Introduction: Obesity is a result of a trifecta of poor diet. Medication for obesity falls into five categories. However, due to their severe adverse effects and low efficacy, existing pharmaceutical therapies are only marginally useful. Therefore, the purpose of this research is to identify natural substances that can be used to prevent and treat obesity and associated diseases. Methods: The 3D structure of pancreatic lipase (PDB ID: pancreatic lipase-colipase) was obtained from the protein data repository with a precision of 2.46. The file, in.pdb format, belongs to the Protein Data Bank. Natural chemicals, was obtained from PubChem. Pharmit software was used to generate the pharmacophore model. The co-crystallized structure served as the foundation for the pharmacophore model. Virtual screening is a drug discovery process that looks for structures with the best likelihood of binding to a therapeutic target. BioVIA Discovery Studio was utilized to identify two-dimensional interactions, whereas PyMOL was utilized to generate intricate receptor and ligand files. We analyze the ADMET properties of the chosen compounds using QikProp. We simulate molecular dynamics for 100 nanoseconds using Desmond software. Results: The Natural Product Atlas database for substances was similar to the properties of the pharmacophore model. Using the PubChem data source, 33372 chemicals were assembled into a library. Sorting 1005 identified hits by their pharmacophore-fit RMSD score resulted in the selection of the top 20 compounds from pharmacophore-based virtual screening. QikProp filtered ADMET properties. Lastly, QPlogKhsa estimated the binding to human serum albumin and provided a range of 1.5 to 1.5. Two medications, NPA002198 and NPA030453, were shown to be the most effective compounds against pancreatic lipase-colipase after lead discovery. Eigenvalues (36.4-76.4% and 25.2-69.9%). The percentage of secondary structural components in pancreatic lipase-colipase-NPA030453 was calculated to be 42.44 percent, with helical and strand rates of 16.17% and 26.26%, respectively. Hydrogen bonds were the most significant receptor-ligand interactions discovered by MD. GLY_76, PHE_77, ILE_78, ASP_79, SER_152, and PHE_215 were the most important hydrogen bonding sites in the pancreatic lipase-colipase-NPA002198 complex. Conclusion: The study found the Natural Product Atlas-approved drugs NPA002198 and NPA030453, which suppressed pancreatic lipase-colipase function. Virtual screening, docking analysis, and pharmacophore modeling was used to identify compounds with the lowest binding affinities to the target protein. We concluded that these compounds might serve as a lead chemical in the development of anti-obesity medicines. These results will benefit science by allowing researchers to develop new pharmaceuticals that can more effectively treat overweight.