Picha, A. K., Wieder, M., & Boresch, S. (2025). Transferable Neural Network Potentials and Condensed Phase Properties. Journal of Chemical Information and Modeling, 65(18), 9483-9496. https://doi.org/10.1021/acs.jcim.5c01355

Wu, Z., Konig, G., Boresch, S., & Cossins, B. P. (2025). Optimizing Absolute Binding Free Energy Calculations for Production Usage. Journal of Chemical Theory and Computation. Advance online publication. https://doi.org/10.1021/acs.jctc.5c00861

Picha, A. K., Tkaczyk, S., Langer, T., Wieder, M., & Boresch, S. (2025). Architecture-Independent Absolute Solvation Free Energy Calculations with Neural Network Potentials. Journal of Physical Chemistry Letters, 16, 12080-12086. https://doi.org/10.1021/acs.jpclett.5c02980

Karwounopoulos, J., Wu, Z., Tkaczyk, S., Wang, S., Baskerville, A., Ranasinghe, K., Langer, T., Wood, G. P. F., Wieder, M., & Boresch, S. (2024). Insights and Challenges in Correcting Force Field Based Solvation Free Energies Using a Neural Network Potential. Journal of Physical Chemistry B, 128(28), 6693-6703. https://doi.org/10.1021/acs.jpcb.4c01417

Boresch, S. (2024). On Analytical Corrections for Restraints in Absolute Binding Free Energy Calculations. Journal of Chemical Information and Modeling, 64(9), 3605-3609. https://doi.org/10.1021/acs.jcim.4c00442

Tkaczyk, S., Karwounopoulos, J., Schöller, A., Woodcock, H. L., Langer, T., Boresch, S., & Wieder, M. (2024). Reweighting from Molecular Mechanics Force Fields to the ANI-2x Neural Network Potential. Journal of Chemical Theory and Computation, 20(7), 2719-2728. https://doi.org/10.1021/acs.jctc.3c01274

Texas A&M University, Hwang, W., Austin, S. L., Blondel, A., Boittier, E. D., Boresch, S., Buck, M., Buckner, J., Caflisch, A., Chang, H. T., Cheng, X., Choi, Y. K., Chu, J. W., Crowley, M. F., Cui, Q., Damjanovic, A., Deng, Y., Devereux, M., Ding, X., ... Brooks, C. L. (2024). CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed. Journal of Physical Chemistry B. Advance online publication. https://doi.org/10.1021/acs.jpcb.4c04100

Karwounopoulos, J., Kaupang, Å., Wieder, M., & Boresch, S. (2023). Calculations of Absolute Solvation Free Energies with Transformato─Application to the FreeSolv Database Using the CGenFF Force Field. Journal of Chemical Theory and Computation, 19(17), 5988–5998. https://doi.org/10.1021/acs.jctc.3c00691

Schöller, A., Woodcock, H. L., & Boresch, S. (2023). Exploring Routes to Enhance the Calculation of Free Energy Differences via Non-Equilibrium Work SQM/MM Switching Simulations Using Hybrid Charge Intermediates between MM and SQM Levels of Theory or Non-Linear Switching Schemes. Molecules, 28(10), Article 4006. https://doi.org/10.3390/molecules28104006

Karwounopoulos, J., Wieder, M., & Boresch, S. (2022). Relative binding free energy calculations with transformato: A molecular dynamics engine-independent tool. Frontiers in Molecular Biosciences, 9, Article 954638. https://doi.org/10.3389/fmolb.2022.954638

Wieder, M., Fleck, M., Braunsfeld, B., & Boresch, S. (2022). Alchemical free energy simulations without speed limits. A generic framework to calculate free energy differences independent of the underlying molecular dynamics program. Journal of Computational Chemistry, 43(17), 1151-1160. https://doi.org/10.1002/jcc.26877

Schoeller, A., Kearns, F., Woodcock, H. L., & Boresch, S. (2022). Optimizing the Calculation of Free Energy Differences in Nonequilibrium Work SQM/MM Switching Simulations. Journal of Physical Chemistry B, 126(15), 2798-2811. https://doi.org/10.1021/acs.jpcb.2c00696

Fleck, M., Wieder, M., & Boresch, S. (2021). Dummy Atoms in Alchemical Free Energy Calculations. Journal of Chemical Theory and Computation, 17(7), 4403-4419. https://doi.org/10.1021/acs.jctc.0c01328

Heid, E., Boresch, S., & Schroeder, C. (2020). Polarizable molecular dynamics simulations of ionic liquids: Influence of temperature control. Journal of Chemical Physics, 152(9), Article 094105. https://doi.org/10.1063/1.5143746

Hudson, P. S., Woodcock, H. L., & Boresch, S. (2019). Use of Interaction Energies in QM/MM Free Energy Simulations. Journal of Chemical Theory and Computation, 15(8), 4632-4645. https://doi.org/10.1021/acs.jctc.9b00084

Kearns, F. L., Warrensford, L., Boresch, S., & Woodcock, H. L. (2019). The Good, the Bad, and the Ugly: "HiPen", a New Dataset for Validating (S)QM/MM Free Energy Simulations. Molecules, 24(4), Article 681. https://doi.org/10.3390/molecules24040681

Hudson, P. S., Boresch, S., Rogers, D. M., & Woodcock, H. L. (2018). Accelerating QM/MM Free Energy Computations via Intramolecular Force Matching. Journal of Chemical Theory and Computation, 14(12), 6327-6335. https://doi.org/10.1021/acs.jctc.8b00517

Siebert, D. C. B., Wieder, M., Schlener, L., Scholze, P., Boresch, S., Langer, T., Schnürch, M., Mihovilovic, M. D., Richter, L., Ernst, M., & Ecker, G. (2018). SAR-Guided Scoring Function and Mutational Validation Reveal the Binding Mode of CGS-8216 at the α1+/γ2- Benzodiazepine Site. Journal of Chemical Information and Modeling, 58(8), 1682-1696. https://doi.org/10.1021/acs.jcim.8b00199

Hudson, P., Boresch, S., Rogers, D., & Woodcock, H. (2017). Enhancing QM/MM indirect free energy simulations with intramolecular force matching. American Chemical Society. Abstracts of Papers (at the National Meeting), 254.

Kearns, F. L., Hudson, P. S., Woodcock, H. L., & Boresch, S. (2017). Computing converged free energy differences between levels of theory via nonequilibrium work methods: Challenges and opportunities. Journal of Computational Chemistry, 38(16), 1376-1388. https://doi.org/10.1002/jcc.24706