Optimizing 3D Structural Predictions of Murine β2-Adrenergic Receptor: Swiss-Model Outperforms AlphaFolds

ABSTRACT

Background and Aim: The β2 adrenergic receptor is vital in physiological processes and a key target for metabolic syndrome. Understanding the structural attributes of the murine β2-AR is crucial for comprehending metabolic regulation due to its close resemblance to the human β2-AR. Our study aimed to model the 3D structure of murine β2-AR using molecular simulation techniques to bridge gaps in structural understanding. Materials and Methods: In this study, we utilized in silico approaches to predict the 3D structure of murine β2-AR, employing 4 distinct modelling servers: SWISS-MODEL, Phyre2, I-TASSER and AlphaFold. Primary sequence analysed using Expasy’s Protparam provided insights into charge distribution, stability and hydrophobic properties. Stereochemical analysis was performed using Ramachandran plot. Results: The primary sequence analysis of murine β2-AR revealed important characteristics, including an isoelectric point of 7.07 and an instability index score of 42.24. The high aliphatic index of 94.86 suggests thermal stability, while the GRAVY score of 0.145 indicates mild hydrophobicity. SWISS-MODEL emerged as the most reliable predictor, producing a highly promising structure with the maximum number of residues in favoured regions of the Ramachandran plot (93.1%) and no residues in disallowed regions. Additionally, the predicted structure exhibited a substantial number of helices (19) and a moderate number of turns (22) and strands (2), indicating its robust conformation. A 50 ns MD simulation demonstrated the consistent stability and integrity of the β2-AR protein. Conclusion: The homology model predicted by SWISS-MODEL outperformed those generated by AlphaFold. Overall, our findings underscore the significance of integrating computational modelling with experimental validation to unravel the intricate structural information of murine β2-AR and its implications in translational research.

KEYWORDS

• β2 adrenergic receptors
• Metabolic syndrome
• AlphaFold
• SWISS-MODEL
• Computational modelling

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• DOI10.5530/ijper.20256524Copy

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