title: Fast and General Method To Predict the Physicochemical Properties of Druglike Molecules Using the Integral Equation Theory of Molecular Liquids.
abstract: We report a method to predict physicochemical properties of druglike molecules using a classical statistical mechanics based solvent model combined with machine learning. The RISM-MOL-INF method introduced here provides an accurate technique to characterize solvation and desolvation processes based on solute-solvent correlation functions computed by the 1D reference interaction site model of the integral equation theory of molecular liquids. These functions can be obtained in a matter of minutes for most small organic and druglike molecules using existing software (RISM-MOL) (Sergiievskyi, V. P.; Hackbusch, W.; Fedorov, M. V. J. Comput. Chem. 2011, 32, 1982-1992). Predictions of caco-2 cell permeability and hydration free energy obtained using the RISM-MOL-INF method are shown to be more accurate than the state-of-the-art tools for benchmark data sets. Due to the importance of solvation and desolvation effects in biological systems, it is anticipated that the RISM-MOL-INF approach will find many applications in biophysical and biomedical property prediction.
authors.affiliation: Department of Pure and Applied Chemistry, University of Strathclyde , Thomas Graham Building, 295 Cathedral Street, Glasgow, Scotland G1 1XL, U.K.
authors.forename: David S
authors.initials: DS
authors.lastname: Palmer
authors.affiliation: Department of Physics, Scottish Universities Physics Alliance (SUPA), University of Strathclyde , John Anderson Building, 107 Rottenrow, Glasgow, Scotland G4 0NG, U.K.
authors.forename: Maksim
authors.initials: M
authors.lastname: Mišin
authors.affiliation: Department of Physics, Scottish Universities Physics Alliance (SUPA), University of Strathclyde , John Anderson Building, 107 Rottenrow, Glasgow, Scotland G4 0NG, U.K.
authors.forename: Maxim V
authors.initials: MV
authors.lastname: Fedorov
authors.affiliation: Respiratory, Inflammation and Autoimmune iMed, AstraZeneca R&D , Pepparedsleden 1, SE-431 83, Mölndal, Sweden.
authors.forename: Antonio
authors.initials: A
authors.lastname: Llinas
mesh_terms: D018938:Caco-2 Cells; D055598:Chemical Phenomena; D002626:Chemistry, Pharmaceutical; D006801:Humans; D008962:Models, Theoretical; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D012997:Solvents / Q000737:chemistry*; D013816:Thermodynamics; D014867:Water / Q000737:chemistry*
chemical_list: D004364:Pharmaceutical Preparations; D012997:Solvents; D014867:Water
keywords: ADME; ADMET; IET; QSAR; QSPR; RISM; Random Forest; bioavailability; caco-2; drug discovery; druglike; hydration free energy; integral equation theory of molecular liquids; permeability; reference interaction site model; solvation free energy; statistical mechanics