Basic Molecular Biology

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Basic Molecular Biology
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Basic Molecular Biology

• Structures of biomolecules
• How does DNA function?
• What is a gene?
• Computer scientists vs Biologists

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Bioinformatics schematic of a cell
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Macromolecule (Polymer) Monomer
DNA Deoxyribonucleotides (dNTP)
RNA Ribonucleotides (NTP)
Protein or Polypeptide Amino Acid
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Nucleic acids (DNA and RNA)

• Form the genetic material of all living
  organisms.
• Found mainly in the nucleus of a cell (hence
  nucleic)
• Contain phosphoric acid as a component (hence
  acid)
• They are made up of nucleotides.

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Nucleotides

• A nucleotide has 3 components
• Sugar (ribose in RNA, deoxyribose in DNA)
• Phosphoric acid
• Nitrogen base
• Adenine (A)
• Guanine (G)
• Cytosine (C)
• Thymine (T) or Uracil (U)

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Monomers of DNA

• A deoxyribonucleotide has 3 components
• Sugar - Deoxyribose
• Phosphoric acid
• Nitrogen base
• Adenine (A)
• Guanine (G)
• Cytosine (C)
• Thymine (T)

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Monomers of RNA

• A ribonucleotide has 3 components
• Sugar - Ribose
• Phosphoric acid
• Nitrogen base
• Adenine (A)
• Guanine (G)
• Cytosine (C)
• Uracil (U)

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Nucleotides
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DNA
RNA
A T G C
T ? U
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Proteins

• Composed of a chain of amino acids.
• R
• H2N--C--COOH
• H

20 possible groups
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Proteins
R
R
H2N--C--COOH
H2N--C--COOH

H H

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Dipeptide
This is a peptide bond
R O R
II
H2N--C--C--NH--C--COOH

H H
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Protein structure

• Linear sequence of amino acids folds to form a
  complex 3-D structure.
• The structure of a protein is intimately
  connected to its function.

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Structure -gt Function

• It is the 3-D shape of proteins that gives them
  their working ability generally speaking, the
  ability to bind with other molecules in very
  specific ways.

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DNA information store RNA information store
and catalyst Protein superior catalyst
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DNA in action

• Questions about DNA as the carrier of genetic
  information
• What is the information?
• How is the information stored in DNA?
• How is the stored information used ?
• Answers
• Information gene ? phenotype
• Information is stored as nucleotide sequences.
• .. and used in protein synthesis.

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• How does the series of chemical bases along a DNA
  strand (A/T/G/C) come to specify the series of
  amino acids making up the protein?

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The need for an intermediary

• Fact 1 Ribosomes are the sites of protein
  synthesis.
• Fact 2 Ribosomes are found in the cytoplasm.
• Question How does information flow from DNA
  to protein?

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The Intermediary

• Ribonucleic acid (RNA) is the messenger.
• The messenger RNA (mRNA) can be synthesized on
  a DNA template.
• Information is copied (transcribed) from DNA to
  mRNA. (TRANSCRIPTION)

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• Biological functions of RNA
• Mediate of the protein synthesis
• Messenger RNA (nRNA)
• Transfer RNA (tRNA)
• Ribosomal RNA (rRNA)
• Structural molecule Ribosomal RNA
• Catalytic molecule ribozyme
• Guide molecule primer of DNA replication,
  protein degradation (tm RNA)
• Ribonucleoprotein (complex of RNA and protein)
  mRAN edition, mRAN spicing, protein transport

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Transcription

• The DNA is contained in the nucleus of the cell.
• A stretch of it unwinds there, and its message
  (or sequence) is copied onto a molecule of mRNA.
• The mRNA then exits from the cell nucleus.
• Its destination is a molecular workbench in the
  cytoplasm, a structure called a ribosome.

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Principal steps of the transcription

• Polymerase RNA randomly binds on the DNA and
  seeks for a promoter (5 ?3)
• Opening of the DNA
• Initiation of the polymerization
• Elongation
• 20-50 nucleotides/sec
• 1 error/104 nucleotides
• Termination (at the termination signal)

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RNA polymerase

• It is the enzyme that brings about transcription
  by going down the line, pairing mRNA nucleotides
  with their DNA counterparts.

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Promoters

• Promoters are sequences in the DNA just upstream
  of transcripts that define the sites of
  initiation.
• The role of the promoter is to attract RNA
  polymerase to the correct start site so
  transcription can be initiated.

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Promoter
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Promoters

• Promoters are sequences in the DNA just upstream
  of transcripts that define the sites of
  initiation.
• The role of the promoter is to attract RNA
  polymerase to the correct start site so
  transcription can be initiated.

5
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Promoter
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Promoter

• So a promoter sequence is the site on a segment
  of DNA at which transcription of a gene begins
  it is the binding site for RNA polymerase.

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Termination site of the transcription
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Next question

• How do I interpret the information carried by
  mRNA?
• Think of the sequence as a sequence of
  triplets.
• Think of AUGCCGGGAGUAUAG as AUG-CCG-GGA-GUA-UAG.
• Each triplet (codon) maps to an amino acid.

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Translation mRNA ? protein

• Codons UAA, UAG and UGA are stop codons because
  there is no corresponding tRNA (except
  exception)
• Codon AUG code for initiator methionine (except
  exception)
• The code is almost-universal.

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The Genetic Code
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Translation

• At the ribosome, both the message (mRNA) and raw
  materials (amino acids) come together to make the
  product (a protein).

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Translation

• The sequence of codons is translated to a
  sequence of amino acids.
• How do amino acids get to the ribosomes?
• They are brought there by a second type of RNA,
  transfer RNA (tRNA).

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Translation

• Transfer RNA (tRNA) a different type of RNA.
• Freely float in the cytoplasm.
• Every amino acid has its own type of tRNA that
  binds to it alone.
• Anti-codon codon binding crucial.

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tRNA
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tRNA
One end of the tRNA links with a specific amino
acid, which it finds floating free in the
cytoplasm.
It employs its opposite end to form base pairs
with nucleic acids with a codon on the mRNA
tape that is being read inside the ribosome.
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tRNA
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• Transfer RNA
• 61 different tRAN, composed of from 75 to 95
  nucleotides
• Recognition of a codon and binding to the
  corresponding amino acid

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Elongation of the translation
The ribosome move by 3 nucleotides toward 3
(elongation) in 1 second a Bacteria ribosome
adds 20 amino acids! Eucaryote 2 amino
acids/second !
A stop codon stop (UAA, UAG, AGA) In the same
reading frame, end the process the ribosome
break away from the mRNA.
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Polyribosome (polysomes) eukaryote and prokaryote
Duration of the protein synthesis between 20
seconds and several minutes multiple initiations
80 nucleotides between 2 ribosomes
Eukaryotes 10 ribosomes / mRNA Procaryotes up
to 300 ribosomes / mRNA
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The gene and the genome

• A gene is a length of DNA that codes for a
  protein.
• Genome The entire DNA sequence within the
  nucleus.

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Estimate of the number of genes (proteins tRNA
rRNA)
Organism Sizee (bp) Number of genes coding Remarks
E.coli 4,639,221 4,397 87 Eubacterie
Methanococcus jannashii 1,664,970 1,758 87 Archae
Saccharomyces cerevisiae 12,057,849 6,551 72
Arabidopsis thaliana 135,000,000 25000 ?
Caenorhabditis elegans 87,567,338 17,687 21 1000 cells
Drosophila melanogaster 180,000,000 13,600 20 Core proteome 8,000 (families)
Human 3,000,000,000 20,000-25,000 4-7 (?)
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Genome coding regions

• Gene definition
• Nucleic acid sequence required for the synthesis
  of
• a functional polypeptide
• a functional RNA (tRNA, rRNA,)
• A gene coding for a protein generally contains
• a coding sequence (CDS)
• control regions for transcription and
  translation (promoter, enhancer, poly A site)
• A gene contains coding and non-coding regions

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More complexity

• The RNA message is sometimes edited.
• Exons are nucleotide segments whose codons will
  be expressed.
• Introns are intervening segments (genetic
  gibberish) that are snipped out.
• Exons are spliced together to form mRNA.

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Standard structure of a gene for vertebrate
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RNA processing Splicing

• Pre-messenger RNA contains coding sequence
  regions (exon express sequence) alternate with
  non-coding regions (intron intervening sequence)
• Splicing excision of the introns

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Splicing generalities

• High variability of the number of intron between
  genes in a given specie
• Ex human from 2 introns (insulin) to more
  than 100 introns (117 introns collagen type VII)
• High variability of the number of intron between
  species
• Ex yeast gene has few introns (max 2 introns
  / gene).
• High variability of the size of the introns (min
  18 nucleotides to 300 kb)
• High variability of the size of the exons (min 8
  coding nucleotides)
• Mitochondrial human genes do not contain
  introns, but mitochondrial vegetal and fungus
  (yeast include) contain introns chloroplasts
  genes contain introns there exists introns for
  some prokaryotes !
• Importance in evolution facilitate genetic
  recombination linked with the notion of domains
  in proteins
• Human average 7kb intron / 1 kb exon

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Alternative splicing
The exon order is generally fixed (except for
exon scrambling)
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Summery of the whole process
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• Proteins
• Several levels from primary to quaternary
  structure
• Composed of amino acids

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Protein Structure

• Proteins are poly-peptides of 70-3000 amino-acids
• This structure is (mostly) determined by the
  sequence of amino-acids that make up the protein

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Functional categories

• Enzymes Kinase,
  Protéase
• Transport Hemoglobin,
• Regulation Insuline, Répresseur lac
• Storage Caséine, Ovalbumine
• Structure Protéoglycan, Collagène
• Contraction Actine, Myosine
• Protection Immunoglobulines, Toxines
• Scaffold proteins Grb 2, crk
• Exotics Resiline, protéines adhésives

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Number of proteins in various organisms
Organism Number Bacteria
500-6000 Yeast 6000 C. elegans
19000 Drosophila 15000 Human
30000-1000000
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Protein Structure
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Example of structural motif HTH

• Helix Turn Helix (HTH) motif very common
  (prokaryotes et eukaryotes)
• DNA binding site
• for procaryotes

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From Genome to Proteome
Human about 25000 genes
Genome
10-42
Alternative splicing of mRNA
 After ribosomes 
Increase in complexity
Post-translational protein modification (PTM)
5 to 10 fold
Definition of PTM Any modification of a
polypeptide chain that involves the formation or
breakage of a covalent bond.
Proteome
Human about one million proteins several
proteomes
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Evolution

• Related organisms have similar DNA
• Similarity in sequences of proteins
• Similarity in organization of genes along the
  chromosomes
• Evolution plays a major role in biology
• Many mechanisms are shared across a wide range of
  organisms
• During the course of evolution existing
  components are adapted for new functions

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Evolution

• Evolution of new organisms is driven by
• Diversity
• Different individuals carry different variants of
  the same basic blue print
• Mutations
• The DNA sequence can be changed due to single
  base changes, deletion/insertion of DNA segments,
  etc.
• Selection bias

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Numerous possible effect of mutation
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The Tree of Life
Source Alberts et al
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Central dogma
ZOOM IN
tRNA
transcription
DNA
rRNA
snRNA
translation
POLYPEPTIDE
mRNA
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Bioinformatics

• Studies the flow of information in biomedicine
• Information flow from genotype to phenotype
• DNA ? Protein ? Function ? Organism ? Population
  ? DNA
• Experimental flow for creating and testing models
• Hypothesis ? Experiment ? Data ? Conflict ?
  Hypothesis

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Computational Biology and Bioinformatics

• The systematic development and application of
  computing systems and computational solution
  techniques to the analysis of biological data
  obtained by experiments, modeling, database
  search, and experimentation
• Explosion of experimental data
• Difficulty in interpreting data
• Need for new paradigms for computing with data
  and extracting new knowledge from it

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Brief history of early bioinformatics

• Molecular sequences and data bases
• Dayhoff (atlas of proteins, 1965) Zuckerkandl
  Pauling (1965), Bilofsky (GenBank, 1986), Hamm
  Cameron (EMBL, 1986), Bairoch (Swiss-Prot, 1986)
• Molecular sequence comparison
• NeedleMan Wunsch (1970), Smith Waterman
  (1981), Pearson-Lipman (Fasta, 1985), Altschul
  (Blast, 1990)
• Multiple alignment and automatic phylogeny
• Aho (common subsequence, 1976), Felsenstein
  (infering phylogenies, 1981-1988), Sankoff
  Cedergren (multiple comparison, 1983), Feng
  Doolittle (Clustal, 1987), Gusfield (inferring
  evolutionary trees, 1991), Thompson (ClustalW,
  1994)
• Motif search and discovery
• Fickett (ORF, 1982), Ukkonen (approximate string
  matching, 1985), Jonassen (Pratt, 1995), Califano
  (Splash, 2000) Pevzner (WINNOVER, 2000)
• But also RNA structure prediction, protein
  threading, protein foldings

Few fields and large use of combinatoric/dynamic
programming approaches
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New biological data imply new bioinformatics
field

• Sequence
• Motif search, motif discovery, alignment
• Data indexing, regular language, dynamic
  programming, HMM, EM, Gibbs sampling
• Structure
• RNA folding, protein threading, protein folding
• Palindrome search, context-(free, sensitive)
  language, dynamic programming, combinatorial
  optimization
• DNA chip
• Classification, clustering, feature selection,
  regulation network
• NN, SVM, Bayesian inference, (hierarchical, k,
  Gaussian)-clustering, differencial model
• Proteomics
• Spectrum analysis, image pattern matching,
  probabilistic model
• Bibliographic data
• Ontology, text mining

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Important source of data and information GENEBANK
http//www.ncbi.nih.gov Swiss-prot
http//us.expasy.org/sprot/relnotes Protein Data
Bank (PDB) http//www.rcsb.org/pdb/home/home.do
Stanford Microarray DB http//smd.stanford.edu Me
dLine or PubMed http//genome.ucsc.edu
or http//www.ebi.ac.uk/ensembl Journals
Bioinformatics, BMC bioinformatics, Nucleic
Acids Research, Journal of Molecular Biology,
Proteomics
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Computer scientists vs Biologists

• (Almost) Nothing is ever completely true or false
  in Biology.
• Everything is either true or false in computer
  science.

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Computer scientists vs Biologists

• Biologists strive to understand the very
  complicated, very messy natural world.
• Computer scientists seek to build their own clean
  and organized virtual worlds.

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Computer scientists vs Biologists

• Biologists are more data driven.
• Computer scientists are more algorithm driven.
• One consequence is CS www pages have fancier
  graphics while Biology www pages have more
  content.

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Computer scientists vs Biologists

• Biologists are obsessed with being the first to
  discover something.
• Computer scientists are obsessed with being the
  first to invent or prove something.

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Computer scientists vs Biologists

• Biologists are comfortable with the idea that all
  data has errors.
• Computer scientists are not.

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Computer scientists vs Biologists

• Computer scientists get high-paid jobs after
  graduation.
• Biologists typically have to complete one or more
  post-docs...

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Computer Science is to Biology what Mathematics
is to Physics