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References

If you use Q2MM in your research, please cite the relevant publications below. Citing these works helps support continued development and gives proper credit to the contributors.

Core Method

  1. Norrby, P.-O. Selectivity in Asymmetric Synthesis from QM-Guided Molecular Mechanics. J. Mol. Struct. (THEOCHEM) 2000, 506, 9–16. DOI: 10.1016/S0166-1280(00)00398-5

    Introduces the foundational Q2MM approach — using quantum mechanical reference data to parameterize molecular mechanics force fields for predicting stereoselectivity in asymmetric catalysis.

  2. Hansen, E.; Rosales, A. R.; Tutkowski, B.; Norrby, P.-O.; Wiest, O. Prediction of Stereochemistry using Q2MM. Acc. Chem. Res. 2016, 49, 996–1005. DOI: 10.1021/acs.accounts.6b00037

    Comprehensive review of Q2MM methodology, covering the theoretical framework, parameter optimization workflow, and successful predictions of stereochemical outcomes in catalytic reactions.

  3. Rosales, A. R.; Quinn, T. R.; Wahlers, J.; Tomberg, A.; Zhang, X.; Helquist, P.; Wiest, O.; Norrby, P.-O. Application of Q2MM to Predictions in Stereoselective Synthesis. Chem. Commun. 2018, 54, 8294–8301. DOI: 10.1039/C8CC03695K

    Demonstrates application of Q2MM to predict stereoselectivity across diverse reaction types, validating the method's generality and predictive power.

QFUERZA / Seminario Method

  1. Farrugia, L. M.; Helquist, P.; Norrby, P.-O.; Wiest, O. Rapid FF Generation via Hessian-Informed Initial Parameters and Automated Refinement. J. Chem. Theory Comput. 2026, 22, 469–476. DOI: 10.1021/acs.jctc.4c01372

    Presents QFUERZA, combining the Seminario method (extracting force constants from QM Hessian eigenvalues) with automated Q2MM refinement for rapid, accurate force field generation.

Applications

  1. Rosales, A. R.; Wahlers, J.; Limé, E.; Meadows, R. E.; Leslie, K. W.; Savin, R.; Bell, F.; Hansen, E.; Helquist, P.; Munday, R. H.; Wiest, O.; Norrby, P.-O. Rapid Virtual Screening of Enantioselective Catalysts using CatVS. Nat. Catal. 2019, 2, 41–45. DOI: 10.1038/s41929-018-0193-3

    Introduces CatVS, a virtual screening platform that uses Q2MM-derived transition state force fields to rapidly evaluate catalyst libraries for enantioselectivity.

  2. Burai Patrascu, M.; Pottel, J.; Pinus, S.; Bezanson, M.; Norrby, P.-O.; Moitessier, N. Virtual Chemist: Prediction of Enantioselectivity. Nat. Catal. 2020, 3, 574–584. DOI: 10.1038/s41929-020-0467-0

    Integrates Q2MM with machine learning to predict enantioselectivity for a broader range of reactions and catalyst types.

  3. Rosales, A. R.; Ross, S. P.; Helquist, P.; Norrby, P.-O.; Sigman, M. S.; Wiest, O. Transition State Force Field for the Asymmetric Redox-Relay Heck Reaction. J. Am. Chem. Soc. 2020, 142, 9700–9707. DOI: 10.1021/jacs.0c01979

    Develops a Q2MM transition state force field for the asymmetric redox-relay Heck reaction, accurately predicting both enantio- and site-selectivity.

  4. Wahlers, J.; Maloney, M.; Salahi, F.; Rosales, A. R.; Helquist, P.; Norrby, P.-O.; Wiest, O. Stereoselectivity Predictions for the Pd-Catalyzed 1,4-Conjugate Addition. J. Org. Chem. 2021, 86, 5660–5667. DOI: 10.1021/acs.joc.0c02918

    Applies Q2MM to predict stereoselectivity in palladium-catalyzed conjugate additions, demonstrating transferability to new reaction classes.

  5. Wahlers, J.; Margalef, J.; Hansen, E.; Bayesteh, A.; Helquist, P.; Diéguez, M.; Pàmies, O.; Wiest, O.; Norrby, P.-O. Proofreading Experimentally Assigned Stereochemistry through Q2MM Predictions. Nat. Commun. 2021, 12, 6508. DOI: 10.1038/s41467-021-27065-2

    Uses Q2MM predictions to identify and correct experimentally misassigned stereochemistry, demonstrating the method's value as a validation tool.

  6. Quinn, T. R.; Patel, H. N.; Koh, K. H.; Haines, B. E.; Norrby, P.-O.; Helquist, P.; Wiest, O. Automated Fitting of Transition State Force Fields for Biomolecular Simulations. PLOS ONE 2022, 17, e0264960. DOI: 10.1371/journal.pone.0264960

    Extends Q2MM automation for biomolecular systems, enabling transition state force field fitting for enzymatic reactions.

  7. Wahlers, J.; Rosales, A. R.; Berkel, N.; Forbes, A.; Helquist, P.; Norrby, P.-O.; Wiest, O. MM3 Force Field for Ferrocenyl Ligands. J. Org. Chem. 2022, 87*, 12334–12341. DOI: 10.1021/acs.joc.2c01396

    Develops specialized MM3* force field parameters for ferrocene-based ligands used in asymmetric catalysis.

  8. Maloney, M. P.; Stenfors, B. A.; Helquist, P.; Norrby, P.-O.; Wiest, O. Interplay of Computation and Experiment in Enantioselective Catalysis. ACS Catal. 2023, 13, 14285–14299. DOI: 10.1021/acscatal.3c03706

    Reviews the synergy between computational (Q2MM) and experimental approaches in developing enantioselective catalysts.