PyLipID: A Python Package for Analysis of Protein-Lipid Interactions from Molecular Dynamics Simulations.
PyLipID: A Python Package for Analysis of Protein-Lipid Interactions from Molecular Dynamics Simulations.
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DOI：
10.1021/acs.jctc.1c00708
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发表时间：
2022-02-08
影响因子：
5.5
通讯作者：
Sansom MSP
中科院分区：
文献类型：
--
作者：
Song W;Corey RA;Ansell TB;Cassidy CK;Horrell MR;Duncan AL;Stansfeld PJ;Sansom MSP
脂类对膜蛋白起着重要的调节和结构作用。分子动力学模拟经常被用来提供对这些蛋白质-脂质相互作用的本质的洞察。系统的比较分析需要为客观评估这种相互作用提供算法的工具。我们介绍了PyLipID，这是一个用于从分子动力学模拟中识别和表征膜蛋白上特定的脂类相互作用和结合位置的Python包。PyLipID使用群落分析方法检测结合部位，计算单个蛋白质残基和检测到的结合部位的脂类停留时间。为了辅助结构分析，PyLipID使用基于密度的评分函数从模拟数据中产生具有代表性的结合脂肪姿势。为了可靠地估计残基接触，PyLipID使用双重截断方案来区分结合和完全解离事件的脂类构象重排。除了表征蛋白质与脂质的相互作用外，PyLipID还适用于膜蛋白与其他配体的相互作用的分析。通过将自动化分析、高效算法和开源分发相结合，PyLipID促进了对来自多种膜蛋白的大型模拟数据集的脂类相互作用的系统分析。
Lipids play important modulatory and structural roles for membrane proteins. Molecular dynamics simulations are frequently used to provide insights into the nature of these protein–lipid interactions. Systematic comparative analysis requires tools that provide algorithms for objective assessment of such interactions. We introduce PyLipID, a Python package for the identification and characterization of specific lipid interactions and binding sites on membrane proteins from molecular dynamics simulations. PyLipID uses a community analysis approach for binding site detection, calculating lipid residence times for both the individual protein residues and the detected binding sites. To assist structural analysis, PyLipID produces representative bound lipid poses from simulation data, using a density-based scoring function. To estimate residue contacts robustly, PyLipID uses a dual-cutoff scheme to differentiate between lipid conformational rearrangements while bound from full dissociation events. In addition to the characterization of protein–lipid interactions, PyLipID is applicable to analysis of the interactions of membrane proteins with other ligands. By combining automated analysis, efficient algorithms, and open-source distribution, PyLipID facilitates the systematic analysis of lipid interactions from large simulation data sets of multiple species of membrane proteins.
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影响因子：
13.6
作者：
Corey RA;Song W;Duncan AL;Ansell TB;Sansom MSP;Stansfeld PJ
通讯作者：
Stansfeld PJ
DOI：
10.1016/j.bbamem.2016.02.037
发表时间：
2016-10
期刊：
Biochimica et biophysica acta
影响因子：
--
作者：
Hedger G;Sansom MSP
通讯作者：
Sansom MSP
DOI：
10.1088/1742-5468/2008/10/p10008
发表时间：
2008-10-01
影响因子：
2.4
作者：
Blondel, Vincent D.;Guillaume, Jean-Loup;Lefebvre, Etienne
通讯作者：
Lefebvre, Etienne
影响因子：
16.6
作者：
Damian M;Louet M;Gomes AAS;M'Kadmi C;Denoyelle S;Cantel S;Mary S;Bisch PM;Fehrentz JA;Catoire LJ;Floquet N;Banères JL
通讯作者：
Banères JL
影响因子：
3
作者：
GARCIA, AE;STILLER, L
通讯作者：
STILLER, L