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计算机辅助药物发现(CADD)方法在治疗神经性疼痛中的应用。

Computer-Aided Drug Discovery (CADD) Approaches for the Management of Neuropathic Pain.

机构信息

Department of Pharmaceutical Analysis, Omega College of Pharmacy, Hyderabad-501 301,India.

Pharmacology Unit, Faculty of Pharmacy, AIMST University, 08100-Bedong, Kedah Darul Aman,Malaysia.

出版信息

Curr Top Med Chem. 2021;21(32):2856-2868. doi: 10.2174/1568026621666211122161932.

DOI:10.2174/1568026621666211122161932
PMID:34809547
Abstract

Neuropathic pain occurs due to physical damage, injury, or dysfunction of neuronal fibers. The pathophysiology of neuropathic pain is too complex. Therefore, an accurate and reliable prediction of the appropriate hits/ligands for the treatment of neuropathic pain is a challenging process. However, computer-aided drug discovery approaches contributed significantly to discovering newer hits/ligands for the treatment of neuropathic pain. The computational approaches like homology modeling, induced-fit molecular docking, structure-activity relationships, metadynamics, and virtual screening were cited in the literature for the identification of potential hit molecules against neuropathic pain. These hit molecules act as inducible nitric oxide synthase inhibitors, FLAT antagonists, TRPA1 modulators, voltage-gated sodium channel binder, cannabinoid receptor-2 agonists, sigma-1 receptor antagonists, etc. Sigma-1 receptor is a distinct type of opioid receptor and several patents were obtained for sigma-1 receptor antagonists for the treatment of neuropathic pain. These molecules were found to have a profound role in the management of neuropathic pain. The present review describes the validated therapeutic targets, potential chemical scaffolds, and crucial protein-ligand interactions for the management of neuropathic pain based on the recently reported computational methodologies of the present and past decades. The study can help the researcher to discover newer drugs/drug-like molecules against neuropathic pain.

摘要

神经病理性疼痛是由于神经元纤维的物理损伤、损伤或功能障碍引起的。神经病理性疼痛的病理生理学非常复杂。因此,准确可靠地预测治疗神经病理性疼痛的合适命中/配体是一个具有挑战性的过程。然而,计算机辅助药物发现方法为发现治疗神经病理性疼痛的新型命中/配体做出了重大贡献。文献中引用了计算方法,如同源建模、诱导契合分子对接、构效关系、元动力学和虚拟筛选,以鉴定针对神经病理性疼痛的潜在命中分子。这些命中分子作为诱导型一氧化氮合酶抑制剂、FLAT 拮抗剂、TRPA1 调节剂、电压门控钠离子通道结合物、大麻素受体 2 激动剂、sigma-1 受体拮抗剂等发挥作用。sigma-1 受体是一种独特类型的阿片受体,已经获得了几种 sigma-1 受体拮抗剂治疗神经病理性疼痛的专利。这些分子在神经病理性疼痛的管理中发挥了重要作用。本综述根据最近几十年报道的计算方法,描述了治疗神经病理性疼痛的已验证的治疗靶点、潜在的化学支架和关键的蛋白-配体相互作用。该研究可以帮助研究人员发现针对神经病理性疼痛的新型药物/类药物分子。

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Curr Top Med Chem. 2021;21(32):2856-2868. doi: 10.2174/1568026621666211122161932.
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