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In silico prediction of the antagonistic activity of natural compounds on neuropeptide S receptor 1 in endometriosis
* 1 , 1 , 1 , 2 , * 3
1  Bioinformatic and Cheminformatics Group, Pharmacology Department, Faculty of Pharmacy and Biochemistry, National University of Trujillo, Trujillo 13011, Peru
2  Laboratory of Medicinal Chemistry, Pharmacology Department, Faculty of Pharmacy and Biochemistry, National University of Trujillo, Trujillo 13011, Peru
3  Laboratory of Research in Biopolymers and Metallopharmaceuticals (LIBIPMET), Faculty of Sciences, National University of Engineering, Lima 150128, Peru.
Academic Editor: Maria Camilla Bergonzi

Abstract:

Endometriosis, an emerging disease affecting approximately 25% of women of reproductive age, presents a complex clinical profile, primarily characterized by dysmenorrhea, bleeding, infertility, and chronic inflammation. Currently, the Neuropeptide S Receptor 1 (NPSR1) is the genetically validated therapeutic target for the treatment of endometriosis, as its blockade prevents the binding of its endogenous ligand (neuropeptide S), thereby inactivating intracellular metabolic pathways related to pain and inflammation mechanisms. Natural compounds have served as structural models for the development of new drugs. Based on the mechanism of its selective antagonist SHA-68R, the structural fragment “CNC(=O)N” was searched across various natural product databases, selecting 54 molecules. These were subsequently analyzed through 2D-QSAR of their molecular descriptors to predict antagonist activity (pKB). Their physicochemical and pharmacokinetic properties were evaluated in silico using SwissADME and Deep-pkCSM, along with their interactions with the NPSR1 receptor (retrieved in PDB format from the GPCR database using the code npsr1_human). To predict binding affinity energy (ΔG°), VINA 1.1.2 was used, and the molecules with the best parameters were visualized using the 2D tool in Discovery Studio. Rotihibin B exhibited optimal binding affinity (-8.7 kcal/mol), likely due to the formation of multiple hydrogen bonds. Its physicochemical profile exceeds Lipinski’s parameters, with a suitable pharmacokinetic profile compared to the antagonist SHA-68R. This research proposes this metabolite as a starting molecule for the design of more potent compounds for the treatment of this disease, thereby improving the quality of life for those affected.

Keywords: Endometriosis, Quantitative Structure-Activity Relationship (QSAR), Molecular Modeling, Chemoinformatics

 
 
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