Pu Jiang, Cong Zhang, Hongshuang Wang, Penghui Li, Xiubo Du, Yibo Wang, Ekaterina Lyukmanova, Cong Lin* and Xiaohui Wang*,
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引用次数: 0
Abstract
Psychoactive substances, including morphine and methamphetamine, have been shown to interact with the classic innate immune receptor Toll-like receptor 4 (TLR4) and its partner protein myeloid differentiation protein 2 (MD2) in a nonenantioselective manner. (−)-Nicotine, the primary alkaloid in tobacco and a key component of highly addictive cigarettes, targets the TLR4/MD2, influencing TLR4 signaling pathways. Existing as two enantiomers, the stereoselective recognition of nicotine by TLR4/MD2 in the context of the innate immune response remains unclear. In this study, we synthesized (+)-nicotine and investigated its effects alongside (−)-nicotine on lipopolysaccharide (LPS)-induced TLR4 signaling. (−)-Nicotine dose-dependently inhibited proinflammatory factors such as tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), and cyclooxygenase-2 (COX-2). In contrast, (+)-nicotine showed no such inhibitory effects. Molecular dynamics simulations revealed that (−)-nicotine exhibited a stronger affinity with the TLR4 coreceptor MD2 than (+)-nicotine. Additionally, in silico simulations revealed that both nicotine enantiomers initially attach to the entrance of the MD2 cavity, creating a metastable state before they fully enter the cavity. In the metastable state, (−)-nicotine established more stable interactions with the surrounding residues at the entrance of the MD2 cavity compared to those of (+)-nicotine. This highlights the crucial role of the MD2 cavity entrance in the chiral recognition of nicotine. These findings provide valuable insights into the distinct interactions between nicotine enantiomers and the TLR4 coreceptor MD2, underscoring the enantioselective effect of nicotine on modulating TLR4 signaling.
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.
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