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DFT calculation Data From the Computational and Experimental Investigation of the Origin of Selectivity in the Chiral Phosphoric Acid-Catalyzed Enantioselective Minisci Reaction


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Description

This dataset contains Gaussian DFT output files of the key ground-states and transition state DFT optimized structures.

The data is organised in one archive containing 95 separate folders. The hierarchical folder structure follows the convention of ‘substrate’/’mechanistic step’/ ’intermediate or TS stereochemistry’/’activation mode (if applicable)’. The substrate, mechanistic step and activation mode naming conventions follow that in the associated paper. Thus, ‘Subst3_QuinValine\II-III_TS
RS\INT_sol’ folder contains the computational data of the substrate 3 R,S-INT deprotonation solvent transition states. Each of these lower level folders contain at least the output of a frequency calculation at B3LYP/6-31g** level with or without SMD(1,4-dioxane) solvent model (_freq.out files), as well as at least one single point calculation at a higher level, usually at M06-2X/def2-TZVP/SMD(1,4-dioxane) or M06-2X/def2-TZVPD/ SMD(1,4-dioxane) level (_sp.out files). All optimized geometries are also provided as *.sdf files for even better usability.

All of the files can be opened in any text editor. Gaussian output structures can be viewed and the frequency modes visualised in GausView, Avogadro, jmol and in most other molecular viewers/editors. *.sdf files can be viewed in essentially all 3D molecular editors and viewers.

Version

Software / Usage instructions

All of the files can be opened in any text editor. Gaussian output structures can be viewed and the frequency modes visualised in GausView, Avogadro, jmol and in most other molecular viewers/editors. *.sdf files can be viewed in essentially all 3D molecular editors and viewers.

Publisher

Rights and licensing

Except where otherwised noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)
Sponsorship
Isaac Newton Trust (17.08(D))
Leverhulme Trust (ECF-2017-255)
We are grateful to the EPSRC and GlaxoSmithKline for PhD studentships (to R.S.J.P. and B.W.H.), the Royal Society for a University Research Fellowship (to R.J.P.), the Leverhulme Trust (RPG-2018-081) and the European Research Council (Starting Grant 757381, NonCovRegioSiteCat). We also thank Leverhulme Trust (ECF-2017-255) and Isaac Newton Trust (17.08(d)) for Early Career Fellowship (to K.E.). The computational work has been performed using resources provided by the Cambridge Tier-2 system operated by the University of Cambridge Research Computing Service (http://www.hpc.cam.ac.uk) funded by EPSRC Tier-2 capital grant EP/P020259/1.