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基于水相分散的脂质体制剂的分子结构和相转变:一种粗粒度分子动力学模拟方法。

Molecular Structuring and Phase Transition of Lipid-Based Formulations upon Water Dispersion: A Coarse-Grained Molecular Dynamics Simulation Approach.

机构信息

Department of Pharmacy, Uppsala University, Uppsala Biomedical Center , P.O. Box 580, SE-751 23 Uppsala, Sweden.

出版信息

Mol Pharm. 2017 Dec 4;14(12):4145-4153. doi: 10.1021/acs.molpharmaceut.7b00397. Epub 2017 Aug 29.

DOI:10.1021/acs.molpharmaceut.7b00397
PMID:28799773
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5836143/
Abstract

The internal molecular structure of lipid-based formulations (LBFs) is poorly understood. In this work we aimed at establishing coarse-grained molecular dynamics simulations as a tool for rapid screening and investigation of the internal environment of these formulations. In order to study complex LBFs composed of different kinds of lipids we simulated a number of systems containing either medium-chain or long-chain lipids with varying proportions of tri-, di-, and monoglycerides. Structural and dynamic measurements and analyses identified that the internal environment in a mixture of lipids was locally ordered even in the absence of water, which might explain some of the previously reported effects on drug solubility in these systems. Further, phase changes occurring upon water dispersion are well captured with coarse-grained simulations. Based on these simulations we conclude that the coarse-grained methodology is a promising in silico approach for rapid screening of structures formed in complex formulations. More importantly it facilitates molecular understanding of interactions between excipients and water at a feasible time scale and, hence, opens up for future virtual drug formulation studies.

摘要

脂质体制剂(LBFs)的内部分子结构尚未被充分理解。在这项工作中,我们旨在建立粗粒度分子动力学模拟作为快速筛选和研究这些制剂内部环境的工具。为了研究由不同种类的脂质组成的复杂 LBFs,我们模拟了许多包含中链或长链脂质的系统,其中三、二和单甘油酯的比例不同。结构和动态测量和分析表明,即使在没有水的情况下,脂质混合物中的内部环境在局部上也是有序的,这可能解释了先前在这些系统中报道的一些对药物溶解度的影响。此外,水分散时发生的相变化可以用粗粒度模拟很好地捕捉到。基于这些模拟,我们得出结论,粗粒度方法是一种很有前途的计算方法,可用于快速筛选复杂制剂中形成的结构。更重要的是,它有助于在可行的时间尺度上理解赋形剂与水之间的相互作用,从而为未来的虚拟药物制剂研究开辟了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/f70a6be764c3/mp-2017-003975_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/eafaea04139b/mp-2017-003975_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/433089b70b31/mp-2017-003975_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/e020465ec7c6/mp-2017-003975_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/c774ef306b63/mp-2017-003975_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/b8a52aecd14d/mp-2017-003975_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/fea6626f0d2c/mp-2017-003975_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/f70a6be764c3/mp-2017-003975_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/eafaea04139b/mp-2017-003975_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/433089b70b31/mp-2017-003975_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/e020465ec7c6/mp-2017-003975_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/c774ef306b63/mp-2017-003975_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/b8a52aecd14d/mp-2017-003975_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/fea6626f0d2c/mp-2017-003975_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/5836143/f70a6be764c3/mp-2017-003975_0007.jpg

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