Thermodynamics-Based Model Construction for the Accurate Prediction of Molecular Properties From Partition Coefficients
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Thermodynamics-Based Model Construction for the Accurate Prediction of Molecular Properties From Partition Coefficients
Authors
Keywords
-
Journal
Frontiers in Chemistry
Volume 9, Issue -, Pages -
Publisher
Frontiers Media SA
Online
2021-09-13
DOI
10.3389/fchem.2021.737579
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Development of pp-LFER and QSPR models for predicting the diffusion coefficients of hydrophobic organic compounds in LDPE
- (2020) Tengyi Zhu et al. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
- Prediction of the aqueous solubility of diverse compounds by 2D-QSPR
- (2020) Silvina E. Fioressi et al. JOURNAL OF MOLECULAR LIQUIDS
- A general linear free energy relationship for predicting partition coefficients of neutral organic compounds
- (2020) Deliang Chen et al. CHEMOSPHERE
- Predicting Aqueous Adsorption of Organic Compounds onto Biochars, Carbon Nanotubes, Granular Activated Carbons, and Resins with Machine Learning
- (2020) Kai Zhang et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Hydrophobicity versus electrophilicity: A new protocol toward quantitative structure-toxicity relationship
- (2019) Ranita Pal et al. Chemical Biology & Drug Design
- e-Sweet: A Machine-Learning Based Platform for the Prediction of Sweetener and Its Relative Sweetness
- (2019) Suqing Zheng et al. Frontiers in Chemistry
- Insights into pesticide toxicity against aquatic organism: QSTR models on Daphnia Magna
- (2019) Lujue He et al. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
- Quantitative Effects of Substrate-Environment Interactions on the Free Energy Barriers of Reactions
- (2019) Deliang Chen et al. Journal of Physical Chemistry C
- Prediction of Apolar Compound Sorption to Aquatic Natural Organic Matter Accounting for Natural Organic Matter Hydrophobicity Using Aqueous Two-Phase Systems
- (2019) Kun Liu et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Development of quantitative structure-activity relationship models to predict potential nephrotoxic ingredients in traditional Chinese medicines
- (2019) Yuqing Sun et al. FOOD AND CHEMICAL TOXICOLOGY
- How are Humans Exposed to Organic Chemicals Released to Indoor Air?
- (2019) Li Li et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- QSPR study on the polyacrylate–water partition coefficients of hydrophobic organic compounds
- (2019) Tengyi Zhu et al. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
- Using Machine Learning to Classify Bioactivity for 3486 Per- and Polyfluoroalkyl Substances (PFASs) from the OECD List
- (2019) Weixiao Cheng et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Quantitative structure‐toxicity relationship: An “in silico study” using electrophilicity and hydrophobicity as descriptors
- (2019) Gourhari Jana et al. INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY
- Development of Predictive Models for Identifying Potential S100A9 Inhibitors Based on Machine Learning Methods
- (2019) Jihyeun Lee et al. Frontiers in Chemistry
- Is it possible to improve the quality of predictions from an “intelligent” use of multiple QSAR/QSPR/QSTR models?
- (2018) Kunal Roy et al. JOURNAL OF CHEMOMETRICS
- Agonists of G-Protein-Coupled Odorant Receptors Are Predicted from Chemical Features
- (2018) C. Bushdid et al. Journal of Physical Chemistry Letters
- OPERA models for predicting physicochemical properties and environmental fate endpoints
- (2018) Kamel Mansouri et al. Journal of Cheminformatics
- In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts
- (2018) Hongbin Yang et al. Frontiers in Chemistry
- ADME properties evaluation in drug discovery: in silico prediction of blood–brain partitioning
- (2018) Lu Zhu et al. MOLECULAR DIVERSITY
- Consensus QSAR modeling of toxicity of pharmaceuticals to different aquatic organisms: Ranking and prioritization of the DrugBank database compounds
- (2018) Kabiruddin Khan et al. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
- Molecular Similarity-Based Domain Applicability Metric Efficiently Identifies Out-of-Domain Compounds
- (2018) Ruifeng Liu et al. Journal of Chemical Information and Modeling
- An application of QSRR approach and multiple linear regression method for lipophilicity assessment of flavonoids
- (2018) Mariusz Zapadka et al. JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
- Rapid Life-Cycle Impact Screening Using Artificial Neural Networks
- (2017) Runsheng Song et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- An equation for the prediction of human skin permeability of neutral molecules, ions and ionic species
- (2017) Keda Zhang et al. INTERNATIONAL JOURNAL OF PHARMACEUTICS
- Structure–Kinetic Relationships of Passive Membrane Permeation from Multiscale Modeling
- (2016) Callum J. Dickson et al. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
- Regulation of protein-ligand binding affinity by hydrogen bond pairing
- (2016) D. Chen et al. Science Advances
- Toward a unifying strategy for the structure-based prediction of toxicological endpoints
- (2015) Pau Carrió et al. ARCHIVES OF TOXICOLOGY
- The transfer of neutral molecules from water and from the gas phase to solvents acetophenone and aniline
- (2015) Michael H. Abraham et al. JOURNAL OF MOLECULAR LIQUIDS
- Aug-MIA-QSPR Modeling of the Soil Sorption of Carboxylic Acid Herbicides
- (2014) Mirlaine R. Freitas et al. BULLETIN OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY
- In Silico ADMET Prediction: Recent Advances, Current Challenges and Future Trends
- (2013) Feixiong Cheng et al. CURRENT TOPICS IN MEDICINAL CHEMISTRY
- QSAR and QSPR Model Interpretation Using Partial Least Squares (PLS) Analysis
- (2012) David T. Stanton Current Computer-Aided Drug Design
- Computational analysis of structure-based interactions and ligand properties can predict efflux effects on antibiotics
- (2012) Aurijit Sarkar et al. EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
- Prediction of gas/particle partitioning coefficients of semi volatile organic compounds via QSPR methods: PC-ANN and PLS analysis
- (2012) O. Deeb et al. Journal of the Iranian Chemical Society
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started