Optimizing protein structures with NOVA
One of the conclusions drawn at the last two
CASP meetings in Asilomar was that applying various force fields during refinement of template-based models tends to move predictions in the wrong direction
- away from the experimentally determined coordinates. NOVA is an all-atom force field aimed at protei
n + nucleotide optimization in vacuo which has been specifically designed to avoid this problem. NOVA resembles common molecular dynamics force fields,
but has been automatically parameterized with two major goals:
The NOVA force field has been relaunched in January 2012, with much higher performance (SIMD&multi core support), much higher accuracy (knowledge-based potentials), and automatic force field parameter assignment for organic molecules. More details about the improved NOVA force field can be found here.
Figure 1: The average RMSD between models and targets during an extensive energy minimization of
14 homology models with two different force fields. Both force fields improve the models during the first
~500 energy minimization steps but then the small errors sum up in the classic force field and guide the minimization in the wrong direction,
away from the target, while the self-parameterizing NOVA force field goes in the right direction. To reach experimental accuracy,
the minimization would have to proceed all the way down to ~0.5 Å which is the uncertainty in experimentally determined coordinates.