Continuous effort to improve our force field parameters for all molecules, fitting procedures and infrastructure by incorporating new scientific findings obtained through optimization and benchmarking cycles following every new force field generation.
Extend the SMIRNOFF typing scheme to produce fully consistent comprehensive biomolecular force fields (including biopolymers such as proteins and nucleic acids, lipids, carbohydrates, and other biomolecules).
Develop data-driven chemical perception models and efficient charge prediction methods to enable automated and accurate parameter assignment.
Build automated and reliable protocols and supporting infrastructure to compute and analyse physical properties, free energies of host-guest and protein-ligand systems, and conformational energy and geometry differences.
Curate or collect extensive biophysical and quantum chemical data needed to build and asses (bio)polymer and small molecule force fields.
Develop Bayesian-based methods to provide rigorous data-driven motivation for choice of functional forms, SMIRNOFF types and assessment of prediction accuracy.