Preprints

  1. Schoepfer, A., Weinreich, J., Laplaza, R., Waser, J., & Corminboeuf, C. (2024). Cost-Informed Bayesian Reaction Optimization. American Chemical Society (ACS); \urlhttp://dx.doi.org/10.26434/chemrxiv-2024-44ft2. http://dx.doi.org/10.26434/chemrxiv-2024-44ft2

Refereed journal articles

  1. Laplaza, R., Wodrich, M. D., & Corminboeuf, C. (2024). Overcoming the Pitfalls of Computing Reaction Selectivity from Ensembles of Transition States. J. Phys. Chem. Lett., 15(29), 7363–7370. http://dx.doi.org/10.1021/acs.jpclett.4c01657
  2. van Gerwen, P., Briling, K. R., Bunne, C., Somnath, V. R., Laplaza, R., Krause, A., & Corminboeuf, C. (2024). 3DReact: Geometric Deep Learning for Chemical Reactions. J. Chem. Inf. Model. http://dx.doi.org/10.1021/acs.jcim.4c00104
  3. Worakul, T., Laplaza, R., Das, S., Wodrich, M. D., & Corminboeuf, C. (2024). Microkinetic Molecular Volcano Plots for Enhanced Catalyst Selectivity and Activity Predictions. ACS Catal., 9829–9839. http://dx.doi.org/10.1021/acscatal.4c01175
  4. Schoepfer, A. A., Laplaza, R., Wodrich, M. D., Waser, J., & Corminboeuf, C. (2024). Reaction-Agnostic Featurization of Bidentate Ligands for Bayesian Ridge Regression of Enantioselectivity. ACS Catal., 9302–9312. http://dx.doi.org/10.1021/acscatal.4c02452
  5. Das, S., Laplaza, R., Blaskovits, J. T., & Corminboeuf, C. (2024). Engineering Frustrated Lewis Pair Active Sites in Porous Organic Scaffolds for Catalytic CO2 Hydrogenation. J. Am. Chem. Soc., 146(23), 15806–15814. http://dx.doi.org/10.1021/jacs.4c01890
  6. Cho, Y., Laplaza, R., Vela, S., & Corminboeuf, C. (2024). Automated prediction of ground state spin for transition metal complexes. Digital Discovery, 3(8), 1638–1647. http://dx.doi.org/10.1039/D4DD00093E
  7. Gallarati, S., van Gerwen, P., Laplaza, R., Brey, L., Makaveev, A., & Corminboeuf, C. (2024). A genetic optimization strategy with generality in asymmetric organocatalysis as a primary target. Chem. Sci., 15(10), 3640–3660. http://dx.doi.org/10.1039/D3SC06208B
  8. Blaskovits, J. T., Laplaza, R., Vela, S., & Corminboeuf, C. (2023). Data‐Driven Discovery of Organic Electronic Materials Enabled by Hybrid Top‐Down/Bottom‐Up Design. Adv. Mater., 36(2), 2305602. http://dx.doi.org/10.1002/adma.202305602
  9. van Gerwen, P., Wodrich, M. D., Laplaza, R., & Corminboeuf, C. (2023). Reply to Comment on ‘Physics-based representations for machine learning properties of chemical reactions.’ Mach. Learn.: Sci. Technol., 4(4), 048002. http://dx.doi.org/10.1088/2632-2153/acee43
  10. Novoa, T., Laplaza, R., Peccati, F., Fuster, F., & Contreras-Garcı́a Julia. (2023). The NCIWEB Server: A Novel Implementation of the Noncovalent Interactions Index for Biomolecular Systems. J. Chem. Inf. Model., 63(15), 4483–4489. https://doi.org/10.1021/acs.jcim.3c00271
  11. Wodrich, M. D., Laplaza, R., Cramer, N., Reiher, M., & Corminboeuf, C. (2023). Toward in silico Catalyst Optimization. CHIMIA, 77(3), 139. https://doi.org/10.2533/chimia.2023.139
  12. Gallarati, S., Gerwen, P. V., Schoepfer, A. A., Laplaza, R., & Corminboeuf, C. (2023). Genetic Algorithms for the Discovery of Homogeneous Catalysts. CHIMIA, 77(1/2), 39. https://doi.org/10.2533/chimia.2023.39
  13. Wieduwilt, E. K., Boto, R. A., Macetti, G., Laplaza, R., Contreras-Garcı́a Julia, & Genoni, A. (2023). Extracting Quantitative Information at Quantum Mechanical Level from Noncovalent Interaction Index Analyses. J. Chem. Theory Comput., 19(3), 1063–1079. https://doi.org/10.1021/acs.jctc.2c01092
  14. Vela, S., Laplaza, R., Cho, Y., & Corminboeuf, C. (2022). cell2mol: Encoding chemistry to interpret crystallographic data. Npj Comput. Mater., 8(1), 188. https://doi.org/10.1038/s41524-022-00874-9
  15. Laplaza, R., Das, S., Wodrich, M. D., & Corminboeuf, C. (2022). Constructing and interpreting volcano plots and activity maps to navigate homogeneous catalyst landscapes. Nat. Protoc., 17(11), 2550–2569. https://doi.org/10.1038/s41596-022-00726-2
  16. Das, S., Laplaza, R., Blaskovits, J. T., & Corminboeuf, C. (2022). Mapping Active Site Geometry to Activity in Immobilized Frustrated Lewis Pair Catalysts. Angew. Chem. Int. Ed., 134(32). https://doi.org/10.1002/ange.202202727
  17. Jurásková, V., Célerse, F., Laplaza, R., & Corminboeuf, C. (2022). Assessing the persistence of chalcogen bonds in solution with neural network potentials. J. Chem. Phys., 156(15), 154112. https://doi.org/10.1063/5.0085153
  18. Laplaza, R., Gallarati, S., & Corminboeuf, C. (2022). Genetic Optimization of Homogeneous Catalysts. Chemistry–Methods, 2(6), e202100107. https://doi.org/10.1002/cmtd.202100107
  19. Schwaller, P., Vaucher, A. C., Laplaza, R., Bunne, C., Krause, A., Corminboeuf, C., & Laino, T. (2022). Machine intelligence for chemical reaction space. WIREs Comput. Mol. Sci., 12(5). https://doi.org/10.1002/wcms.1604
  20. Laplaza, R., Contreras-Garcia, J., Fuster, F., Volatron, F., & Chaquin, P. (2022). Dependence of hydrocarbon sigma CC bond strength on bond angles: The concepts of “inverted”, “direct” and “superdirect” bonds. Comput. Theor. Chem., 1207, 113505. https://doi.org/10.1016/j.comptc.2021.113505
  21. Gallarati, S., van Gerwen, P., Laplaza, R., Vela, S., Fabrizio, A., & Corminboeuf, C. (2022). OSCAR: An Extensive Repository of Chemically and Functionally Diverse Organocatalysts. Chem. Sci., 13(46), 13782–13794.
  22. Garner, M. H., Laplaza, R., & Corminboeuf, C. (2022). Helical versus linear Jahn–Teller distortions in allene and spiropentadiene radical cations. Phys. Chem. Chem. Phys., 24(42), 26134–26143. https://doi.org/10.1039/d2cp03544h
  23. Landeros-Rivera, B., Gallegos, M., Munarriz, J., Laplaza, R., & Contreras-Garcia, J. (2022). New venues in electron density analysis. Phys. Chem. Chem. Phys., 24(36), 21538–21548. https://doi.org/10.1039/d2cp01517j
  24. Laplaza, R., Sobez, J.-G., Wodrich, M. D., Reiher, M., & Corminboeuf, C. (2022). The (not so) simple prediction of enantioselectivity – a pipeline for high-fidelity computations. Chem. Sci., 13(23), 6858–6864. https://doi.org/10.1039/d2sc01714h
  25. Gallarati, S., Laplaza, R., & Corminboeuf, C. (2022). Harvesting the fragment-based nature of bifunctional organocatalysts to enhance their activity. Org. Chem. Front., 9(15), 4041–4051. https://doi.org/10.1039/d2qo00550f
  26. Romero-Tamayo, S., Laplaza, R., Velazquez-Campoy, A., Villanueva, R., Medina, M., & Ferreira, P. (2021). W196 and the β-Hairpin Motif Modulate the Redox Switch of Conformation and the Biomolecular Interaction Network of the Apoptosis-Inducing Factor. Oxid. Med. Cell. Longev., 2021, 1–19. https://doi.org/10.1155/2021/6673661
  27. Gallarati, S., Fabregat, R., Laplaza, R., Bhattacharjee, S., Wodrich, M. D., & Corminboeuf, C. (2021). Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts. Chem. Sci., 12(20), 6879–6889. https://doi.org/10.1039/d1sc00482d
  28. Laplaza, R., Cárdenas, C., Chaquin, P., Contreras-Garcı́a Julia, & Ayers, P. W. (2020). Orbital energies and nuclear forces in DFT : Interpretation and validation. J. Comput. Chem., 42(5), 334–343. https://doi.org/10.1002/jcc.26459
  29. Laplaza, R., Peccati, F., A. Boto, R., Quan, C., Carbone, A., Piquemal, J.-P., Maday, Y., & Contreras-Garcı́a Julia. (2020). NCIPLOT and the analysis of noncovalent interactions using the reduced density gradient. WIREs Comput. Mol. Sci., 11(2).
  30. Boto, R. A., Peccati, F., Laplaza, R., Quan, C., Carbone, A., Piquemal, J.-P., Maday, Y., & Contreras-Garcı́a Julia. (2020). NCIPLOT4: Fast, Robust, and Quantitative Analysis of Noncovalent Interactions. J. Chem. Theory Comput., 16(7), 4150–4158. https://doi.org/10.1021/acs.jctc.0c00063
  31. Laplaza, R., Contreras-Garcia, J., Fuster, F., Volatron, F., & Chaquin, P. (2020). The “Inverted Bonds” Revisited: Analysis of “In Silico” Models and of [1.1.1]Propellane by Using Orbital Forces. Chem. Eur. J. , 26(30), 6839–6845. https://doi.org/10.1002/chem.201904910
  32. Laplaza, R., Boto, R. A., Contreras-Garcı́a Julia, & Montero-Campillo, M. M. (2020). Steric clash in real space: Biphenyl revisited. Phys. Chem. Chem. Phys., 22(37), 21251–21256. https://doi.org/10.1039/d0cp03359f
  33. Laplaza, R., Polo, V., & Contreras-Garcı́a Julia. (2019). A Bond Charge Model Ansatz for Intrinsic Bond Energies: Application to C–C Bonds. J. Phys. Chem. A, 124(1), 176–184. https://doi.org/10.1021/acs.jpca.9b10251
  34. Villanueva, R., Romero-Tamayo, S., Laplaza, R., Martı́nez-Olivan Juan, Velázquez-Campoy, A., Sancho, J., Ferreira, P., & Medina, M. (2019). Redox- and Ligand Binding-Dependent Conformational Ensembles in the Human Apoptosis-Inducing Factor Regulate Its Pro-Life and Cell Death Functions. Antioxid. Redox Signal., 30(18), 2013–2029. https://doi.org/10.1089/ars.2018.7658
  35. Peccati, F., Laplaza, R., & Contreras-Garcı́a Julia. (2019). Overcoming Distrust in Solid State Simulations: Adding Error Bars to Computational Data. J. Phys. Chem. C, 123(8), 4767–4772. https://doi.org/10.1021/acs.jpcc.8b10510
  36. Munárriz, J., Laplaza, R., Martı́n Pendás A., & Contreras-Garcı́a Julia. (2019). A first step towards quantum energy potentials of electron pairs. Phys. Chem. Chem. Phys., 21(8), 4215–4223. https://doi.org/10.1039/c8cp07509c
  37. Laplaza, R., Polo, V., & Contreras-Garcı́a Julia. (2019). Localizing electron density errors in density functional theory. Phys. Chem. Chem. Phys., 21(37), 20927–20938. https://doi.org/10.1039/c9cp02806d
  38. Munárriz, J., Laplaza, R., & Polo Vı́ctor. (2018). A bonding evolution theory study on the catalytic Noyori hydrogenation reaction. Mol. Phys., 117(9-12), 1315–1324. https://doi.org/10.1080/00268976.2018.1542168
  39. Quero, J., Cabello, S., Fuertes, T., Mármol, I., Laplaza, R., Polo, V., Gimeno, M. C., Rodriguez-Yoldi, M. J., & Cerrada, E. (2018). Proteasome versus Thioredoxin Reductase Competition as Possible Biological Targets in Antitumor Mixed Thiolate-Dithiocarbamate Gold(III) Complexes. Inorg. Chem., 57(17), 10832–10845. https://doi.org/10.1021/acs.inorgchem.8b01464
  40. Martı́nez-Júlvez Marta, Goñi, G., Pérez-Amigot, D., Laplaza, R., Ionescu, I., Petrocelli, S., Tondo Marı́a, Sancho, J., Orellano, E., & Medina, M. (2017). Identification of Inhibitors Targeting Ferredoxin-NADP+ Reductase from the Xanthomonas citri subsp. citri Phytopathogenic Bacteria. Molecules, 23(1), 29. https://doi.org/10.3390/molecules23010029

Refereed book chapters

  1. Laplaza, R., Munárriz, J., & Contreras-García, J. (2022). Chemical Information. In Conceptual Density Functional Theory: Towards a New Chemical Reactivity Theory (pp. 349–374). Wiley. https://doi.org/10.1002/9783527829941.ch18
  2. Laplaza, R., Peccati, F., Arias-Olivares, D., & Contreras-Garcı́a Julia. (2021). 14 Visualizing non-covalent interactions with NCIPLOT. In Complementary Bonding Analysis (pp. 353–378). De Gruyter. https://doi.org/10.1515/9783110660074-014