苯并咪唑类缓蚀剂的HQSAR研究及分子设计

采用分子全息定量构效关系(HQSAR)方法, 构建苯并咪唑衍生物在酸性环境中的缓蚀性能与结构之间的定量构效关系模型, 研究不同碎片区分参数及碎片大小对模型质量的影响, 寻找最优HQSAR模型, 并对其稳定性及预测能力进行评价. 结果显示: 选取碎片区分参数为原子类型(A)、化学键类型(B)、连接性(C)、氢原子(H)、手性(Ch)、氢键给体和受体(D&;A), 碎片大小为1-3 建模时, 得到的HQSAR 模型(r²(非交叉验证系数)=0.996, q²(交叉验证系数)=0.960, SE_cv(交叉验证标准误差)=3.709)具有良好的统计学稳定性及预测能力. 根据最优HQSAR模型图设计出的38种苯并咪唑类化合物理论上均具有较好的缓蚀性能. 本研究为油气田新型高效缓蚀剂研发提供可靠的理论依据.

HQSAR Study and Molecular Design of Benzimidazole Derivatives as Corrosion Inhibitors

Hologram quantitative structure-activity relationship (HQSAR) analysis was conducted on a series of benzimidazole compounds to build the HQSAR model between corrosion inhibition properties and molecular structures in acid environment. The optimal HQSAR model was determined by investigating the influence of different fragment distinction and fragment size on the models, and the models’ stability and predictive ability were evaluated. The results show that the optimal HQSAR model was generated using atoms(A), bonds(B), connectivity(C), hydrogen(H), chirality(Ch), donor and acceptor(D&;A) as fragment distinction and fragment size of 1-3. The model had a non-cross validated coefficient (r²) value of 0.996, a cross-validated (q²) value of 0.960, and a cross-validated standard error (SE_cv) value of 3.709, which indicates good statistics stability and predictive power. On the basis of the maps derived from the optimal HQSAR model, 38 new benzimidazole derivatives were designed and screened using the optimal HQSAR model, giving potential candidates with high predictive inhibition efficiency. This work provides valuable information for further research and design of more promising corrosion inhibitors in the oil and gas field.