摘要
配体构象应变能(ligand conformational strain energy,LCSE)是计算机辅助药物发现中考虑的一个重要参数.通过量子力学(quantum mechanical,QM)方法对自由态配体和蛋白质口袋中的结合态配体的结构进行计算并比较,可以获得配体构象应变能.然而,对配体构象应变能的合理范围以及计算方法仍然存在争议.选择8个柔性较大、特征结构模式多样的配体,这些结构的分辨率在高分辨率(0.86×10^(−10))与中等分辨率(3.10×10^(−10))之间,分别采用3种不同的量子力学方法:密度泛函(density functional theory,DFT)M062XD3、Hartree-Fock和GFN1-xTB,对8个配体进行逐步优化并计算配体能量,分析在结合态配体逐步优化到局域能量最小的自由态配体的过程中配体在结构和能量上的差异.量子力学计算结果显示,配体构象应变能小于6.0 kcal/mol,结合态配体结构中显著的几何参数误差是结合态和自由态配体结构的主要能量差异.因此,在分析配体构象应变能之前,对结合态配体结构进行精确实验测定非常重要.
Ligand conformational strain energy(LCSE)is an important parameter in computer-aided drug discovery.LCSE may be calculated through quantum mechanical(QM)computations by comparing free and protein pocket-bound ligand structures.However,there is still a dispute on the plausible LCSE range and the methodology to obtain it.In this work,8 highly flexible ligand structures with a good variety of patterns were chosen to be optimized step-by-step with energy calculations to analyze the differences in structure and relative energies from protein-bound ligands to free ligand with the minimum local energy.The structures with resolutions between high(0.86×10^(−10))and medium(3.1×10^(−10))are calculated through 3 QM methods,namely the density functional theory(DFT)with the M062X-D3 function as well as Hartree-Fock and GFN1-xTB approaches.QM calculation results show that LCSE was lower than 6.0 kcal/mol.In several cases,the energy differences between bound and unbound ligand structures was mainly due to significant errors in the geometrical parameters of the former,highlighting the need of accurate experimental determination of protein-bound ligand structures prior to LCSE analyses.
作者
乔琳琳
李永乐
郭聪
BICZYSKO Malgorzata
QIAO Linlin;LI Yongle;GUO Cong;BICZYSKO Malgorzata(College of Sciences,Shanghai University,Shanghai 200444,China;International Center for Quantum and Molecular Structure,Shanghai University,Shanghai 200444,China)
出处
《上海大学学报(自然科学版)》
CAS
CSCD
北大核心
2024年第2期229-242,共14页
Journal of Shanghai University:Natural Science Edition
基金
国家自然科学基金资助项目(31870738)。