Max Planck Institute for Dynamics of Complex Technical Systems, Molecular Simulations and Design Group, 39106 Magdeburg, Germany.
Int J Mol Sci. 2021 Mar 17;22(6):3078. doi: 10.3390/ijms22063078.
Small molecule receptor-binding is dominated by weak, non-covalent interactions such as van-der-Waals hydrogen bonding or electrostatics. Calculating these non-covalent ligand-receptor interactions is a challenge to computational means in terms of accuracy and efficacy since the ligand may bind in a number of thermally accessible conformations. The conformational rotamer ensemble sampling tool (CREST) uses an iterative scheme to efficiently sample the conformational space and calculates energies using the semi-empirical 'Geometry, Frequency, Noncovalent, eXtended Tight Binding' (GFN2-xTB) method. This combined approach is applied to blind predictions of the modes and free energies of binding for a set of 10 drug molecule ligands to the cucurbit[n]urils CB[8] receptor from the recent 'Statistical Assessment of the Modeling of Proteins and Ligands' (SAMPL) challenge including morphine, hydromorphine, cocaine, fentanyl, and ketamine. For each system, the conformational space was sufficiently sampled for the free ligand and the ligand-receptor complexes using the quantum chemical Hamiltonian. A multitude of structures makes up the final conformer-rotamer ensemble, for which then free energies of binding are calculated. For those large and complex molecules, the results are in good agreement with experimental values with a mean error of 3 kcal/mol. The GFN2-xTB energies of binding are validated by advanced density functional theory calculations and found to be in good agreement. The efficacy of the automated QM sampling workflow allows the extension towards other complex molecular interaction scenarios.
小分子受体结合主要由弱的非共价相互作用主导,如范德华氢键或静电作用。由于配体可能以多种热可及构象结合,因此使用计算方法计算这些非共价配体-受体相互作用在准确性和功效方面都是一项挑战。构象旋转体集合采样工具 (CREST) 使用迭代方案来有效地采样构象空间,并使用半经验的“几何形状、频率、非共价、扩展紧束缚”(GFN2-xTB) 方法计算能量。这种组合方法应用于最近“蛋白质和配体建模的统计评估”(SAMPL) 挑战中 10 种药物分子配体与葫芦[n]脲 CB[8]受体结合模式和自由能的盲预测,包括吗啡、氢吗啡、可卡因、芬太尼和氯胺酮。对于每个系统,使用量子化学哈密顿量充分采样游离配体和配体-受体复合物的构象空间。大量结构构成最终构象-旋转体集合,然后计算结合自由能。对于那些大而复杂的分子,结果与实验值吻合良好,平均误差为 3 千卡/摩尔。结合的 GFN2-xTB 能量通过高级密度泛函理论计算进行验证,结果发现吻合良好。自动 QM 采样工作流程的功效允许向其他复杂分子相互作用场景扩展。