Área de Concentração: 95131

Concentration area: 95131

Criação: 12/07/2016

Creation: 12/07/2016

Ativação: 09/08/2016

Activation: 09/08/2016

Nr. de Créditos: 4

Credits: 4

Carga Horária:

Workload:

Docentes Responsáveis:

Professors:

Fernando Luis Barroso da Silva

Catherine Jeanne Chantal Etchebest

Objetivos:

Objectives:

 To explain how bioinformatics helps in gaining information about protein structure and function, how this new field is accompanying biologists in their daily work, and why physical-chemistry is extremely valuable to go further in the understanding of protein function. The course could include the lectures described above plus an introduction to explain what is bioinformatics, what is the daily environment of a bioinformatician (description of Linux, database and classical websites)

Justificativa:

Rationale:

Bioinformatics is now routinely used in labs and pharmaceutical companies. It is important to better know bioinformatics methods and approaches but also importantly their limits.

Conteúdo:

Part A: Data and Methods of Bioinformatics. How to get Structural and Functional information from protein or RNA sequence Biological Databases A survey of the most important databases: Their content and organization UniProt, Uniref, STING. Pairwise and Multiple Sequence Alignment Algorithms: Methods and Tools: The course explains i) the principles of dynamical programming with the two main algorithms (Needleman & Wunsch, Smith & Waterman) used to compare two sequences at a local and global level ii) the Blast algorithm iii) the principles of multiple sequences alignment and the difficulties to evaluate its relevance. 3D structures of proteins from sequence: Homology modeling, Threading methods, ab initio methods This course introduces the importance of 3D structure and the necessity of a well-defined 3D structure to accomplish a function. So it is devoted to the main principles of protein and RNA structure prediction. It introduces important notions like folds and folding, the importance of environment (e.g. soluble versus membrane proteins) and evolution notions e.g. homology. that are used in 3D models building, The second part is devoted to main algorithms of 3D structure predictions and associated tools (webservices) Prediction of mutation impact. Protein/Ligand-Protein interactions: from experimental techniques to in silico predictions The course briefly introduces in a first part the experimental concepts to get information about protein/ligand-protein interactions and in a second part, what are the methods and tools to get information about protein-protein interfaces. In a third part, specific methods for predicting small molecules (peptides, drugs)-protein interaction are briefly detailed. Part B: Molecular modeling and Dynamics of Biological Macromolecules: Energy and Force field: Potential Energy, Free Energy. The course describes a few physical principles and the simplifications made to calculate atomic interactions in a classical mechanics model. Energy Minimization: Why is it important and How Conformational space and energy landscape: Sampling The course describes the concept of conformational states related to the energy landscape of macromolecules. Methods to sample conformational space are introduced: MonteCarlo, Molecular Dynamics etc. A few examples of tools and free softwares

Content:

Part A: Data and Methods of Bioinformatics. How to get Structural and Functional information from protein or RNA sequence Biological Databases A survey of the most important databases: Their content and organization UniProt, Uniref, STING. Pairwise and Multiple Sequence Alignment Algorithms: Methods and Tools: The course explains i) the principles of dynamical programming with the two main algorithms (Needleman & Wunsch, Smith & Waterman) used to compare two sequences at a local and global level ii) the Blast algorithm iii) the principles of multiple sequences alignment and the difficulties to evaluate its relevance. 3D structures of proteins from sequence: Homology modeling, Threading methods, ab initio methods This course introduces the importance of 3D structure and the necessity of a well-defined 3D structure to accomplish a function. So it is devoted to the main principles of protein and RNA structure prediction. It introduces important notions like folds and folding, the importance of environment (e.g. soluble versus membrane proteins) and evolution notions e.g. homology. that are used in 3D models building, The second part is devoted to main algorithms of 3D structure predictions and associated tools (webservices) Prediction of mutation impact. Protein/Ligand-Protein interactions: from experimental techniques to in silico predictions The course briefly introduces in a first part the experimental concepts to get information about protein/ligand-protein interactions and in a second part, what are the methods and tools to get information about protein-protein interfaces. In a third part, specific methods for predicting small molecules (peptides, drugs)-protein interaction are briefly detailed. Part B: Molecular modeling and Dynamics of Biological Macromolecules: Energy and Force field: Potential Energy, Free Energy. The course describes a few physical principles and the simplifications made to calculate atomic interactions in a classical mechanics model. Energy Minimization: Why is it important and How Conformational space and energy landscape: Sampling The course describes the concept of conformational states related to the energy landscape of macromolecules. Methods to sample conformational space are introduced: MonteCarlo, Molecular Dynamics etc. A few examples of tools and free softwares

Forma de Avaliação:

Type of Assessment:

will be mainly on projects, reports and presentation

Observação:

The course covers the main topics dedicated to the analysis, prediction of 3D structures and conformational space. Theoretical concepts are introduced but also the tools to get information about protein and RNA structures. It starts with the description of the current knowledge about proteins and RNA, their importance in all the biological processes and the difficulty to get functional information from high-throughput sequencing experiments. It provides students with different approaches, i.e. the “how-to” and importantly the limits of the tools to predict and scrutinize 3D structures. The course makes the bridge between biology and chemistry to better understand functional mechanisms in relation with therapeutics goals.

Notes/Remarks:

The course covers the main topics dedicated to the analysis, prediction of 3D structures and conformational space. Theoretical concepts are introduced but also the tools to get information about protein and RNA structures. It starts with the description of the current knowledge about proteins and RNA, their importance in all the biological processes and the difficulty to get functional information from high-throughput sequencing experiments. It provides students with different approaches, i.e. the “how-to” and importantly the limits of the tools to predict and scrutinize 3D structures. The course makes the bridge between biology and chemistry to better understand functional mechanisms in relation with therapeutics goals.

Bibliografia:

1) Molecular Modelling: Principles and Applications, Andrew Leach, Pearson, 2001 2) Structural Bioinformatics, Jenny Gu & Philip E. Bourne (Editores), Wiley-Blackwell, 2009 3) Set of original research papers and reviews.

Bibliography:

1) Molecular Modelling: Principles and Applications, Andrew Leach, Pearson, 2001 2) Structural Bioinformatics, Jenny Gu & Philip E. Bourne (Editores), Wiley-Blackwell, 2009 3) Set of original research papers and reviews.