Preprint / Version 1

Metabolomic Profiling of Leptadenia reticulata: Unveiling Therapeutic Potential for Inflammatory Diseases through Network Pharmacology and Docking Studies

Authors

  • Yashaswini Adinarayanaswamy Department of Genetic Engineering, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur 603203, Tamil Nadu, India; [email protected] (Y.M.A.); [email protected] (D.P.)
  • Deepthi Padmanabhan Department of Genetic Engineering, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur 603203, Tamil Nadu, India; [email protected] (Y.M.A.); [email protected] (D.P.)
  • Purushothaman Natarajan Department of Biology, West Virginia State University, Institute, WV 25112-1000, USA; [email protected]
  • Senthilkumar Palanisamy Department of Genetic Engineering, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur 603203, Tamil Nadu, India; [email protected] (Y.M.A.); [email protected] (D.P.)

Keywords:

drug discovery, medicinal plants, network pharmacology, phytocompounds, small molecules

Abstract

Medicinal plants have been utilized since ancient times for their therapeutic properties, offering potential solutions for various ailments, including epidemics. Among these, Leptadenia reticulata, a member of the Asclepiadaceae family, has been traditionally employed to address numerous conditions such as diarrhea, cancer, and fever. In this study, employing HR-LCMS/MS(Q-TOF) analysis, we identified 113 compounds from the methanolic extract of L. reticulata. Utilizing Lipinski’s rule of five, we evaluated the drug-likeness of these compounds using SwissADME and ProTox II. SwissTarget Prediction facilitated the identification of potential inflammatory targets, and these targets were discerned through the Genecard, TTD, and CTD databases. A network pharmacology analysis unveiled hub proteins including CCR2, ICAM1, KIT, MPO, NOS2, and STAT3. Molecular docking studies identified various constituents of L. reticulata, exhibiting high binding affinity scores. Further investigations involving in vivo testing and genomic analyses of metabolite-encoding genes will be pivotal in developing efficacious natural-source drugs. Additionally, the potential of molecular dynamics simulations warrants exploration, offering insights into the dynamic behavior of protein–compound interactions and guiding the design of novel therapeutics. Keywords: drug discovery, medicinal plants, network pharmacology, phytocompounds, small molecules

Author Biographies

Deepthi Padmanabhan, Department of Genetic Engineering, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur 603203, Tamil Nadu, India; [email protected] (Y.M.A.); [email protected] (D.P.)

Methodology, Resources, Writing – review & editing

Purushothaman Natarajan, Department of Biology, West Virginia State University, Institute, WV 25112-1000, USA; [email protected]

Software, Validation

Senthilkumar Palanisamy, Department of Genetic Engineering, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur 603203, Tamil Nadu, India; [email protected] (Y.M.A.); [email protected] (D.P.)

Conceptualization, Investigation, Supervision, Project administration