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<p>Quinoa (<i>Chenopodium quinoa</i> Willd.) is a valuable source of bioactive compounds with therapeutic potential, including peptides, saponins, and polyphenols. In recent years, <i>in silico</i> tools have emerged as key strategies for predicting, characterizing, and optimizing the interactions of these compounds with relevant biological targets in pathologies such as hypertension, type 2 diabetes, cancer, and viral diseases. The objective of this work was to analyze recent studies on quinoa bioactive compounds and their interactions with biological targets using <i>in silico</i> approaches, as well as to discuss the technical challenges, limitations, and future perspectives of these computational tools. <i>In silico</i> techniques such as molecular docking, molecular dynamics, and structural modeling using artificial intelligence have been used in the study of quinoa bioactive compounds, as well as bioinformatics tools for screening and toxicity assessment. Highlighted cases include the identification of peptides with inhibitory activity against enzymes, such as ACE and DPP-IV, AMPK-modulating saponins, and flavonoids capable of binding to key receptors in glycemic metabolism. The role of simulated gastrointestinal digestion in the release of bioactive fragments was also discussed. Overall, current evidence shows that in silico studies represent an effective platform for accelerating the discovery of functional compounds derived from quinoa, and could be used to study other Andean crops.</p>

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In silico Techniques for the Investigation of Bioactive Compounds in Quinoa (Chenopodium quinoa Willd.): Recent Advances in Molecular Modeling and Identification of Therapeutic Targets

  • 期刊论文

  • 发表日期：

    2025年10月29日

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  • Julio Vidaurre-Ruiz,
  • Claudia Huamaní-Perales,
  • Hans Minchán-Velayarce,
  • Walter Salas-Valerio,
  • Ritva Repo-Carrasco-Valencia

摘要

Quinoa (Chenopodium quinoa Willd.) is a valuable source of bioactive compounds with therapeutic potential, including peptides, saponins, and polyphenols. In recent years, in silico tools have emerged as key strategies for predicting, characterizing, and optimizing the interactions of these compounds with relevant biological targets in pathologies such as hypertension, type 2 diabetes, cancer, and viral diseases. The objective of this work was to analyze recent studies on quinoa bioactive compounds and their interactions with biological targets using in silico approaches, as well as to discuss the technical challenges, limitations, and future perspectives of these computational tools. In silico techniques such as molecular docking, molecular dynamics, and structural modeling using artificial intelligence have been used in the study of quinoa bioactive compounds, as well as bioinformatics tools for screening and toxicity assessment. Highlighted cases include the identification of peptides with inhibitory activity against enzymes, such as ACE and DPP-IV, AMPK-modulating saponins, and flavonoids capable of binding to key receptors in glycemic metabolism. The role of simulated gastrointestinal digestion in the release of bioactive fragments was also discussed. Overall, current evidence shows that in silico studies represent an effective platform for accelerating the discovery of functional compounds derived from quinoa, and could be used to study other Andean crops.