, Our infrastructure automates ﬁtting, allowing force ﬁeld science and driving innovation Open Force Field: Improving the accuracy and applicability of open molecular models OpenFF partners with industry to build accurate, pre-competitive force ﬁelds for general use OpenFF 2.0.0 (Sage) is a leading public small molecule force ﬁeld OpenFF Toolkit Interchange External components BespokeFit Topology SMIRNOFF force ﬁeld (.offxml) Chemical structure ﬁle(s) (SMILES, .PDB, .SDF, etc.) Plugins ForceField SMIRNOFF: Assign parameters directly to chemistry Use of industry-standard SMARTS/SMIRKS chemical perception greatly simpliﬁes tooling for parameter assignment while solving issues with extensibility and ﬂexibility Protein parameters Rosemary OpenFF-3.0.0 Sage OpenFF-2.2.0 Parsley OpenFF-1.2.0 Parsley OpenFF-1.3.0 Sage OpenFF-2.1.0 Water model and ion parameters Rosemary OpenFF-3.1.0 Neural network charges Automated chemical perception General polarisability General neural network force ﬁeld Surrogate modelling Parsley OpenFF-1.1.0 Parsley OpenFF-1.0.0 First OpenFF force ﬁeld Sage OpenFF-2.0.0 Re-trained van der Waals’ 2019 – 2022 2023 2024 Thyme OpenFF-4.0.0 Virtual sites and BCCs Alternate functional forms Jeffrey Wagner, Open Force Field ACADEMIC INDUSTRY AbbVie Amgen Bayer Cresset Eli Lilly Janssen John Chodera (MSKCC) Michael Gilson (UC San Diego) David Mobley (UC Irvine) Michael Shirts (CU Boulder) OpenEye Pﬁzer Redesign Roche Ventus Vertex … and others Afﬁliates Simon Boothroyd (Psivant) Chapin Cavender (UCSD) Connor Davel (CU Boulder) Danny Cole (Newcastle) Lorenzo D’Amore (Janssen) Dennis Della Corte (BYU) PROJECT STAFF Lily Wang - Science Lead Jeff Wagner - Technical Lead Matt Thompson - Software Scientist David Dotson - Software Scientist Alexandra McIsaac - Staff Scientist Brent Westbrook - Staff Scientist Josh Mitchell - Scientiﬁc Communicator James Eastwood - Project Manager Trevor Gokey (UCI) David Hahn (Janssen) Josh Horton (Newcastle) Tobias Hüfner (UCSD) Meghan Osato (UCI) Ben Pritchard (MolSSI) Willa Wang (UCSD) Jeffry Setiadi (UCSD) Lee-Ping Wang (UCD) Yuanqing Wang (NYU) Marcus Weider (MSKCC) Prototype now available (*not the most up-to-date model!) OpenFF NAGL will use ML models to rapidly assign partial charges, even to large molecules Fitting self-consistent parameters for proteins and small molecules Null model: trained with extra data, no additional parameters Speciﬁc model: trained with extra data with additional parameters Performance equivalent to Sage Proﬁle shape mismatch Virtual sites are now a top priority for small molecule improvement HF/6-31G* Sage With virtual sites RMSD (A) length=1.469 A k=467.3 kcal/mol/A**2 The OpenFF community shares insights, experiences, code and workﬂows. More than a dozen industry partners participate. Contact: info@openforceﬁeld.org The OpenFF Software Ecosystem Where we’ve been and where we’re going Software and standards in the OpenFF ecosystem How to join OpenFF as an industrial partner Gapsys et al. JCIM 2022 Boothroyd et al. JCTC 2023 D’Amore et al. JCIM 2022 2023 OpenFF Keynote The SMIRNOFF speciﬁcation OpenFF-2.1.0 our most recent FF Notebook using NAGL prototype New wayﬁnding documentation