Transcript PowerPoint - Center for Biological Sequence Analysis

It & Health 2010
Summary
Thomas Nordahl Petersen
DNA/RNA
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DNA findes I celle kernen (Eukaryoter)
base paring
T substituted with U in RNA
Reading direction
Reading frame (1,2,3,-1,-2,-3)
64 codons
DNA -> mRNA
Intron, exon & UTR (non-coding exon)
Intron/Exon splice site
Reading frame and
reverse complement
Having a piece of DNA like:
TGCCATGCATAGCCCCTGCCATATCT
Forward strings & reading frames
1 : TGCCATGCATAGCCCCTGCCATATCT
2 : GCCATGCATAGCCCCTGCCATATCT
3 :
CCATGCATAGCCCCTGCCATATCT
Reverse complement strings & reading frames
-1: TCTATACCGTCCCCGATACGTACCGT
-2: CTATACCGTCCCCGATACGTACCGT
-3:
TATACCGTCCCCGATACGTACCGT
Amino acids
20 naturally occurring amino acids
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mRNA -> protein
Reading direction
4 backbone atoms
Amino acid properties
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Acidic, basic, polar, charged, hydrophibic
1 and 3 letter codes
Amino Acids
Amine and carboxyl groups. Sidechain ‘R’ is attached to C-alpha carbon
The amino acids found in Living organisms are L-amino acids
Amino Acids - peptide bond
N-terminal
C-terminal
Databases and web-tools
Databases and biological information
• Genbank
• Uniprot
Web-tools
• NCBI Blast
• UCSC genome browser
• Weblogo
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS
Theory of evolution
Charles Darwin
1809-1882
Phylogenetic tree
Global versus local alignments
Global alignment: align full length of both sequences.
“Needleman-Wunsch” algorithm).
(The
Global alignment
Local alignment: find best partial alignment of two sequences
(the “Smith-Waterman” algorithm).
Seq 1
Local alignment
Seq 2
Pairwise alignment: the solution
”Dynamic programming”
(the Needleman-Wunsch algorithm)
Sequence alignment - Blast
Sequence alignment - Blast
Blosum & PAM matrices
• Blosum matrices are the most commonly used
substitution matrices.
• Blosum50, Blosum62, blosum80
• PAM - Percent Accepted Mutations
• PAM-0 is the identity matrix.
• PAM-1 diagonal small deviations from 1, offdiag has small deviations from 0
• PAM-250 is PAM-1 multiplied by itself 250
times.
Sequence profiles (1J2J.B)
>1J2J.B mol:aa PROTEIN TRANSPORT
NVIFEDEEKSKMLARLLKSSHPEDLRAANKLIKEMVQEDQKRMEK
Log-odds scores
• BLOSUM is a log-likelihood matrix:
• Likelihood of observing j given you have i is
– P(j|i) = Pij/Pi
• The prior likelihood of observing j is
– Qj , which is simply the frequency
• The log-likelihood score is
– Sij = 2log2(P(j|i)/log(Qj) = 2log2(Pij/(QiQj))
– Where, Log2(x)=logn(x)/logn(2)
– S has been normalized to half bits, therefore the factor 2
BLAST Exercise
Genome browsers - UCSC
Intron - Exon structure
Single Nucleotide polymorphism - SNP
SNPs
Protein 3D-structure
Protein structure
Primary structure: Amino acids sequences
Secondary structure: Helix/Beta sheet
Tertiary structure: Fold, 3D cordinates
Protein structure
-helix
helix
-helix
Pi-helix
3 residues/turn - few, but not uncommon
3.6 residues/turn - by far the most common helix
4.1 residues/turn - very rare
Protein structure
strand/sheet
Protein folds
Class
Alpha,beta, alpha+beta and alpha/beta
And last class – none or few SS-elements
Architecture
Overall shape of a domain
Topology
Share secondary structure connectivity
Protein 3D-structure
Neural Networks
From knowledge to information
Protein sequence
Biological feature
Use of artificial neural networks
• A data-driven method to predict a feature, given a set of training data
• In biology input features could be amino acid sequence or nucleotides
• Secondary structure prediction
• Signal peptide prediction
• Surface accessibility
• Propeptide prediction
C
N
Signal
peptide
Propeptide
Mature/active protein
Prediction of biological features
Surface accessible
Predict surface accessible from
amino acid sequence only.
Logo plots
Information content, how is it calculated - what does it mean.
Logo plots - Information Content
Calculate Information Content
I = a palog2pa + log2(4), Maximal value is 2 bits
Sequence-logo
Completely conserved
~0.5 each
• Total height at a position is the ‘Information Content’ measured in bits.
• Height of letter is the proportional to the frequency of that letter.
• A Logo plot is a visualization of a mutiple alignment.