Our new preprint just dropped on ChemRxiv:
Model selection using replica averaging with Bayesian inference of conformational populations.
Raddi RM, Marshall T, Ge Y, Voelz V. https://doi.org/10.26434/chemrxiv-2023-396mm
In this work, we describe and demonstrate with examples how equipping our BICePs algorithm with a replica-averaged forward model makes it a Maximum-Entropy reweighting method with some key advantages:
- It is a post-processing method that does not require restraints implemented inside simulations
- Heuristic estimates of uncertainty are not needed; posterior sampling enables learning uncertainties from the data
- BICePs has improved likelihood models to account for outliers
- The BICePs score can be used for objective model selection
- Automated force field and forward model parameterization can be performed using the BICePs score as an objective function.
I recently spoke about this work at the ACS Fall 2023 symposium “Emerging Techniques to Quantify Biomolecular Conformational Ensembles” symposium.