Multiple linear regression models for predicting the n‑octanol/water partition coefficients in the SAMPL7 blind challenge.

ABSTRACT: A multiple linear regression model called MLR-3 is used for predicting the experimental n-octanol/water partition coefficient (log P_N) of 22 N-sulfonamides proposed by the organizers of the SAMPL7 blind challenge. The MLR-3 method was trained with 82 molecules including drug-like sulfonamides and small organic molecules, which resembled the main functional groups present in the challenge dataset. Our model, submitted as "TFE-MLR", presented a root-mean-square error of 0.58 and mean absolute error of 0.41 in log P units, accomplishing the highest accuracy, among empirical methods and also in all submissions based on the ranked ones. Overall, the results support the appropriateness of multiple linear regression approach MLR-3 for computing the n-octanol/water partition coefficient

SUBMITTER: Lopez K 

PROVIDER: S-EPMC8273033 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature