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Full-Atomistic Optimized Potentials for Liquid Simulations and Polymer Consistent Force Field Models for Biocompatible Shape-Memory Poly(ε-caprolactone)

[Image: see text] Thermally induced shape memory poly(ε-caprolactone) (PCL)-based polymers are one of the most extensively researched families of biocompatible materials. They are degradable under physiological conditions and have high applicability in general biomedical engineering, with cross-link...

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Autores principales: Yungerman, Irena, Starodumov, Ilya, Fulati, Ailifeire, Uto, Koichiro, Ebara, Mitsuhiro, Moskovitz, Yevgeny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169671/
https://www.ncbi.nlm.nih.gov/pubmed/35605974
http://dx.doi.org/10.1021/acs.jpcb.2c01973
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author Yungerman, Irena
Starodumov, Ilya
Fulati, Ailifeire
Uto, Koichiro
Ebara, Mitsuhiro
Moskovitz, Yevgeny
author_facet Yungerman, Irena
Starodumov, Ilya
Fulati, Ailifeire
Uto, Koichiro
Ebara, Mitsuhiro
Moskovitz, Yevgeny
author_sort Yungerman, Irena
collection PubMed
description [Image: see text] Thermally induced shape memory poly(ε-caprolactone) (PCL)-based polymers are one of the most extensively researched families of biocompatible materials. They are degradable under physiological conditions and have high applicability in general biomedical engineering, with cross-linked PCL networks being particularly useful for tissue engineering. In this study, we used the optimized potentials for liquid simulations (OPLS) force field, which is well suited for describing intermolecular interactions in biomolecules, and the class II polymer consistent force field (PCFF) to investigate the properties of telechelic PCL with diacrylates as reactive functionalities on its end groups. PCFF has been specifically parameterized for simulating synthetic polymeric materials. We compare the findings of all-atom molecular dynamics simulations with known experimental data and theoretical assumptions to verify the applicability of both these force fields. We estimated the melt density, volume, transition temperatures, and mechanical characteristics of two-branched PCL diacrylates with a molecular weight of 2481 Da. Our findings point to the utility of the aforementioned force fields in predicting the properties of PCL-based polymers. It also opens avenues for developing PCL cross-linked polymer models and employing OPLS to investigate the interactions of synthetic polymers with biomolecules.
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spelling pubmed-91696712023-05-23 Full-Atomistic Optimized Potentials for Liquid Simulations and Polymer Consistent Force Field Models for Biocompatible Shape-Memory Poly(ε-caprolactone) Yungerman, Irena Starodumov, Ilya Fulati, Ailifeire Uto, Koichiro Ebara, Mitsuhiro Moskovitz, Yevgeny J Phys Chem B [Image: see text] Thermally induced shape memory poly(ε-caprolactone) (PCL)-based polymers are one of the most extensively researched families of biocompatible materials. They are degradable under physiological conditions and have high applicability in general biomedical engineering, with cross-linked PCL networks being particularly useful for tissue engineering. In this study, we used the optimized potentials for liquid simulations (OPLS) force field, which is well suited for describing intermolecular interactions in biomolecules, and the class II polymer consistent force field (PCFF) to investigate the properties of telechelic PCL with diacrylates as reactive functionalities on its end groups. PCFF has been specifically parameterized for simulating synthetic polymeric materials. We compare the findings of all-atom molecular dynamics simulations with known experimental data and theoretical assumptions to verify the applicability of both these force fields. We estimated the melt density, volume, transition temperatures, and mechanical characteristics of two-branched PCL diacrylates with a molecular weight of 2481 Da. Our findings point to the utility of the aforementioned force fields in predicting the properties of PCL-based polymers. It also opens avenues for developing PCL cross-linked polymer models and employing OPLS to investigate the interactions of synthetic polymers with biomolecules. American Chemical Society 2022-05-23 2022-06-02 /pmc/articles/PMC9169671/ /pubmed/35605974 http://dx.doi.org/10.1021/acs.jpcb.2c01973 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Yungerman, Irena
Starodumov, Ilya
Fulati, Ailifeire
Uto, Koichiro
Ebara, Mitsuhiro
Moskovitz, Yevgeny
Full-Atomistic Optimized Potentials for Liquid Simulations and Polymer Consistent Force Field Models for Biocompatible Shape-Memory Poly(ε-caprolactone)
title Full-Atomistic Optimized Potentials for Liquid Simulations and Polymer Consistent Force Field Models for Biocompatible Shape-Memory Poly(ε-caprolactone)
title_full Full-Atomistic Optimized Potentials for Liquid Simulations and Polymer Consistent Force Field Models for Biocompatible Shape-Memory Poly(ε-caprolactone)
title_fullStr Full-Atomistic Optimized Potentials for Liquid Simulations and Polymer Consistent Force Field Models for Biocompatible Shape-Memory Poly(ε-caprolactone)
title_full_unstemmed Full-Atomistic Optimized Potentials for Liquid Simulations and Polymer Consistent Force Field Models for Biocompatible Shape-Memory Poly(ε-caprolactone)
title_short Full-Atomistic Optimized Potentials for Liquid Simulations and Polymer Consistent Force Field Models for Biocompatible Shape-Memory Poly(ε-caprolactone)
title_sort full-atomistic optimized potentials for liquid simulations and polymer consistent force field models for biocompatible shape-memory poly(ε-caprolactone)
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169671/
https://www.ncbi.nlm.nih.gov/pubmed/35605974
http://dx.doi.org/10.1021/acs.jpcb.2c01973
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