*Back to Mover page.*

The "off rotamer" sidechain-only Monte Carlo sampler. For a rather large setup cost, individual moves can be made efficiently.

The underlying mover is still under development/benchmarking, so it may or may not work with backbone flexibility or amino acid identity changes.

`<SidechainMC name="(&string)" ntrials="(10000 &int)" scorefxn="(score12 &string)" temperature="(1.0 &real)" inherit_scorefxn_temperature="(0 &bool)" preserve_detailed_balance="(1 &bool)" task_operations="(&string,&string,&string)" prob_uniform="(0.0 &real)" prob_withinrot="(0.0 &real)" prob_random_pert_current="(0.0 &real)"/>`

- ntrials: number of Monte Carlo trials to make per mover application - should be at least several thousand
- scorefxn: score function used for acceptance
- temperature: Boltzmann acceptance temperature - usually around 1.0
- inherit_scorefxn_temperature: override scorefxn and temperature with values from MetropolisHastings
- preserve_detailed_balance: balance acceptance criterion with proposal density ratio
- task_operations: list of operations for generating a PackerTask
- prob_uniform: probability of a "uniform" move - all sidechain chis are uniformly randomized between -180° and 180°
- prob_withinrot: "within rotamer" - sidechain chis are picked from the Dunbrack distribution for the current rotamer
- prob_random_pert_current: "random perturbation of current position" - the current sidechain chis are perturbed ±10° from their current positions, biased by the resulting Dunbrack energy. Note that if your score function contains a Dunbrack energy term, this will result in double counting issues.
- - If the previous three probabilities do not add to 1.0, the remainder is assigned to a "between rotamer" move - a random rotamer of the current amino acid is chosen, and chi angles for that rotamer are selected from the Dunbrack distribution

- SidechainMover
- TryRotamersMover
- PackRotamersMover
- I want to do x: Guide to choosing a mover