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Bioactive Natural Products Identification Using Automation of Molecular Networking Software.
Baskiyar, Swati; Ren, Chang; Heck, Kabre L; Hall, Audrey M; Gulfam, Muhammad; Packer, Sadaira; Seals, Cheryl D; Calderón, Angela I.
Affiliation
  • Baskiyar S; Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, 3306 Walker Building, Auburn, Alabama 36849, United States.
  • Ren C; Department of Computer Science and Software Engineering, Auburn University, Auburn, Alabama 36849, United States.
  • Heck KL; Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, 3306 Walker Building, Auburn, Alabama 36849, United States.
  • Hall AM; Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, 3306 Walker Building, Auburn, Alabama 36849, United States.
  • Gulfam M; Department of Computer Science and Software Engineering, Auburn University, Auburn, Alabama 36849, United States.
  • Packer S; Department of Computer Science and Software Engineering, Auburn University, Auburn, Alabama 36849, United States.
  • Seals CD; Department of Computer Science and Software Engineering, Auburn University, Auburn, Alabama 36849, United States.
  • Calderón AI; Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, 3306 Walker Building, Auburn, Alabama 36849, United States.
J Chem Inf Model ; 62(24): 6378-6385, 2022 12 26.
Article in En | MEDLINE | ID: mdl-35947427
Secondary metabolites from natural sources are promising starting points for discovering and developing drug prototypes and new drugs, as many current treatments for numerous diseases are directly or indirectly related to such compounds. Recent advances in bioinformatics tools and molecular networking methods have made it possible to identify novel bioactive compounds. In this study, a workflow combining network-based methods for identifying bioactive compounds found in natural products was streamlined by innovating an automated bioinformatics software. The workflow relies on Global Natural Product Social Molecular Networking (GNPS), a web-based mass spectrometry ecosystem that aims to be an open-access knowledge base for community-wide organization and sharing of raw, processed, or annotated fragmentation mass spectrometry data. By combining computational tools including MZmine2, GNPS, and Cytoscape, the integrated dashboard quickly creates bioactive molecular networks with minimal user intervention and reduces the processing time of the original workflow by over 80%. This newly automated workflow quickens the process of discovering bioactive compounds from natural products. This study uses extracts from Psidium guajava leaves to demonstrate the application of our automated software.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Biological Products Type of study: Diagnostic_studies Language: En Journal: J Chem Inf Model Journal subject: INFORMATICA MEDICA / QUIMICA Year: 2022 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Biological Products Type of study: Diagnostic_studies Language: En Journal: J Chem Inf Model Journal subject: INFORMATICA MEDICA / QUIMICA Year: 2022 Type: Article Affiliation country: United States