Molecular Mimicry Inference, Therapeutic Target Identification, and Natural Product Inhibition Study in Cardiobacterium valvarum through Bioinformatics Approach

利用生物信息学方法对瓣膜心杆菌进行分子模拟推断、治疗靶点鉴定和天然产物抑制研究

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Abstract

Cardiobacterium valvarum is a known cause of infective endocarditis (IE). Autoimmune responses have been implicated in contributing to the inflammatory processes observed in IE. Molecular mimicry significantly influences the interaction between pathogens and host immune systems, frequently resulting in autoimmune responses. This study employs a bioinformatics approach to identify candidate proteins exhibiting molecular mimicry in C. valvarum that might elicit immune reactions and contribute to inflammation. A total of 18 proteins depicted potential for autoimmunity based on homology and antigenicity. Further, subtractive proteomics was then applied to identify potential drug targets in the pathogen, and purK gene product (5-(carboxyamino)-imidazole ribonucleotide synthase) was utilized for downstream analysis. Molecular docking was used to assess the inhibitory potential of natural products derived from Ocimum tenuiflorum, Leonurus cardiaca, and Panax ginseng, which have previously been associated with protective effects against endocarditis. Five compounds were prioritized based on their AutoDock Vina binding scores: (1) a complex triterpenoid from P. ginseng, (2) a flavonoid derivative from L. cardiaca, and (3) a steroid and flavonoid from O. tenuiflorum. Among these, LTS0201798 and LTS0158828 appear to be more suitable for oral administration, while using a nanocarrier or complexing with cyclodextrin could enhance the suitability of the other compounds as well. LTS0201798 and LTS0158828 also showed good binding affinity and stable complexation over 100 ns of molecular dynamics simulation. Hence, we propose that future research should focus on validating our findings through experimental assays to confirm the efficacy of these compounds in clinical settings.

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