Prediction of toluene/water partition coefficients in the SAMPL9 blind challenge: assessment of machine learning and IEF-PCM/MST continuum solvation models-Reference-Cited by-同舟云学术

Prediction of toluene/water partition coefficients in the SAMPL9 blind challenge: assessment of machine learning and IEF-PCM/MST continuum solvation models

Published:2023 Issue:27 Volume:25 Page:17952-17965
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Zamora William J.¹²³^ORCID,Viayna Antonio⁴⁵⁶^ORCID,Pinheiro Silvana¹²^ORCID,Curutchet Carles⁶⁷^ORCID,Bisbal Laia⁵⁸,Ruiz Rebeca⁹^ORCID,Ràfols Clara⁵⁸^ORCID,Luque F. Javier⁴⁵⁶^ORCID

Affiliation:

1. CBio3 Laboratory, School of Chemistry, University of Costa Rica, San Pedro, San José, Costa Rica

2. Laboratory of Computational Toxicology and Artificial Intelligence (LaToxCIA), Biological Testing Laboratory (LEBi), University of Costa Rica, San Pedro, San José, Costa Rica

3. Advanced Computing Lab (CNCA), National High Technology Center (CeNAT), Pavas, San José, Costa Rica

4. Departament de Nutrició, Ciències de l’Alimentació i Gastronomia, Facultat de Farmàcia i Ciències de l’Alimentació, Universitat de Barcelona (UB), Av. Prat de la Riba 171, 08921 Santa Coloma de Gramenet, Spain

5. Institut de Biomedicina (IBUB), Universitat de Barcelona (UB), Barcelona, Spain

6. Institut de Química Teòrica i Computacional (IQTC-UB), Universitat de Barcelona (UB), Barcelona, Spain

7. Departament de Farmàcia i Tecnologia Farmacèutica, i Fisicoquímica, Facultat de Farmàcia i Ciències de l’Alimentació, Universitat de Barcelona (UB), Av. Joan XXIII 27-31, 08028, Barcelona, Spain

8. Departament d’Enginyeria Química i Química Analítica, Universitat de Barcelona (UB), Martí i Franquès 1-11, 08028 Barcelona, Spain

9. Pion Inc., Forest Row Business Park, Forest Row RH18 5DW, UK

Abstract

In recent years the use of partition systems other than the widely used biphasic n-octanol/water has received increased attention to gain insight into the molecular features that dictate the lipophilicity of compounds.

Funder

Generalitat de Catalunya

Ministerio de Ciencia e Innovación

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2023/CP/D3CP01428B

Reference88 articles.

1. The influence of lipophilicity in drug discovery and design

2. Lipophilic Efficiency as an Important Metric in Drug Design

3. Beyond the Rule of 5: Lessons Learned from AbbVie’s Drugs and Compound Collection

4. Predicting the Blood-Brain Barrier Permeability of New Drug-Like Compounds via HPLC with Various Stationary Phases

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