Computational Analysis of Network Model Based Relationship of Mental Disorder with Depression

Biointerface Research in Applied Chemistry - Tập 10 Số 5 - Trang 6293-6305
Md. Rakibul Hasan1, Bikash Kumar2,1,3, Kawsar Ahmed2,3, Shahin Mahmud4, Mithun Dutta5, Touhid Bhuyian1
1Department of Software Engineering, Daffodil International University, Sukrabad, Dhanmondi, Dhaka 1205, Bangladesh
2Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University (MBSTU), Santosh, Tangail, 1902, Bangladesh
3Group of Bio-photomatiχ, Mawlana Bhashani Science and Technology University (MBSTU), Santosh, Tangail, 1902, Bangladesh
4Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Santosh, Tangail 1902, Bangladesh
5Department of Computer Science and Engineering, Rangamati Science and Technology University, Vedvedi, Rangamati-4500, Bangladesh

Tóm tắt

In this study, we present the network relationship of anxiety, eating and mood disorder with depression. Different computational network models have been demonstrated using different ongoing technologies. One of the most common mental illnesses can be classified as anxiety disorders. These are observable psychological conditions or a category of mental illnesses believed to be caused either by genetic weakness or by causes of environmental sensitivity. A wide range of psychological chronic conditions is often correlated with eating disorders (ED). However, the increasing role of lipid metabolism in ED pathogenesis has been highlighted by recent research studies. Depression (DE) acknowledgement is traced back to the ancient Greeks, who called it melancholia. The word depression has originated with the Greeks who used it to identify a specific condition, a God-given spiritual state, or a response involving rage or excitement, in different ways. Throughout drug research and development, finding innovative mechanisms is a massive challenge. In this field, structure-based design is a basic methodology and has become an essential part of developing drugs. The detailed three-dimensional structure of the protein is shown for a significant number of drug targets. While simulation docking and similar biotechnology have progressed in recent times, a suitable set of docking simulations for simulation performance is difficult to identify.

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