Decoding Anti-Amyloidogenic and Fibril Neutralizing Action of Gut Microbiota-Derived Indole 3-Acetic Acid on Insulin Fibrillation through Multispectroscopic, Machine Learning, and Hybrid Quantum Mechanics/Molecular Mechanics Approaches.
Saswati Soumya Mohapatra, Krishna Singh Bisht, Sakshi Suryawanshi, Shreshth Gupta, Viplov Kumar Biswas, Ayon Chakraborty, Sunil Kumar Raghav, Tushar Kanti Maiti, Rajiv K Kar, Ashis Biswas
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引用次数: 0
Abstract
Insulin fibrillation inflicts both economic and clinical challenges by causing bioactivity loss, inflammation, and adverse effects during storage, transport, and injection. The present study explores antiamyloidogenic and fibril-disaggregating effects of a gut microbiota-derived indole metabolite, indole-3-acetic acid (IAA) on insulin fibrillation. According to Thioflavin T (ThT) fluorescence assays and transmission electron microscopy (TEM), IAA significantly inhibited both primary and seed-induced fibrillation of insulin. We note that IAA reduced insulin aggregate sizes as evident from the scattering profiles, while circular dichroism studies confirmed that IAA preserves native α-helical structure possibly minimizing the exposed surface hydrophobicity of insulin. Additionally, IAA showed effectiveness in breaking apart preformed fibrils, indicated by a time-dependent decrease in ThT fluorescence and further confirmed by TEM. Our biolayer interferometry interaction studies revealed a moderate 2:1 binding affinity between IAA and insulin. Two key binding sites on insulin were identified via machine-learning-based-docking and hybrid QM/MM studies, where IAA interacts. Site I (Leu13A, Tyr14A, Glu17A, Phe1B) showed more favorable interaction energetics than site II (Tyr19A, Phe25B, Thr27B) based on SAPT0 residue-wise interaction energy analysis. IAA also protected cells from fibril-induced cytotoxicity and hemolysis, thereby offering a promising therapeutic option for amyloid-related disorders, with dual action in preventing fibril formation and promoting fibril disaggregation.
期刊介绍:
An essential criterion for acceptance of research articles in the journal is that they provide new physical insight. Please refer to the New Physical Insights virtual issue on what constitutes new physical insight. Manuscripts that are essentially reporting data or applications of data are, in general, not suitable for publication in JPC B.