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Objectives

Team

Main objective:

Find and implement a fast and accurate method for assigning charges in OFF toolkit. Test the influence of charges and LJ parameters on force field accuracy / parameterization protocols. 

Project owner: Michael Schauperl (Deactivated)

Objectives for 2020:

Team members: Michael Gilson John Chodera Hyesu Jang

Problem Space

Scientific questions

  • Is the current charge model optimal?

    • Can we use ML for quick charge assignment?

  • BCC reparameterization

  • RESP:

    • High-quality bespoke charges via multiconformer RESP-like methods

    • How do alternate RESP models impact accuracy?

    • ESP data on QCArchive?

  • How much do virtual sites help?

  • How much does polarization help? Which model (Drude, point polarizable, fluc-q) is best, or how do they compare?

  • Do we have right LJ types / type refinement?

  • Fitting electrostatics to condensed phase data - how? Which parameters?

  • Benchmarking results for different charge models 

Possible solutions

Ongoing Work

Problem Owner

Problem

Solution

Personal space

Infrastructure requirements

  • Library charge implementation in OFF toolkit

  • BCC support

  • RESP implementation / support

  • Graph convolutional network (GCN) charges and WBOs

  • Fast, free replacements for AM1-BCC and WBO

    • Conformer generation and quantum chemistry

    • Graph convolutional networks

Data resources

Notes

  • AMBER, GROMACS and OpenMM have capability of running simulations with off-site charges. The problem is that not all off-site charges will work in all packages. We got the specific ones we want implemented in OpenMM, but not all are necessarily available in AMBER and GROMACS..

Idea Bucket

This is the space to collect scientific questions, ideas, solution proposals, etc for future work in chemical perception space

Idea Owner

Idea

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