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Solubility prediction

Solubility is one of basic physical chemistry properties important for understanding how molecules interact with solvents. Following script allows to predict solubility by molecular descriptors. #{x.18b704d0-0b50-11e9-b846-1fa94a4da5d1."Predict Solubility"} model was trained using #{x.Demo:SolubilityTrain."Solubility Train"} dataset on H2O modelling engine. Modelling method is "Generalized Linear Modeling"

Molecular Descriptors used in model:

  • MolWt - Molecular Weight
  • Ipc - The information content of the coefficients of the characteristic polynomial of the adjacency matrix of a hydrogen-suppressed graph of a molecule
  • TPSA - Total Polar Surface Area
  • LabuteASA - Labute's Approximate Surface Area
  • NumHDonors - Number of Hydrogen Donors
  • NumHAcceptors - Number of Hydrogen Acceptors
  • MolLogP - Wildman-Crippen LogP value
  • HeavyAtomCount - Number of Heavy Atoms
  • NumRotatableBonds - Number of Rotatable Bonds
  • RingCount - Number of Rings
  • NumValenceElectrons - Number of Valence Electrons

See also:

References: