Mining the Dynamical Properties of Substrate and FAD Binding Pockets of LSD1: Hints for New Inhibitor Design Direction

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-06-05 DOI:10.1021/acs.jcim.4c00398
Kecheng Yang*,  and , Hongmin Liu, 
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Abstract

Lysine-specific demethylase 1 (LSD1), a highly sophisticated epigenetic regulator, orchestrates a range of critical cellular processes, holding promising therapeutic potential for treating diverse diseases. However, the clinical research progress targeting LSD1 is very slow. After 20 years of research, only one small-molecule drug, BEA-17, targeting the degradation of LSD1 and CoREST has been approved by the U.S. Food and Drug Administration. The primary reason for this may be the lack of abundant structural data regarding its intricate functions. To gain a deeper understanding of its conformational dynamics and guide the drug design process, we conducted molecular dynamics simulations to explore the conformational states of LSD1 in the apo state and under the influence of cofactors of flavin adenine dinucleotide (FAD) and CoREST. Our results showed that, across all states, the substrate binding pocket exhibited high flexibility, whereas the FAD binding pocket remained more stable. These distinct dynamical properties are essential for LSD1’s ability to bind various substrates while maintaining efficient demethylation activity. Both pockets can be enlarged by merging with adjacent pockets, although only the substrate binding pocket can shrink into smaller pockets. These new pocket shapes can inform inhibitor design, particularly for selectively FAD-competitive inhibitors of LSD1, given the presence of numerous FAD-dependent enzymes in the human body. More interestingly, in the absence of FAD binding, the united substrate and FAD binding pocket are partitioned by the conserved residue of Tyr761, offering valuable insights for the design of inhibitors that disrupt the crucial steric role of Tyr761 and the redox role of FAD. Additionally, we identified pockets that positively or negatively correlate with the substrate and FAD binding pockets, which can be exploited for the design of allosteric or concurrent inhibitors. Our results reveal the intricate dynamical properties of LSD1 as well as multiple novel conformational states, which deepen our understanding of its sophisticated functions and aid in the rational design of new inhibitors.

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挖掘 LSD1 底物和 FAD 结合口袋的动态特性:新抑制剂设计方向的提示。
赖氨酸特异性去甲基化酶1(LSD1)是一种高度复杂的表观遗传调控因子,协调着一系列关键的细胞过程,具有治疗各种疾病的潜力。然而,针对 LSD1 的临床研究进展非常缓慢。经过 20 年的研究,只有一种靶向降解 LSD1 和 CoREST 的小分子药物 BEA-17 获得了美国食品药品管理局的批准。其主要原因可能是缺乏有关其复杂功能的丰富结构数据。为了深入了解其构象动态并指导药物设计过程,我们进行了分子动力学模拟,以探索 LSD1 在 apo 状态以及在黄素腺嘌呤二核苷酸(FAD)和 CoREST 等辅助因子影响下的构象状态。我们的研究结果表明,在所有状态下,底物结合口袋都表现出很高的灵活性,而 FAD 结合口袋则更加稳定。这些不同的动态特性对于 LSD1 在保持高效去甲基化活性的同时结合各种底物的能力至关重要。这两个口袋都可以通过与相邻口袋合并而扩大,但只有底物结合口袋可以缩小成更小的口袋。鉴于人体内存在大量依赖 FAD 的酶,这些新的口袋形状可以为抑制剂的设计提供参考,尤其是为 LSD1 的选择性 FAD 竞争性抑制剂提供参考。更有趣的是,在没有 FAD 结合的情况下,底物和 FAD 结合口袋由 Tyr761 这一保守残基分割,这为设计能破坏 Tyr761 的关键立体作用和 FAD 的氧化还原作用的抑制剂提供了宝贵的启示。此外,我们还发现了与底物和 FAD 结合口袋正相关或负相关的口袋,可用于设计异位或并发抑制剂。我们的研究结果揭示了 LSD1 复杂的动态特性以及多种新的构象状态,加深了我们对其复杂功能的理解,有助于合理设计新的抑制剂。
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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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