The correlation of structural and binding affinity of insulin analog to the onset of action for diabetic therapy
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Computation, Docking, Insulin analogue, Sequence similarity, Structure
Abstract
Background: These days, insulin analog production has been improved and becoming popular. The advantages of insulin analog have been extensively reviewed in terms of effectiveness compared to human insulin. Each of the insulin analog industries has claimed their safety and efficacy based on in vivo and in vitro to overcome type 2 diabetes. Hereby, we report on the identification of highly effective analog-based insulin on structure and binding affinity computationally, to confirm its potential and give a broader point of view to insulin analog users.
Methods: Five types of insulin analogs, Aspart, Glargine, Detemir, Lispro and Degludec, were analyzed. We grouped and clustered the sequence by alignment to identify the closeness and sequence similarity between samples, continued by superimposing analysis and undertaking binding affinity identification utilizing of a docking analysis approach.
Results: Lispro had the least sequence similarity to other types, close to Aspart (96%) and Glargine (90.5%), while Detemir and Degludec showed 100% similarity we decide to only use Degludec for the next analysis. Furthermore, Lispro, Aspart, and Glargine exhibited structural similarity strengthened by the lack of significant difference in the RMSD data. Importantly, Aspart had the highest binding affinity score (-66.1 +/- 7.1 Kcal/mol) in the docking analysis to the insulin receptor (INSR) and similar binding site areas to human insulin.
Conclusion: Our finding revealed that the strength of insulin analogs towards insulin receptors is identic with its rapid mechanism in the human body.
Keywords: computation, docking, insulin analog, sequence similarity, structure
Abstrak
Latar belakang: Saat ini, produksi analog insulin meningkat dan menjadi popular. Keuntungan analog insulin telah ditinjau secara ekstensif dalam hal efektivitas dibandingkan dengan insulin manusia. Masing-masing industri analog insulin mengklaim keamanan dan kemanjurannya berdasarkan in vivo dan in vitro untuk mengatasi diabetes tipe 2. Kami melaporkan identifikasi insulin analog yang efektif berdasarkan struktur dan afinitas pengikatan secara komputasi, untuk mengonfirmasi potensi serta memberikan sudut pandang yang lebih luas kepada pengguna insulin analog.
Metode: Lima jenis analog insulin, Aspart, Glargine, Detemir, Lispro, dan Degludec, dianalisis. Kami membandingkan dan mengelompokkan urutan tersebut dengan penyelarasan untuk mengidentifikasi kedekatan dan kesamaan urutan antar sampel dilanjutkan dengan superimposing analysis dan melakukan identifikasi binding affinity menggunakan pendekatan analisis docking.
Hasil: Lispro memiliki kemiripan sekuen paling rendah dengan jenis lainnya, mendekati Aspart (96%) dan glargine (90,5%), sedangkan Determir dan Degludec menunjukkan kemiripan 100% sehingga kami menggunakan Degludec untuk analisis selanjutnya. Selain itu, Lispro, Aspart, dan Glargine menunjukkan kesamaan struktural yang diperkuat oleh rendahnya nilai signifikansi pada data RMSD. Perlu digarisbawahi bahwa Aspart memiliki skor afinitas pengikatan tertinggi (-66.1 +/- 7.1 kkal / mol) dalam analisis docking ke reseptor insulin (INSR) dan memiliki area pengikatan yang serupa dengan insulin manusia.
Kesimpulan: Penemuan kami mengungkapkan bahwa kekuatan insulin analog sejalan dengan laju mekanismenya di dalam tubuh manusia
Kata kunci: komputasi, docking, insulin analog, kemiripan sekuen, struktur
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