IN SILICO STUDY OF APTAMER SPECIFICITY FOR DETECTION OF ADENOSINE TRIPHOSPHATE (ATP) AS BIOSENSOR DEVELOPMENT FOR MITOCHONDRIA DIABETES DIAGNOSIS

Year 2023, Volume: 7 Issue: 2, 58 - 69, 15.05.2023

Rustaman Rustaman , Rizky Rafi Rahmawan , Iman Permana Maksum

https://doi.org/10.33435/tcandtc.1181299

Cited By: 1

Abstract

Diabetes Mellitus (DM) is characterized by increased blood glucose levels. It is generally caused by the pancreas' inability to produce insulin due to cell damage or insulin resistance. Due to the inhibition of adenosine triphosphate (ATP) production, which is essential for insulin secretion, one clinical pathology of this complication is insulin secretion dysfunction. Common methods of blood sugar diagnostics cannot distinguish mitochondrial diabetes and can lead to medication errors. Furthermore, an approach was developed through ATP biomarkers using an electrochemical biosensor with the help of an aptamer. However, it remains unknown precisely how and where the molecular interactions between the modified aptamer and ATP occur. Simulations were conducted in this study for 100 ns in silico using the amber18 computer program to determine the stability of the interaction and specificity between aptamer-ATP were compared to ADP and AMP. The results showed that the significant interactions are three hydrogen bonds between ATP and G7, G8, and A24. It was discovered that the aptamer-ATP complex had moderately good interaction and better potential for specificity than ADP and AMP. According to the RMSD, RMSF, and binding energy profiles, the system is still searching for the best conformation, necessitating a longer simulation time and additional studies to optimize the system. As a result, the system can reach a stable state and determine a more accurate energy calculation, hence, it is interpreted according to real applications.

Keywords

aptamer, atp, diabetes mellitus, in silico

Thanks

The author is grateful to the Directorate of Research and Community Service (DRPM) Unpad for the RDPD grant (Research Data Library and Online) No. 1318/UN6.3.1/PT.00/2022 and the 2020 Academic Leadership Grant (ALG) [1427/UN6.3.1/LT/2020 for funding this research.

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