Title:Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta
Volume: 24
Issue: 3
Author(s): Jad Abbass and Jean-Christophe Nebel
Affiliation:
Keywords:
Rosetta, ab initio protein structure prediction, fragment-based protein structure prediction, CATH, protein
structural class, 9-mers, 3-mers.
Abstract: Protein structure prediction is considered a main challenge in computational biology. The
biannual international competition, Critical Assessment of protein Structure Prediction (CASP), has
shown in its eleventh experiment that free modelling target predictions are still beyond reliable accuracy,
therefore, much effort should be made to improve ab initio methods. Arguably, Rosetta is considered
as the most competitive method when it comes to targets with no homologues. Relying on
fragments of length 9 and 3 from known structures, Rosetta creates putative structures by assembling
candidate fragments. Generally, the structure with the lowest energy score, also known as first
model, is chosen to be the “predicted one”.
A thorough study has been conducted on the role and diversity of 3-mers involved in Rosetta’s
model “refinement” phase. Usage of the standard number of 3-mers – i.e. 200 – has been shown to
degrade alpha and alpha-beta protein conformations initially achieved by assembling 9-mers. Therefore,
a new prediction pipeline is proposed for Rosetta where the “refinement” phase is customised
according to a target’s structural class prediction. Over 8% improvement in terms of first model
structure accuracy is reported for alpha and alpha-beta classes when decreasing the number of 3-
mers.
