Predictive Simulation and Functional Insights of Serotonin Transporter: Ligand Interactions Explored through Database Analysis

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Through its ability to facilitate the absorption of serotonin into presynaptic neurons, the serotonin transporter, also known as SERT, an essential component in the control of neurotransmission. To discover SERT possible therapeutic application, it is essential to have a solid understanding of its dynamic behavior, ligand interactions, and functional consequences. Within the scope of this investigation, the predictive simulations is crucial to investigate the complexities of SERT to gain a fresh understanding of its operation. We use the 6AWN model to describe the sequence and simulate the behavior of SERT in silico. Within this simulation, we anticipate the conformational changes of SERT and its reaction to ligand binding with paroxetine, cholesterol, dodecyl-beta-D-maltose (DDM), and sodium hydrogen ion. We discover critical residues that are crucial in the interaction between ligands and proteins. They have paroxetine binding to I.172, I.172, Y.176, and F.341 are examples of hydrophobic interactions. Example of hydrogen bonds include A.96 and pi-stacking: F.341. The blockage of the serotonin transporter is the principal mechanism of action that paroxetine has. Cholesterol interacts with SERT W.500, W.500, W.500, W.500, L.504, and A.507, and it also interacts with the outward-facing conformation of this transporter in two different ways. In general, cholesterol interacts with SERT and ligands to stabilize their optimal activity and structure. DDM contact with SERT is also a part of this interaction. R.104, D.328, E.494, Y.495, G.498, P.499, T.503, F.556, L.557, S.559, P.561, Y.579, G.582, T.583, and F.586 are the numbers that are currently in use. Within the context of glucosyl transfer processes, DDM has been utilized as an acceptor. And the interaction of Na with SERT S.263, which causes a change in the structure of SERT. Serotonin transporters are present in the environment.

Original languageEnglish
Pages (from-to)52-59
Number of pages8
JournalPharmacognosy Journal
Issue number1
Publication statusPublished - 2024


  • Database Analysis
  • Functional analysis
  • Predictive in silico
  • Serotonin Transporter


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