Importance of Engineered and Learned Molecular Representations in Predicting Organic Reactivity, Selectivity, and Chemical Properties

Gallegos, L. C.; Luchini, G.; St. John, P. C.; Kim, S.; Paton, R. S. Acc. Chem. Res. 2021, 54, 827–836

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Goodvibes

A Python program to compute quasi-harmonic thermochemical data and potential energy surface diagrams from frequency calculations at a given temperature/concentration, corrected for the effects of vibrational scaling-factors. All (electronic, translational, rotational and vibrational) partition functions are recomputed and can be correct to any temperature or concentration. The first public version of GoodVibes was released in 2016 and it has undergone several revisions since, during which time it has been used by many groups around the world. The program is described in the publication: GoodVibes: automated thermochemistry for heterogeneous computational chemistry data

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wSterimol

A program to generate Boltzmann-weighted Sterimol Steric Parameters for conformationally-flexible substituents that integrates with PyMol. The program contains an automated computational workflow which computes multidimensional Sterimol parameters. For flexible molecules or substituents, the program will generate & optimize a conformational ensemble, and produce Boltzmann-weighted Sterimol parameters. It has been developed as a PyMol plugin and can be run from within the graphical user interface. The wSterimol code is described in more detail in Conformational Effects on Physical-Organic Descriptors – the Case of Sterimol Steric Parameters

Effects of substituents X and Y on the NMR chemical shifts of 2-(4-X phenyl)-5-Y pyrimidines

Yuan, H.; Chen, P.-W.; Li, M.-Y.; Zhang, Y.; Peng, Z.-W.; Liu, W.; Paton, R. S.; Cao, C. J. Mol. Struct. 2020, 1204, 127489

Prediction of homolytic bond dissociation enthalpies for organic molecules at near chemical accuracy with sub-second computational cost

St John, P.; Guan, Y.; Kim, Y.; Kim, S.; Paton, R. S. Nat. Commun. 2020, 11, 2328

Selective Halogenation Using Designed Phosphine Reagents

Levy, J. N.; Alegre-Requena, J. V.; Liu, R.; Paton, R. S.; McNally, A. J. Am. Chem. Soc. 2020, 142, 11295–11305

GoodVibes: automated thermochemistry for heterogeneous computational chemistry data

Luchini, G.; Alegre-Requena, J. V.; Funes-Ardoiz, I.; Paton, R. S. F1000Research 2020, 9, 291

Structure Determination of a Chloroenyne from Laurencia Majuscula Using Computational Methods and Total Synthesis

Shepherd, E. D.; Dyson, B. S.; Hak, W. E.; Nguyen, Q. N. N.; Lee, M.; Kim, M. J.; Sohn, T.-I.; Kim, D.; Burton, J. W.; Paton, R. S. J. Org. Chem. 2019, 84, 4971–4991