Non-Bonded Protein Interactions for Larger Proteins
Implemented features to handle larger proteins. This required implementing MPI in order to distribute the protein data and calculation onto multiple cores to deal with scaling to larger proteins. This also required implementing a new coarse-grained model that defines generic non-native interactions to reduce the number of adjustable parameters thereby reducing the search space of protein model parameters.
Updated Features
- Implemented non-bonded pair interactions into a protein model. (requires pysph)
- Implemented parallelization using the mpi4py package to improve scaling to larger proteins and larger data-sets.
- Model loaders now work so that models can be loaded in parallel.
- Implemented helper functions that partition the data onto multiple cores based upon the discrete state assignment of the protein conformation.
- Compute the quality factor in a distributed manner thereby speeding up the computation.
Dependencies
- model_builder (https://github.com/ajkluber/model_builder)
- mdtraj
- numpy
- scipy
- multiprocessing
- mpi4py
- pysph (https://pysph.readthedocs.io/en/latest/)
See publication: Chen, J., Chen, J., Pinamonti, G. & Clementi, C. Learning Effective Molecular Models from Experimental Observables. J. Chem. Theory Comput. 14, 3849–3858 (2018).