Structural information of Fc-Fc receptor interaction may contribute to the design of drugs or therapeutic antibodies associated with the interaction. Computational protein-protein docking can be employed in structural study of protein-protein interaction, but its efficiency and reliability are still unstable and need to be validated and optimized for respective target protein complexes. In this study, we investigated and assessed the computational modeling efficiency of Fc-FcγR complex through HADDOCK by defining five different sets of active residues, a major parameter to determine the prediction efficiency of HADDOCK. The binding residues identified experimentally or the residues in the binding pocket were confirmed to be efficient active residues to achieve a high prediction efficiency, and too narrower or wider specification of active residues led to poor prediction efficiency. Most binding residues and crucial molecular interactions such as conserved interactions and hydrogen bonds in the crystal structure were reproduced in the best model. The HADDOCK docking condition determined in this study is expected to be applied to the computational characterization of various Fc-Fc receptor complexes and mutants.

Fc-Fc受体相互作用的结构信息可能有助于与相互作用相关的药物或治疗性抗体的设计。计算性蛋白质-蛋白质对接可用于蛋白质-蛋白质相互作用的结构研究，但其效率和可靠性仍然不稳定，需要针对各个目标蛋白质复合物进行验证和优化。在这项研究中，我们通过定义五组不同的活性残基（确定HADDOCK预测效率的主要参数），研究并评估了通过HADDOCK通过Fc-FcγR复合物的计算建模效率。实验确定的结合残基或结合袋中的残基被确认为有效的活性残基，可实现较高的预测效率，活性残基的规格太窄或太宽都会导致预测效率低下。在最佳模型中，复制了大多数结合残基和关键的分子相互作用，例如晶体结构中的保守相互作用和氢键。在这项研究中确定的HADDOCK对接条件有望应用于各种Fc-Fc受体复合物和突变体的计算表征。