Mohamed Ahmed, Visco Donald P, Breimaier Karl, Bastidas David M
National Center for Education and Research on Corrosion and Materials Performance, NCERCAMP-UA, Dept. Chemical, Biomolecular, and Corrosion Engineering, The University of Akron, 302 E Buchtel Ave, Akron, Ohio 44325-3906, United States.
ACS Omega. 2025 Jan 15;10(3):2799-2808. doi: 10.1021/acsomega.4c08626. eCollection 2025 Jan 28.
Compounds possessing a small highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap ( ) are highly desirable due to their instability and reactivity, making them useful for a wide range of applications. However, the search for new organic compounds with a low is an expensive endeavor due to the exponentially increasing pool of virtual compounds. Accordingly, in this study, atomic Signatures were utilized as molecular descriptors to investigate the correlation between the molecular structure and the B3LYP-computed , thus aiding in the development of a quantitative structure-property relationship (QSPR). An easy-to-use robust model was constructed using forward-stepping multilinear regression with leave-one-out cross validation, resulting in a regression coefficient ( ) of 0.86 and a predictability ( ) of 0.76. The use of atomic Signatures as molecular descriptors successfully inferred correlations between different structural motifs and . The atomic fragments containing π-bonds in various aromatic compounds were found to be the most significant atomic Signatures, explaining nearly 50% of the variance in the data, with regression coefficients that decreased . This is attributed to π-electron delocalization, making this molecular fragment a reactive site in a molecule. Finally, an external test set was used to further evaluate the model's predictive performance. The developed QSPR can be utilized as a reliable initial screening tool to identify potential candidates possessing low values.
由于具有较小的最高占据分子轨道-最低未占据分子轨道(HOMO-LUMO)能隙( )的化合物具有不稳定性和反应活性,使其在广泛的应用中很有用,因此备受青睐。然而,由于虚拟化合物库呈指数增长,寻找具有低 的新型有机化合物是一项昂贵的工作。因此,在本研究中,原子特征被用作分子描述符,以研究分子结构与B3LYP计算的 之间的相关性,从而有助于建立定量结构-性质关系(QSPR)。使用前向逐步多元线性回归和留一法交叉验证构建了一个易于使用的稳健模型,得到的回归系数( )为0.86,预测能力( )为0.76。将原子特征用作分子描述符成功推断出不同结构基序与 之间的相关性。发现各种芳香族化合物中含有π键的原子片段是最重要的原子特征,解释了数据中近50%的方差,回归系数随之降低。这归因于π电子离域,使该分子片段成为分子中的反应位点。最后,使用外部测试集进一步评估模型的预测性能。所开发的QSPR可作为一种可靠的初始筛选工具,用于识别具有低 值的潜在候选物。