Consensus-based protein structure prediction by means of distance restraints

by Marcin Skwark (SBC)

Wednesday 10 Mar 2010, 16:00 → 17:00 Europe/Stockholm

RB35 (RB35)

Predicting 3D protein structures is an important task of contemporary computational biology, due to the high cost and low throughput of experimental methods. It has been empirically shown, that prediction approaches depending on diverse methods and selecting the most suitable models result in greater accuracy than any other approach. One of such methods is Pcons.net, developed locally at SBC/CBR.

The problem behind consensus methods is that they are only able to perform as well as the best of their compound methods. Therefore, in their intrinsic form, their are not able to to devise a model better than any of the ones obtained from the input predictors. Taking into account the vast amount of information contained within the input models, it should be possible to create a method, that would not only select the best model, but rather identify the prevalent structural features and produce a superior model basing on them.

I will talk about one of the attempts of harnessing the structural information contained within the individual protein structure models and its preliminary results. The approach I will talk about is based on inter-atom distance statistics and for some protein sequences it is able to produce models of higher quality than any other method. This, in connection to the method's speed (compound methods' time plus less than 15 minutes) makes it a viable method for real-life structure predictions.