OpenFF Science Roadmap 2020

This scientific roadmap includes the next two planned force field releases and a list of scientific studies which need to be performed in 2020. Each study has a priority assigned to it. This roadmap will be continuously updated.

Force Fields

Upcoming force field versions:

Version	Codename	Features	Expected release date	Comment / Blocker

Version

Codename

Features

Expected release date

Comment / Blocker

openff-1.2.0

Parsley

Redesigned QM dataset for parameterization with better/broader coverage
Parameter fixes

Expected: May 2020

Released: Jun 3, 2020

openff-1.3.0

Parsley

Improvements to priors by element, etc., allowing for more accurate fitting
Filtering of molecules used in fitting certain torsions (esp. for amides) to improve parameter quality (came up in the progress of fixing a problem elsewhere)
Discussed in this release call: 2020-09-17 FF Release Meeting notes

When ready. September-December 2020.

openff-2.0.0

Sage

LJ refit (based on the ongoing feasibility study)
Limited WBO torsion interpolation for systems for which data already exists (more torsional data needed for a wide range application)

Exepected: Release date to be set by November 2020 and will have three month lead time. Likely release between December 2020 and Feb. 2021.

How fast can we do WBO interpolations (Pavan)
@Simon Boothroyd needs to get in touch with @David Hahn and folks from the Chodera lab to discuss some free energy benchmarking after LJ fitting
Late 2020/early 2021 still feasible

Scientific studies

The list of scientific studies which need to be performed in 2020, which will be updated every 3 months, as suggested in the science project management workflow. Each study should be linked to its Confluence page with more information about study design, execution and results. The study design should be submitted before study is about to begin.

Estimate start dates and end dates when possible before study has started. Record the real start and end dates for each study below the estimated dates.

Labels

Category	Labels

Category	Labels
Priority	high \| MEDIUM \| LOW
Effort	high \| MEDIUM \| LOW
Status	Not started \| In Progress \| PROTOTYPE \| Completed \| BLOCKED \|

Study	Priority	Effort	Science dependencies	Infrastructure dependencies	Comment	Start date	End date	Status	Driver/Team
Chemical perception
Addition of new parameters – manually fixing problems	high	high		Made easier by benchmarking dashboard (Optional)	Made easier by benchmarking dashboard (Optional			in progress	@Hyesu Jang @David Mobley @Jessica Maat (Deactivated) @Victoria Lim (Deactivated)
Automated typing inference from scratch	Medium	high			Organise a meeting to coordinate efforts. Update: @Tobias Huefner is doing some basic research, but we don’t have a timeline defined here. Perhaps a more specific study to look at typing issues similar to Schauperl’s work on LJ typing.			in progressSlowly	Full-time person needed – to be discussed further. Work of @Josh Fass (Deactivated) and @Tobias Huefner may assist here. @Owen Madin interested. @Trevor Gokey is also actively working in this area.
Mixture Properties
Binary Mixture Data Feasibility Study	high				In the writing stage.			COMPLETED	Driver: @Simon Boothroyd Team: @Michael Shirts @Owen Madin
Non-bonded optimization	high	high			Parent study for in a long-term progress stage.			in progress	Driver:@Simon Boothroyd Team: @Michael Shirts @Owen Madin
Chemical potential-like properties	MEdium		Non-bonded optimization	Implementation in `Evaluator`	Need to evaluate the data first (testing needed). Add Confluence page here.			In Progress PROTOTYPE	@Simon Boothroyd spinoff
Solvent-solvent partition coefficients	MEdium			Implementation in `Evaluator`	Data needed, harder problem. Update: Access to solubility phase, data is less of a problem now (MNSOL)			not started	@Simon Boothroyd spinoff
Data coverage and availability	high		Feasibility studies		Check the available data and identify missing data points. Worry in the future what to do about it. We will use what we have for Sage.			Ongoing	@Simon Boothroyd @Owen Madin @Michael Shirts
QM Data Generation
QM Data Selection (training data) for OpenFF-1.2.0	high				Need to expand to benchmarking set.			completed	@David Mobley @Jessica Maat (Deactivated) @Hyesu Jang
QM dataset selection for OpenFF-2.0.0	high							in progress	@David Mobley @Jessica Maat (Deactivated) @Hyesu Jang Lead: @Hyesu Jang ??
Benchmarking/re-evaluating our choice of QM theory	high			(Optional) QC Dataset submission infrastructure	Test of the whole torsiondrive. Keep within 10-50 torsiondrives. More is better. Some datasets ready, but analysis is still required (@Hyesu Jang ) Pavan might help with this. No changes made to our fitting data til after 2.0 release, but decision may be made before that (eg while fitting)			in progress	@Hyesu Jang lead; @Lee-Ping Wang @Pavan Behara @Hyesu Jang also leading molecule set selection with help from @Jessica Maat (Deactivated) and @Victoria Lim (Deactivated)
Protomer/tautomer enumerated molecules	high		QM level of theory validation (QMLoTV)	Protonation/tautomer enumeration integration (@Joshua Horton doing OE version in toolkit; there’s currently no good protonation state enumeration with RDKit – see )	It can only do enumeration with OpenEye			PRototyped	@Joshua Horton
Data selection for ionic species					What kind of experimental data would we need to include charged molecules?			NOt started	Lead: @Simon Boothroyd (oversight, to assemble team?)
Data on molecules with nonzero formal charges	high		QM level of theory validation (QMLoTV)	(Optional) QC Dataset submission infrastructure	Couples to benchmarking			NOt started	@Pavan Behara
Enamine REAL fragment coverage	MEDIUM			Automated fragmentation integration @Joshua Horton				in progress	@Trevor Gokey
Ligand Expo fragment coverage	MEDIUM			Automated fragmentation integration @Joshua Horton	Ligand Expo has higher priority than Enamine Real.			NOT started
Richer torsion data for WBO fitting	Low			WBO torsion implementation	What data to generate and				(person needed to continue work of @Chaya Stern (Deactivated); Will be @Pavan Behara with @Jessica Maat (Deactivated) , eventually coordinating with @Simon Boothroyd as he moves to his new position. )
Biopolymer data selection (ensure sidechain data is available in QCA)	high				One dataset ready, but a lot more data needs to be generated if we want sidechain sampling			in progress	@David Cerutti (Deactivated)
Biopolymer data computation	MEDIUM			(Optional) QC Dataset submission infrastructure				in progress	@David Cerutti (Deactivated) @David Dotson
More efficient torsion sampling with less grid points during scan	Low								spinoff
Fitting
Addition of new parameters – manually fixing problems	high	high				Ongoing		in progress	@Hyesu Jang @David Mobley @Jessica Maat (Deactivated) @Victoria Lim (Deactivated)
LJ refitting (Sage)	high		Non-bonded optimization					in progress	@Simon Boothroyd and @Owen Madin
WBO refitting (Sage)	high		More torsion data	WBO torsion implementation: Done.	Implement what Chaya has already done. Infrastructure ready. @Pavan Behara and @Jessica Maat (Deactivated) to divide up chemical space for fitting/test fixes. @Hyesu Jang will do central fitting of production FF. Additional discussion: https://openforcefield.atlassian.net/wiki/spaces/OFFO/pages/670629936/90-day+plan+Onboarding+for+Pavan+Behara?accessType=view&grantAccess=true&username=5f592e4d0b6be2006ef56679&userFullName=Pavan%20Behara#Notes-from-9%2F16%2F20-planning-meeting-(feel-free-to-migrate)	After May meeting	Late 2020 (Sep 2020)	in progress	@Jessica Maat (Deactivated) and @Pavan Behara . @Pavan Behara will eventually oversee.
BCC refitting	high		LJ refit Patterns for BCCs; could start with something simple like bond SMARTS.	ChargeIncrementModel implementation (early May)				in progress	@Simon Boothroyd @Owen Madin
Study how to set prior widths and weights for different sorts of data during FF optimization	medium