Shelley Mee Y, Selvan Myvizhi Esai, Zhao Jun, Babin Volodymyr, Liao Chenyi, Li Jianing, Shelley John C
Schrödinger, Inc. , 101 SW Main Street, Suite 1300, Portland, Oregon 97204, United States.
Schrödinger, Inc. , 120 W. 45th Street, 17th Floor, New York, New York 10036, United States.
J Chem Theory Comput. 2017 Aug 8;13(8):3881-3897. doi: 10.1021/acs.jctc.7b00071. Epub 2017 Jul 11.
We introduce a new mixed resolution, all-atom/coarse-grained approach (AACG), for modeling peptides in aqueous solution and apply it to characterizing the aggregation of melittin. All of the atoms in peptidic components are represented, while a single site is used for each water molecule. With the full flexibility of the peptide retained, our AACG method achieves speedups by a factor of 3-4 for CPU time reduction and another factor of roughly 7 for diffusion. An Ewald treatment permits the inclusion of long-range electrostatic interactions. These characteristics fit well with the requirements for studying peptide association and aggregation, where the system sizes and time scales require considerable computational resources with all-atom models. In particular, AACG is well suited for biologics since changes in peptide shape and long-range electrostatics may play an important role. The application of AACG to melittin, a 26-residue peptide with a well-known propensity to aggregate in solution, serves as an initial demonstration of this technology for studying peptide aggregation. We observed the formation of melittin aggregates during our simulations and characterized the time-evolution of aggregate size distribution, buried surface areas, and residue contacts. Key interactions including π-cation and π-stacking involving TRP19 were also examined. Our AACG simulations demonstrated a clear salt effect and a moderate temperature effect on aggregation and support the molten globule model of melittin aggregates. As a showcase, this work illustrates the useful role for AACG in investigations of peptide aggregation and its potential to guide formulation and design of biologics.
我们引入了一种新的混合分辨率全原子/粗粒度方法(AACG),用于对水溶液中的肽进行建模,并将其应用于表征蜂毒肽的聚集。肽组分中的所有原子都被表示出来,而每个水分子用一个单点表示。在保留肽的完全灵活性的同时,我们的AACG方法在减少CPU时间方面实现了3至4倍的加速,在扩散方面实现了大约7倍的加速。采用埃瓦尔德处理方法可以纳入长程静电相互作用。这些特性非常符合研究肽缔合和聚集的要求,因为系统规模和时间尺度对于全原子模型来说需要大量的计算资源。特别是,AACG非常适合生物制品,因为肽形状和长程静电的变化可能起着重要作用。将AACG应用于蜂毒肽(一种在溶液中具有众所周知的聚集倾向的26个残基的肽),是该技术用于研究肽聚集的初步示范。我们在模拟过程中观察到了蜂毒肽聚集体的形成,并表征了聚集体尺寸分布、埋藏表面积和残基接触的时间演变。还研究了包括涉及TRP19的π-阳离子和π-堆积在内的关键相互作用。我们的AACG模拟表明盐效应和适度的温度效应会对聚集产生明显影响,并支持蜂毒肽聚集体的熔球模型。作为一个展示,这项工作说明了AACG在肽聚集研究中的有用作用及其指导生物制品配方和设计的潜力。