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• W2061531844 abstract "A combination of molecular dynamics (MD) simulations and docking calculations was employed to model and predict polymer−drug interactions in self-assembled nanoparticles consisting of ABA-type triblock copolymers, where A-blocks are poly(ethylene glycol) units and B-blocks are low molecular weight tyrosine-derived polyarylates. This new computational approach was tested on three representative model compounds: nutraceutical curcumin, anticancer drug paclitaxel and prehormone vitamin D3. Based on this methodology, the calculated binding energies of polymer−drug complexes can be correlated with maximum drug loading determined experimentally. Furthermore, the modeling results provide an enhanced understanding of polymer−drug interactions, revealing subtle structural features that can significantly affect the effectiveness of drug loading (as demonstrated for a fourth tested compound, anticancer drug camptothecin). The present study suggests that computational calculations of polymer−drug pairs hold the potential of becoming a powerful prescreening tool in the process of discovery, development and optimization of new drug delivery systems, reducing both the time and the cost of the process." @default.
• W2061531844 created "2016-06-24" @default.
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• W2061531844 date "2009-08-18" @default.
• W2061531844 modified "2023-10-16" @default.
• W2061531844 title "Polymer−Drug Interactions in Tyrosine-Derived Triblock Copolymer Nanospheres: A Computational Modeling Approach" @default.
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• W2061531844 doi "https://doi.org/10.1021/mp900114w" @default.
• W2061531844 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2758936" @default.
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