MOlecular NAnotechnology for LIfe Science Applications (MoNaLiSA) Theory Group, Department of Medical and Biological Sciences, University of Udine, Piazzale Kolbe 4, 33100 Udine, Italy.
Center for biomedical sciences and engineering, University of Nova Gorica, Glavni Trg 8, 5271 Vipava, Slovenia.
Sci Rep. 2016 Oct 10;6:34869. doi: 10.1038/srep34869.
Nanobodies (VHHs) have proved to be valuable substitutes of conventional antibodies for molecular recognition. Their small size represents a precious advantage for rational mutagenesis based on modelling. Here we address the problem of predicting how Camelidae nanobody sequences can tolerate mutations by developing a simulation protocol based on all-atom molecular dynamics and whole-molecule docking. The method was tested on two sets of nanobodies characterized experimentally for their biophysical features. One set contained point mutations introduced to humanize a wild type sequence, in the second the CDRs were swapped between single-domain frameworks with Camelidae and human hallmarks. The method resulted in accurate scoring approaches to predict experimental yields and enabled to identify the structural modifications induced by mutations. This work is a promising tool for the in silico development of single-domain antibodies and opens the opportunity to customize single functional domains of larger macromolecules.
纳米抗体(VHH)已被证明是分子识别中传统抗体的有价值替代品。它们的小尺寸代表了基于建模的合理诱变的宝贵优势。在这里,我们通过开发一种基于全原子分子动力学和全分子对接的模拟方案来解决预测骆驼科纳米抗体序列如何耐受突变的问题。该方法在两组经实验表征的纳米抗体上进行了测试,这些纳米抗体的生物物理特性具有特征。一组包含引入的点突变,用于人源化野生型序列,在第二组中,CDR 在具有骆驼科和人类特征的单域框架之间交换。该方法得出了准确的评分方法来预测实验产率,并能够识别突变引起的结构修饰。这项工作是单域抗体的计算机开发的有前途的工具,并为定制更大的大分子的单个功能域提供了机会。