Article ; Online: Computational Modeling of Human Serum Albumin Binding of Per- and Polyfluoroalkyl Substances Employing QSAR, Read-Across, and Docking.
Molecules (Basel, Switzerland)
2023 Volume 28, Issue 14
Abstract: Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals in widespread use that have been shown to be toxic to wildlife and humans. Human serum albumin (HSA) is a known transport protein that binds PFAS at various sites, leading to ... ...
Abstract | Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals in widespread use that have been shown to be toxic to wildlife and humans. Human serum albumin (HSA) is a known transport protein that binds PFAS at various sites, leading to bioaccumulation and long-term toxicity. In silico tools like quantitative structure-activity relationship (QSAR), read-across, and quantitative read-across structure-property relationship (q-RASPR) are proven techniques for modeling chemical toxicity based on experimental data which can be used to predict the toxicity of untested and new chemicals, while at the same time, help to identify the major features responsible for toxicity. Classification-based and regression-based QSAR models are employed in the present study to predict the binding affinities of 24 PFAS to HSA. Regression-based QSAR models revealed that the packing density index ( |
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MeSH term(s) | Humans ; Serum Albumin, Human ; Quantitative Structure-Activity Relationship ; Molecular Docking Simulation ; Computer Simulation ; Fluorocarbons |
Chemical Substances | Serum Albumin, Human (ZIF514RVZR) ; Fluorocarbons |
Language | English |
Publishing date | 2023-07-13 |
Publishing country | Switzerland |
Document type | Journal Article |
ZDB-ID | 1413402-0 |
ISSN | 1420-3049 ; 1431-5165 ; 1420-3049 |
ISSN (online) | 1420-3049 |
ISSN | 1431-5165 ; 1420-3049 |
DOI | 10.3390/molecules28145375 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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