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Molecular docking and dynamic simulation studies of bioactive compounds from traditional medicinal compounds against exfoliative toxin b from staphylococcus aureus

By: Contributor(s): Publication details: New York SAGE 2024Edition: Vol.15(3), SepDescription: 316-326pSubject(s): Online resources: In: Journal of pharmacology and pharmacotherapeuticsSummary: Staphylococcal scalded skin syndrome (SSSS) is a dermatological condition caused by Staphylococcus aureus, characterized by exfoliative toxin B, and its increasing resistance to conventional antibiotics necessitates the search for new therapeutic options. Aim The study aimed to investigate the potential of traditional medicinal compounds (TMCs) as potential pharmaceuticals against SSSS using molecular-level research. Introduction Staphylococcus aureus, commonly known as S. aureus, is the main cause of SSSS. These infections are a major concern for public health because they are becoming resistant to antibiotics. There is an urgent need for new medications to effectively fight against this infection. The main objective of this study was to assess the interaction between TMC compounds and S. aureus exfoliative toxins ETA and ETB utilizing computational approaches.
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Staphylococcal scalded skin syndrome (SSSS) is a dermatological condition caused by Staphylococcus aureus, characterized by exfoliative toxin B, and its increasing resistance to conventional antibiotics necessitates the search for new therapeutic options.
Aim
The study aimed to investigate the potential of traditional medicinal compounds (TMCs) as potential pharmaceuticals against SSSS using molecular-level research.
Introduction
Staphylococcus aureus, commonly known as S. aureus, is the main cause of SSSS. These infections are a major concern for public health because they are becoming resistant to antibiotics. There is an urgent need for new medications to effectively fight against this infection. The main objective of this study was to assess the interaction between TMC compounds and S. aureus exfoliative toxins ETA and ETB utilizing computational approaches.

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