``A Physics-aware Neural Network for Protein-ligand Interactions with Quantum Chemical Accuracy,'' Z. L. Glick, D. P. Metcalf, C. S. Glick, S. A. Spronk, A. Koutsoukas, D. L. Cheney, and C. D. Sherrill, Chem. Sci. 15, 13313-13324 (2024)
(doi: 10.1039/d4sc01029a)
``Directional ΔG Neural Network (DrΔG-Net): A Modular Neural Network Approach to Binding Free Energy Prediction,'' D. P. Metcalf, Z. L. Glick, A. Bortolato, A. Jiang, D. L. Cheney, and C. D. Sherrill, J. Chem Inf. Model. 64, 1907-1918 (2024)
(doi: 10.1021/acs.jcim.3c02054)
``A Quantum Chemical Interaction Energy Dataset for Accurately Modeling Protein-Ligand Interactions,'' S. A. Spronk, Z. L. Glick, D. P. Metcalf, C. D. Sherrill, and D. L. Cheney, Sci. Data 10, 619 (2023)
(doi: 10.1038/s41597-023-02443-1)
``Benchmark Coupled-Cluster Lattice Energy of Crystalline Benzene and Assessment of Multi-Level Approximations in the Many-Body Expansion,'' C. H. Borca, Z. L. Glick, D. P. Metcalf, L. A. Burns, and C. D. Sherrill, J. Chem. Phys. 158, 234102 (2023)
(doi: 10.1063/5.0159410)
``Benchmarking Two-Body Contributions to Crystal Lattice Energies and a Range-Dependent Assessment of Approximate Methods,'' C. T. Sargent, D. P. Metcalf, Z. L. Glick, C. H. Borca, and C. D. Sherrill, J. Chem. Phys. 158, 054112 (2023)
(doi: 10.1063/5.0141872)
``Range-Dependence of Two-Body Intermolecular Interactions and Their Energy Components in Molecular Crystals,'' D. P. Metcalf, A. Smith, Z. L. Glick, and C. D. Sherrill, J. Chem. Phys. 157, 084503 (2022)
(doi: 10.1063/5.0103644)
``Electron-Passing Neural Networks for Atomic Charge Prediction in Systems with Arbitrary Molecular Charge,'' D. P. Metcalf, A. Jiang, S. A. Spronk, D. L. Cheney, and C. D. Sherrill, J. Chem Inf. Model. 61, 115 (2021)
(doi: 10.1021/acs.jcim.0c01071)
``AP-Net: An Atomic-Pairwise Neural Network for Smooth and Transferable Interaction Potentials,'' Z. L. Glick, D. P. Metcalf, A. Koutsoukas, S. A. Spronk, D. L. Cheney, and C. D. Sherrill, J. Chem. Phys. 153, 044112 (2020)
(doi: 10.1063/5.0011521)
``Approaches for Machine Learning Intermolecular Interaction Energies and Application to Energy Components From Symmetry Adapted Perturbation Theory,'' D. P. Metcalf, A. Koutsoukas, S. A. Spronk, B. L. Claus, D. A. Loughney, S. R. Johnson, D. L. Cheney, and C. D. Sherrill, J. Chem. Phys. 152, 074103 (2020)
(doi: 10.1063/1.5142636)
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