Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
Glycobiology. 2021 Aug 7;31(7):787-799. doi: 10.1093/glycob/cwab017.
N-linked glycans are ubiquitous in nature and play key roles in biology. For example, glycosylation of pathogenic proteins is a common immune evasive mechanism, hampering the development of successful vaccines. Due to their chemical variability and complex dynamics, an accurate molecular understanding of glycans is still limited by the lack of effective resolution of current experimental approaches. Here, we have developed and implemented a reductive model based on the popular Martini 2.2 coarse-grained force field for the computational study of N-glycosylation. We used the HIV-1 Env as a direct applied example of a highly glycosylated protein. Our results indicate that the model not only reproduces many observables in very good agreement with a fully atomistic force field but also can be extended to study large amount of glycosylation variants, a fundamental property that can aid in the development of drugs and vaccines.
N-连接的聚糖在自然界中普遍存在,在生物学中发挥着关键作用。例如,致病性蛋白的糖基化是一种常见的免疫逃避机制,阻碍了成功疫苗的开发。由于其化学变异性和复杂动态,聚糖的准确分子理解仍然受到当前实验方法缺乏有效分辨率的限制。在这里,我们基于流行的 Martini 2.2 粗粒力场开发并实施了一种还原模型,用于 N-糖基化的计算研究。我们使用 HIV-1 Env 作为高度糖基化蛋白的直接应用实例。我们的结果表明,该模型不仅能很好地再现许多可观测到的现象,与全原子力场非常吻合,而且还可以扩展到研究大量糖基化变体,这一基本特性有助于药物和疫苗的开发。