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Interaction of antitumoral drug erlotinib with biodegradable triblock copolymers: a molecular modeling study

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Combination of molecular dynamics simulations and miscibility calculations was used to investigate erlotinib drug delivery systems based on poly-ε-caprolactone–polyethylene glycol–poly-ε-caprolactone (PCL–PEG–PCL) and poly-ε-caprolactone–polyglycolic acid–poly-ε-caprolactone (PCL–PGA–PCL) biodegradable copolymers. The molecular modeling strategy involving visual observation of models, concentration profile analysis, Flory–Huggins χ parameter, cohesive energy density, and mean square displacement calculations reproduced experimental evidence of erlotinib release from PCL–PEG–PCL matrix successfully. Increasing portion of PCL in PCL–PEG–PCL copolymer led to dissolution of erlotinib aggregates recorded in visual and concentration profile analyses. Higher portion of PCL led to higher cohesive energy density and lower mean square displacement values. Success of this strategy in reproduction of experimental data made an opportunity to utilize the same modeling design in prediction of erlotinib release from similar but not yet experimentally tested PCL–PGA–PCL matrix. In this case, agglomeration of erlotinib molecules and stronger cohesive energy density values were observed.

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Acknowledgements

This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic (project number SP2016/75), European Regional Development Fund in the IT4Innovations national supercomputing center – path to exascale project (project number CZ.02.1.01/0.0/0.0/16_013/0001791) within the Operational Programme Research, Development and Education, and National Programme of Sustainability II – IT4Innovations excellence in science (project number LQ1602). Support by two IT4Innovations internal projects (IT4I-7-10 and IT4I-9-20) is also highly appreciated.

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Correspondence to Diana Klushina.

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Hlaváč, D., Klushina, D. & Tokarský, J. Interaction of antitumoral drug erlotinib with biodegradable triblock copolymers: a molecular modeling study. Chem. Pap. 72, 2023–2034 (2018). https://doi.org/10.1007/s11696-018-0413-y

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  • DOI: https://doi.org/10.1007/s11696-018-0413-y

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