I have been using constraints to model protein structure using the AbinitioRelax protocol.
As my data is very noisy, it occurred to me that KofNConstraint could be a way to have more success.
However, I noticed that the use of KofNConstraint totally ignore the constraints in both centroid and full atom steps of the MonteCarlo trajectory (as Atom_pair_constraint vanishes from the scoring tables during the folding process) and it is used only to score the model at the end. That is, it seems my constraints are being ignored during the trajectory itself and it does not contribute to the gradient-based sampling.
The ideal would be to ignore k-n constraints that have the large violations but have the same behavior as in the absence of KofNConstraint: being used during the whole folding process.
Any ideas on how to turn on this behavior?