Drug Discovery Process Quiz

Contact Information

• Professor: Dr. Andrzej Bąk
• Email: [email protected], [email protected]
• Phone: 32 359 11 97
• Address: UI. Szkolna 9, Katowice, room 40, I floor

In-silico Medicine Outline

• Data, informatics, knowledge in medicine
• Coding of drug structure – molecular editors
• Receptors as molecular targets
• Molecular descriptors – lipophilicity
• Computer Assisted Molecular Design (CAMD) – QSAR modeling
• Artificial intelligence in medicine (AI) – essentials of neural networks (NN)
• Basics of biostatistics
• Data preprocessing
• Basic procedures of data modeling
• Essential techniques of data visualization and data grouping

Literature of Subject

• Edited by Thomas Engel and Johann Gasteiger
• Chemoinformatics: Basic Concepts and Methods
• Textbook of Medical Statistics (for Medical Students, editors Xiuhua Guo and Fuzhong Xue)
• Introduction to Medicinal Chemistry (seventh edition, by Graham L. Patrick)
• Wold Wide Web database

Computer Assisted Drug Design (CADD)

• AIM – production of substances that act in the human body →rational drug production
• Molecular production of properties → drug modeling

Medicine

• Medicine – the art of human treatment/healing
• Pharmacy/Pharmacology/Medicinal Chemistry: The science of molecules and their transformations
• Drug Molecule: A molecule with medicinal properties
• Paracelsus XVI century quote – “All things are poison, and nothing is without poison, only the dose permits something not be poisonous.”

History of Drug Discovery

• 5100 years ago – China: Chiang Shan herbs (fever), Ma Huang (anti-cough drug)
• 3 w.p.n.e.: Extract from poppy grain (pain-killers), scopolamine (truth serum), Belladona (atropine)
• Inca nations: coca (energizing)
• India: rezorcinol (high blood pressure)
• 1633: Calancha monk – extract from quina tree (drug to malaria)
• 1928: Alexander Fleming – penicillin (antibiotics, antybiotos)
• “Sometimes you find what you are not looking for”
• “The Nature produced penicilline, I have just discovered it”

Accident = Serendipity - "lucky shot"

• Engineer in the military health service
• Study of biological discharge to kill bacteria
• Lisozyme (1921) - first antibiotics
• Penicillin (1928): fungus (Penicillium notatum) → Staphylococcus
• 1941: Florey and Chain – experiment on mice (infected with streptococcus)
• 1941: Albert Aleksander – patient 0 (experiment with thorn of rose) and patient survival despite death
• Karl Folkers (Merk) – specification of Penicillin structure

Medicinal Product

• Directive 2001/83/EC of the European Parliament and the Council (November 6, 2001) → any substance or mixture of substances intended for diseases in humans or animals, and substance/mixture of substances used for diagnosis or restoring, correcting or modifying physiological functions

Classification of Drug Molecules

• Natural compounds - materials from plants and animals (e.g. vitamins, hormones, amino acids, antibiotics, alkaloids, glycosides)
• Synthesis compounds - pure synthesis or synthesis from naturally occurring compounds (e.g. morphine, atropine, steroids, cocaine
• Semi-synthesis compounds - compounds that cannot be purely synthesized or isolated from natural sources inexpensively thus using natural intermediates for desired product (e.g. semi-synthetic penicillins)

Data Exploration

• Graph of compounds published in CAS, rising exponentially since 1965
• Graph relating number of new drugs & R&D spending exhibiting a negative trend correlating to log-scale graph exhibiting an exponential negative trend

Why new drugs are so expensive?

• Absorption
• Distribution
• Metabolism
• Excretion
• Toxicity
• ADMET

Drug Analysis

• 2D → 3D molecular generators (CORINA, MOPAC, BABEL, SYBYL, MOE, etc.) → input data
• Pre-processing/descriptor selection (scaling, centering, standardization)
• Structure coding
• Statistical methods
• Artificial intelligence (neural networks)
• Data analysis

Chemoinformatics of Drugs

• Molecule
• Structure
• Descriptors
• Data Analysis
• Database Exploration
• Measures

From data to Drugs

• Chemoinformatics (pharmacophore, serendipity)
• Bioinformatics (de novo)
• Similarity searching
• Molecular docking

Two Directions of Drug Design

• Ligand-based Drug Discovery (RI): ligand collection → maps of interactions → reverse image of target structure
• CC&HTS → lead structure → optimization → clinical studies
• Structure-based Drug Discovery (RD): searching for drugs of low molecular weight as complementary fulfillment of target molecule
• Identification of target → preparation of target molecule → docking → assessment of bioactivity

Two Directions of CAMD Study

• Preparation of receptor and ligand
• Structural and physicochemical filters
• Drug likeness
• Docking
• Ligand-receptor geometry
• Post processing
• Scoring/Rescoring
• Variable selection
• Activity prediction
• Model assessment
• Pose evaluation
• ADMET
• Chemical stability

Drug → from idea to implementation

• Disease specification → Optimization of Lead
• Determination of interaction place → Identifying pharmacophore
• Selection of biological test → Identification of Lead

• Metabolic and toxic studies → Clinical studies → Final Drug Confirmation

Directions of future evolution in drug design and medicine

Searching for synthetic analogues of natural products NP → Searching for leading structures of selected biological targets → Personalized Drug Design

Virtual Drug Coding Problems

• Storing molecular structure in a database
• Searching structures in a database
• Deriving structures from measured data
• Predicting properties for a structure
• Treating chemical reactions and synthesis planning

Chemical presentation of drugs.

• 3D model
• Model 2D
• Nomenclature (Chemical names)
• Content (Chemical structures)
• Information structure

Racemic Mixtures Stereochemistry

• Oral medication for cancers (e.g. multiple myeloma) and skin disorders
• Human teratogen with life-threatening birth defects during pregnancy
• Skeletal deformities (amelia, absence of legs/arms); phocomelia (limb malformation)
• (R)-enantiomer → sedative effect and (S)-enantiomer → embryo-toxic and teratogenic effect.
• Enantiomers can racemize to each other in vivo

Linear notation in drug coding

• Trivial name: Phenylalanine
• IUPAC name: 2-amino-3-phenylpropanoic acid
• WLN: VQYZ1R
• ROSDAL: 10-2=30,2-4-5N,4-6-7=-12-7
• Smiles: NC(Cc1ccccc1)C(O)=O
• SLN: C[1]H:CH:CH:CH:CH:C(:@1)CH2CH(NH2)C(=O)OH

Molecular surfaces in drug design

• Van der Waals' surface
• Connolly's surface

Graph theory

• L. Euler (1736) → Königsberg’s seven bridges problem
• Molecular graphs G={V,E}
  • V = vertexes (atoms), E = edges (bonds)
• Drug – undirected coherent graph

Coding of Drug Constitution

• Neighboring matrix/bonding matrix
• Connection table CT

Drug in MDL Molfile format

• Compound information and properties, formatted as a text file for importing and using chemical compounds

Molecular Editors

• Molecule editor
• Viewer
• Connection table

Survey of molecular editors

• Various software tools (Chem3D, ChemDraw, ACD/ChemSketch, ISIS/Draw, etc.) for molecular structure drawing, analysis, and manipulation

SMILES (Simplified Molecular Input Line Entry System)

• Entering molecular structure using a set of rules;
• Generating unique representations

Statistical Metrics

• Arithmetic mean
• Geometric mean
• Median
• Standard deviation
• Variance
• Kurtosis
• Skewness

Basic parameters of statistical data

• Variance and standard deviation

Scaling, centering, standardization

• Formulas for scaling, centering, and standardization of data

Estimation in Statistics

• Estimation of the mean of a distribution
• Point estimation
• Interval estimation (t distribution)

Hypothesis Testing

• One-sample t-test for the mean of normal distribution with unknown variance

Two-Sample t Test for independent samples with equal variances

• Test statistic formula

Types of Statistics

• Descriptive statistics: Continuous, discrete, proportions, central tendency, dispersion
• Inferential statistics: Estimation, hypothesis testing, p-values, confidence intervals

Planning/Design of the Study

• Primary question
• Sample size
• Participant selection
• Group assignment

Biomedical research

• Relationship between patient characteristics/treatments and a health condition
• Establishing cause and effect

Errors

• Nonsampling error
• Sampling error:
  • Error of measurement
  • Error of non-response
  • Error of misinterpretation
  • Error of calculation or arithmetical error
  • Error of sampling bias

Statistical Community

• One-dimensional versus Multidimensional
• Static versus Dynamic
• Relatively homogeneous versus Heterogeneous
• Qualitative versus Quantitative

Populations and Samples

• Population
• Sample
• Representative sample
• Random sample

Regression and Correlation Methods

• Relate a normally distributed output variable
• Types of correlation: Linear positive, linear negative, non-linear
• Pearson linear correlation coefficient

ANOVA

• Hypotheses for comparing three+ groups
• ANOVA formula/calculation

Telemedicine

• Use of information and communication technologies to transfer medical data;
• Types: Teleoperations, telemonitoring, teledagnosis, teleradiology, telecardiology;
• Models: Direct, intermediate
• Benefits, barriers, needed requirements

Biomolecules

• Primary sequence representation of biomolecules

Molecular Descriptors

• Representation of molecular properties into numbers
• Descriptor dimensionality (1D, 2D, 3D)

Lipophilicity

• Importance in medicinal chemistry
• Methods for measuring lipophilicity

Pharmacophore concept

• A collection of steric and electronic features
• Drug-receptor interactions

QSAR

• Quantitative structure-activity relationship analysis to predict drug activity

QSAR - Data Analysis Techniques

• Approaches for analyzing data (artificial intelligence, neural networks, Hebb rule, Kohonen neural network)

Test your knowledge of the drug discovery process with this quiz. It covers various aspects such as drug design techniques, docking processes, and statistical analysis related to sample size. Understand key terminologies like SAR, ADMET, and pharmacophore identification through this engaging quiz.