First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
Faculty of Medicine and Surgery
MEDICAL BIOTECHNOLOGIES
Course unit
PROTEOMICS AND BIOINFORMATICS
MEO2045677, A.A. 2012/13

Information concerning the students who enrolled in A.Y. 2012/13

Information on the course unit
Degree course Second cycle degree in
MEDICAL BIOTECHNOLOGIES
ME1934, Degree course structure A.Y. 2012/13, A.Y. 2012/13
N0
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination PROTEOMICS AND BIOINFORMATICS
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit CANNOT be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge STEFANO TOPPO BIO/10

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses BIO/10 Biochemistry 6.0

Course unit organization
Period First semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 6.0 48 102.0 No turn

Calendar
Start of activities 01/10/2012
End of activities 26/01/2013
Show course schedule 2019/20 Reg.2012 course timetable

Examination board
Board From To Members of the board
7 Commissione 2019/2020 01/10/2019 30/10/2020 TOPPO STEFANO (Presidente)
LOREGIAN ARIANNA (Membro Effettivo)
6 Commissione 2018/19 01/10/2018 30/09/2019 TOPPO STEFANO (Presidente)
LOREGIAN ARIANNA (Membro Effettivo)
5 Commissione 2017/18 01/10/2017 30/09/2018 TOPPO STEFANO (Presidente)
LOREGIAN ARIANNA (Membro Effettivo)
4 Commissione 01/10/2016 30/09/2017 TOPPO STEFANO (Presidente)
LOREGIAN ARIANNA (Membro Effettivo)
3 Commissione 2015/16 01/10/2015 31/12/2018 TOPPO STEFANO (Presidente)
LOREGIAN ARIANNA (Membro Effettivo)
2 Commissione 2014/2015 01/10/2014 30/09/2015 TOPPO STEFANO (Presidente)
LOREGIAN ARIANNA (Membro Effettivo)
1 Commissione 2013/2014 01/10/2013 30/09/2014 TOPPO STEFANO (Presidente)
LOREGIAN ARIANNA (Membro Effettivo)

Syllabus
Prerequisites:
Target skills and knowledge:: The course aims to provide students with basic concepts of structure and function of proteins, Mass Spectrometry in proteomics, and bioinformatics in the field of protein alignments and structure prediction
Course unit contents: PROTEOMICS AND BIOINFORMATICS

The course is focused on aspects dealing with protein structure and folding, mass spectrometry in proteomics, and structural bioinformatics. The following are the points that are treated:

PROTEOMICS

1) Amino acids: general properties, pKa, stereochemistry, peptide bond, classification, separation techniques, Reactions of amino acids, Edman degradation, dihedral angle, Ramachandran plot
2) Secondary structure: alpha helix, 3-10 helix, helix capping, helix properties, amphiphilicity, fibrous proteins, coiled-coil, collagen, beta strand parallel and anti-parallel, beta hairpin, beta turns type I, II
3) Supersecondary structure elements: description of alpha-alpha, beta-alpha-beta, and other motifs part of protein repeats. LLR, Ankyrin, Beta helix.
4) Protein domains: organization, classification and description of protein domains. List of most common domain motifs and features of packing rules as helix bundles.
5) Novel theories of finding protein domains in structures using layers.
6) Brief description of multimeric proteins, quaternary structures
7) Description of most common folds
8) Interactions forces in proteins from quantum chemistry to molecular mechanics and dynamics
9) Introduction to force fields in molecular mechanics and the different interaction forces bonded and non-bonded.
10) 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
11) Protein folding in the cell: Folding Accessory proteins and mechanism in Eukaryotes and Prokaryotes: PDI, GroEL/GroES, Heat Shock Proteins. Brief introduction to protein misfolding, amyloid formation
12) Conformational diversity and protein evolution
13) Mass spectrometry MS: the basic principles of proteomics techniques up to mass spectrometry present era
14) Description of MS instrumentations: ESI and MALDI sources. Mass Analyzers: Quadrupole, stability diagram, Mathieu equations. 3D and linear Ion Trap: stability diagram and working process as ion ejections and fragmentation. Time Of Flight and equations of ion trajectories. Orbitrap basic principles
15) Mass Spectrum interpretation: m/z ion detection, isotope distribution, mass accuracy, resolution, Deconvolution and charge state determination
16) Fragmentation rules and ion series
17) MS fingerprinting and MS/MS data identification analysis
18) Interpreting a MS/MS spectrum: algorithms techniques implemented in Mascot and Sequest, PeptideProphet
19) Parametric and non-parametric methods, FDR, decoy sets, spectral clustering
20) Mass spectrometry quantification techniques: label free, tag-based techniques
21) Signal processing, statistical analysis, normalization, Clustering and classification, Gene Set Enrichment Analysis (GSEA), Hypergeometric testing, Statistical experiment design

BIOINFORMATICS (see extended program section)
Planned learning activities: 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. Introduction of molecular phylogeny concepts, neighbor joining
10) Patterns: how to build a sequence pattern
11) Frequency matrices and protein profiles
12) PSI-BLAST and the PSSM
13) Markov chains and Hidden Markov Chains (HMM).
14) Machine learning: Neural Networks an introduction.
15) Protein structure prediction from 3D structures; DSSP and STRIDE
16) Secondary protein structure prediction: from Chou-Fasmann, GOR to second generation techniques based on multiple alignments and third generation strategies based on Neural Networks. Pros and Cons, Benchmarking evaluation scores. The meta server approach
17) Structural modeling from Comparative modeling to Fold recognition techniques
18) Comparative modeling: steps to create the final model; template, alignment, raw model, loop modeling, sidechain placement, refinement.
19) Fold recognition strategies. Threading techniques, back-validation of low scoring hits, secondary structures alignments, meta-servers
Textbooks:
Teaching methods: theoretical lectures
Assessment criteria: test with open-ended questions on the entire contents of the course
Further information: