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CS 177 Introduction to Bioinformatics Fall 2004 • Instructor: Anna Panchenko ( [email protected] ) • Instructor: Tom Madej ( [email protected] ) • Co-Instructor: Rahul Simha ( [email protected] )

CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko ([email protected])[email protected] Instructor: Tom Madej ([email protected])[email protected]

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Page 1: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

CS 177 Introduction to BioinformaticsFall 2004

• Instructor: Anna Panchenko ([email protected])

• Instructor: Tom Madej ([email protected])

• Co-Instructor: Rahul Simha ([email protected])

Page 2: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Lecture 1: Introduction

• Instructors• Course goals• Grading policy• Motivating problem• Course overview• Molecular basis of cellular processes• Historical timeline

Page 3: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Course Goals• The student will be introduced to the fundamental problems and

methods of bioinformatics.

• The student will become thoroughly familiar with on-line public bioinformatics databases and their available software tools.

• The student will acquire a background knowledge of biological systems so as to be able to interpret the results of database searches, etc.

• The student will also acquire a general understanding of how important bioinformatics algorithms/software tools work, and how the databases are organized.

Page 4: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Grading Policy

• Homework: 50%, weekly assignments

• Final exam: 50%

“All examinations, papers, and other graded work products and assignments are to be completed in conformance with: The George Washington University Code of Academic Integrity”.

Page 5: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov
Page 6: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

P.E. Bourne and H. Weissig(2003), Structural Bioinformatics,Wiley & Sons.

Optional Texts

Page 7: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

What is Bioinformatics?

• A merger of biology, computer science, and information technology.

• Enables the discovery of new biological insights and unifying principles.

• Born from necessity, because of the massive amount of information required to describe biological organisms and processes.

Page 8: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Severe Acute Respiratory Syndrome (SARS)

• SARS is a respiratory illness caused by a previously unrecognized coronavirus; first appeared in Southern China in Nov. 2002.

• Between Nov. 2002 and July 2003, there were 8,098 cases worldwide and 774 fatalities (WHO).

• The global outbreak was over by late July 2003. A few new cases have arisen sporadically since then in China.

• There is currently no vaccine or cure available.

Page 9: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov
Page 10: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov
Page 11: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov
Page 12: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Fig. 2 from Rota et al.

Page 13: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Phylogenetic analysis of coronavirus proteins

Fig. 2 from Rota et al.

Page 14: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov
Page 15: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Conserved motifs in coronavirus S proteins.

Fig. 2 from Rota et al.

Page 16: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Exercise!

Look up the SARS genome on the NCBI website: www.ncbi.nlm.nih.gov

Page 17: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

The (ever expanding) Entrez System

EntrezEntrez

PopSet

Structure

PubMed

Books

3D Domains

Taxonomy

GEO/GDS

UniGene

Nucleotide

Protein

Genome

OMIM

CDD/CDART

Journals

SNP

UniSTS

PubMed Central

Page 18: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Course Overview

Lecture 1: Introduction

• Instructors• Grading policy• Motivating problem• Course overview• Molecular basis of cellular processes• Historical timeline

Page 19: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Lecture 2: General principles of DNA/RNA structure and stability

• Physico-chemical properties of nucleic acids• RNA folding and structure prediction• Gene identification• Genome analysis

Lecture 3: General principles of protein structure and stability

• Physico-chemical properties of proteins• Prediction of protein secondary structure• Protein domains and prediction of domain boundaries• Protein structure-function relationships

Page 20: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Lecture 4: Sequence alignment algorithms

• The alignment problem• Pairwise sequence alignment algorithms• Multiple sequence alignment algorithms• Sequence profiles and profile alignment methods• Alignment statistics

Page 21: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Lecture 5: Computational aspects of protein structure, part I

• Protein folding problem• Problem of protein structure prediction• Homology modeling• Protein design• Prediction of functionally important sites

Lecture 6: Computational aspects of protein structure, part II

• Structure-structure alignment algorithms• Significance of structure-structure similarity• Protein structure classification

Page 22: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Lecture 7: Bioinformatics databases

• Sequence and sequence alignment formats, data exchange• Public sequence databases• Sequence retrieval and examples• Public protein structure databases• Lab exercises

Lecture 8: Bioinformatics database search tools

• Sequence database search tools• Structure database search tools• Assessment of results, ROC analysis• Lab exercises

Page 23: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Lecture 9: Phylogenetic analysis, part I

• Molecular basis of evolution• Taxonomy and phylogenetics• Phylogenetic trees and phylogenetic inference• Software tools for phylogenetic analysis

Lecture 10: Phylogenetic analysis, part II

• Accuracies and statistical tests of phylogenetic trees• Genome comparisons• Protein structure evolution

Page 24: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Lecture 11: Experimental techniques for macromolecular analysis

• Sequencing, PCR• Protein crystallography• Mass spectroscopy• Microarrays• RNA interference

Page 25: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Lecture 12: Systems biology

• Genomic circuits• Modeling complex integrated circuits• Protein-protein interaction• Metabolic networks

Lectures 13, 14: To be decided…

Page 26: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Molecular Biology Background

• Cells – general structure/organization

• Molecules – that make up cells

• Cellular processes – what makes the cell alive

Page 27: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Two Cell Organizations

• Prokaryotes – lack nucleus, simpler internal structure, generally quite smaller

• Eukaryotes – with nucleus (containing DNA) and various organelles

Page 28: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov
Page 29: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov
Page 30: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Selected organelles…

• Nucleus – contains chromosomes/DNA

• Mitochondria – generate energy for the cell, contains mitochrondrial DNA

• Ribosomes – where translation from mRNA to proteins take place (protein synthesis machinery)

• Lysosomes – where protein degradation takes place

Page 31: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Cells can become specialized…

Page 32: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Three domains of life

• Prokarya

Bacteria

Archaea

• Eukarya

Eukaryotes

Page 33: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Universal phylogenetic tree.

Fig. 1 from:N.R. Pace, Science 276(1997) 734-740.

Page 34: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Molecules in the cell

• Proteins – catalyze reactions, form structures, control membrane permeability, cell signaling, recognize/bind other molecules, control gene function

• Nucleic acids – DNA and RNA; encode information about proteins

• Lipids – make up biomembranes

• Carbohydrates – energy sources, energy storage, constituents of nucleic acids and surface membranes

• Other small molecules – e.g. ATP, water, ions, etc.

Page 35: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

The Central Dogma of Molecular Biology

Page 36: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov
Page 37: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov
Page 38: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Exercise!

Retrieve a protein structure from the SARS coronavirus from the NCBI website; you can use: www.ncbi.nlm.nih.gov/Structure/

Look at the structure for the SARS protease using Cn3D.

Page 39: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline

1859 Darwin publishes On the Origin of Species…

1865 Mendel’s experiments with peas show that hereditary traits are passed on to offspring in discrete units.

1869 Meischer isolates DNA.

1895 Rőntgen discovers X-rays.

1902 Sutton proposes the chromosome theory of heredity.

Page 40: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)

1911 Morgan and co-workers establish the chromosome theory of heredity, working with fruit flies.

1943 Astbury observes the first X-ray pattern of DNA.

1944 Avery, MacLeod, and McCarty show that DNA transmits heritable traits (not proteins!).

1951 Pauling and Corey predict the structure of the alpha-helix and beta-sheet.

Page 41: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)

1953 Watson and Crick propose the double helix model for DNA based on X-ray data from Franklin and Wilkins.

1955 Sanger announces the sequence of the first protein to be analyzed, bovine insulin.

1955 Kornberg and co-workers isolate the enzyme DNA polymerase (used for copying DNA, e.g. in PCR).

1958 The first integrated circuit is constructed by Kilby at Texas Instruments.

Page 42: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)1960 Perutz and Kendrew obtain the first X-ray structures of

proteins (hemoglobin and myoglobin).

1961 Brenner, Jacob, and Meselson discover that mRNA transmits the information from the DNA in the nucleus to the cytoplasm.

1965 Dayhoff starts the Atlas of Protein Sequence and Structure.

1966 Nirenberg, Khorana, Ochoa and colleagues crack the genetic code!

1970 The Needleman-Wunsch algorithm for sequence comparison is published.

Page 43: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)

1972 Dayhoff develops the Protein Sequence Database (PSD).

1972 Berg and colleagues create the first recombinant DNA molecule.

1973 Cohen invents DNA cloning.

1975 Sanger and others (Maxam, Gilbert) invent rapid DNA sequencing methods.

Page 44: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)

1980 The first complete gene sequence for an organism (Bacteriophage FX174) is published. The genome consists of 5,386 bases coding 9 proteins.

1981 The Smith-Waterman algorithm for sequence alignment is published.

1981 IBM introduces its Personal Computer to the market.

1982 The GenBank sequence database is created at Los Alamos National Laboratory.

Page 45: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)1983 Mullis and co-workers describe the PCR reaction.

1985 The FASTP algorithm is published by Lipman and Pearson.

1986 The SWISS-PROT database is created.

1986 The Human Genome Initiative is announced by DOE.

1988 The National Center for Biotechnology Information (NCBI) is established at the National Library of Medicine in Bethesda.

Page 46: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)

1992 Human Genome Systems, in Gaithersburg, MD, is founded by Haseltine.

1992 The Institute for Genomic Research (TIGR) is established by Venter in Rockville, MD.

1995 The Haemophilus influenzea genome is sequenced (1.8 Mb).

1996 Affymetrix produces the first commercial DNA chips.

Page 47: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)

1988 The FASTA algorithm for sequence comparison is published by Pearson and Lipman.

1990 Official launch of the Human Genome Project.

1990 The BLAST program by Altschul et al., is published.

1991 The CERN research institute in Geneva announces the creation of the protocols which make up the World Wide Web.

Page 48: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)

1996 The yeast genome is sequenced; the first complete eukaryotic genome.

1996 Human DNA sequencing begins.

1997 The E. coli genome is sequenced (4.6 Mb, approx. 4k genes).

1998 The C. elegans genome is sequenced (97 Mb, approx. 20k genes); the first genome of a multicellular organism.

Page 49: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)

1998 Venter founds Celera in Rockville, MD.

1998 The Swiss Institute of Bioinformatics is established in Geneva.

1999 The HGP completes the first human chromosome (no. 22).

2000 The Drosophila genome is completed.

Page 50: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Timeline (cont.)

2000 Human chromosome no. 21 is completed.

2001 A draft of the entire human genome (3,000 Mb) is published.

2003 The Human Genome is “completed”! Approx. 30,000 genes (estimated).

Page 51: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

DNA, RNA, protein overview

Questions about the genome in an organism:

How much DNA, how many nucleotides?

How many genes are there?

What types of proteins appear to be coded by these genes?

Questions about the proteome:

What proteins are present?

Where are they?

When are they present - under what conditions?

DNA RNA  Mutations

Amino acids, protein structure

Page 52: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

DNA overview

DNA

deoxyribonucleic acid

4 bases

A =

T =

C =

G =

Adenine

Thymine

Cytosine

Guanine

Nucleoside

base + sugar (deoxyribose)

Pyrimidine (C4N2H4) Purine (C5N4H4)

Nucleotide

base + sugar + phosphate

4’

5 ’

3 ’ 2 ’

1 ’

O

sug a r

P OO -

O -

Pyrimidine (C4N2H4)

Thymine

Cytosine

P O 4--

Numbering of carbons?H

HH H

HO H

C H2O

O H

DNA RNA  Mutations

Amino acids, protein structure

Page 53: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Linking nucleotides

5’

3 ’

3’

3 ’

3 ’

3’

5’

3 ’

3’

What next?

3’ 3 ’

3 ’

3’

2nm

Hydrogen bonds

N-H------N

N-H------O

Adenine

Guanine

Thymine

Cytosine

Linking nucleotides:

The 3’-OH of one nucleotide is linked to the 5’-phosphate of the next nucleotide

DNA RNA  Mutations

Amino acids, protein structure

Page 54: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Base pairing

5’

3 ’

3’

3 ’

3 ’

3’

5’

3 ’

3’

3 ’

3 ’

3’

G

C

T

A

T

A

G

C

T

A

Base pairing (Watson-Crick):

A/T (2 hydrogen bonds)

G/C (3 hydrogen bonds)

Always pairing a purine and a pyrimidine yields a constant width

DNA base composition:

A + G = T + C (Chargaff’s rule)

DNA RNA  Mutations

Amino acids, protein structure

Page 55: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

DNA conventions

1. DNA is a right-handed helix

DNA RNA  Mutations

Amino acids, protein structure

Page 56: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

5’ 3’

DNA conventions

1. DNA is a right-handed helix

2. The 5’ end is to the left by convention

-ATCGCAATCAGCTAGGTT- sense (forward)

antisense (reverse)-TAGCGTTAGTCGATCCAA-3’ 5’

5’ -ATCGCAATCAGCTAGGTT- 3’

3’ -TAGCGTTAGTCGATCCAA- 5’

5’-ATCGCAATCAGCTAGGTT-3’

3’-TAGCGTTAGTCGATCCAA-5’

DNA RNA  Mutations

Amino acids, protein structure

Page 57: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

DNA structure

Some more facts:

1. Forces stabilizing DNA structure: Watson-Crick-H-bonding and base stacking (planar aromatic bases overlap geometrically and electronically energy gain)

2. Genomic DNAs are large molecules:Eschericia coli: 4.7 x 106 bp; ~ 1 mm contour lengthHuman: 3.2 x 109 bp; ~ 1 m contour length

3. Some DNA molecules (plasmids) are circular and have no free ends:

mtDNAbacterial DNA (only one circular chromosome)

4. Average gene of 1000 bp can code for average protein of about 330 amino acids

5. Percentage of non-coding DNA varies greatly among organisms

Organism # Base pairs # Genes Non-coding DNA

small virus 4 x 103 3 very little‘typical’ virus 3 x 105 200 very little

bacterium 5 x 106 3000 10 - 20%yeast 1 x 107 6000 > 50%

human 3.2 x 109 30,000? 99%

amphibians < 80 x 109 ? ?

plants < 900 x 109 23,000 - >50,000 > 99%

DNA RNA  Mutations

Amino acids, protein structure

Page 58: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

ribonucleic acid

4 bases

A =

U =

C =

G =

Adenine

Uracil

Cytosine

Guanine

Pyrimidine (C4N2H4) Purine (C5N4H4)

Nucleoside Nucleotide

base

HHH H

O HO H

C H2O

O H

+ sugar (ribose)

4’

5 ’

3 ’ 2 ’

1 ’

base + sugar + phosphate

O

sug a r

P OO -

O -

P O 4--

RNA

RNA structure

3 major types of RNA

messenger RNA (mRNA); template for protein synthesis transfer RNA (tRNA); adaptor molecules that decode the genetic coderibosomal RNA (rRNA); catalyzing the synthesis of proteins

Thymine (DNA) Uracil (RNA)

DNA RNA  Mutations

Amino acids, protein structure

Page 59: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Base interactions in RNA

Base pairing:

U/A/(T) (2 hydrogen bonds)

G/C (3 hydrogen bonds)

RNA base composition:

A + G = U + C/ Chargaff’s rule does not apply (RNA usually prevails as single strand)

RNA structure:

- usually single stranded

- many self-complementary regions RNA commonly exhibits an intricate secondary structure (relatively short, double helical segments alternated with single stranded regions)

- complex tertiary interactions fold the RNA in its final three dimensional form

- the folded RNA molecule is stabilized by interactions (e.g. hydrogen bonds and base stacking)

DNA RNA  Mutations

Amino acids, protein structure

Page 60: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

RNA structure

Primary structure

Secondary structure

A

A) single stranded regions

C) hairpinC

D

D) internal loop

EE) bulge loop

FF) junctionB

B) duplex

G

G) pseudoknot

formed by unpaired nucleotides

double helical RNA (A-form with 11 bp per turn)

duplex bridged by a loop of unpaired nucleotides

nucleotides not forming Watson-Crick base pairs

unpaired nucleotides in one strand,other strand has contiguous base pairing

three or more duplexes separated by singlestranded regions

tertiary interaction between bases of hairpin loopand outside bases

DNA RNA  Mutations

Amino acids, protein structure

Page 61: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

RNA structure

Primary structure

Secondary structure

A

C

D

E

FB

G

Tertiary structure

DNA RNA  Mutations

Amino acids, protein structure

Page 62: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

RNA structure

How to predict RNA secondary/tertiary structure?

Probing RNA structure experimentally:

- physical methods (single crystal X-ray diffraction, electron microscopy)

- chemical and enzymatic methods

- mutational analysis (introduction of specific mutations to test change in some function or protein-RNA interaction)

Thermodynamic prediction of RNA structure:

- RNA molecules comply to the laws of thermodynamics, therefore it should be possible to deduce RNA structure from its sequence by finding the conformation with the lowest free energy

- Pros: only one sequence required; no difficult experiments; does not rely on alignments

- Cons: thermodynamic data experimentally determined, but not always accurate; possible interactions of RNA with solvent, ions, and proteins

Comparative determination of RNA structure:

- basic assumption: secondary structure of a functional RNA will be conserved in the evolution of the molecule (at least more conserved than the primary structure); when a set of homologous sequences has a certain structure in common, this structure can be deduced by comparing the structures possible from their sequences

- Pros: very powerful in finding secondary structure, relatively easy to use, only sequences required, not affected by interactions of the RNA and other molecules

- Cons: large number of sequences to study preferred, structure constrains in fully conserved regions cannot be inferred, extremely variable regions cause problems with alignment

DNA RNA  Mutations

Amino acids, protein structure

Page 63: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

Amino acids/proteins

The “central dogma” of modern biology: DNA RNA protein

Getting from DNA to protein:

Two parts: 1. Transcription in which a short portion of chromosomal DNA is used to make a RNA molecule small enough to leave the nucleus.

2. Translation in which the RNA code is used to assemble the protein at the ribosome

- Bases are read in groups of 3 (= a codon)

The genetic code

- The code consists of codons 64 (43 = 64)

- All codons are used in protein synthesis:- 20 amino acids- 3 stop codons

- The code problem: 4 nucleotides in RNA, but 20 amino acids in proteins

- AUG (methionine) is the start codon (also used internally)

- The code is non-overlapping and punctuation-free

- The code is degenerate (but NOT ambiguous): each amino acid is specified by at least one codon

- The code is universal (virtually all organisms use the same code)

DNA RNA  Mutations

Amino acids, protein structure

Page 64: CS 177 Introduction to Bioinformatics Fall 2004 Instructor: Anna Panchenko (panch@ncbi.nlm.nih.gov)panch@ncbi.nlm.nih.gov Instructor: Tom Madej (madej@ncbi.nlm.nih.gov)madej@ncbi.nlm.nih.gov

The genetic code

methionine and tryptophan

five: proline, threonine,valine, alanine, glycine

AUG

In-class exercise

2. How many amino acids are specified by the first two nucleotides only?

3. What is the RNA code for the start codon?

1. Which amino acids are specified by single codons?

Base 2

T C A G

T Phenylalanine F

Tyrosine Y

Cysteine C C

STOP A T

Leucine L

Serine S

STOP Tryptophan W G

T Histidine H C

A C

Leucine L

Proline P

Glutamine Q

Arginine R

G

T Asparagine N

Serine S C

Isoleucine I

A A

Methionine M

Threonine T

Lysine K

Arginine R G

T Aspartate B C

A

Bas

e 1

G Valine

V Alanine

A Glutamate

Z

Glycine G

G

Base 3

DNA RNA  Mutations

Amino acids, protein structure