Shahfar Hassan, Forder James K, Roberts Christopher J
Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States.
Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716, United States.
J Phys Chem B. 2021 Apr 15;125(14):3574-3588. doi: 10.1021/acs.jpcb.1c01903. Epub 2021 Apr 6.
A series of coarse-grained models for molecular simulation of proteins are considered, with emphasis on the application of predicting protein-protein self-interactions for monoclonal antibodies (MAbs). As an illustrative example and for quantitative comparison, the models are used to predict osmotic virial coefficients over a broad range of attractive and repulsive self-interactions and solution conditions for a series of MAbs where the second osmotic virial coefficient has been experimentally determined in prior work. The models are compared based on how well they can predict experimental behavior, their computational burdens, and scalability. An intermediate-resolution model is also introduced that can capture specific electrostatic interactions with improved efficiency and similar or improved accuracy when compared to the previously published models. Guidance is included for the selection of coarse-grained models more generally for capturing a balance of electrostatic, steric, and short-ranged nonelectrostatic interactions for proteins from low to high concentrations.
本文考虑了一系列用于蛋白质分子模拟的粗粒度模型，重点是预测单克隆抗体（MAb）的蛋白质-蛋白质自相互作用。作为一个示例并用于定量比较，这些模型被用于预测一系列MAb在广泛的吸引和排斥自相互作用以及溶液条件下的渗透压维里系数，其中第二渗透压维里系数已在先前的工作中通过实验测定。基于这些模型预测实验行为的能力、计算负担和可扩展性对它们进行了比较。还引入了一种中等分辨率模型，与先前发表的模型相比，该模型能够以更高的效率捕获特定的静电相互作用，并且具有相似或更高的准确性。本文还提供了更一般的指导，用于选择粗粒度模型，以平衡从低浓度到高浓度蛋白质的静电、空间位阻和短程非静电相互作用。
