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In silico computational prediction of Saussurea pulchella compounds with inhibitory effects on plasmepsin X in Plasmodium falciparum
- Source :
- Informatics in Medicine Unlocked, Vol 49, Iss , Pp 101549- (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
Abstract
- Malaria poses serious problems in countries located in tropical and subtropical regions worldwide. Plasmodium falciparum is responsible for approximately 90 % of malaria-related deaths worldwide. Therefore, alternative treatments are required to effectively reduce the number of malaria cases. Therefore, the objective of this study was to explore alternative malaria treatments by identifying compounds targeting P. falciparum plasmepsin X and characterizing the interactions under various temperatures. Molecular docking was used to evaluate interactions between polyphenolic compounds from Saussurea pulchella and plasmepsin X, followed by stability analyses using molecular dynamics (MD) simulations. Selected compounds were analyzed for biological activity, reactivity, and toxicity. RMSD (root mean square deviation), RMSF (root mean square fluctuation), Rg (radius of gyration), SASA (solvent-accessible surface area), and H-bonds were evaluated. Furthermore, MM-PBSA (molecular mechanics Poisson–Boltzmann surface area), PCA (principal component analysis), and DCCM (dynamic cross-correlation matrix) were use to evaluate effects of various temperatures. Pinoresinol 4-glucoside had a binding energy of 10.006 kcal/mol and was predicted to be nontoxic. MD simulations of pinoresinol 4-glucoside were conducted at different temperatures (298 K, 300 K, 305 K, 310 K, and 320 K) over a trajectory of 150 ns, revealing a strong binding energy using the MM-PBSA method. Our findings suggest that pinoresinol 4-glucoside is an alternative treatment for malaria and should be further evaluated at the laboratory and clinical levels.
Details
- Language :
- English
- ISSN :
- 23529148
- Volume :
- 49
- Issue :
- 101549-
- Database :
- Directory of Open Access Journals
- Journal :
- Informatics in Medicine Unlocked
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f37667e51984c6db2d621c60907d8e9
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.imu.2024.101549