Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.
Department of Chemistry, Aarhus University, Langelandsgade 140, 8000, Aarhus C, Denmark.
J Comput Aided Mol Des. 2023 Nov;37(11):537-549. doi: 10.1007/s10822-023-00525-1. Epub 2023 Aug 12.
The treatment of various disorders of the central nervous system (CNS) is often impeded by the limited brain exposure of drugs, which is regulated by the human blood-brain barrier (BBB). The screening of lead compounds for CNS penetration is challenging due to the biochemical complexity of the BBB, while experimental determination of permeability is not feasible for all types of compounds. Here we present a novel method for rapid preclinical screening of libraries of compounds by utilizing advancements in computing hardware, with its foundation in transition-based counting of the flux. This method has been experimentally validated for in vitro permeabilities and provides atomic-level insights into transport mechanisms. Our approach only requires a single high-temperature simulation to rank a compound relative to a library, with a typical simulation time converging within 24 to 72 h. The method offers unbiased thermodynamic and kinetic information to interpret the passive transport of small-molecule drugs across the BBB.
中枢神经系统（CNS）各种疾病的治疗常常受到血脑屏障（BBB）限制，药物在大脑中的暴露量有限。由于 BBB 的生化复杂性，先导化合物对 CNS 穿透性的筛选具有挑战性，而对于所有类型的化合物，实验确定渗透性都是不可行的。在这里，我们提出了一种利用计算硬件的进步对化合物文库进行快速临床前筛选的新方法，其基础是基于通量的基于转换的计数。该方法已经通过体外渗透性进行了实验验证，并提供了有关运输机制的原子级见解。我们的方法仅需要一次高温模拟即可相对于文库对化合物进行排序，典型的模拟时间在 24 至 72 小时内收敛。该方法提供了无偏的热力学和动力学信息，以解释小分子药物通过 BBB 的被动转运。
