The density-threshold affinity: Calculating lipid binding affinities from unbiased coarse-grained molecular dynamics simulations.

4区 生物学 Q3 Biochemistry, Genetics and Molecular Biology
Methods in enzymology Pub Date : 2024-01-01 Epub Date: 2024-04-04 DOI:10.1016/bs.mie.2024.03.008
Jesse W Sandberg, Ezry Santiago-McRae, Jahmal Ennis, Grace Brannigan
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引用次数: 0

Abstract

Many membrane proteins are sensitive to their local lipid environment. As structural methods for membrane proteins have improved, there is growing evidence of direct, specific binding of lipids to protein surfaces. Unfortunately the workhorse of understanding protein-small molecule interactions, the binding affinity for a given site, is experimentally inaccessible for these systems. Coarse-grained molecular dynamics simulations can be used to bridge this gap, and are relatively straightforward to learn. Such simulations allow users to observe spontaneous binding of lipids to membrane proteins and quantify localized densities of individual lipids or lipid fragments. In this chapter we outline a protocol for extracting binding affinities from these localized distributions, known as the "density threshold affinity." The density threshold affinity uses an adaptive and flexible definition of site occupancy that alleviates the need to distinguish between "bound'' lipids and bulk lipids that are simply diffusing through the site. Furthermore, the method allows "bead-level" resolution that is suitable for the case where lipids share binding sites, and circumvents ambiguities about a relevant reference state. This approach provides a convenient and straightforward method for comparing affinities of a single lipid species for multiple sites, multiple lipids for a single site, and/or a single lipid species modeled using multiple forcefields.

密度-阈值亲和力:通过无偏粗粒度分子动力学模拟计算脂质结合亲和力。
许多膜蛋白对其局部脂质环境非常敏感。随着膜蛋白结构方法的改进,越来越多的证据表明脂质与蛋白质表面有直接的特异性结合。遗憾的是,了解蛋白质与小分子相互作用的主要工具--特定位点的结合亲和力--在这些系统中无法通过实验获得。粗粒度分子动力学模拟可用于弥合这一差距,而且相对简单易学。此类模拟可让用户观察脂质与膜蛋白的自发结合,并量化单个脂质或脂质片段的局部密度。在本章中,我们将概述一种从这些局部分布中提取结合亲和力的方案,即 "密度阈值亲和力"。密度阈值亲和力使用了一种适应性强且灵活的位点占有率定义,从而无需区分 "结合''脂质和只是通过位点扩散的大量脂质。此外,该方法允许 "珠子级 "分辨率,适合脂质共享结合位点的情况,并避免了相关参考状态的模糊性。这种方法为比较单个脂质物种与多个位点、多个脂质与单个位点和/或使用多个力场建模的单个脂质物种的亲和力提供了一种方便、直接的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Methods in enzymology
Methods in enzymology 生物-生化研究方法
CiteScore
2.90
自引率
0.00%
发文量
308
审稿时长
3-6 weeks
期刊介绍: The critically acclaimed laboratory standard for almost 50 years, Methods in Enzymology is one of the most highly respected publications in the field of biochemistry. Each volume is eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. Now with over 500 volumes the series contains much material still relevant today and is truly an essential publication for researchers in all fields of life sciences, including microbiology, biochemistry, cancer research and genetics-just to name a few. Five of the 2013 Nobel Laureates have edited or contributed to volumes of MIE.
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