Design of bisamide inhibitors of the TASK-1 potassium channel in silico†

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL Physical Chemistry Chemical Physics Pub Date : 2024-12-09 DOI:10.1039/D4CP03521F
Lu Liu, Jixiang Liu, Liang Chen, Risong Na, Lianjuan Yang, Xiaoping Liu and Xi Zhao
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Abstract

TWIK-related acid-sensitive potassium channel 1 (TASK-1) is expressed ubiquitously across various tissues and plays a significant role in neural activity and anesthetic modulation, making it a crucial target for pharmaceutical research. The high conservation of binding site residues within the TASK family, particularly between TASK-1 and TASK-3, necessitates the development of selective inhibitors for TASK-1. In this study, we utilized a combination of structure-based drug design (SBDD) and ligand-based drug design (LBDD) approaches. Initially, several bisamide-centered molecules were designed using the program MolAICal, which is recognized for its ability to generate selective inhibitors containing bisamide segments, and conducted preliminary screening via molecular docking. Subsequently, 3D-QSAR models were developed for 56 bisamide derivatives targeting TASK-1 and TASK-3, with the models exhibiting robust predictive capabilities (TASK-1: Q2 = 0.61, R2pred = 0.84; TASK-3: Q2 = 0.60, R2pred = 0.71). Using these models, the candidate molecules were subjected to activity prediction and subsequent filtering. Ultimately, molecular dynamics simulations, coupled with free energy calculations, pinpointed two bisamide-core molecules with favorable ADMET properties as potential selective inhibitors for TASK-1. Furthermore, molecular dynamics simulations revealed the critical role of the key residue Leu122 in conferring selectivity to bisamide compounds for TASK-1 channel proteins.

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硅中TASK-1钾通道双酰胺抑制剂的设计
twik相关的酸敏感钾通道1 (TASK-1)在多种组织中普遍表达,在神经活动和麻醉调节中起重要作用,是药物研究的重要靶点。TASK家族中结合位点残基的高度保守性,特别是TASK-1和TASK-3之间,需要开发TASK-1的选择性抑制剂。在本研究中,我们结合了基于结构的药物设计(SBDD)和基于配体的药物设计(LBDD)方法。最初,使用molaic程序设计了几个以双酰胺为中心的分子,该程序具有生成含有双酰胺片段的选择性抑制剂的能力,并通过分子对接进行了初步筛选。随后,针对56种针对TASK-1和TASK-3的双酰胺衍生物建立了3D-QSAR模型,模型具有较强的预测能力(TASK-1: Q2 = 0.61, R2pred = 0.84;TASK-3: Q2 = 0.60, r2 = 0.71)。利用这些模型,候选分子进行活性预测和随后的过滤。最终,分子动力学模拟,结合自由能计算,确定了两种具有良好ADMET特性的双酰胺核分子作为TASK-1的潜在选择性抑制剂。此外,分子动力学模拟揭示了关键残基Leu122在赋予双酰胺化合物对TASK-1通道蛋白的选择性方面的关键作用。
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来源期刊
Physical Chemistry Chemical Physics
Physical Chemistry Chemical Physics 化学-物理:原子、分子和化学物理
CiteScore
5.50
自引率
9.10%
发文量
2675
审稿时长
2.0 months
期刊介绍: Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.
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