Diabetic Kidney Disease (DKD), a frequent consequence of diabetes, has substantial implications for both morbidity and mortality rates, prompting the exploration of new metabolic biomarkers due to limitations in current methods like creatinine and albumin measurements. Pentraxin 3 (PTX3) shows promise for assessing renal inflammation in DKD. This study investigates how DKD metabolites could influence PTX3 expression through molecular docking, ADMET profiling, and dynamic simulation. Network and pathway analyses were conducted to explore metabolite interactions with DKD genes and their contributions to DKD pathogenesis. Thirty-three DKD-associated metabolites were screened, using pentoxifylline (PEN) as a reference. The pharmacokinetic properties of these compounds were evaluated through molecular docking and ADMET profiling. Molecular dynamics simulations over 200 ns assessed the stability of PTX3 (apo), the PRE-PTX3 complex, and PEN-PTX3 across multiple parameters. Cytoscape identified 1082 nodes and 1381 edges linking metabolites with DKD genes. KEGG pathway analysis underscored PTX3's role in inflammation. Molecular docking revealed pregnenolone sulfate (PRE) with the highest binding affinity (-6.25 kcal/mol), followed by hydrocortisone (-6.03 kcal/mol) and 2-arachidonoylglycerol (-5.92 kcal/mol), compared to PEN (-5.35 kcal/mol). ADMET profiling selected PRE for dynamic simulation alongside PEN. Analysis of RMSD, RMSF, RG, SASA, H-bond, PCA, FEL, and MM-PBSA indicated stable complex behavior over time. Our findings suggest that increasing PRE levels could be beneficial in managing DKD, potentially through isolating PRE from fungal sources, synthesizing it as dietary supplements, or enhancing endogenous PRE synthesis within the body.
Keywords: diabetes kidney disease; docking; dynamic simulation; metabolites; pharmacokinetics profile.
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