The overproduction of nitric oxide by neuronal nitric oxide synthase (nNOS) is associated with several neuropathological conditions. As a result, inhibition of nNOS is a desirable therapeutic goal while avoiding the inhibition of endothelial NOS (eNOS) given its essential role in maintaining cardiovascular tone. Designing inhibitors with high specificity for nNOS over eNOS is challenging given the close similarity in the active site structure of all mammalian NOS isoforms. Computational methods like free energy perturbation (FEP) and thermodynamic integration (TI) offer attractive avenues for rational drug design, but application of these methods to NOS is hindered by several challenges, including proper handling of highly charged inhibitors with diverse structures as well as computational expense. To address these issues, we present a simplified approach combining continuum dielectric generalized born (GB) solvent models with linear interaction energy (LIE) calculations. Our method demonstrates excellent agreement with experimental data for charged inhibitors targeting mammalian NOS isoforms (mNOS). Our results highlight the utility of the GB-LIE method as a promising tool for screening NOS inhibitors and potentially other protein targets with charged active sites and diverse inhibitor structures.

中文翻译：

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线性相互作用能法在基于一氧化氮合酶结构的抑制剂设计中的应用


神经元一氧化氮合酶 （nNOS） 过量产生一氧化氮与多种神经病理状况有关。因此，抑制 nNOS 是一个理想的治疗目标，同时避免抑制内皮 NOS （eNOS），因为它在维持心血管张力中起着重要作用。鉴于所有哺乳动物 NOS 亚型的活性位点结构非常相似，因此设计对 nNOS 比 eNOS 具有高特异性的抑制剂具有挑战性。自由能扰动 （FEP） 和热力学积分 （TI） 等计算方法为合理的药物设计提供了有吸引力的途径，但将这些方法应用于 NOS 受到一些挑战的阻碍，包括正确处理具有不同结构的高电荷抑制剂以及计算费用。为了解决这些问题，我们提出了一种将连续介质广义本国 （GB） 溶剂模型与线性相互作用能 （LIE） 计算相结合的简化方法。我们的方法与靶向哺乳动物 NOS 亚型 （mNOS） 的带电抑制剂的实验数据非常吻合。我们的结果强调了 GB-LIE 方法作为筛选 NOS 抑制剂和潜在其他具有带电活性位点和不同抑制剂结构的蛋白质靶标的有用工具。