Daré Joyce K, Freitas Matheus P
Departamento de Química, Instituto de Ciências Naturais, Universidade Federal de Lavras, Lavras, Minas Gerais, Brazil.
J Comput Chem. 2022 May 15;43(13):917-922. doi: 10.1002/jcc.26848. Epub 2022 Mar 22.
Conformation has a key role in the mechanism of interaction between small molecules and biological receptors. However, encoding this type of information in molecular descriptors for the construction of robust quantitative structure-activity relationships (QSAR) models is not an easy task and, so far, the dependence of these models on such feature has not been thoroughly investigated. In the present study, the authors explore the effects of conformational information on a 3D-QSAR technique by comparing models built with descriptors that encode fully described tridimensional aspects (structures docked inside a biological target), with descriptors in which this information is suppressed (flat structures) or not fully described (structures with quantum-chemically optimized geometries). As a result, the validation parameters indicate that the robustness of the models seems to be more related to the alignment aspect of the structures than to how well their tridimensional features are described.
构象在小分子与生物受体的相互作用机制中起着关键作用。然而，将这类信息编码到分子描述符中以构建稳健的定量构效关系（QSAR）模型并非易事，而且到目前为止，这些模型对这类特征的依赖性尚未得到充分研究。在本研究中，作者通过比较用编码了完整三维信息的描述符（对接在生物靶点内的结构）构建的模型与抑制了该信息的描述符（平面结构）或未完全描述该信息的描述符（经量子化学优化几何结构的结构）构建的模型，探讨了构象信息对一种三维定量构效关系技术的影响。结果表明，验证参数表明模型的稳健性似乎与结构的比对方面更为相关，而非与三维特征的描述程度相关。
