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Benchmark Data Sets of Boron Cluster Dihydrogen Bonding for the Validation of Approximate Computational Methods.

Jindřich FanfrlíkAdam PecinaJan ŘezáčMartin LepsikMenyhárt-Botond SárosiDrahomír HnykPavel Hobza
Published in: Chemphyschem : a European journal of chemical physics and physical chemistry (2020)
The success of approximate computational methods, such as molecular mechanics, or dispersion-corrected density functional theory, in the description of non-covalent interactions relies on accurate parameterizations. Benchmark data sets are thus required. This area is well developed for organic molecules and biomolecules but practically non-existent for boron clusters, which have been gaining in importance in modern drug as well as material design. To fill this gap, we have introduced two data sets featuring the most common non-covalent interaction of boron clusters, the dihydrogen bond, and calculated reference interaction energies at the "golden standard" CCSD(T)/CBS level. The boron clusters studied interact with formamide, methanol, water and methane at various distances and in two geometrical arrangements. The performance of the tested approximate methods is variable and recommendations for further use are given.
Keyphrases
  • density functional theory
  • electronic health record
  • big data
  • molecular dynamics
  • emergency department
  • deep learning
  • artificial intelligence
  • drug induced
  • adverse drug