BIOC3010: Bioinformatics - Revision lecture Dr. Andrew C.R. Martin

Data Creation Analysis Prediction Presentation Searching Organizing Sequences DNA Protein Computers Structures

Introductionary Lecture

Introduction helps you create data example of fragment assembly Bioinformatics…

Introduction provides tools to store and search data databases and databanks primary/secondary/composite/gateways Bioinformatics…

Introduction allows you to make predictions prediction techniques –moving windows, –computer learning Bioinformatics…

Introduction allows you to create 3D models separate lecture Bioinformatics…

Introduction allows transfer of annotations homologous proteins likely to perform similar functions Bioinformatics…

Introduction Annotations… Pre-genome world Post-genome world Annotations will change

Genomes and Gene Prediction Lectures

Genome structure C-paradox Compare prokaryotes and eukaryotes Complexity of eukaryotes: –Introns/exons, –Repeated sequences, –Transposable elements, –Pseudogenes Problems introduced by these...

ORF Scanning in Eukaryotes exonintron exon 5’ 3’ Intron/exon splice sites

Finding Genes in Genomic DNA Ab initio methods Similarity based methods Integrated approaches TRY4

Prediction accuracy Nucleotide level Exon level Measures for assessment

Computing Lecture

Computers

Operating systems What is an operating system? Examples of operating systems Choice of operating systems for different areas of research

Computers and computer science Data structures and information retrieval –Relational databases –Design of databases to reduce errors in data Simple examples of SQL and structuring data into tables Must handle:

Computers and computer science Algorithms: how to solve a problem –Defined an algorithm –Looked at an example Must handle:

Computers and computer science Data mining and machine learning –Extract patterns, etc from data –Computer software which learns from examples and is then able to make predictions Must handle:

Comparative Modelling Lecture

What is comparative modelling? Build a three-dimensional (3D) model of a protein... …based on known structure of a (generally) homologous protein sequence "Homology Modelling" is misleading: –fold recognition and threading allow recognition of non-homologous sequences which adopt the same fold

Stages in CM 1. Identify templates (or ‘parents’)‏ 2. Align the target sequence with the parent(s), 3. Find: structurally conserved regions structurally variable regions 4. Inherit the SCRs from the parent(s)‏ 5. Build the SVRs 6. Build the sidechains 7. Refine the model 8. Evaluate errors in the model

Correct alignment is the structural alignment. Align target with parent(s)‏ Structure of Target Optimal alignment based on Structural Equivalents Structure of Parent We don’t have this! Guess structural alignment from sequence alignment

An example MLSA

Sequence alignment quality

Assessing the model Ideal is to compare the model with the true target structure - 4-6Å; 2Å; 0.5Å

Model quality The main factors are:  The sequence identity with the primary parent  The number and size of indels  The quality of the alignment  The amount of change which has been necessary to the parent(s) to create the model.

Summary of CASP2 results CASP8 ran summer

Medical Applications Lecture

Mutations, Alleles & Polymorphisms Mutation: –any change in DNA sequence Allele: –alternative form of a genetic locus; one inherited from each parent –e.g. eye colour locus - brown and blue alleles Polymorphism: –genetic variation present in >= 1% of a normal population

How are SNPs useful? Understanding evolution –Some alleles may be advantageous in one environment, but disadvantageous in another DNA fingerprinting Markers to map traits –diseases, characteristics Pharmacogenomics –genotype-specific medications

Drug responses Drug efficacy may be affected by: transporters metabolism receptors signalling pathways, etc.

Potentially lethal SNPs First described ~2000 years ago “What is food to some men may be fierce poison to others” Lucretius Caro

Protein Sequence DNA Sequence Protein StructureProtein Function Mutation Altered Sequence Altered Structure Altered Function Understand Structure & Function Restore Structure Restored Function Design Drugs

Looked at p53... Local level - effects of mutations General classes –Functional –Fold Preventing –Destabilizing Types of mutations

How human? Chimeric: 67% human Humanized: 90% human Mouse: 0% human

Antibody Humanization

Summary –Diagnosis of disease –Prediction of disease risk –Prognosis –Customized response to disease –Identifying drug targets - treatments –Engineering of proteins for therapy

Docking and Drug Design Lecture

Van der Waals forces Electrostatic (Salt bridge) Interaction Hydrogen bonds Hydrophobic bonding Surface complementarity

Six degrees of freedom - protein and ligand both treated as rigid - 3 rotations / 3 translations Docking methods - rigid body Just like docking the space shuttle with a satellite Image from NASA

Treat receptor as static / ligand as flexible Dock ligand into binding pocket - generate large number of possible orientations Evaluate and select by energy function Docking methods - flexible ligand

Ligand Matching Match sphere centres against ligand atoms Find possible ligand orientations Often >10,000 orientations possible Find the transformation (rotation + translation) to maximize sphere matching DOCK

Virtual Screening Docking can be used for virtual screening Scan a library of potential drug molecules Identify leads

LUDI (InsightII) - find fragments that can bind GRID - uses molecular mechanics potential to find interaction sites for probe groups X-site - uses an empirical potential to find interaction sites for probe groups De Novo Drug Design

Stupid mistakes... Don't confuse secondary databases with secondary structure! Ensure you know the difference between SCOP/PFam functional domains and CATH structural domains

Summary Find pockets Principles for docking - complementarity Docking –rigid body / ligand flexibility Virtual screening Identifying probe interaction sites –build ligands de novo