A Computational Study of Doxorubicin Analogues Conjugated To Polysorbate 80 for Targeted Delivery to the Brain Tumor

Abstract

Drug discovery for the treatment of central nervous system (CNS) diseases is a highly complex affair, especially due to the blood brain barrier (BBB) restricting the entry of many drugs. In the present study, we utilized in silico studies to screen twelve derivatives of doxorubicin (DOX) against seven tumor proteins (3LGL,2IG0, 3LGF, 4RG2, 3PG7, 3LH0 and 4HBM). The DOX ligands were modelled and optimized using DFT, and the binding affinity was evaluated. Later, an attempt was made to model modified DOX ligands with polysorbate 80 (PS80). After categorizing 12 DOX ligands and 12 DOX‐PS80 conjugated ligands, the top‐ranked three DOX ligands (R6_, R4, and R9) are conjugated with PS80 (R6‐PS80, R4‐PS80, and R9‐PS80). The LE of the best docked system also showed the highest which indicates a minimal number of atoms for strong binding and is favorable for drug‐like properties. Total of six systems is underwent comprehensiveMD analysis. The best DOX ligands and their conjugated systems were subjected to a thorough examination for structural stability (RMSD), H‐bond, effect of SASA, and R_g. The results demonstrated that all six systems exhibited folding behavior and were highly stable. Furthermore, we employed MM/GBSA to figure out realistic binding free energy of the top three DOX‐PS80 systems. Using the ADMET AI server it is shown that attaching to PS80 could potentially decrease the overall toxicity of DOX ligands. These findings indicate that the modified DOX ligands when combined with PS80, have the potential to cross the BBB and could be used for further in vitro and in vivo evaluation.