Ranking beta sheet topologies of proteins – Københavns Universitet

Ranking beta sheet topologies of proteins

Rasmus Fonseca, Glennie Helles and Pawel Winter

Proc. of the Int. Conf. on Computational Biology ICCB'10, San Francisco, USA, October 2010. 

Abstract: One of the main reasons why ab initio protein structure predictors do not perform very well is their inability to reliably identify long-range interactions between amino acids. To achieve reliable long-range interactions, all potential pairings of beta-strands (beta-topologies) of a given protein are enumerated. The beta-topologies are enumerated such that it is certain that the native beta-topology is among the enumerated. [full abstract] Two very different beta-topology scoring methods from the literature are used to rank potential beta-topologies. This has not previously been attempted for any scoring method. The main result of this paper is that in particular one of the scoring methods consistently top-ranks native beta-topologies.

Since the number of potential beta-topologies grows exponentially with the number of beta-strands, it is unrealistic to expect that all potential beta-topologies can be enumerated and scored for large proteins. The second result of this paper is an enumeration scheme of a subset of beta-topologies. It is shown that native-consistent beta-topologies often are among the top-ranked beta-topologies of this subset.

The presence of the native or native-consistent beta-topologies in the subset of enumerated potential beta-topologies relies heavily on the correct identification of strands. The third contribution of this paper is a method to deal with the inaccuracies of secondary structure predictors when enumerating potential beta-topologies.

The results reported in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. They indicate that decoy generation can be constrained using top-ranked beta-topologies as they are very likely to contain native or native-consistent beta-topologies.