Computer-aided design of carbon nanotubes with the desired bioactivity and safety profiles

Growing experimental evidences suggest the existence of direct relationships between the surface chemistry of nanomaterials and their biological effects. Herein, we have employed computational approaches to design a set of biologically active carbon nanotubes (CNTs) with controlled protein binding and cytotoxicity. Quantitative structure–activity relationship (QSAR) models were built and validated using a dataset of 83 surface-modified CNTs. A subset of a combinatorial virtual library of 240 000 ligands potentially attachable to CNTs was selected to include molecules that were within the chemical similarity threshold with respect to the modeling set compounds. QSAR models were then employed to virtually screen this subset and prioritize CNTs for chemical synthesis and biological evaluation. Ten putatively active and 10 putatively inactive CNTs decorated with the ligands prioritized by virtual screening for either protein-binding or cytotoxicity assay were synthesized and tested. We found that all 10 putatively inactive and 7 of 10 putatively active CNTs were confirmed in the protein-binding assay, whereas all 10 putatively inactive and 6 of 10 putatively active CNTs were confirmed in the cytotoxicity assay. This proof-of-concept study shows that computational models can be employed to guide the design of surface-modified nanomaterials with the desired biological and safety profiles.

越来越多的实验证据表明，纳米材料的表面化学性质与其生物学效应之间存在直接关联。在此，我们采用计算方法设计了一系列可调控蛋白质结合能力与细胞毒性的生物活性碳纳米管（carbon nanotubes, CNTs）。我们基于83个表面修饰碳纳米管的数据集构建并验证了定量构效关系（Quantitative structure–activity relationship, QSAR）模型。我们从可附着于碳纳米管的24万个配体组合虚拟库中选取了一个子集，该子集内的分子与建模集化合物的化学相似度处于设定阈值范围内。随后利用该QSAR模型对该子集进行虚拟筛选，以优先选出适合开展化学合成与生物学评价的碳纳米管。我们合成并测试了10个推测具有活性、10个推测无活性的碳纳米管，这些碳纳米管表面附着了经虚拟筛选优先选出的配体，用于蛋白质结合实验或细胞毒性实验。实验结果显示：在蛋白质结合实验中，10个推测无活性的碳纳米管全部得到验证，10个推测活性的碳纳米管中有7个得到确认；在细胞毒性实验中，10个推测无活性的碳纳米管全部得到验证，10个推测活性的碳纳米管中有6个得到确认。本概念验证研究表明，可利用计算模型指导设计具有预期生物学效应与安全特性的表面修饰纳米材料。