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Background Human nucleotide triphosphate diphosphatase (NUDT15) is one of the essential proteins involved in the hydrolysis of anti-cancer drugs against leukemia. Polymorphisms in NUDT15 significantly affect the hydrolysis activity that leads to side effects, including leucopenia. Drugs having a better affinity with NUDT15 protein and contributing stable conformation may benefit patients from leucopenia. Most frequent NUDT15 polymorphisms causing structure variability and their association with leukemia were screened. The selected protein variants and anti-cancer drug structures were collected. Further, molecular docking was performed between drugs and NUDT15 variants along with the wild-type. Finally, molecular dynamics were executed for 100 ns to understand the stability of the protein with the anti-cancer drug based on molecular trajectories. Results Three-dimensional structures of NUDT15 wild, the most frequent variants (Val18Ile, Arg139Cys, and Arg139), and the anti-cancer drugs (azathioprine, mercaptopurine, and thioguanine) were selected and retrieved from structure databases. On molecular docking the binding energies of anti-cancer drugs against NUDT15 structures ranged from − 5.0 to − 5.9 kcal/mol. Among them, azathioprine showed the highest affinities (− 7.3 kcal/mol) for the wild and variant structures. Additionally, the molecular dynamics suggest all analyzed NUDT15 were stable with azathioprine based on the dynamic trajectories. Conclusion Our results suggest azathioprine could be the preferable anti-cancer drug for the population with NUDT15 variants that could effectively be hydrolyzed as evidenced by molecular docking and dynamic simulation.

Background Based on network pharmacology we forecast the targets and signal pathways of Sea buckthorns (SB) in the treatment of coronary artery disease (CAD).MethodsSB active components and possible targets were taken from the ChEMBL and SWISS-Prot prediction database. CAD-related targets were collected from the Genome-Wide Association Study database (GWAS). The STRING analysis was used to identify the " SB -active ingredient-target" network utilizing the common targets. Then, using a string database, we built and examined protein-to-protein interactions (PPI). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed. Further, we performed molecular docking analysis to identify the binding interaction of key targets and the SB active components. ResultsWe found 10 active SB components and 3 potential CAD targets. That Campesterol is the most active compound according to molecular docking results. Our GO enrichment study revealed 42 biological processes and 42 GO items. The apoptosis, focal adhesion, and T cell receptor signaling pathways were among the 33 KEGG signaling pathways found. SB might have a role in CAD therapy by modulating distinct signaling pathways, according to our findings. The target-compound correlation was validated by the molecular docking experiment.ConclusionsWe identified SB active compound campesterol can be used for the treatment of CAD. Further, experimental and clinical study needed to confirm the efficacy of the active compound.