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Chemistry, Biological Activities and In Silico Bioprospection of Sterols and Triterpenes from Mexican Columnar Cactaceae

Authors: Juan Rodrigo Salazar; Marco A. Loza-Mejía; Diego Soto-Cabrera;

Chemistry, Biological Activities and In Silico Bioprospection of Sterols and Triterpenes from Mexican Columnar Cactaceae

Abstract

The Cactaceae family is an important source of triterpenes and sterols. The wide uses of those plants include food, gathering, medicinal, and live fences. Several studies have led to the isolation and characterization of many bioactive compounds. This review is focused on the chemistry and biological properties of sterols and triterpenes isolated mainly from some species with columnar and arborescent growth forms of Mexican Cactaceae. Regarding the biological properties of those compounds, apart from a few cases, their molecular mechanisms displayed are not still fully understand. To contribute to the above, computational chemistry tools have given a boost to traditional methods used in natural products research, allowing a more comprehensive exploration of chemistry and biological activities of isolated compounds and extracts. From this information an in silico bioprospection was carried out. The results suggest that sterols and triterpenoids present in Cactaceae have interesting substitution patterns that allow them to interact with some bio targets related to inflammation, metabolic diseases, and neurodegenerative processes. Thus, they should be considered as attractive leads for the development of drugs for the management of chronic degenerative diseases.

Keywords

Cactaceae, Plant Extracts, in silico screening, Anti-Inflammatory Agents, Organic chemistry, Review, bioprospection, Triterpenes, Sterols, sterol, QD241-441, Computational Chemistry, bioactivity, triterpene, Hypoglycemic Agents, Computer Simulation

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    14
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Average
Top 10%
Green
gold