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Molecular Docking and In Silico Simulation of Trichinella spiralis Membrane-Associated Progesterone Receptor Component 2 ( Ts-MAPRC2 ) and Its Interaction with Human PGRMC1.

Muhammad Tahir AleemAsad KhanZhaohai WenZhengqing YuKun LiAftab ShaukatCheng ChenTauseef-Ur -RehmanMingmin LuLixin XuXiaokai SongXiangrui LiRuofeng Yan
Published in: BioMed research international (2022)
Background . Trichinellosis is a foodborne zoonotic disease caused by Trichinella spp., including Trichinella spiralis . This parasitic disease ranks as seven of the most infectious in the world. In this context, it is important to develop a vaccine that can combat Trichinellosis , especially for humans and pigs. This would be an important step in preventing transmission. In this study, we focus on homology modelling, binding site prediction, molecular modelling, and simulation techniques used to explore the association between Trichinella spiralis membrane-associated progesterone receptor component 2 ( Ts-MAPRC2 ) and the human PGRMC1 protein. It was found that the progesterone receptor component 2 of T. spirali s has 44.54% sequence identity with human PGRMC1 (PDB ID: 4X8Y). Binding sites predicted for human PGRMC1 are GLU 7, PHE 8, PHE 10, PHE 18, LEU 27, ASP 36, and VAL 104. Molecular docking has six clusters based on Z scores. They range from -1.5 to 1.8. It was found that the progesterone receptor component 2 of T. spiralis has 44.54% sequence identity with human PGRMC1. During simulation, the average RMSD was 2.44 ± 0.20 Å, which indicated the overall stability of the protein. Based on docking studies and computational simulations, we hypothesized that the interaction of the proteins Trichinella spiralis membrane-associated progesterone receptor component 2 and human PGRMC1 formed stable complexes. The discovery of Ts-MAPRC2 may pave the way for the development of drugs and vaccines to treat Trichinellosis .
Keyphrases
  • molecular docking
  • endothelial cells
  • induced pluripotent stem cells
  • pluripotent stem cells
  • molecular dynamics simulations
  • estrogen receptor
  • single cell
  • case control