Department of Chemistry, Brooklyn College of the City University of New York, New York, USA.
PhD Program in Biochemistry, Graduate Center of the City University of New York, USA.
Phys Chem Chem Phys. 2023 Sep 20;25(36):24364-24376. doi: 10.1039/d3cp02125d.
We apply the Alchemical Transfer Method (ATM) and a bespoke fixed partial charge force field to the SAMPL9 bCD host-guest binding free energy prediction challenge that comprises a combination of complexes formed between five phenothiazine guests and two cyclodextrin hosts. Multiple chemical forms, competing binding poses, and computational modeling challenges pose significant obstacles to obtaining reliable computational predictions for these systems. The phenothiazine guests exist in solution as racemic mixtures of enantiomers related by nitrogen inversions that bind the hosts in various binding poses, each requiring an individual free energy analysis. Due to the large size of the guests and the conformational reorganization of the hosts, which prevent a direct absolute binding free energy route, binding free energies are obtained by a series of absolute and relative binding alchemical steps for each chemical species in each binding pose. Metadynamics-accelerated conformational sampling was found to be necessary to address the poor convergence of some numerical estimates affected by conformational trapping. Despite these challenges, our blinded predictions quantitatively reproduced the experimental affinities for the β-cyclodextrin host and, to a lesser extent, those with a methylated derivative. The work illustrates the challenges of obtaining reliable free energy data in drug design for even seemingly simple systems and introduces some of the technologies available to tackle them.
我们将应用炼金术转移方法（ATM）和定制的固定部分电荷力场，对 SAMPL9 bCD 主客体结合自由能预测挑战进行分析，该挑战包括五个吩噻嗪客体和两个环糊精主体形成的复合物的组合。多种化学形式、竞争结合构象和计算建模挑战对这些系统获得可靠的计算预测构成了重大障碍。吩噻嗪客体在溶液中以通过氮反转相关的对映异构体的外消旋混合物形式存在，以各种结合构象与主体结合，每个构象都需要单独的自由能分析。由于客体的尺寸较大以及主体的构象重组，这阻止了直接的绝对结合自由能途径，因此通过每个结合构象中每种化学物质的一系列绝对和相对结合化学计量步骤来获得结合自由能。元动力学加速构象采样被发现对于解决一些受构象捕获影响的数值估计的较差收敛性是必要的。尽管存在这些挑战，但我们的盲法预测定量再现了实验亲和力，β-环糊精主体，并且在较小程度上，对甲基化衍生物的亲和力。这项工作说明了即使对于看似简单的系统，在药物设计中获得可靠的自由能数据也面临挑战，并介绍了一些可用的技术来解决这些挑战。
