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.

报告人简介: Dr. Marcin J. Skwark obtained his doctor degree from Stockholm University, and is now a postdoctoral researcher at Aalto University, Finland. His research interest is protein structure prediction.