Suating Paolo, Nguyen Thong T, Ernst Nicholas E, Wang Yang, Jordan Jacobs H, Gibb Corinne L D, Ashbaugh Henry S, Gibb Bruce C
Department of Chemistry , Tulane University , New Orleans , LA 70118 , USA . Email:
Department of Chemical and Biomolecular Engineering , Tulane University , New Orleans , LA 70118 , USA.
Chem Sci. 2020 Mar 17;11(14):3656-3663. doi: 10.1039/c9sc06268h. eCollection 2020 Apr 14.
Science still does not have the ability to accurately predict the affinity that ligands have for proteins. In an attempt to address this, the Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) series of blind predictive challenges is a community-wide exercise aimed at advancing computational techniques as standard predictive tools in rational drug design. In each cycle, a range of biologically relevant systems of different levels of complexity are selected to test the latest modeling methods. As part of this on-going exercise, and as a step towards understanding the important factors in context dependent guest binding, we challenged the computational community to determine the affinity of a series of negatively and positively charged guests to two constitutionally isomeric cavitand hosts: octa-acid , and -octa acid . Our affinity determinations, combined with molecular dynamics simulations, reveal asymmetries in affinities between host-guest pairs that cannot alone be explained by simple coulombic interactions, but also point to the importance of host-water interactions. Our work reveals the key facets of molecular recognition in water, emphasizes where improvements need to be made in modelling, and shed light on the complex problem of ligand-protein binding in the aqueous realm.
科学仍然无法准确预测配体与蛋白质之间的亲和力。为了解决这个问题,蛋白质和配体建模统计评估(SAMPL)系列盲预测挑战是一项全社区参与的活动,旨在推动计算技术成为合理药物设计中的标准预测工具。在每个周期中,会选择一系列不同复杂程度的生物学相关系统来测试最新的建模方法。作为这项持续活动的一部分,也是朝着理解上下文依赖性客体结合中的重要因素迈出的一步,我们向计算科学界发起挑战,要求确定一系列带负电荷和正电荷的客体与两种结构异构的穴状配体主体:八酸和 - 八酸之间的亲和力。我们的亲和力测定结果,结合分子动力学模拟,揭示了主客体对之间亲和力的不对称性,这种不对称性不能仅用简单的库仑相互作用来解释,同时也指出了主体 - 水相互作用的重要性。我们的工作揭示了水中分子识别的关键方面,强调了建模中需要改进的地方,并阐明了水相中配体 - 蛋白质结合这一复杂问题。