Homology modeling identified for purported drug targets to the neuroprotective effects of levodopa and asiaticoside-D in degenerated cerebral ganglions of Lumbricus terrestris

通过同源建模,确定了左旋多巴和积雪草苷D在蚯蚓退化脑神经节中发挥神经保护作用的潜在药物靶点。

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Abstract

CONTEXT: Homology modeling plays role in determining the therapeutic targets dreadful for condition such as neurodegenerative diseases (NDD), which pose challenge in achieving the effective managements. The structures of the serotonin transporter (SERT), aquaporin (AQP), and tropomyosin receptor kinase (TrkA) which are implicated in NDD pathology are still unknown for Lumbricus terrestris, but the three-dimensional (3D) structure of the human counterpart for modeling. AIM: This study aims to generate and evaluate the 3D structure of TrkA, SERT, and AQP proteins and their interaction with the ligands, namely Asiaticoside-D (AD) and levodopa (L-DOPA) the anti-NDD agents. SUBJECTS AND METHODS: Homology modeling for SERT, AQP, and TrkA proteins of Lumbricus terrestris using SWISS-MODEL Server and the modeled structure was validated using Rampage Server. Wet-lab analysis of their correspondent m-RNA levels was also done to validate the in silico data. RESULTS: It was found that TrkA had moderately high homology (67%) to human while SERT and AQP could exhibit 58% and 42%, respectively. The reliability of the model was assessed by Ramachandran plot analysis. Interactions of AD with the SERT, AQP-4, and TrkA showed the binding energies as -9.93, 8.88, and -7.58 of Kcal/mol, respectively, while for L-DOPA did show -3.93, -5.13, and -6.0 Kcal/mol, respectively. The levels of SERT, TrkA, and AQP-4 were significantly reduced (P < 0.001) on ROT induced when compared to those of control worms. On ROT + AD supplementation group (III), m-RNA levels were significantly increased (P < 0.05) when compared to those of ROT induced worms (group II). CONCLUSION: Our pioneering docking data propose the possible of target which is proved useful for therapeutic investigations against the unconquered better of NDD.

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