Bipolar disorder is a psychiatric condition that consists of recurring episodes of severe mood swings between depression and manic episodes. The diagnosis is generally based on clinical interviews and observations, but is often misdiagnosed as unipolar depression, leading to significant delays in treatment. However, the disorder's heterogeneous nature and overlap with other psychiatric conditions, such as schizophrenia, present challenges in its diagnosis and treatment. To address these challenges, this study aims to explore the gene targets of differentially expressed miRNA associated with differentially expressed genes and to find a suitable phytochemical through molecular docking studies. The altered expression level of miRNAs (either increased or decreased) and genes had been observed to play a crucial role in different psychiatric disorders, thus suggesting their potential as biomarkers. The data of patients with bipolar disorder was retrieved from the Gene expression omnibus and Sequence read archive. The differentially expressed genes and miRNAs were identified through DESeq2 post processing. The gene targets of the downregulated miRNA and the upregulated genes were compared to identify the main targets of bipolar disorder. Furthermore, the phytochemicals with neuro-protective properties were identified through a literature study. The drug likeness property of each phytochemical was evaluated on the basis of Lipinski's rule of 5, followed by a toxicity evaluation. Molecular docking studies were carried out using AutoDock to determine the best drug against bipolar disorder. Therefore, the present study targets key proteins overexpressed in patients with bipolar disorder to facilitate a multi-faceted treatment approach.
Citation: Harshita Maheshwari, Maitreyi Pathak, Prekshi Garg, Prachi Srivastava. Computational analysis reveals the therapeutic potential of Asiatic acid against the miRNA correlated differentially expressed genes of bipolar disorder[J]. AIMS Molecular Science, 2024, 11(2): 99-115. doi: 10.3934/molsci.2024007
Bipolar disorder is a psychiatric condition that consists of recurring episodes of severe mood swings between depression and manic episodes. The diagnosis is generally based on clinical interviews and observations, but is often misdiagnosed as unipolar depression, leading to significant delays in treatment. However, the disorder's heterogeneous nature and overlap with other psychiatric conditions, such as schizophrenia, present challenges in its diagnosis and treatment. To address these challenges, this study aims to explore the gene targets of differentially expressed miRNA associated with differentially expressed genes and to find a suitable phytochemical through molecular docking studies. The altered expression level of miRNAs (either increased or decreased) and genes had been observed to play a crucial role in different psychiatric disorders, thus suggesting their potential as biomarkers. The data of patients with bipolar disorder was retrieved from the Gene expression omnibus and Sequence read archive. The differentially expressed genes and miRNAs were identified through DESeq2 post processing. The gene targets of the downregulated miRNA and the upregulated genes were compared to identify the main targets of bipolar disorder. Furthermore, the phytochemicals with neuro-protective properties were identified through a literature study. The drug likeness property of each phytochemical was evaluated on the basis of Lipinski's rule of 5, followed by a toxicity evaluation. Molecular docking studies were carried out using AutoDock to determine the best drug against bipolar disorder. Therefore, the present study targets key proteins overexpressed in patients with bipolar disorder to facilitate a multi-faceted treatment approach.
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Figures(5) / Tables(4)
Harshita Maheshwari, Maitreyi Pathak, Prekshi Garg, Prachi Srivastava. Computational analysis reveals the therapeutic potential of Asiatic acid against the miRNA correlated differentially expressed genes of bipolar disorder[J]. AIMS Molecular Science, 2024, 11(2): 99-115. doi: 10.3934/molsci.2024007
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