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Protein Structure Prediction

Dr. Marcin J. Skwark
The Finnish Centre of Excellence in
Computational Inference Research (COIN)
Aalto University, Finland

 
Abstract: Proteins are large molecules that living cells make by stringing together building blocks called amino acids or peptides, following their blue-prints in the DNA. Freshly made proteins are typically long, structure-less chains of peptides, but shortly afterwards most of them fold into characteristic structures. Proteins execute many functions in the cell, for which they need to have the right structure, which is therefore very important in determining what the proteins can do. The structure of a protein can be determined by X-ray diffraction and other experimental approaches which are all, to this day, somewhat labor-intensive and difficult. On the other hand, the order of the peptides in a protein can be read off from the DNA blue-print, and such protein sequences are today routinely produced in large numbers. It is known that protein structure is uniquely encoded by its sequence (s.c. Anfinsen's dogma). Therefore, it should be in theory possible to predict such structures computationally, basing on the previously established knowledge. This talk will present the problem of protein structure prediction, including the classic approaches to tackling this problem. Current state-of-art methods and their challenges will be discussed in the context of CASP (Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction) experiment. Finally, recent developments in the field, aiming at solving some of these challenges will be presented. 
  
About the Speaker: Marcin J. Skwark is a post-doctoral researcher at The Finnish Centre of Excellence in Computational Inference Research (COIN) at Aalto University, Finland. Marcin has received his PhD in theoretical chemistry at Stockholm University in 2013 with a dissertation on "Ensemble methods for protein structure prediction". He pursued undergraduate studies in computer science at \AA{}bo Akademi University, Finland. During his PhD studies, he has been a European Commission Marie Curie ITN "Transys" fellow, collaborating with experimental scientists from universities in UK, The Netherlands, Denmark and France, as well as working with the industrial biotechnologists at DSM in The Netherlands. His research interests lie in the area of protein bioinformatics, especially protein structure prediction and modeling biological systems with use of sparse and noisy data. The current research focuses on leveraging the growing amount of genomic data for modeling protein structures basing on predicted features and first principles, without relying on previously known structural data. He has been participating in CASP (Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction) since 2008, consistently ranking among the most successful prediction groups worldwide.
 
Date&Time: March 24, 2014 (Monday), 14:00 -15:00
Location: 606 Conference Room


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