Litcius/Paper detail

Prediction of n-octanol/water partition coefficients and acidity constants (pKa) in the SAMPL7 blind challenge with the IEFPCM-MST model

Antonio Viayna, Silvana Pinheiro, Carles Curutchet, F. Javier Luque, William J. Zamora

2021Journal of Computer-Aided Molecular Design24 citationsDOIOpen Access PDF

Abstract

Abstract Within the scope of SAMPL7 challenge for predicting physical properties, the Integral Equation Formalism of the Miertus-Scrocco-Tomasi (IEFPCM/MST) continuum solvation model has been used for the blind prediction of n -octanol/water partition coefficients and acidity constants of a set of 22 and 20 sulfonamide-containing compounds, respectively. The log P and p K a were computed using the B3LPYP/6-31G(d) parametrized version of the IEFPCM/MST model. The performance of our method for partition coefficients yielded a root-mean square error of 1.03 (log P units), placing this method among the most accurate theoretical approaches in the comparison with both globally (rank 8th) and physical (rank 2nd) methods. On the other hand, the deviation between predicted and experimental p K a values was 1.32 log units, obtaining the second best-ranked submission. Though this highlights the reliability of the IEFPCM/MST model for predicting the partitioning and the acid dissociation constant of drug-like compounds compound, the results are discussed to identify potential weaknesses and improve the performance of the method.

Topics & Concepts

ChemistrySolvationPartition coefficientDissociation constantComputational chemistryOctanolThermodynamicsMathematicsMoleculeOrganic chemistryPhysicsReceptorBiochemistryComputational Drug Discovery MethodsFree Radicals and AntioxidantsAnalytical Chemistry and Chromatography
Prediction of n-octanol/water partition coefficients and acidity constants (pKa) in the SAMPL7 blind challenge with the IEFPCM-MST model | Litcius