B2.10.11 Mainly α Folds

B2.10.12 Mainly β Folds

B2.10.13 Mixed α-β Folds

B2.10.14 Databases of Folds

B2.11 Quaternary Structure


B2.11.2 Dimers, Trimers, Tetramers etc...

B2.11.3 Homo-Oligomers: Identical Polypeptide Chains

B2.11.4 Hetero-Oligomers: Different Polypeptide Chains

B2.12 Structural Classification of Proteins

B2.12.1 Structural Classification of Proteins

B2.12.2 Globular Proteins

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B2.12.3 Hydrophilic Surface and Hydrophobic Core

B2.12.4 Hydrophobic Effect

B2.12.5 Hydration Layer

B2.12.6 Membrane Proteins

B2.12.7 The Lipid Bilayer B2.12.8 Membrane Model

B2.12.9 Membrane Proteins Types

B2.12.10 Transmembrane Protein Surface

B2.12.11 Transmembrane Protein Folds

B2.12.12 Fibrous Proteins

B2.12.13 Collagen

B2.12.14 α-Keratin

B2.12.15 Silk Fibroin

B2.13 Perspectives

B2.13.1 The History

B2.13.2 The Pharmaceutical Connection

B2.13.3 A Fascinating Field

B2.14 CHAPTER QUIZZES (Available only in Academic License)

B3. MOLECULAR DYNAMICS

B3.1 Introduction

B3.1.1 What is Molecular Dynamics?

B3.1.2 Ergodicity Assumption

B3.1.3 Historical Note

B3.1.4 Four Types of Applications of MD Simulation

B3.1.5 Macroscopic Behavior

B3.1.6 MD Between Experiment and Theory

B3.1.7 Refinement and Validation of MD B3.1.8 Access to Unavailable Data

B3.1.9 MD Applied to Living Systems

B3.1.10 Example 1: Relation between Structure and Function



B3.1.13 Proteins are not Static

B3.1.14 Thermal Fluctuations

B3.1.15 Conformational Changes

B3.1.16 MD as a Way to Study Molecular Motions

B3.1.17 Mimicking the Way a Molecule Moves B3.1.18 Average Properties Derived from MD Trajectories

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B3.1.19 Calculating Molecular Properties of a System

B3.1.20 Studying Thermodynamic Properties

B3.1.21 Studying Kinetic Properties

B3.1.22 Studying Conformational Changes

B3.2 Energy Calculations

B3.2.1 Calculation of Forces & Energies

B3.2.2 Two Families of MD Methods

B3.2.3 The Quantum Mechanics Approach

B3.2.4 Quantum Methods are Computationally Expensive

B3.2.5 The Classical Mechanics Approach

B3.2.6 Classical vs. Quantum Methods

B3.2.7 Classical MD Simulates the Dynamics of the Nuclei

B3.2.8 The Born-Oppenheimer Approximation

B3.2.9 Force Field for Classical MD B3.2.10 General Force Field Equation

B3.2.11 Stretching Term

B3.2.12 Bending Term

B3.2.13 Torsional Term

B3.2.14 Van der Waals Term

B3.2.15 Electrostatic Term

B3.2.16 A Couple of Practical Remarks

B3.2.17 The Link between Forces and Potential Energies

B3.3 MD Algorithm

B3.3.1 Newton's Equation of Motion

B3.3.2 Prediction of Next Position

B3.3.3 Integration Step

B3.3.4 Molecular Dynamics Algorithm

B3.3.5 Trajectories: List of Positions and Velocities

B3.3.6 Atomic Positions at Time (t+∆t)

B3.3.7 Solving Newton's Equations

B3.3.8 Numerical Integration with the Verlet Formula

B3.3.9 Summary of the MD Algorithm

B3.4 Fundamental Issues

B3.4.1 Time Step

B3.4.2 Choice of Time Step

B3.4.3 Time-Scale of Molecular Motions

B3.4.4 Method for Increasing the Time Step: Constrained MD

B3.4.5 Periodic Boundary Condition

B3.4.6 Importance of Long Range Forces

B3.4.7 The Distance Cutoff Concept

B3.4.8 Problems with Cutoffs B3.4.9 Switching Functions

Page 16 of 54



B3.4.10 Choice of the Cutoff

B3.4.11 Strategies to Incorporate the Solvent

B3.4.12 Implicit Solvent Model

B3.4.13 Explicit Solvent Molecules

B3.4.14 The Ewald Summation Method

B3.5 MD Protocols

B3.5.1 Typical Steps for MD Simulation

B3.5.2 Define and Prepare the Molecular System

B3.5.3 Preparing the Coordinates

B3.5.4 Manual Assembly of a Complex Molecular System

B3.5.5 Solvating the System

B3.5.6 Addition of Counterions

B3.5.7 Choose the MD Package & Force-Field

B3.5.8 Extending the Parameterization of the Force Field B3.5.9 Configuration Parameters of the MD Simulation

B3.5.10 Time-step

B3.5.11 Length of the Simulation

B3.5.12 Distance Cutoffs

B3.5.13 Reassigning the List of Non-Bonded Atom Pairs

B3.5.14 Initial Velocities

B3.5.15 SHAKE Parameters

B3.5.16 Preliminary Treatments: Minimization & Equilibration

B3.5.17 Minimization of Initial Coordinates

B3.5.18 Thermal Equilibration of the System B3.5.19 Maxwell-Boltzmann Equation

B3.5.20 Molecular Dynamics Run

B3.5.21 Conservation of the Total Energy

B3.5.22 Test Energy Fluctuation

B3.5.23 Possible Crash of the Program

B3.6 Analysis of the Results of the MD Simulation

B3.6.1 Analysis of the Results

B3.6.2 Thermodynamic Properties

B3.6.3 Kinetic Properties

B3.6.4 Visualization of Time Dependent Properties

B3.6.5 Deriving Average Properties from the Trajectory

B3.6.6 Average Energies

B3.6.7 Specific Heat

B3.6.8 Radius of Gyration

B3.6.9 Local Motions

B3.6.10 Interesting Motions

B3.6.11 Movies

B3.7 Examples of MD Applications

Page 17 of 54



B3.7.1 First µs MD Simulation of Protein Folding

B3.7.2 Protein-Folding Dynamics using Folding@Home

B3.7.3 MD of the Complete Satellite Tobacco Mosaic Virus

B3.7.4 How Does RNA Moves Along DNA?

B3.8 Using MD for Conformational Sampling

B3.8.1 The Sampling Approach in Optimization Problems

B3.8.2 MD as a Tool for Sampling the Space

B3.8.3 Sampling to Find the Global Minimum

B3.8.4 Conformational Analysis of a Small Molecule

B3.8.5 Conformational Analysis of Biomolecules

B3.8.6 Loop Conformation in Proteins

B3.8.7 How Do Ligands and Receptors Bind Together?

B3.8.8 Protein Folding Problem

B3.8.9 Systematic and Random Sampling B3.8.10 Alternative Methods for Sampling

B3.8.11 Monte Carlo Random Search

B3.8.12 Monte Carlo Algorithm

B3.8.13 Metropolis Monte Carlo Approach

B3.8.14 Simulated Annealing

B3.8.15 Diffusion Equation Methods

B3.8.16 Replica Exchange MD Method

B3.9 MD for the Calculation of Binding Energies

B3.9.1 In Silico Drug Design

B3.9.2 FEP Approach for Calculating Binding Energies

B3.9.3 FEP Thermodynamic Cycle

B3.9.4 Exploiting the Thermodynamic Cycle

B3.9.5 FEP: Computational Alchemy

B3.9.6 Limitation of FEP Method

B3.9.7 FEP Study: Example 1

B3.9.8 FEP Study: Example 2

B3.10 MD Packages

B3.10.1 Examples of Popular MD Packages

B3.10.2 NAMD

B3.10.3 VMD

B3.10.4 TINKER

B3.10.5 AMBER

B3.10.6 CHARMM

B3.10.7 GROMACS

B3.10.8 MOIL

B3.10.9 GROMOS

B3.11 Limitations and Perspectives

Page 18 of 54



B3.11.1 Limitations of MD

B3.11.2 Error Introduced by Empirical Potentials?

B3.11.3 Trade Off Between Efficiency and Accuracy

B3.11.4 Supramolecular Systems

B3.11.5 Long Range Forces as a Computational Bottleneck B3.11.6 Time and Size Limitations

B3.11.7 Alternative Techniques for Long Time Dynamics

B3.11.8 From Impossible to Feasible

B3.11.9 Classical MD is not for Bond Breaking Mechanisms

B3.11.10 Present and Future

B3.12 CHAPTER QUIZZES (Available only in Academic License)

C. STRUCTURE-BASED DESIGN

C1. INTRODUCTION TO PROTEIN-LIGAND BINDING

C1.1 Introduction

C1.1.1 Receptor-Based Drug Design

C1.1.2 Macromolecular Targets

C1.1.3 Mechanism of Action of Drugs

C1.1.4 Drug Targets

C1.1.5 Contribution of Recombinant Technologies

C1.1.6 Operational Strategy: Docking

C1.2 Analytical Process

C1.2.1 The Analytical Process

C1.2.2 Data Collection: X-Ray Crystallography

C1.2.3 Data Collection: NMR Spectroscopy

C1.2.4 Data Collection: Homology Models

C1.2.5 Analysis

C1.2.6 Design Phase

C1.3 Principles of Analysis

C1.3.1 Analysis of the Morphology of the Active Site

C1.3.2 Morphology of the Active Site of a Protein Kinase

C1.3.3 Complexes with Ligands

C1.3.4 Forces That Contribute to the Binding

C1.3.5 The Molecular Recognition Process

C1.3.6 Electrostatic C1.3.7 Hydrogen Bonding

Page 19 of 54



C1.3.8 Hydrophobic

C1.3.9 Hydrophobic Interactions

C1.3.10 Consider Hydrophobic Interactions

C1.3.11 Elementary Hydrophobic Interactions

C1.3.12 Example of Hydrophobic Binding C1.3.13 Strengthening Hydrophobic Interactions

C1.3.14 Hydrogen Bond Features

C1.3.15 Proteins Capabilities in Hydrogen Bonding

C1.3.16 Consider Hydrogen Bond Formations

C1.3.17 Elementary Hydrogen Bond Interactions

C1.3.18 Example of the Hydrogen Bond Binding

C1.3.19 Electrostatic Interactions

C1.3.20 Elementary Electrostatic Interactions

C1.3.21 Strength of Electrostatic Interactions

C1.3.22 Example of Electrostatic Interactions

C1.3.23 Increase of Potency by the Formation of a Salt Bridge

C1.3.24 OH Analog Much Less Potent

C1.4 Example of Tight Interactions

C1.4.1 An Example of a Tight Ligand-Receptor Interaction

C1.4.2 The X-ray Structure of the Biotin/Streptavidin

C1.4.3 The Binding Mode of Biotin with Streptavidin (1/4)




C1.5 Receptor & Ligand Flexibility

C1.5.1 Flexibility of the Receptor

C1.5.2 Flexibility of The Ligand

C1.5.3 Entropic Effects

C1.6 Role of the Solvent

C1.6.1 Solvation and Desolvation

C1.6.2 The Role of the Solvent C1.6.3 Relay with Water Molecules

C1.6.4 Relay with Several Water Molecules

C1.6.5 Relay with Water Molecule Having Four H-Bonds

C1.7 Prediction of Binding Modes

C1.7.1 Binding Modes Predicted by Analogy

C1.7.2 Inversion of Binding Modes

C1.7.3 Inverted Binding Mode of Olomoucine

C1.7.4 X-Ray Structure of ATP Bound to a Protein Kinase

C1.7.5 Intuitive 2D Alignment for Olomoucine

C1.7.6 Experimental Binding Mode of Olomoucine

Page 20 of 54



C1.7.7 Origin of the Inverted Binding Mode of Olomoucine

C1.7.8 Inverted Binding Mode of Methotrexate

C1.7.9 Intuitive 2D Alignment for Methotrexate

C1.7.10 Experimental Binding Mode of Methotrexate

C1.7.11 Origin of the Inverted Binding Mode of Methotrexate C1.7.12 Binding Mode Predicted from SAR

C1.8 Methods for Analyzing Binding

C1.8.1 Analyzing Ligand-Receptor Binding

C1.8.2 Ligand-Binding Predictions

C1.8.3 Visual Analyses

C1.8.4 Docking Analyses

C1.8.5 Manual Docking with Computer Graphics

C1.8.6 Automated Methods for Docking

C1.8.7 Calculation of Binding Energies C1.8.8 Free Energy Perturbation Techniques

C1.8.9 Energies from Force Field Calculations

C1.8.10 Correlation with Biological Activities

C1.8.11 Energies from Scoring Functions

C1.8.12 Limitations of Scoring Functions

C1.8.13 Calculating Desolvation Energies

C1.9 Conclusion

C1.9.1 Conclusion

C1.10 CHAPTER QUIZZES (Available only in Academic License)

C2. PRINCIPLES OF STRUCTURE-BASED DESIGN

C2.1 Introduction

C2.1.1 Design of Drug Candidates: An Iterative Process

C2.1.2 Steps in Structure-Based Drug Design

C2.1.3 Small Changes Can Produce Huge Effects

C2.1.4 p38 Wild

C2.1.5 p38 Mutant

C2.1.6 ERK-2 Wild

C2.1.7 ERK-2 Mutant

C2.1.8 Increasing Biological Activity

C2.1.9 Beginning the Design Phase

C2.1.10 A Simple Example of Design

C2.1.11 Extension of the Molecule to Form another H-Bond

Page 21 of 54



C2.1.12 Checking the Validity of the Design

C2.1.13 Definition of Docking

C2.1.14 Docking Treatments

C2.2 Eight Golden Rules

C2.2.1 Eight Golden Rules in Receptor-Based Ligand Design

C2.2.2 Rule 1: Coordinate to Key Anchoring Sites

C2.2.3 Desolvation Upon Binding

C2.2.4 Rule 2: Exploit Hydrophobic Interactions

C2.2.5 Many Small Contributions

C2.2.6 Rule 3: Exploit Hydrogen Bonding Capabilities

C2.2.7 Hydrogen Bonds with Backbone Atoms

C2.2.8 Geometry of a Hydrogen Bond and Solvation Issues

C2.2.9 Hydrogen Bonds with Residue Atoms

C2.2.10 Rule 4: Exploit Electrostatic Interactions C2.2.11 Rule 5: Favor Bioactive Form & Avoid Energy Strain

C2.2.12 Advantage and Limitation of a Rigid Ligands

C2.2.13 Rule 6: Optimize VDW Contacts and Avoid Bumps

C2.2.14 The Frontier between an Excellent Fit and a Bump

C2.2.15 Rule 7: Structural Water Molecules and Solvation

C2.2.16 Desolvation Energies

C2.2.17 Leave Some Room to Solvate Charged Centers

C2.2.18 Rule 8: Consider Entropic Effect

C2.2.19 Gaining Binding by Reduction of Entropy

C2.2.20 Example of Ligand Rigidification C2.2.21 Making a Flexible Molecule More Rigid

C2.3 The Four Design Methods

C2.3.1 The Four Design Methods

C2.4 Analog Design

C2.4.1 Principles of Analog Design

C2.4.2 Example of Analog Design

C2.4.3 Additional Binding with Arginine Residue

C2.5 Database Searching

C2.5.1 3D Database Searching

C2.5.2 Scoring the Hits

C2.5.3 Advantages of Database Searching

C2.5.4 Problems of Conformational Complexity

C2.5.5 Assessing the Validity of the 3D Structures

C2.5.6 Example of Database Searching

C2.5.7 Limitations in Database Approaches

C2.5.8 Unexpected Binding Mode of Haloperidol

C2.5.9 Databases of Molecules in 3D

Page 22 of 54



C2.5.10 The Main Purpose of a 3D-Database Search

C2.6 De-Novo Design

C2.6.1 Automated Construction Approaches

C2.6.2 Molecule Generated by an Automated Method

C2.7 Manual Design

C2.7.1 Manual Design

C2.7.2 Importance of Visualization

C2.7.3 Tools in Manual Design

C2.7.4 Fully Exploiting the Fruits of the Analyses

C2.7.5 Design of a Hybrid Molecule

C2.8 Another Iteration

C2.8.1 Another Round of Analysis & Design

C2.9 A Success Story

C2.9.1 Example of Successful Structure-Based Design

C2.9.2 Mechanism of Action of the HIV-1 Protease

C2.9.3 The Crystallographic Structure of the HIV-1 Protease

C2.9.4 Hydrophobic Cavity of the HIV-1 Protease

C2.9.5 Flap of the HIV-1 Protease

C2.9.6 Transition State Concept for the Design of Inhibitors

C2.9.7 Topography of the Active Site of the Enzyme

C2.9.8 The MVT-101 Inhibitor

C2.9.9 Crystallographic Resolution of the HIV-1 Protease

C2.9.10 X-ray of the Complex of MVT-101 with the Enzyme (1/3)



C2.9.13 Design of Peptide-Like Structures

C2.9.14 Optimization to Fit the hydrophobic pockets

C2.9.15 Example of Optimized Structure

C2.9.16 X-ray Structure of the A-77003 Complex (1/4)




C2.9.20 A Drug Design Solution Using Database Searching

C2.9.21 The Terphenyl Hit

C2.9.22 In Depth Analysis of the Hit

C2.9.23 Incorporating Binding Features of the Water Molecule

C2.9.24 Rigidification of the Linear Inhibitor

C2.9.25 Considerations for Specificity

C2.9.26 Design of Cyclohexanone Scaffold

C2.9.27 The Design of Cyclic Ureas

C2.9.28 Limitation of the 6-Membered Ring Scaffold

Page 23 of 54



C2.9.29 The 7-Membered cyclic Urea Scaffold

C2.9.30 Design of the Cyclic Urea XK-263

C2.9.31 The Crystallographic Structure of XK-263 Complex (1/3)

C2.9.32 The Crystallographic Structure of XK-263 Complex (2/3)

C2.9.33 The Crystallographic Structure of XK-263 Complex (3/3) C2.9.34 Lessons From HIV-1 Protease Inhibition

C2.10 Conclusion

C2.10.1 Conclusion


C3. MOLECULAR DOCKING: PRINCIPLES AND METHODS

C3.1 Introduction to Computational Docking

C3.1.1 Molecular Recognition

C3.1.2 Molecular Recognition Process: Molecular Docking

C3.1.3 Understanding Molecular Recognition

C3.1.4 Molecular Docking Models

C3.1.5 The Lock and Key Theory

C3.1.6 The Induced-Fit Theory C3.1.7 The Conformation Ensemble Model

C3.1.8 From the Lock and Key to the Ensemble Model

C3.1.9 Experimental Methods to Study Molecular Docking

C3.1.10 Limitations of Experimental Techniques

C3.1.11 A Bottleneck in Drug Discovery

C3.1.12 Triggering the Computational Docking Discipline

C3.1.13 Definition of Computational Docking

C3.1.14 Applications of Computational Docking

C3.2 The Docking Problem

C3.2.1 The Docking Problem

C3.2.2 Great Diversity of Molecular Interactions

C3.2.3 Atomic Basis of Molecular Recognition

C3.2.4 Definition of the "Pose"

C3.2.5 Docking Viewed as a Black Box

C3.2.6 Current Computational Docking Programs

C3.2.7 Simulation and non-Simulation Approaches

C3.2.8 Simulation Approaches

C3.2.9 Non-Simulation Approaches

C3.2.10 Molecular Complementarity in Computational Docking

Page 24 of 54



C3.2.11 Shape Complementarity

C3.2.12 Chemical Complementarity

C3.2.13 Energy Dictates Molecular Associations

C3.2.14 Find a Complex that Minimizes the Energy

C3.2.15 Accounting for Molecular Flexibility in Docking C3.2.16 Flexible Docking: Increasing Levels of Complexity

C3.2.17 Initial Data and Nature of the Docking Difficulty

C3.2.18 Bound Docking

C3.2.19 Unbound Docking

C3.2.20 Modeled Docking

C3.2.21 The Three Generations in Computational Docking

C3.2.22 Three Components of Docking Software

C3.3 System Representation

C3.3.1 Molecular Representation C3.3.2 Atomic Representation

C3.3.3 Complexity of the Atomic Repesentation

C3.3.4 Internal Coordinates

C3.3.5 Protein Preparation

C3.3.6 Small Molecule Preparation

C3.3.7 Surface Representation

C3.3.8 Molecular Surface Matching

C3.3.9 Surface-Based Representation

C3.3.10 Accessible Surface Area

C3.3.11 Solvent Contact & Reentrant Surfaces C3.3.12 Example of Contact & Reentrant Surface

C3.3.13 Describing the Molecular Shape

C3.3.14 Connolly's Contact and Reentrant Surfaces

C3.3.15 Sparse Surface

C3.3.16 Delaunay Triangulation

C3.3.17 "Knob" and "Hole" Descriptors

C3.3.18 Using Knobs and Holes for Complementarity

C3.3.19 Other Examples of Shape Descriptors

C3.3.20 Grid Representation

C3.3.21 Use of GRID Potentials to Simplify the Docking C3.3.22 Assessing Shape Complementarity Using Grid

C3.4 Scoring Methods

C3.4.1 Need to Assess the Quality of Docked Complexes

C3.4.2 A Good Understanding of the Binding

C3.4.3 Important Questions

C3.4.4 Molecular Determinants for Binding

C3.4.5 Interaction Forces and Binding Energies

C3.4.6 Favorable Forces

C3.4.7 Unfavorable Forces

Page 25 of 54



C3.4.8 Desolvation Energies

C3.4.9 Entropic Effects

C3.4.10 Calculation of the Binding Energies

C3.4.11 Free Energy Equations

C3.4.12 Conversion of K to Energies C3.4.13 Difficulty of Calculating Free Energies of Binding ∆G

C3.4.14 Approximating ∆G by Molecular Mechanics

C3.4.15 Force-Field Calculations

C3.4.16 CHARMM Force Field to Score the Docking

C3.4.17 Approximating ∆G by Quantum Mechanics

C3.4.18 Development of Scoring Functions for Docking

C3.4.19 Scoring Functions

C3.4.20 Empirical Scoring Functions

C3.4.21 Example of Empirical Scoring Function

C3.4.22 Knowledge-Based Scoring Functions

C3.4.23 The Statistical Analyses

C3.4.24 Knowledge-Based Potentials

C3.4.25 The DrugScore Program

C3.4.26 DrugScore: The Thrombin Example

C3.4.27 Refinement of Scoring Functions

C3.4.28 Other Scoring Methods

C3.4.29 Shape and Property Complementarity Scoring

C3.4.30 Method to Measure Shape Complementarity

C3.4.31 Free Energy Perturbation

C3.5 Rigid Docking Methods

C3.5.1 Docking Algorithms

C3.5.2 The Mathematical Problem

C3.5.3 Two Docking Philosophies

C3.5.4 The Feature-Based Matching Approach

C3.5.5 Docking Using Feature-Based Methods

C3.5.6 Match Complementarity or Similarity Features

C3.5.7 Components of Feature-Based Matching Methods

C3.5.8 Step 1: Feature Extraction

C3.5.9 Step 2: Feature Matching C3.5.10 Step 3: Transformation (Assembly)

C3.5.11 Step 4: Filtering and Scoring

C3.5.12 Virtual Screening and De Novo Design

C3.5.13 Programs with Feature-Based Matching Methods

C3.5.14 Algorithms of Matching

C3.5.15 Clique-Search Based Approaches

C3.5.16 Goal of the Docking Algorithm

C3.5.17 Distance Compatibility Graph

C3.5.18 Clique Detection Methods

C3.5.19 Pose-Clustering C3.5.20 Searching for Compatible Triangles

Page 26 of 54



C3.5.21 Transformation that Align a Maximum of Triangles

C3.5.22 Complementarity and Similarity Matching

C3.5.23 Speed up of Pose-Clustering

C3.5.24 The Bottleneck of Pose-Clustering

C3.5.25 Geometric Hashing C3.5.26 Fast Retrieval of Matching Features

C3.5.27 Invariant Representation of Features

C3.5.28 Improvement of Pose-Clustering

C3.5.29 PatchDock Example

C3.5.30 The Stepwise Search Approach

C3.5.31 Components of a Stepwise Docking Program

C3.5.32 Exhaustive and Stochastic Search

C3.5.33 Exhaustive vs. Stochastic Search

C3.5.34 Exhaustive Search

C3.5.35 Mapped-Grid Method

C3.5.36 Physico-Chemical Properties of the Receptor

C3.5.37 Assessing Shape Complementarity

C3.5.38 Fast-Fourier Transform (FFT) Method

C3.5.39 FFT vs. Exhaustive Method

C3.5.40 FFT - Geometric Shape Complementarity

C3.5.41 FFT - Different Scores

C3.5.42 Docking of Plastocyanin and Cytochrome C

C3.5.43 Spherical Polar Fourier Correlations - Fast FFT

C3.5.44 Stochastic Algorithms

C3.5.45 A Typical Computational Docking Program

C3.5.46 Optimization Methods to Find the Best Solution

C3.5.47 Monte Carlo Methods

C3.5.48 Simulated Annealing

C3.5.49 Genetic Algorithms (GA)

C3.5.50 General Principle of GA

C3.5.51 Creating a New Generation

C3.5.52 Simulating the Reproduction Process

C3.5.53 Steps in Genetic Algorithms

C3.5.54 Lamarckian Genetic Algorithm

C3.5.55 Tabu Search

C3.5.56 Tabu Algorithm

C3.5.57 Avoiding Being Trapped in a Local Minimum

C3.5.58 Better Exploration of the Space

C3.5.59 The Hybrid Docking Method

C3.6 Methods for Incorporating Flexibility

C3.6.1 Implementation of Flexibility into Docking Software

C3.6.2 Degrees of Freedom in Flexible Docking

C3.6.3 Possible Classification of Methods for Flexibility

C3.6.4 Classification of Methods C3.6.5 Incorporating Small Molecule Flexibility

Page 27 of 54



C3.6.6 Modeling Small Molecules as Flexible Entities

C3.6.7 Small Molecule Flexibility

C3.6.8 Integration of Ligand Flexibility and Protein Structure

C3.6.9 Methods for Handling Ligand Flexibility Explicitly

C3.6.10 The Ensemble Docking Method C3.6.11 Advantage of the Ensemble Docking Method

C3.6.12 The FLOG Software

C3.6.13 Problem of the Ensemble Docking Approach

C3.6.14 The Improved Ensemble Docking Method

C3.6.15 Remove Redundancy in the Rigid Fragment

C3.6.16 Remove Redundancy in the Flexible Fragment

C3.6.17 Score: Sum of Atom Interactions

C3.6.18 Step-1: Conformational Analysis

C3.6.19 Step-2: Superimposition and Positioning

C3.6.20 Step-3: Conformational Analysis

C3.6.21 Dramatic Improvement in Computing Time

C3.6.22 Efficient Treatment of Clashes

C3.6.23 Validation of the Lorber-Shoichet Method

C3.6.24 Extension to Analog Compounds

C3.6.25 The Fragmentation Docking Method

C3.6.26 Place-and-Join Algorithm

C3.6.27 Principle of the Place-and-Join Method

C3.6.28 Difficulty of the Place and Join Method

C3.6.29 Incremental-Based Methods

C3.6.30 Incremental Algorithm

C3.6.31 Stochastic Search Methods

C3.6.32 GOLD Program

C3.6.33 Incorporating Protein Flexibility

C3.6.34 Importance of Modeling Protein Flexibility

C3.6.35 Historical Note

C3.6.36 Flexibility Through Soft Scoring Functions

C3.6.37 Reduce the Importance of Steric Clashes

C3.6.38 Soft Van der Waals Repulsion Functions

C3.6.39 Decreasing Van der Waals Radii

C3.6.40 Soft Electrostatic Repulsion Potentials

C3.6.41 Soft Scoring Functions in Protein-Protein Docking

C3.6.42 Implicit Flexibility in Protein-Protein Docking

C3.6.43 Problems with Soft Scoring

C3.6.44 Soft Scoring as a First Filtering Method

C3.6.45 Protein Side-Chains Flexibility

C3.6.46 Importance of Modeling Side-Chain Mobility

C3.6.47 Determine the Optimum Combination of Side-Chains

C3.6.48 Combinatorial Explosion

C3.6.49 Side Chain Rotamer Libraries

C3.6.50 From Folding to Docking

C3.6.51 The Leach Algorithm

Page 28 of 54



C3.6.52 Generation and Minimization of Complexes

C3.6.53 Other Optimization Methods

C3.6.54 Restricting Searches and Minimizations

C3.6.55 Identify Key Residues for the Interaction

C3.6.56 Restrict the Search to Exposed Side Chains C3.6.57 Backbone and Side Chain Flexibility

C3.6.58 Conventional Methods not Adapted

C3.6.59 The Multiple Protein Structure (MPS) Approach

C3.6.60 Principle of the MPS Approach

C3.6.61 Sources of Multiple Protein Structures

C3.6.62 MPS: a Good Model for the Recognition Process

C3.6.63 How the MPS are Exploited?

C3.6.64 Successive and Independent Docking Treatments

C3.6.65 Acetylcholinesterase Example

C3.6.66 The United Protein Approach

C3.6.67 Key Concept of FlexE

C3.6.68 Remove Redundant Information

C3.6.69 FlexE: Incompatibility Graph

C3.6.70 FlexE: Search & Scoring

C3.6.71 The Average Grid Approach

C3.6.72 Single Grid Combining MPS Information

C3.6.73 Scoring Tolerance with MPS-based Grids

C3.6.74 Average Grid Approach vs. Soft Scoring

C3.6.75 Dynamic Pharmacophore-Based Approach

C3.6.76 Dynamic Pharmacophore Model for HIV-1 Integrase

C3.6.77 Hybrid Pharmacophore Models using LigandScout

C3.6.78 Domain Movements

C3.6.79 Example of Calmodulin Domain Movements

C3.6.80 Conventional Modeling Methods are not Suited

C3.6.81 Intrinsic Flexibility

C3.6.82 Hinge-Bent Movements

C3.6.83 Automated Methods for Hinge Detection

C3.6.84 Incorporating Hinge-Bent Movements in Docking

C3.6.85 Docking with Hinge-Bent Movements

C3.6.86 Ball-and-Socket Motions

C3.7 Uses of Docking in Research

C3.7.1 Computational Docking in Drug Discovery

C3.7.2 Virtual Screening

C3.7.3 Lead Hopping

C3.7.4 Increasing HTS Hit Rates

C3.7.5 Confirm Choice of Prototype Structure

C3.7.6 Manual Design of a New Scaffold

C3.7.7 New Cores from a Database of Scaffolds

C3.7.8 De Novo Design of Spacers C3.7.9 Modulating Protein-Protein Interactions

Page 29 of 54



C3.7.10 Query for 3D Database Searching

C3.7.11 Creative Molecular Design Conditions

C3.7.12 Design of Combinatorial Libraries

C3.7.13 Understanding SAR

C3.7.14 Reducing Multiple Hypotheses to a Single One C3.7.15 Series Optimization

C3.7.16 Explaining Incomprehensible Observations

C3.7.17 Identifying Incorrect Working Hypotheses

C3.7.18 Align Chemically Unrelated Molecules in 3D

C3.7.19 Improving the Solubility of a Ligand

C3.7.20 Understand the Intrinsic Limitations of a Scaffold

C3.7.21 Assessing the Potential of a Hit

C3.7.22 Elucidating Exact Mode of Action

C3.7.23 Assessing Multiple Alignment Hypotheses

C3.7.24 Molecular Mimicry

C3.7.25 Computational Validation of Hypotheses

C3.8 Docking Softwares

C3.8.1 Docking Programs

C3.8.2 Dock

C3.8.3 Autodock

C3.8.4 DockVision

C3.8.5 DockIt

C3.8.6 FlexX

C3.8.7 Ligin C3.8.8 FT-Dock

C3.8.9 GOLD

C3.8.10 GRAMM

C3.8.11 Hex

C3.8.12 eHiTS

C3.8.13 LigandFit

C3.8.14 FRED

C3.8.15 Glide

C3.8.16 Which Software is Better?

C3.9 Future and Perspectives

C3.9.1 Limitations in Computational Docking

C3.9.2 Trade Off Between Efficiency and Accuracy

C3.9.3 Screening Large Chemical Libraries

C3.9.4 A Two Step Strategy

C3.9.5 High-throughput Docking Using Grid-Computing

C3.9.6 How Does it Work?

C3.9.7 Wide In Silico Docking On Malaria (WISDOM)

C3.9.8 Enrichment Factor

C3.9.9 Current Status of the Docking Problem

Page 30 of 54



C3.9.10 The Docking Bottlenecks

C3.9.11 More Effective Scoring Functions

C3.9.12 Modeling the Solvent

C3.9.13 Validation of Scoring Functions

C3.9.14 Target Trainable Scoring Functions C3.9.15 Database of Decoys

C3.9.16 Consensus Scoring

C3.9.17 The Molecular Flexibility Challenge

C3.9.18 Developing Better Models of Flexibility

C3.9.19 Importance of Visual Docking

C3.9.20 Requirement for Manual Docking

C3.9.21 Illustration of Manual Docking

C3.9.22 Manual Docking with Solid Models

C3.9.23 Virtual Reality Docking System

C3.9.24 Example of Docking using CAVE

C3.9.25 Synergy Between Interactive & Automated Docking

C3.9.26 Interactive Computer-Guided Docking

C3.9.27 Protein-Protein Docking Benchmarks

C3.9.28 The CAPRI Competition

C3.9.29 Six Weeks for Submitting Predicted Complexes

C3.9.30 Assessment of the Predictions

C3.9.31 A New CAPRI Scoring Category

C3.9.32 CAPRI History and Experience

C3.9.33 Perspectives


C4. CASE STUDIES IN STRUCTURE-BASED DESIGN

C4.1 Case Study-1 : Phenyl Imidazoles

C4.1.1 Phenyl-Imidazoles Inhibit Cytochrome P450

C4.1.2 Simple Consideration: Shape Similarity

C4.1.3 Perhaps Binding Elements are more Complex ?

C4.1.4 The Structure-Based Answer

C4.1.5 Phenyl-Imidazole Browser

C4.1.6 Limitations of Chemical Intuition

C4.2 Case Study-2 : BACE-1 Inhibitors

C4.2.1 BACE-1 Inhibitors

C4.2.2 Screening the J&J Corporate Compound Collection

C4.2.3 Structural Determinants of the Biological Activity of 1 C4.2.4 X-ray Structure of the Complex of 1 with BACE-1

Page 31 of 54



C4.2.5 Flap Flexibility in Aspartyl Proteases

C4.2.6 Compound with Increased Folding Capability

C4.2.7 How to Gain Additional Binding

C4.2.8 Design of a More Potent Inhibitor

C4.2.9 X-Ray Structure of the Complex with 3a C4.2.10 Pharmacological Action of Compound 3a

C4.2.11 Important Structural Determinants for Binding

C4.2.12 Summary

C4.3 Case Study-3 : Factor Xa Inhibitors

C4.3.1 Therapeutic Utility of Factor Xa Inhibitors

C4.3.2 DX-9065a : a Factor Xa Inhibitor

C4.3.3 Complex Between Factor Xa and DX-9065a

C4.3.4 Analysis of the Factor Xa and DX-9065a Complex (1/4)

C4.3.5 Analysis of the Factor Xa and DX-9065a Complex (2/4) C4.3.6 Analysis of the Factor Xa and DX-9065a Complex (3/4)

C4.3.7 Analysis of the Factor Xa and DX-9065a Complex (4/4)

C4.3.8 Role of the Carboxylic Acid in Selectivity (1/3)



C4.3.11 Initial Inhibitor Design

C4.3.12 Design (step 1): Structural Moiety for Pocket S1

C4.3.13 Phenyl-Amidine Entered into the S1 Pocket

C4.3.14 Phenyl-Amidine Oriented in Lowest Energy Orientation

C4.3.15 Design (step 2): Structural Moiety for Pocket S4 C4.3.16 Phenyl Ring Introduced in Pocket S4

C4.3.17 Phenyl Substituted with an Amidine

C4.3.18 Stacking Interaction of Phenyl-Amidine with Trp-215

C4.3.19 Phenyl-Amidine Orientation

C4.3.20 Design (step 3): Design of the Spacer

C4.3.21 Phenyl-Amidine Groups in their Preferred Orientations

C4.3.22 Spacer with three Atoms

C4.3.23 Candidate Prototype in the Catalytic Site

C4.3.24 Design (step 4): Positioning of the Carboxylate

C4.3.25 Discovery of a Lead Compound C4.3.26 Optimization of the Designed Series

C4.3.27 Interaction of Compound 21 with Factor Xa

C4.3.28 Finding an Optimal Spacer

C4.4 Case Study-4 : Kinase Inhibitors

C4.4.1 Pyrrolo-Pyrimidine & Quinazoline EGF-R Inhibitors

C4.4.2 Novartis and Parke-Davis Opposite Binding Models

C4.4.3 Controversy: Novartis & Parke-Davis Binding Modes

C4.4.4 Parke-Davis Analyses

C4.4.5 Novartis Analyses

Page 32 of 54



C4.4.6 X-ray Structure of ATP Bound to a Kinase

C4.4.7 Binding Mode of ATP

C4.4.8 Binding Mode of Staurosporine

C4.4.9 Homology Model of EGF-R Catalytic Site

C4.4.10 From Staurosporine to Pyrrolo-pyrimidine C4.4.11 The Novartis Binding Mode of Pyrrolo-pyrimidine

C4.4.12 The Pyrrole Ring in the Large Pocket

C4.4.13 The Pyrrole Ring Pointing Towards the Sugar Pocket

C4.4.14 Parke-Davis Analyses the Quinazoline Scaffold

C4.4.15 Additional SAR Analyses made by Parke-Davis

C4.4.16 Parke-Davis Model of the Quinazoline Analogs

C4.4.17 Specificity Observed in EGF-R Kinase Inhibition

C4.4.18 Anilino Towards the Sugar Pocket not Reasonable

C4.4.19 Parke-Davis Model Consistent with Observed SAR

C4.4.20 Binding Mode of the Pyrrolo-Pyrimidine Series

C4.4.21 Binding Mode of the Quinazoline Series

C4.4.22 What is the Correct Solution?

C4.4.23 Ligand Observed with a Novartis Binding Mode

C4.4.24 Alignment with the Novartis Model

C4.4.25 Ligand Observed with a Parke-Davis Binding Mode

C4.4.26 Alignment with the Parke-Davis Model

C4.4.27 X-Ray Resolution of Tarceva Bound to EGF-R Kinase

C4.4.28 Conclusion

C4.5 ADDITIONAL CASE STUDIES

C4.5.1 Additional Case Studies

C5. CASE STUDIES OF DOCKING IN DRUG DISCOVERY

C5.1 Case Study 1 : Pyrimidin-4-yl-ureas for Kinase Inhibition

C5.1.1 Inhibitor Active on Several Protein Kinases

C5.1.2 Structural Determinants for the Activity

C5.1.3 Correlation with the Volume of Gate Keeper Residue

C5.1.4 Outcome of this Study

C5.2 Case Study 2 : Inhibition of CHK1

C5.2.1 The CHK1 Kinase

C5.2.2 The Indazole Series

C5.2.3 Binding Mode of the Indazole Core

C5.2.4 Binding Modes of the Potent Indazole Analog C5.2.5 Pocket may Help for Selectivity

Page 33 of 54



C5.2.6 Overlay with Other Chk1 Inhibitors

C5.2.7 Structure-Based Screening of Chk1 Inhibitors

C5.2.8 Hits Identified by Virtual Screening

C5.2.9 X-Ray Structures of Four Virtual Screening Hits

C5.2.10 Binding Modes Predicted for Other Five Hits C5.2.11 Outcome of this Study

C5.3 Case Study 3 : Thrombin Inhibitors

C5.3.1 Two Methods of Virtual Screening

C5.3.2 Combining Structure-Based and Ligand-Based VS

C5.3.3 Screening Protocol

C5.3.4 Steps of the Docking Treatment

C5.3.5 Specificity Pockets in Thrombin

C5.3.6 Development of the Hybrid Approach

C5.3.7 Inhibition Assays of Top-Scoring Compounds C5.3.8 Analysis of the Binding Mode of Compound 1

C5.3.9 Binding Mode Compared with Known Inhibitors

C5.3.10 What was Learned in this Test Study ?

C5.3.11 Analyzing Top Ranked Compounds

C5.3.12 Limitations of Scoring Functions

C5.4 Case Study 4 : Salicylamide Renin Inhibitor

C5.4.1 Search for New Scaffold in Renin Inhibition

C5.4.2 3D Analyses

C5.4.3 Preferred Location of Phenyl Ring in Pocket P3

C5.4.4 Docking Experiment

C5.4.5 Results of the Docking

C5.4.6 Search for an Optimal Spacer

C5.4.7 The Salicylamide Lead

C5.4.8 Predictions Confirmed by X-Ray Study

C5.4.9 Browser of Salicylamide Inhibitor

C5.4.10 Optimization of the Salicylamide Series

C5.4.11 Summary

C5.4.12 Lead Hopping

C5.5 Case Study 5 : Inhibition of Human Neutrophil Elastase

C5.5.1 Inhibition of Human Neutrophil Elastase

C5.5.2 Sesquiterpene Lactones

C5.5.3 Studies on 17 Sesquiterpene Lactones

C5.5.4 Docking Studies

C5.5.5 Docking Protocol

C5.5.6 Results of the Docking Studies

C5.5.7 Elucidation of the Mode of Action

C5.5.8 Docking Results of Melampolides 2 and 4 C5.5.9 Docking Results of Podachaenin 14

Page 34 of 54



C5.5.10 Docking Results of Germacranolide 8

C5.5.11 Structural Determinants for Binding to HNE

C5.5.12 Summary



C6. ANALYSES OF PROTEIN-LIGAND COMPLEXES

C6.1 Elastase Inhibitors

C6.1.1 Therapeutic Utility of Elastase Inhibitors

C6.1.2 Analysis of the HLE Active Site (1/3)



C6.1.5 Complex of MSACK with HLE

C6.1.6 Analysis of the Binding of MSACK (1/3)



C6.1.9 The Design of a New Elastase Inhibitor

C6.1.10 Complex of Inhibitor with PPE Elastase

C6.1.11 Binding of Aminopyrimidone Candidate (1/4)




C6.2 Thymidylate Synthase Inhibitors

C6.2.1 The Thymidylate Synthase Enzyme

C6.2.2 The Thymidylate Synthase Active Site

C6.2.3 The Thymidylate Synthase Catalytic Mechanism

C6.2.4 Two Possible Strategies for Inhibiting TS C6.2.5 Inhibition by Binding to the TS Substrate Site

C6.2.6 X-Ray of TS with 5-FdUMP and Cofactor

C6.2.7 Inhibition by Binding to Cofactor Site

C6.2.8 Complex of CB3717 with Thymidylate Synthase

C6.2.9 Analysis of the Binding of CB3717 (1/4)




C6.2.13 Design of a New TS Inhibitor

C6.2.14 The Quinazolinone Scaffold C6.2.15 One Atom Spacer

Page 35 of 54



C6.2.16 The Glutamic Acid Component

C6.2.17 Designed and Reference Molecules in 3D

C6.3 Inhibitors of Phospholipase A-2

C6.3.1 Phospholipase A2

C6.3.2 PLA2 Transition State Analogues

C6.3.3 Complex of an Inhibitor with PLA2

C6.3.4 Analysis of the Binding of the Inhibitor (1/4)




C6.3.8 Design of a New Class of PLA2 Inhibitors

C6.3.9 Binding of Acenaphthene with PLA2

C6.4 Thrombin Inhibitors

C6.4.1 Therapeutic Utility of Thrombin Inhibitors

C6.4.2 Examples of Thrombin Inhibitors

C6.4.3 The Catalytic Mechanism of Thrombin

C6.4.4 The "Ser-His-Asp" Catalytic Triad

C6.4.5 First Step: Transfer of H from the Ser to the His

C6.4.6 Second Step: Tetrahedral Intermediate

C6.4.7 Third Step: Binding to the Oxyanion Hole

C6.4.8 Final Step: The Peptide Bond is Cleaved

C6.4.9 The Product of the Reaction

C6.4.10 Reaction-Intermediate-Based Inhibitors

C6.4.11 Another Class of Potent Thrombin Inhibitors

C6.4.12 The Complex of Thrombin with NAPAP

C6.4.13 Analysis of the NAPAP-Thrombin Complex (1/5)





C6.4.18 The Design of a New Thrombin Inhibitor

C6.5 Human Rhinovirus Inhibitors

C6.5.1 Inhibition of Human Rhinovirus Protein

C6.5.2 The Mechanism of Action of WIN54954

C6.5.3 Complex of WIN54954 with Rhinovirus HRV14

C6.5.4 Binding of WIN54954 with Rhinovirus HRV14 (1/6)





C6.5.9 Binding of WIN54954 with Rhinovirus HRV14 (6/6) C6.5.10 Optimization of WIN54954

Page 36 of 54



C6.6 Rotamase Inhibitors

C6.6.1 Utility of Rotamase Inhibitors

C6.6.2 Complex of FK506 with FKBP

C6.6.3 Analysis of the Binding of FK506 (1/4) C6.6.4 Analysis of the Binding of FK506 (2/4)

C6.6.5 Analysis of the Binding of FK506 (3/4)

C6.6.6 Analysis of the Binding of FK506 (4/4)

C6.6.7 Design of a New Rotamase Inhibitor

C6.6.8 The Pipecolyl Inhibitor Mimics FK506

C6.6.9 Binding of the Pipecolyl Inhibitor (1/3)



C6.7 Renin Inhibitors

C6.7.1 Therapeutic Utility of Renin Inhibitors

C6.7.2 The Design of Renin Inhibitors

C6.7.3 Complex of Statine with Rhizopuspepsin

C6.7.4 Analysis of the Binding of Statine (1/3)



C6.7.7 Design of a Macrocyclic Renin Inhibitor

C6.7.8 Inaccuracies in Homology Models

C6.8 Inhibitors of PNP

C6.8.1 The Purine Nucleoside Phosphorylase Protease

C6.8.2 Therapeutic Utility of PNP Inhibitors

C6.8.3 The Complex of Guanine with PNP

C6.8.4 Analysis of the Active Site of PNP (1/2)

C6.8.5 Analysis of the Active Site of PNP (2/2)

C6.8.6 Strategy for the Design of PNP Inhibitors

C6.8.7 Design of 9-Deazaguanine Derivatives

C6.8.8 Binding of 9-Deaza-Guanine Candidate (1/3)



C6.8.11 Browser of PNP Inhibitors

C6.9 Intercalating Antibiotics

C6.9.1 Therapeutic Utility of Intercalating Agents

C6.9.2 Daunorubicin a Potent Anthracycline Antibiotic

C6.9.3 Prerequisite for Antibiotic Activity

C6.9.4 Complex of Daunorubicin with a Hexanucleotide

C6.9.5 Analysis of the Binding of Daunorubicin (1/5)

C6.9.6 Analysis of the Binding of Daunorubicin (2/5) C6.9.7 Analysis of the Binding of Daunorubicin (3/5)

Page 37 of 54





C6.9.10 Design of Novel Intercalating Agents

C6.10 Dihydrofolate Reductase Inhibitors

C6.10.1 Utility of Dihydrofolate Reductase Inhibitors

C6.10.2 Complex of Methotrexate with DHFR

C6.10.3 Binding Mode of Methotrexate with DHFR (1/5)





C6.10.8 Trimethoprim: a DHFR Inhibitor

C6.10.9 The Design of a Novel DHFR-Inhibitor

C6.10.10 Complex of Brodimoprim with DHFR C6.10.11 Binding of Brodimoprim with DHFR (1/2)

C6.10.12 Binding of Brodimoprim with DHFR (2/2)

C6.11 Sialidase Inhibitors

C6.11.1 The Sialidase Enzyme

C6.11.2 Therapeutic Utility of Sialidase Inhibitors

C6.11.3 Complex of Sialic Acid with Sialidase

C6.11.4 Analysis of Sialic Acid Binding (1/4)




C6.11.8 The Design of a Potent Sialidase Inhibitor




D. MOLECULAR BASIS OF DRUGS

D1. MOLECULAR GEOMETRY

D1.1 2D/3D

D1.1.1 Molecules Considered as 2D Structures

D1.1.2 The Three-Dimensional Shape of a Molecule

Page 38 of 54



D1.1.3 2D and 3D Representations

D1.1.4 A Molecule: An Assembly of Atoms in 3D

D1.1.5 Molecular Lego

D1.1.6 Molecular Fragments for Constructing Molecules

D1.2 Conformers

D1.2.1 A Molecule is a Flexible Entity

D1.2.2 Conformation Definition

D1.2.3 Example of Conformations of a Molecule

D1.2.4 Bioactive Conformation

D1.3 Torsion Angles

D1.3.1 Interconversion Between Conformers

D1.3.2 How Do Interconversions Occur?

D1.3.3 Definition of the Conformers of a Molecule

D1.3.4 The Torsion Angle Concept

D1.3.5 Definition of Torsion Angles

D1.3.6 Monitoring Torsion Angles

D1.3.7 Newman Projections and Torsion Angles

D1.3.8 Convention for the Sign of Torsion Angles

D1.3.9 Ring Conformations

D1.4 Conformational Complexity

D1.4.1 Rigid and Flexible Molecules D1.4.2 Codeine and Fenoxedil

D1.4.3 Monitoring Torsion Angle Combinations

D1.4.4 Conformational Explosion

D1.5 Ratio of Conformers

D1.5.1 Mixtures of Conformers

D1.5.2 Ratio of Conformers and Population

D1.6 CHAPTER QUIZZES (Available only in Academic License)

D2. MOLECULAR PROPERTIES

D2.1 Introduction

D2.1.1 Properties of a Molecule

D2.1.2 Average of a Conformational-Dependent Property

D2.1.3 Importance of the 3D Molecular Geometries

Page 39 of 54



D2.2 Biological Properties

D2.2.1 Biological Properties of Proteins

D2.2.2 Biological Properties of Chiral Analgesics

D2.3 Physical Properties

D2.3.1 Physical Properties

D2.3.2 Calculation of Other Physical Properties

D2.4 Chemical Properties

D2.4.1 Chemical Properties

D2.4.2 Enolization of Keto-3 Steroids

D2.4.3 Relative Stability of Isomers

D2.4.4 Relative Stability of the two Isomers of Trans-Octalin

D2.4.5 Geometrical Preference Explains Enolization

D2.4.6 Reactivity of Alkyl Halides

D2.4.7 SN2 Mechanism

D2.4.8 E2 Elimination Mechanism

D2.4.9 Molecular Geometries and Chemical Properties

D2.5 Many Properties

D2.5.1 Many Properties of a Molecule


D3. STEREOCHEMISTRY

D3.1 Introduction

D3.1.1 Introduction on Stereochemistry

D3.1.2 Bond Lengths D3.1.3 Bond Multiplicity

D3.1.4 Atom Size

D3.1.5 Electronegativity

D3.1.6 Hybridization

D3.1.7 Bond Angles

D3.1.8 Thorpe-Ingold Effect

D3.1.9 Torsion Angles

D3.1.10 Torsion Angle Sign Convention

D3.1.11 Examples of Torsion Angles

D3.1.12 Torsion Angle Descriptor (sp3-sp3) D3.1.13 Torsion Angle Descriptor (sp2-sp3)

Page 40 of 54



D3.2 Chirality

D3.2.1 Chirality

D3.2.2 Example 1

D3.2.3 Example 2 D3.2.4 Chirality Descriptor: Optical Rotation

D3.2.5 Chirality Nomenclature

D3.2.6 The Order of Priority (1/5)





D3.2.11 Examples of R/S Assignments (1/4)




D3.2.15 The Newman Projection

D3.2.16 The Fischer Projection (1/3)



D3.2.19 Chirality: D/L

D3.2.20 D-alanine

D3.2.21 L-alanine

D3.2.22 Chirality: Erythro/Threo

D3.2.23 Threo

D3.2.24 Erythro

D3.2.25 Other Examples of Chiral Molecules: Example 1

D3.2.26 Example 2 of Chiral Molecule





D3.3 Double Bonds

D3.3.1 Cis-Trans Stereochemistry of Double Bonds D3.3.2 E/Z Stereochemistry of Double Bonds

D3.3.3 s-cis/s-trans Conformations

D3.3.4 Re/Si Nomenclature of the Faces of Double Bonds

D3.4 Rings

D3.4.1 Rings

D3.4.2 Chair

D3.4.3 Boat

D3.4.4 Twist Boat

D3.4.5 Crown

Page 41 of 54



D3.4.6 Rings: Axial and Equatorial Orientations

D3.5 Symmetry

D3.5.1 Introduction on Symmetry Operations

D3.5.2 Symmetry C2

D3.5.3 Symmetry C3

D3.5.4 Symmetry Sigma

D3.5.5 Inversion (i)

D3.5.6 Example of Inversion

D3.5.7 Rotatory Reflection (Sn)


D4. MOLECULAR ENERGIES

D4.1 Introduction

D4.1.1 Internal Energy of a Molecule

D4.1.2 Internal Energy Associated to a Conformation

D4.1.3 Transition State

D4.1.4 Potential Surface

D4.1.5 Thermodynamics & Kinetics

D4.2 Thermodynamics

D4.2.1 Thermodynamics: Conformer Populations

D4.2.2 Thermodynamics: Boltzmann Equation

D4.2.3 Boltzmann Population Analysis for Two Conformers

D4.2.4 Boltzmann Population Analysis for 3 Conformers

D4.2.5 Thermodynamics: Cyclohexane Example

D4.2.6 Populations of Twisted-Boat and Chair Conformers

D4.2.7 Thermodynamics: Methylcyclohexane Example

D4.3 Kinetics

D4.3.1 Kinetics

D4.3.2 Kinetics: Arrhenius Equation

D4.3.3 Kinetics: Arrhenius Graph

D4.3.4 Kinetics Ethane Example

D4.3.5 Torsional Barrier in Ethane

D4.3.6 Kinetics Cyclohexane Example

D4.3.7 Interconversion Barrier in Cyclohexane

D4.3.8 Kinetics Amide Bond Example D4.3.9 Amide Barrier Crossed Every 10 Seconds

Page 42 of 54



D4.4 Molecular Modeling

D4.4.1 Molecular Modeling

D4.4.2 Example of Kinetic or Thermodynamic Control

D4.4.3 Interconversion Between the Two Forms D4.4.4 Lowering the Energy of the Transition State

D4.4.5 Interconversion Between the Two Forms

D4.4.6 Raising the Energy of the Transition State

D4.4.7 Interconversion Between the Two Forms

D4.4.8 Modifying Conformers Populations

D4.4.9 Repulsions More Important in the Boat Form

D4.4.10 Tropane is Found Only in a Chair Conformation

D4.4.11 Example of Atropisomerism

D4.4.12 Molecular Energies: The Key of Molecular Modeling

D4.5 Modeling in Drug Design

D4.5.1 Molecular Modeling in Drug Design

D4.5.2 Importance of Energies: the Morphinan Example

D4.5.3 Morphinan and D-nor Morphinan Alignment

D4.5.4 Conformational Analysis of Morphinan

D4.5.5 Conformational Analysis of D-nor Morphinan

D4.5.6 A Rationale for Explaining the Activities Observed

D4.5.7 Morphinan: Validation and Design

D4.5.8 Preferred Conformer of Active Enantiomer

D4.5.9 Preferred Conformer of Inactive Enantiomer D4.5.10 Restoring Activities to the Inactive Analog?

D4.5.11 Morphinan Browser

D4.5.12 What We Can Learn From The Morphinan Example

D4.6 How to Calculate Energies

D4.6.1 The Need of Tools for Calculating Energies

D4.6.2 Two Methods for Calculating Energies

D4.7 Quantum Mechanics

D4.7.1 Calculation of Energies by the Schrodinger Equation

D4.7.2 Ab-Initio and Semi-empirical Calculations

D4.7.3 Calculation of Energies

D4.7.4 The Density Function Theory

D4.7.5 The Choice of a Method

D4.8 Molecular Mechanics

D4.8.1 Molecular Mechanics

D4.8.2 Force-Field

D4.8.3 Force Field Components

D4.8.4 Bond Lengths: Stretching Contributions

Page 43 of 54



D4.8.5 Function

D4.8.6 Examples of Elementary Stretching Contributions

D4.8.7 Bond Angles: Bending Contributions

D4.8.8 Function

D4.8.9 Examples of Elementary Bending Contributions D4.8.10 Torsion Angles: Torsional Contributions

D4.8.11 Function

D4.8.12 Examples of Elementary Torsional Contributions

D4.8.13 Van der Waals Interactions

D4.8.14 Function

D4.8.15 Examples of Elementary Van der Waals

D4.8.16 Electrostatic Dipolar Contributions

D4.8.17 Function

D4.8.18 Examples of Elementary Electrostatic Contributions

D4.8.19 Hydrogen Bond Energy Contributions

D4.8.20 Function

D4.8.21 Examples of Elementary Hydrogen Bond Contributions

D4.8.22 Total Energy in a Force Field Calculation

D4.8.23 Main Force Fields

D4.8.24 What One Should Remember

D4.8.25 Relative Energies


D5. CONFORMATIONAL ANALYSIS

D5.1 Introduction

D5.1.1 Geometries, Energies and Conformational Analysis

D5.1.2 Energy Profile: a Global Information

D5.1.3 Definition of Conformational Analysis

D5.2 Potential Surface

D5.2.1 Conformational Potential Surface: One Rotation

D5.2.2 Conformational Potential Surface: Two Rotations

D5.2.3 Energy Profile Viewed from the Top

D5.2.4 Energy Profile Viewed as Contour Lines

D5.2.5 Conformational Potential Surface

D5.2.6 Special Forms

D5.2.7 Interconversion Between Conformers

D5.2.8 Energy Barriers

D5.2.9 Interconversion Pathway

Page 44 of 54



D5.3 Conformational Analysis

D5.3.1 Conformational Analysis Principles

D5.3.2 Systematic Scanning of All Potential Surfaces

D5.3.3 Systematic Scanning is Time Consuming D5.3.4 How to Reduce Conformational Search?

D5.3.5 One Conformer Represents a Whole Family

D5.3.6 Working with a Set of Representative Conformers

D5.3.7 Sildenafil Example

D5.3.8 Family Representatives: Small Rings

D5.3.9 Family Representatives: Acyclic Bonds

D5.3.10 Consequence: Minimization Treatments

D5.3.11 Example: Analysis of Elementary Fragments

D5.3.12 Example: Generation of Representative Conformers

D5.3.13 Example: Results of Conformational Analysis

D5.3.14 Conformational Analysis Principles: Summary

D5.4 Minimizations

D5.4.1 Definition of the Minimization of a Conformer

D5.4.2 Improved Geometries and Good Energies

D5.4.3 The Minimization Treatment

D5.4.4 How Does Minimization Works?

D5.4.5 Minimization Methods

D5.4.6 Many Variables Are Minimized

D5.4.7 Minimization is a Time-Consuming Treatment

D5.5 Examples of Minimization

D5.5.1 Minimization with Stretching Strain

D5.5.2 Minimization with Bending Strain

D5.5.3 Minimization with Torsional Strain

D5.5.4 Minimization with Van der Waals Strain

D5.5.5 Minimization with Electrostatic Component

D5.5.6 Minimization with Hydrogen Bond Component

D5.5.7 Typical Minimization Example

D5.5.8 Distribution of Energy Strain

D5.6 Conformational Analysis in Drug Design

D5.6.1 Conformational Analysis in Drug Design

D5.6.2 Energy of the Bioactive Form

D5.6.3 Low Energy of the Bioactive Conformation

D5.6.4 Geometry of the Bioactive Conformation

D5.6.5 The Experienced Molecular Modeler

D5.6.6 Common Errors Made with Minimization

D5.6.7 Example 1 D5.6.8 Example 2

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D5.7 Molecular Dynamics

D5.7.1 Molecular Dynamics

D5.7.2 Theoretical Basis of Molecular Dynamic Calculations

D5.7.3 Local Minima and Global Minimum D5.7.4 Simulated Annealing, a Special Type of Dynamics

D5.7.5 Coherency of Molecular Motions

D5.7.6 A Typical Molecular Dynamics Run


D6. MOLECULAR GRAPHICS

D6.1 Introduction

D6.1.1 Importance of Molecular Graphics

D6.1.2 Almost Science Fiction

D6.1.3 History of Molecular Visualizations

D6.1.4 1975-1978

D6.1.5 1978-1980

D6.1.6 1980-1995

D6.1.7 1995-now

D6.1.8 Commercially Available Molecular Kits

D6.1.9 Progress in Graphical Hardware and Algorithms

D6.1.10 Algorithm 1

D6.1.11 Algorithm 2

D6.1.12 Molecular Graphics Functions

D6.2 3D Perception

D6.2.1 The Perception of the Third Dimension

D6.2.2 From 3D Coordinates to Screen Coordinates

D6.2.3 2D Projection is Not Sufficient D6.2.4 Real Time Manipulation

D6.2.5 Depth Cueing

D6.2.6 Perspective

D6.2.7 Stereo

D6.2.8 Hardware Stereo

D6.3 Visualization

D6.3.1 3D Representation of Small Molecules

D6.3.2 Line

D6.3.3 Stick

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D6.3.4 Ball & Stick

D6.3.5 CPK

D6.3.6 Quality of Rendering

D6.3.7 Atomic Color-Code Convention

D6.3.8 Coloring Molecules or Sets of Atoms D6.3.9 By Atom-type

D6.3.10 By Molecule

D6.3.11 By Color

D6.3.12 By Properties

D6.3.13 Labeling Functionalities

D6.3.14 Atom Labels

D6.3.15 Atom Numbering

D6.3.16 Proteins Representation

D6.3.17 Carbon Alpha

D6.3.18 Ribbon Representation

D6.3.19 Ribbon Types

D6.3.20 Visualization of Protein Properties

D6.4 Editing & Manipulation

D6.4.1 Structure Manipulation & Editing

D6.4.2 Add Atoms Function

D6.4.3 Delete Atoms Function

D6.4.4 Fuse Atoms Function

D6.4.5 Connect atoms Function

D6.4.6 3D Molecular Constructions D6.4.7 Real-Time Rotations, Translations and Zoom

D6.4.8 Translations

D6.4.9 Rotations

D6.4.10 Zoom

D6.4.11 Control of Torsion Angles

D6.4.12 Slab and Clip

D6.5 Surfaces & Volumes

D6.5.1 Concept and Definition of Molecular Surfaces

D6.5.2 Van der Waals

D6.5.3 Solvent

D6.5.4 Connolly

D6.5.5 Surface Types

D6.5.6 Normal

D6.5.7 Transparent

D6.5.8 Dots

D6.5.9 Visualization of Properties on Molecular Surfaces

D6.5.10 Color Coded

D6.5.11 Visualization of Properties on Molecular Surfaces

D6.5.12 The Visualization of Volumes

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D6.5.13 Mathematical Boolean Operations with Volumes

D6.6 Visualizing Interactions

D6.6.1 Visualization of Hydrogen Bonds

D6.6.2 Visualization of Molecular Bumps

D6.6.3 Surface Representations for Bump Analyses

D6.6.4 Complementary Surface Properties

D6.6.5 Electrostatic Potentials

D6.6.6 Lipophilicity Potentials

D6.6.7 Visualization of Intramolecular Interaction

D6.6.8 Schematic Complex Interaction

D6.6.9 Visualization of a Complex Cavity

D6.6.10 Overview of the Entire Complex

D6.6.11 Results of Quantum Mechanical Calculations


D7. SELECTED EXAMPLES IN 3D ANALYSIS

D7.1 Conformational Analysis

D7.1.1 Ethane D7.1.2 n-Butane

D7.1.3 1-Butene

D7.1.4 Butadiene

D7.1.5 Amide

D7.1.6 Cyclohexane

D7.2 Conjugated Systems

D7.2.1 Butadiene

D7.2.2 Pentenone

D7.2.3 Dipyrrole

D7.2.4 Biphenyl

D7.2.5 Atropisomerism of Biphenyls

D7.2.6 Binaphthyl

D7.3 Aromatic Systems

D7.3.1 Planarity of Polyaromatic Systems

D7.3.2 Distorted Naphthalene

D7.3.3 Annelated Polyaromatic Benzenes

D7.3.4 Fusing Another Ring D7.3.5 Fusing Again Another Ring

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D7.3.6 Continue to Fuse Additional Rings

D7.4 Cyclic Systems

D7.4.1 Why Substituents Prefer to be Equatorial?

D7.4.2 Mono-Substituted Cyclohexanes

D7.4.3 t-Bu

D7.4.4 Phenyl

D7.4.5 Methyl

D7.4.6 Hydroxy

D7.4.7 Example of Preferred Axial Conformer

D7.4.8 Di-Methyl-1,2-Cyclohexane

D7.4.9 Trans

D7.4.10 Cis


D7.4.12 Trans D7.4.13 Cis


D7.4.15 Trans

D7.4.16 Cis

D7.4.17 Trans 1,3-Di-t-Butyl-Cyclohexane

D7.4.18 Chloro-2 Cyclohexanone

D7.5 Other Systems

D7.5.1 Decalins

D7.5.2 Cis-decalin

D7.5.3 Methyl-Cis-decalin

D7.5.4 Trans-decalin

D7.5.5 Interactions of Aromatic Rings

D7.5.6 Interactions Revealed by X-Ray Crystallography

D7.5.7 Two Major Types of Aromatic Interactions

D7.5.8 Overview of Possible Interactions

D7.5.9 Geometry of Ester Groups

D7.5.10 Cyclic Ester

D7.5.11 Geometry of Amide Groups

D7.5.12 Substituted Amide

D7.5.13 Cyclic Amide

E. GENERAL TOPICS

E1. GENERAL INTRODUCTION TO DRUGS

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E1.1 What is a Drug

E1.1.1 What is a Drug?

E1.1.2 Improvement of Life Expectancy

E1.1.3 Origin of Active Principles E1.1.4 Drug Formulation

E1.1.5 Multiple Names of Drugs

E1.1.6 Example of Multiple Names of a Drug

E1.1.7 Requirements for the Ideal Drug

E1.1.8 Safety

E1.1.9 Properties

E1.1.10 Compliance

E1.1.11 Pharmacology

E1.1.12 Metabolism and ADME

E1.1.13 Side Effects and Toxicity

E1.2 The Pharmaceutical Industry

E1.2.1 Drug Discovery and Development, a Long Process

E1.2.2 Drug Discovery and Drug Development

E1.2.3 One Million Studied for One to Reach the Market

E1.2.4 Pharmaceutical R&D, a High-Risk Undertaking

E1.2.5 The Time of Developing a New Drug

E1.2.6 The Cost of Developing a New Drug

E1.2.7 Reasons for Termination of Development

E1.3 Industry Focus Area

E1.3.1 Industry Focus Areas and Examples of Useful Drugs

E1.3.2 Cardiovascular System (CVS)

E1.3.3 Antiarrhytmics

E1.3.4 Antihypertensive

E1.3.5 Vasodilatation

E1.3.6 Anticoagulants

E1.3.7 Antihyperlipidemic

E1.3.8 Anti-infective Agents

E1.3.9 Antibiotics

E1.3.10 Antiviral

E1.3.11 Antifungals

E1.3.12 Antimalarias

E1.3.13 Antituberculosis

E1.3.14 Central Nervous System (CNS) Agents

E1.3.15 Antipsychotics

E1.3.16 Cholinergic

E1.3.17 Parkinsonians

E1.3.18 Anticonvulsants

E1.3.19 Antidepressants

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E1.3.20 Tranquilizers

E1.3.21 Adrenergic

E1.3.22 Gastro-Intestinal Drugs

E1.3.23 Antidiarrhea

E1.3.24 Laxatives E1.3.25 Anti-emetics

E1.3.26 Anti-Ulcers

E1.3.27 Anti-Neoplastic (Anti Cancer) Agents

E1.3.28 Alkylating

E1.3.29 Antimetabolites

E1.3.30 Anti-neoplastic

E1.3.31 Immunosuppressants

E1.3.32 Taxoids

E1.3.33 Respiratory Agents

E1.3.34 Bronchodilators

E1.3.35 Antihistamines

E1.3.36 Antitussives

E1.3.37 Anti-Rheumatism and Pain Agents

E1.3.38 Anti-inflammatory

E1.3.39 Anti-rheumatism

E1.3.40 Analgesics

E1.3.41 Anesthetics

E1.3.42 Agents Against Metabolic Disorders

E1.3.43 Antidiabetic

E1.3.44 Antiosteoporotic

E1.3.45 Thyroid Hormone

E1.3.46 Steroids

E1.3.47 Diagnostic Agents

E1.4 CHAPTER QUIZZES (Available only in Academic License)

E2. DRUG DISCOVERY

E2.1 Introduction

E2.1.1 Drug Discovery

E2.1.2 Target Identification

E2.1.3 Lead Discovery

E2.1.4 Lead Optimization

E2.1.5 Disciplines Involved in Drug Discovery

E2.2 Discovery Methods

E2.2.1 How Are Leads Discovered?

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E2.3 Serendipity

E2.3.1 The Serendipitous Pathway

E2.3.2 Penicillin

E2.3.3 Aspirin E2.3.4 Glafenine

E2.3.5 Furosemide

E2.3.6 Chlorpromazine

E2.3.7 Cyclosporin A

E2.3.8 Viagra

E2.4 Screening

E2.4.1 The Screening Pathway

E2.4.2 Example of Molecules Discovered by Screening

E2.5 Chemical Modification

E2.5.1 The Chemical Modification Pathway

E2.5.2 Tagamet

E2.5.3 Beta-Blockers

E2.5.4 Limitation of the Chemical Modification Approach

E2.6 Rational Drug Design

E2.6.1 The Rational Pathway

E2.6.2 Captopril Story E2.6.3 Cimetidine Story

E2.6.4 The Histamine Action

E2.6.5 Screening Molecules Related to Histamine

E2.6.6 The Guanidine Analog

E2.6.7 The Burimamide Lead

E2.6.8 The Metiamide Molecule

E2.6.9 The Cimetidine Drug

E2.6.10 The Ranitidine Drug

E2.6.11 Advantages of Rational Drug Design

E2.7 Chemistry in Drug Discovery

E2.7.1 Chemistry in Drug Discovery

E2.7.2 Synthesis of Complicated Molecules

E2.7.3 Penicillin

E2.7.4 Taxol

E2.7.5 Steroid

E2.7.6 Three Methods in Synthetic Chemistry

E2.7.7 Classical

E2.7.8 Parallel

E2.7.9 Combinatorial

E2.7.10 Chemistry in Lead Discovery

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E2.7.11 Protein Kinase Example

E2.7.12 Chemistry in Lead Optimization

E2.7.13 Optimization of the Gleevec Series

E2.7.14 CCK-A Receptor Antagonist Example

E2.7.15 Chemistry in Drug Development

E2.8 Patents

E2.8.1 Intellectual Property and Patents

E2.8.2 What Can be Patented?

E2.8.3 Requirements for Patentability

E2.8.4 Lifetime of a Patent

E2.8.5 Effective Patent Lifetime

E2.8.6 Patent Protection


E3. DRUG DEVELOPMENT

E3.1 Introduction

E3.1.1 Drug Development

E3.1.2 Pipe-Line of Development E3.1.3 Pre-Clinical Development

E3.1.4 Clinical Development

E3.1.5 Post-marketing Surveillance

E3.1.6 Disciplines Involved in Drug Development

E3.1.7 Effective Teams: Interactivity and Cooperativity

E3.2 The Pre-Clinical Studies

E3.2.1 Pre-Clinical Studies

E3.2.2 Chemical Development

E3.2.3 Pharmacological Studies

E3.2.4 Drug Metabolism and Pharmacokinetics

E3.2.5 Toxicology Studies

E3.2.6 Acute Toxicity

E3.2.7 Safety Studies

E3.2.8 Carcinogenicity

E3.2.9 Mutagenicity

E3.2.10 Reproduction Studies

E3.2.11 Formulation Development

E3.2.12 Stability Tests

E3.2.13 Disciplines Involved in Pre-Clinical Development

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E3.3 Clinical Development

E3.3.1 Introduction on Clinical Trials

E3.3.2 Clinical Trials Phase 1

E3.3.3 Clinical Trials Phase 2 E3.3.4 Clinical Trials Phase 3

E3.3.5 Clinical Trials Phase 4

E3.3.6 Disciplines Involved in Drug Development

E3.4 Regulatory Affairs

E3.4.1 The Role of the Food and Drug Administration (FDA)

E3.4.2 The Investigational New Drug Application (IND)

E3.4.3 The New Drug Application (NDA)

E3.4.4 The Regulatory Approval Process


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