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      Deciphering functional biomolecule potential of marine diatoms through complex network approach.

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          Abstract

          Marine diatoms are unique reservoirs of bioactive compounds having enormous applications in therapeutics. But high-throughput screening methods are needed to elucidate the interaction between numerous biomolecules and their targets, facilitating rapid screening for novel drug molecules. So, in the present study chemical constituents were extracted from five marine diatoms using un-targeted metabolite profiling and in-silico virtual screening bioinformatics was employed to predict their bioactivity and molecular targets. A total of 17 chemical constituents out of 51 showed interactions with 76 protein targets associated with 213 pathways. Ingredient-target-pathway network revealed oleic acid, linoleic acid and cholest-5-en-3-ol as major active constituents. Core subnetwork and protein association network showed involvement of these compounds in key metabolic pathways related to cell signaling, cell growth and metabolism of xenobiotics. Thus, the present study for the first time revealed the main active ingredients and their associated pathways from marine diatoms using complex network approach.

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          Author and article information

          Journal
          Bioresour Technol
          Bioresource technology
          Elsevier BV
          1873-2976
          0960-8524
          Dec 2021
          : 342
          Affiliations
          [1 ] Algae Biomass and Energy System R&D Center (ABES), University of Tsukuba, Tennodai 1-1-1, Tsukuba, Ibaraki, Japan.
          [2 ] Amity Institute of Biotechnology, Amity University, Uttar Pradesh, India.
          [3 ] Department of Separation Science, LUT School of Engineering Science, LUT University, Sammonkatu 12, Mikkeli, Finland.
          [4 ] Amity Institute of Biotechnology, Amity University, Uttar Pradesh, India. Electronic address: panarchana@gmail.com.
          Article
          S0960-8524(21)01269-4
          10.1016/j.biortech.2021.125927
          34543817
          462cbd79-9774-4fa7-a068-ac19618f0d81
          History

          Pathway analysis,Diatoms,Complex network approach,Bioactive compounds

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