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Other literature type . 2024
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Conference object . 2024
License: CC BY
Data sources: Datacite
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Conference object . 2024
License: CC BY
Data sources: Datacite
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In silico Binding Prediction of Mitragyna speciosa Alkaloids to Human Opioid Receptors

Authors: Norazizi, Nur Balqis Nasuha; Ab Razak, Nurul Suhada; Jusoh, Siti Azma;

In silico Binding Prediction of Mitragyna speciosa Alkaloids to Human Opioid Receptors

Abstract

Kratom (Mitragyna speciosa), a tropical tree native to Southeast Asia, is traditionally used for its stimulant and sedative effects, which vary with dosage. The primary alkaloids, mitragynine, and 7-hydroxymitragynine, are known for their significant pharmacological activities, especially in pain management, making kratom a subject of growing scientific interest and legal debate. This study aims to bridge knowledge gaps by investigating the interactions of 35 distinct kratom alkaloids with the human mu (MOR), delta (DOR), and kappa (KOR) opioid receptors. These receptors are crucial in modulating pain, mood, and addictive behaviors. Using molecular docking, the binding affinities and receptor selectivity of these alkaloids were explored, shedding light on their pharmacological potential. The aim is to identify the promising kratom alkaloids for the future development of better drugs for pain management and disease treatments.

Keywords

kratom, molecular docking, alkaloids, Mitragyna speciosa

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selected citations
These citations are derived from selected sources.
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!
0
Average
Average
Average
Green