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Journal of biomolecular structure & dynamics · 2026

Structure-function studies of four disulfide-containing insulins from Conus textile and Conus memiae and a snail-guided human insulin analogue.

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Dhannura Shweta, Patil Kashibai, Radhakrishna Krishnappa, Karemunge Ganesh, Revanasiddappa Prasanna D, Pasupulati Anil Kumar, Gowd Konkallu Hanumae

Аннотация

Cone snail insulins represent a unique class of insulin-like polypeptides that can regulate the human insulin receptor, offering valuable lead compounds for the treatment of diabetes and its complications. Among these, signalling insulins constitute the predominant class of snail insulins and are characterized by the presence of an additional fourth disulfide bond in the sequence. However, studies examining their affinity for the human insulin receptor remain limited. Database analysis revealed signalling insulins from Conus textile (Scon-ins Tx1) and Conus memiae (Scon-ins Me1) with chain lengths comparable to that of human insulin. In this study, computational approaches were employed to predict the 3D structures of these signalling insulins and evaluate their binding affinity toward the human insulin receptor (hIR). The 3D structures of Scon-ins Tx1 and Scon-ins Me1 were computed using AlphaFold 3 and modelling-simulation methods, yielding in distinct conformations for the same polypeptide. AlphaFold 3 models retained the canonical three-helix fold, whereas the modelled-simulated structures exhibited reduced helical content. Further, AlphaFold 3 models possess higher disulfide strain energy compared to the modelled-simulated structures. Binding affinity calculations showed that Scon-ins Tx1 exhibits comparable affinity to human insulin at the site-1 pocket of hIR but lower affinity at the site-2 pocket. Furthermore, a newly designed snail-guided human insulin (SHum-Ins-A4-B2-4SS) exhibited structural features and binding affinities comparable to those of Scon-ins Tx1, further supporting the findings of this study. The results of current computational findings identify Scon-ins Tx1 as a suitable candidate for future experimental validation and potential development as a diabetes therapeutic.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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