ABSTRACT

The quantitative structure‐property relationship (QSPR) method is commonly used to predict different physicochemical characteristics of interest of chemical compounds with an objective to accelerate the process of design and development of novel chemical compounds in the biotechnology and healthcare industries. In the present report, we have employed a QSPR approach to predict the different properties of the aminoglycoside-derived polymers (i.e. polymer DNA binding and aminoglycoside-derived polymers mediated transgene expression). The final QSPR models were obtained using the partial least squares (PLS) regression approach using only specific categories of two-dimensional descriptors and subsequently evaluated considering different internationally accepted validation metrics. The proposed models are robust and non-random, demonstrating excellent predictive ability using test set compounds. We have also developed different kinds of consensus models using several validated individual models to improve the prediction quality for external set compounds. The present findings provide new insight for exploring the design of an aminoglycoside-derived polymer library based on different identified physicochemical properties as well as predict their property before their synthesis.

摘要

定量结构性质关系 (QSPR) 方法通常用于预测化合物的不同理化特性，目的是加快生物技术和医疗保健行业中新型化合物的设计和开发过程。在本报告中，我们采用 QSPR 方法来预测氨基糖苷衍生聚合物的不同特性（即聚合物 DNA 结合和氨基糖苷衍生聚合物介导的转基因表达）。最终的 QSPR 模型是使用偏最小二乘 (PLS) 回归方法获得的，仅使用特定类别的二维描述符，随后考虑不同的国际公认验证指标进行评估。所提出的模型是稳健且非随机的，使用测试集化合物展示了出色的预测能力。我们还使用多个经过验证的单个模型开发了不同类型的共识模型，以提高外部集合化合物的预测质量。本研究结果为探索基于不同物理化学性质的氨基糖苷衍生聚合物文库的设计以及在合成前预测其性质提供了新的见解。