PROTEOMICS AND BIOINFORMATICS

Second cycle degree in MEDICAL BIOTECHNOLOGIES

Campus: PADOVA

Language: English

Teaching period: First Semester

Lecturer: STEFANO TOPPO

Number of ECTS credits allocated: 6


Syllabus
Prerequisites: Good knowledge of spoken and written English is required
Examination methods: The examination is typically 1 hour and a half in length and closed book in format. The test is with open-ended questions on the entire contents of the course. Also planned seminar activity and evaluation
Course unit contents: BIOCHEMICAL CONCEPTS

1) Basic concepts on general properties of amino acids, secondary structures, protein domains, and common folds
2) Interactions forces in proteins from quantum chemistry to molecular mechanics and dynamics
3) Introduction to force fields in molecular mechanics and the different interaction forces bonded and non-bonded.
4) Protein folding from Anfisen to modern theories: hydrophobic collapse, diffusion and collision, funnel theories and the Levinthal’s paradox. Lattice simulations in a Hydrophobic Polar model
5) Protein folding in the cell: Folding Accessory proteins and mechanism in Eukaryotes and Prokaryotes: PDI, GroEL/GroES, Heat Shock Proteins. Brief introduction to ER stress and protein misfolding, amyloid formation


MASS SPECTROMETRY IN PROTEOMICS

1) Mass spectrometry MS: the basic principles of proteomics techniques up to mass spectrometry present era
2) Description of MS instrumentations
a. ESI and MALDI sources
b. Mass Analyzers: Quadrupole, stability diagram, Mathieu equations
c. 3D and linear Ion Trap: stability diagram and working process as ion ejections and fragmentation
d. Time Of Flight and equations of ion trajectories
e. Orbitrap basic principles
3) Mass Spectrum interpretation: m/z ion detection, isotope distribution, mass accuracy, resolution, Deconvolution and charge state determination
4) Fragmentation rules and ion series
5) MS fingerprinting and MS/MS data identification analysis
6) Interpreting a MS/MS spectrum: algorithms techniques implemented in Mascot and Sequest, PeptideProphet
7) Parametric and non-parametric methods, FDR, decoy sets, spectral clustering
8) Mass spectrometry quantification techniques: label free, tag-based techniques
9) Signal processing, statistical analysis, normalization, Clustering and classification, Gene Set Enrichment Analysis (GSEA), Hypergeometric testing, Statistical experiment design


BIOINFORMATICS

1) Sequence alignments algorithms: motivation
2) Brief introductions to issues and unsolved questions from phylogenetic analysis to protein structure and function. Structural evolutionary models, folds and protein disorders
3) Dot Plot analysis, repeat and inverse repeats
4) Sequence alignment scores: random vs. match model to calculate the alignment score
5) Scoring matrices: PAM and BLOSUM
6) Local (Smith and Waterman), global (Needleman-Wunsch), freeshift algorithms
7) K-tuple algorithms: BLAST and FASTA for database searches, introduction to raw score, bitscore, e-value, detailed FASTA, BLAST algorithms steps
8) Confusion matrices, ROC curves
9) Multiple alignments: progressive and iterative strategies. The operation of CLUSTAL , introduction of molecular phylogeny concepts, neighbor joining
10) Patterns and Profiles
11) Structural modeling from Comparative modeling to Fold recognition techniques
12) Gene Ontology and protein function prediction