* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download A common ancestor
Frameshift mutation wikipedia , lookup
Koinophilia wikipedia , lookup
Protein moonlighting wikipedia , lookup
Microevolution wikipedia , lookup
Therapeutic gene modulation wikipedia , lookup
Quantitative comparative linguistics wikipedia , lookup
Human genome wikipedia , lookup
No-SCAR (Scarless Cas9 Assisted Recombineering) Genome Editing wikipedia , lookup
Non-coding DNA wikipedia , lookup
Genetic code wikipedia , lookup
Microsatellite wikipedia , lookup
Point mutation wikipedia , lookup
Artificial gene synthesis wikipedia , lookup
Helitron (biology) wikipedia , lookup
Genome editing wikipedia , lookup
Metagenomics wikipedia , lookup
Computational phylogenetics wikipedia , lookup
Smith–Waterman algorithm wikipedia , lookup
Evolutionary and Genetic Origins of Protein Sequences Voet-Voet Chapter 7.3A-7.3B Petsko-Ringe 4.0 to 4.3 A common ancestor • All organisms are similar at the molecular level • Why? • The higher the level of biochemical organization, the greater the molecular differences among species 1 Phylogenetic tree Similar sequence imply descent from a common ancestor • 1000 nucleotides (~333 aa) – 41000 or 10600 different sequences – ~1079 atoms in the universe 100 amino acids - 20100 or 10130 different sequences 2 Genes and proteins • When are they homologues? Partial homology • % similarity vs % homology Lys Arg Asp Glu Ser Thr Tyr Phe Trp Ala Val Leu Ile Met Similarity vs Identity • % sequence similarity – S = [(Ls x 2)/ (La + Lb)] x 100 • % sequence identity – I = [(Li x 2)/ (La + Lb)] x 100 – or I = Li/La% 3 E-values: probability that the two sequences will have this degree of overall similarity by chance single domain multidomain Functional assignment from sequence comparison none fold function Enzymes Non-enzymes fold What can be predicted from sequence comparison? 4 Detecting sequence homology • Sequence alignment and comparison – Curr. Op. Struc. Biol. 15, 254 (2005) – Curr. Op. Struc. Biol. 15, 261 (2005) – Curr. Op. Struc. Biol. 16, 368 (2006) – Curr. Op. Struc. Biol. 16, 374 (2006) Pairwise Sequence Alignment • Methods – Global alignment • Closely related sequences • Similar length – Local alignment • Divergent sequences • Different length • Identify domains or motifs 5 Alignment Algorithms • Dot matrix method – Visually identify similar regions http://bioweb.pasteur.fr/seqanal/interfaces/dotmatcher.html • Dynamic programming method – To find optimal alignments Use scoring matrices (PAM, BLOSUM) and gap penalties • Word method Database similarity searching (BLAST, FASTA) Comparing homologous proteins • Essential residues for its function • Less significant • Little specific function 6 Invariant Conservatively substituted Hypervariable 7 Phylogenetic tree of cytochrome c Rates of evolution Unit of evolutionary period 8 Mutations rates are constant in time Errors in replication or random chemical degradation 9