Bioinformatics

Not only small molecules and QM, MM techniques rule the world.

Central dogma of molecular biology

• • • Term is due to Francis Crick The conversion DNA involved → protein is not direct, RNA is DNA is the information store, RNA is messenger (mRNA), transporter (tRNA), biomolecular nanomachine (rRNA)

source: wikipedia.org

Nucleic acids

• four letters (DNA, RNA) • sequence AACTAACG (5’ → 3’) • DNA – double helix • RNA – “single stranded” helix, folding (double helical regions, C2’ -OH → secondary and tertiary motifs)

nucleotide nucleoside

B-DNA A-DNA Z-DNA A B Z

RNA secondary motifs

Nowakowski and Tinoco, Seminars in Virology 8, 153, 1997.

RNA

source: http://complex.upf.es/~josep/RNA.jpg, http://www.biosci.ki.se/groups/ljo/images/phe_trna_large.jpg, http://rna.ucsc.edu/rnacenter/images/70s_atrna.jpg

Proteins

• 20 letters • primary structure - sequence AMNTSSTVG (N-end → C end) Alberts, Molecular Biology of the Cell, 5th Ed.

• secondary structure (random coil,  -helix, β-sheet, loops) • • several secondary structure elements form

motifs

e.g. greek key, β-α-β, HTH

• tertiary structure (the arrangements of motifs into

domain/s

) • quartenary structure (multimeric complexes)

Proteins

source:http://calstate.fullerton.edu/news/arts/2003/photos/protein-art.jpg

Proteins

source: Petsko, Ringe – Protein structure and function

http://www.cellsignal.com/reference/pathway/NF_kappaB.html

Systems biology

• focuses on the systematic study of complex interactions in biological systems using a new perspective - holism instead of reductionism •

holism

– the properties of a system cannot be determined or explained by its component parts alone • one of the goals of systems biology is to discover new emergent properties • new field, boom since 2000, very little covered in CZ

Systems biology

source: wikipedia.org

Systems biology

• based on mathematical modelling of systems, control theory, cybernetics • engineering view on complex biological systems • e.g. answers questions about robustness of the given system when one of its part fails • or about response of a systems upon the change of the environmental conditions

quantum chemistry molecular dynamics bioinformatics systems biology

Bioinformatics

• application of information technology to the field of molecular biology, genomics and related biological disciplines • tremendous amount of data • the creation and advancement of databases, algorithms, computational and statistical techniques, and theory to solve problems arising from the management and analysis of biological data

Podle definičního třídění ruských vědců rozlišujeme dva obory paranormálních jevů:

bioinformatika

bioenergetika. Bioinformatika (tzn. mimosmyslové vnímání, ESP) zahrnuje získávání a výměnu informací mimosmyslovou cestou (nikoli normálními smyslovými orgány). V podstatě rozlišujeme následující formy bioinformace: hypnózu (kontrolu vědomí), telepatii, dálkové vnímání, prekognici, retrokognici, mimotělní zkušenost, "vidění" rukama nebo jinými částmi těla, inspiraci a zjevení. a

zdroj: http://www.esoterika.cz/clanek/2992-mimosmyslova_spionaz_dalkove_pozorovani_i_.htm

Bioinformatics

• sequence analysis (sequence bioinformatics) • structural analysis (structural bioinformatics) • functional analysis (systems biology)

• • • genetic code gene genome, genomics • • large data sets high throughput • human genome • DNA localized mainly in nucleus, each nucleus carries the whole genetic information • • • 3.2 billions bp 25 000 – 30 000 genes ca 1,5 % codes for proteins, the rest - junk DNA • what is proteome?

• proteomics • Is it more difficult to study genome or proteome?

Sequential bioinformatics

• reconstruction of sequence fragments • searching of genes and other interesting regions in the genome •

junk DNA

– 95% of human genome is made by non-coding sequences, either no function, or not yet understood • querying huge genomes for a given sequence • comparison of genes within a specie – similarities between protein functions • comparison of genes between species – organism's evolutionary relationships (phylogenetic analysis)

Sequence alignment

• Procedure of comparing sequences • Point mutations – easy ACGTCTGAT

A

CGCC

G

TAT

A

GTCTATCT ACGTCTGAT

T

CGCC

C

TAT

C

GTCTATCT • More difficult example

AC

G

TC

T

GAT

A

CGCCG

TAT

AGTCTATCT CT

G

AT

T

CGC

A

TCGTC

TAT

CT

gapless alignment • However, gaps can be inserted to get something like this insertion × deletion indel ACGTCTGAT

A

CGCCGTAT

A

GTCTATCT ----CTGAT

T

CGC---AT

C

GTCTATCT gapped alignment

Flavors of sequence alignment

pair-wise alignment

×

multiple sequence alignment

Flavors of sequence alignment

global alignment

×

local alignment

global local align entire sequence stretches of sequence with the highest density of matches are aligned, generating islands of matches or subalignments in the aligned sequences

Scoring systems I

• DNA and protein sequences can be aligned so that the number of identically matching pairs is maximized. A T T G - - - T A – - G A C A T • Counting the number of matches gives us a score (3 in this case). Higher score means better alignment.

• This procedure can be formalized using

substitution matrix

.

A T C G Identity matrix A T C G 1 0 0 0 1 0 0 1 0 1

Scoring systems II

• For nucleotide sequences identity matrix is usually good enough.

• • For protein sequences, identity matrix is not sufficient to describe biological and evolutionary proceses.

It’s because amino acids are not exchanged with the same probability as can be conceived theoretically.

• For example substitution of aspartic acids D by glutamic acid E is frequently observed. And change from aspartic acid to tryptophan W is very rare.

• Why is that?

1.

2.

Triplet-based genetic code GAT (D) → GAA (E), GAT (D) → TGG (W) Both D and E have similar properties, but D and W differ considerably. D is hydrophylic, W is hydrophobic, D → W mutation can greatly alter 3D structure and consequently function.

Substitution matrices

small, polar small, nonpolar polar or acidic

Zvelebil, Baum, Understanding bioinformatics .

Positive score

– frequency of substitutions is greater than would have occurred by random chance.

Zero score

– frequency is equal to that expected by chance.

Negative score

– frequency is less than would have occurred by random chance.

basic large, hydrophobic aromatic

Sequence database search

BLAST Google of sequence world

Phylogenetic analysis

Structural bioinformatics

• • the function of chemical moiety is given by its structure while DNA structure is “given” (double-helix), RNA and proteins can accommodate very different conformations (i.e. specific arrangements of atoms in 3D space) • structural bioinformatics covers • • analysis of the NA and proteins structure prediction of structure from the sequence

Protein structure prediction

• secondary structure prediction • the conformational state of each residue is predicted as H (helix), E (extended, β-sheet), C (coil) • accuracy: 80% • tertiary structure prediction • why?

• many sequences are known, not that many 3D structures has been solved • some proteins (e.g. transmembrane) are difficult to characterize experimentally • many proteins have known function, but unknown structure (which is however needed to understand their behavior in detail) • ab initio, threading, homology modelling

CASP

• Critical Assessment of Structure Prediction • http://predictioncenter.org/ • since 1994, every 2 years, CASP10 in preparation • predict solved, but not publicly released structures • competition of individual groups in 3D prediction: • • human groups – answer in 14 days software (automated prediction) – answer in 48 hours