Introduction to Protein Structure Analysis, autumn session

Introduction to Protein Structure Analysis, autumn session

basic bioinformatics
Location:

        

Start date:

31 August 2020

General context

Depending on the status of COVID19, this session can be face to face or online.

Please register if you're interested in this training. One month after we reach 15 registrations the training will be organized. 

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This training session will provide the basics of protein structure determination and how this information is stored in databases. We will explore and search in online databases containing protein structure information. With the aid of the Yasara View program we will visualize the structure. Different hands-on exercises will allow you to compare the structure of homologues, to predict a structural model of proteins (without any structure information) and to find homologous structures. We will use online tools to quantify various interactions in the structures.

Objectives
  • Get to know the data generated from protein structure determination experiments (high-resolution NMR spectroscopy, X-ray crystallography, electron microscopy, ...) and where to get it.
  • Display protein structure data and compare structures, through the use of Yasara.
  • Create high-quality graphical representations of the structures.
  • Calculate the effect of mutations on the stability of your protein.
Required skills

You are encouraged to use your own laptop. For those who do not have a laptop, the YASARA software can be run in a remote Linux environment (access to cloud via webbrowser).

Software demonstrated

Trainers

Alexander Botzki

Alexander Botzki is head of the VIB Bioinformatics Core

Contact Alexander Botzki :

Program

Exploring the Protein Data Bank and related databases.

Assessing the quality of a structure and the information that can be derived from it

Visualizing protein structures (YASARA)

Comparing structures

Predicting the effect of point mutations on protein structures

Predicting protein structures of close homologues by homology modeling