Authors: A.D. Costache, L. Sheihet, D.D. Knight, J. Kohn
Affilation: Rutgers University, United States
Pages: 76 - 78
Keywords: drug delivery systems, molecular dynamics, docking
The intensive labor and high cost of developing new vehicles for the delivery of drugs in a controlled manner, highlights the need for a change in their discovery process. Predictive computational models can be used to accelerate the selection process of lead compounds to deliver drugs, from large polymer libraries, prior synthesis and biological characterization. Current research suggests that efficient and stable incorporation of drugs into nanoparticles is governed not only by solubility and hydrophobicity, but also by other factors such as rigidity, interactions, conformation and/or configuration of the nanospheres-forming polymer and drug. Tyrosine-derived nanospheres composed of an ABA-type block copolymer, where the A blocks are poly (ethylene glycol) and the B-blocks are hydrophobic low molecular weight polyarylates, have previously shown an effective binding of certain lipophilic drugs. To better understand the interaction and binding affinity of drugs with these nanospheres, we have developed a computational method that combines Molecular Dynamics (MD) simulations and docking studies. Curcumin (nutraceutical) and paclitaxel (anti-cancer) drugs were used as model compounds and compared with experimental data regarding their binding to nanospheres made of poly(desaminotyrosyl–tyrosine octyl ester suberate) and 5000Da PEG blocks, (DTO-SA/5K). Preliminary results demonstrate the feasibility of the proposed model and the predicted relative binding affinity is in agreement with experimental values. The proposed method has the potential to become an important step in prescreening studies. The computational approach can accelerate the discovery of suitable polymers for specific drug delivery systems without the need to synthesize the polymers first. In this way, the cost of development can be reduced.