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The Adapted POM Analysis of Avenanthramides In Silico
Tibor Maliar1, Mária Maliarová1, Andrea Purdešová1
1Department of Chemistry, Faculty of Natural Sciences, University of Ss. Cyril and Methodius in Trnava, Námestie J. Herdu 2, 917 01 Trnava, Slovakia.
Physicochemical analysis of avenanthramides (AVNs), natural oat compounds, identified promising drug candidates. In silico evaluation revealed significant differences in bioactivity, ADME properties, and toxicity among AVNs.
Area of Science:
- Medicinal Chemistry
- Natural Products Chemistry
- Computational Chemistry
Background:
- Avenanthramides (AVNs) are oat-derived polyphenols with diverse biological activities, including antioxidant and anti-inflammatory effects.
- Physicochemical analysis and related methods are crucial for predicting drug-likeness, ADME parameters, and toxicity.
- Identifying promising AVN drug candidates requires in silico evaluation of their properties.
Purpose of the Study:
- To perform a modified physicochemical analysis (POM) of 42 identified avenanthramides (AVNs).
- To predict biological activity, ADME parameters, and toxicity of AVNs using computational tools.
- To identify the most promising AVN candidates for further research and drug development.
Main Methods:
- Utilized MOLINSPIRATION, SWISSADME, and OSIRIS software for in silico analysis.
- Calculated various physicochemical properties for 42 AVNs.
- Evaluated predicted biological activity, ADME profiles, and toxicity of each AVN.
Main Results:
- Significant variations in physicochemical properties, bioactivity predictions, ADME parameters, and toxicity were observed among the 42 AVNs.
- The analysis highlighted specific AVNs with favorable predicted profiles.
- Preliminary in silico data provides a basis for prioritizing AVNs for further investigation.
Conclusions:
- Modified POM analysis effectively differentiated the potential of various AVNs as drug candidates.
- The study identified specific AVNs with promising bioactivity, optimal ADME properties, and low predicted toxicity.
- These findings will guide future research efforts toward developing AVNs for therapeutic applications.
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