Year: 2025
Type: article
Abstract: High Resolution Image Download MS PowerPoint Slide This study presents a comprehensive in silico framework, integrating network pharmacology, molecular docking, survival analysis, and pharmacokinetic profiling, to identify and prioritize bioactive porcine placenta peptides for lymphoma therapy. Initial protein–protein interaction (PPI) network analysis identified BCL2L1, CASP3, and NFKB1 as key hub proteins, with pathway enrichment analysis highlighting their significant involvement in apoptosis and the sphingolipid signaling pathway. Validating their clinical relevance, survival analysis in an Acute Myeloid Leukemia (AML) cohort confirmed that high expression of BCL2L1 (HR = 0.79, p = 0.00011) and CASP3 (HR = 0.83, p = 0.0018) is significant favorable prognostic markers, underscoring their value as therapeutic targets. Molecular docking studies on the key antiapoptotic target, BCL2L1, revealed that peptides ILLEVNNR and ESLITLIEK exhibited the highest binding affinities (−189.95 kcal/mol and −181.02 kcal/mol, respectively). However, a critical subsequent pharmacokinetic analysis predicted that these high-affinity candidates, along with most others, would be substrates for the P-glycoprotein (P-gp) efflux pump, a primary mechanism of drug resistance that limits therapeutic potential. In stark contrast, the peptide QPLLLDDR, despite a more moderate binding affinity (−157.25 kcal/mol), was uniquely identified as a P-gp nonsubstrate. This advantageous pharmacokinetic profile suggests that QPLLLDDR can evade efflux-mediated resistance, thereby achieving higher and more sustained intracellular concentrations. Collectively, this research underscores the necessity of a multiparameter approach for lead compound identification. By balancing high target efficacy with crucial drug-like properties, QPLLLDDR is identified not merely as a candidate but as the most pragmatically viable lead compound for future experimental validation as a parenteral therapeutic for lymphoma.
Source: ACS Omega
Institutions: Walailak University, Umeå University
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,935
Funder: Walailak University
OpenAlex ID: W4417311701