CMSC423: Bioinformatic Algorithms, Databases and ToolsLecture 21Protein foldingProteomicsMass spectrometryProtein folding• Note: mis-folded proteins may cause disease (e.g. Creutzfeld-Jakob a.k.a. mad cow)• Drugs (e.g. antibiotics) often inhibit protein function – knowing structure can help design drugs•Folding@home – lend your computer’s unused cycles to help fold proteins (like SETI@home) (do you believe in evolution or aliens ?)Protein structure (primary structure = sequence)http://www.tulane.edu/~biochem/med/second.htmφψhttp://web.mit.edu/esgbio/www/lm/proteins/aa/aminoacids.htmlhate waterlike watercan’t decideNot all bends equally likelyRamachandran plotSecondary structure (motifs)helixsheetturnhttp://alpha2.bmc.uu.se/~kenth/bioinfo/structure/secondary/01.htmlTertiary structure (3D shape)http://www.umass.edu/microbio/rasmol/sayle1.htmFolded shape: lowest free energy• Energy components– electrostatic (~1/D2) (n2 terms)–van der Waals (n2 terms)– hydrogen bonding (n terms)–“bending” (n terms)– solvent (water/salt) (?? terms)–exclusion principle (no two atoms share same volume)•Energy minimzation–small perturbations & computation: hill climbing, simulated annealing, etc.•Molecular dynamicsHow do we know the truth?•X-ray crystallography–crystallize protein–shine X-rays–examine diffraction patterns•Nuclear Magnetic Resonance (NMR)–no crystallization necessary–magnetic field “vibrates” hydrogen atoms–Nobel prize: Kurt Wuethrichhttp://www.cryst.bbk.ac.uk/BBS/whatis/cryst_an.htmlhttp://www.cryst.bbk.ac.uk/PPS2/projects/schirra/html/2dnmr.htmSimpler problems•Secondary structure prediction•Side-chain conformation (assuming fixed backbone)•Protein docking (how do proteins interact)•Database searches (protein threading)•Simpler energy functions •Folding on a lattice (theoretical approximation)•Critical Assessment of Fully Automated Structure Prediction – competition on proteins with unpublished 3D structureProteomics•Large-scale analysis of proteins–protein-protein interactions (e.g. yeast 2-hybrid)–2D gels (mass vs. isoelectric point)–Mass-spectrometry–Protein microarrays–etc.Proteomics• Why proteomics? Are DNA/RNA microarrays not sufficient?• RNA abundance is not necessarily related to protein abundance•Many proteins are modified post-translation– addition of additional molecules (phosphate, sugars, etc.)–creation of complexes (hemoglobin is actually 4 molecules)Mass spectrometry•Technique for measuring the mass-to-charge ratio of ions•Basic idea–shoot ions into a magnetic field–deflection depends on mass•Output of a mass-spectrometer–ions “sorted” by mass–for each mass bucket - number of ions with that specific massMass-spectrometryhttp://www.cem.msu.edu/~reusch/VirtualText/Spectrpy/MassSpec/masspec1.htmTandem Mass Spectrometry•First mass-spectrometer “focuses” on a specific protein•Second mass-spectrometer breaks the protein into smaller chunks•Problem: given the chunks, what was the original protein?Peptide sequencing•Peptide - a chunk of a protein, usually obtained by enzymatic cleavage of the protein (using trypsin)•Problem: Given an MS spectrum (weights of fragments), what was the sequence of the peptide? •Or: find the peptide (of mass m) that best matches the experimental dataMS Algorithms•Database search–build database of “all possible” peptides (better - all peptides observed in known proteins)–match experimental spectrum to the database–closest hit is our peptide•“Assembly” (de novo sequencing)–start with a spectrum–identify masses that likely represent the same fragment–build graph (spectral graph) that represents adjacency of fragments•nodes = fragments (or ion types)•edges = edge v->w indicates fragments v and w differ by exactly 1 amino-acid–path through this graph represents a peptide sequenceSome Mass Differences between Peaks Correspond to Amino
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