模拟人亮氨酸氨基肽酶对潜在恶性疟原虫亮氨酸氨基肽酶(PfA-M17)特异性抑制剂的硅脱靶结合分析。

Shakti Sahi, Utkarsh Raj, Meenakshi Chaudhary, Vikrant Nain
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引用次数: 3

摘要

疟疾是世界上传播最广泛的传染病之一。多重耐药疟原虫菌株的出现使得确定抗疟疾治疗的新类别化合物至关重要。来自天然来源的新型抗疟疾化合物(Gomphostema niveum)以及合成化学品(5-氨基乙酰丙酸)在最近的专利中得到了报道。恶性疟原虫亮基氨基肽酶(PfA-M17)是抗疟药物开发的有效靶点。然而,已知的氨基肽酶抑制剂存在着非特异性的问题。因此,预测PfA-M17人类同源物亮氨酸氨基肽酶3 (hLAP3)和可能亮氨酸氨基肽酶(hNPEPL1)的3D结构模型,基于分子对接筛选潜在抑制剂的脱靶活性。高活性hLAP3抑制剂的IC50与对接评分比较显示出良好的相关性(r(2)≈0.8)。此外,与潜在的PfA-M17抑制剂Compound-X(通过虚拟筛选鉴定)对接分析显示,与PfA-M17的结合亲和力(对接评分-11.44)远高于hLAP3(对接评分-4.26)和hNPEPL1(对接评分-5.08)。该先导化合物化合物- x可以作为进一步提高PfA-M17结合亲和力的支架,hLAP3和hNPEPL1的3D结构模型将有助于筛选PfA-M17特异性抑制剂。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling of human leucyl aminopeptidases for in silico off target binding analysis of potential Plasmodium falciparum leucine aminopeptidase (PfA-M17) specific inhibitors.

Malaria is one of the most widespread infectious diseases in the world. Emergence of multi-drug resistant Plasmodium strains makes it crucial to identify new classes of compounds for anti-malarial therapy. Novel anti-malarial compounds from natural sources (Gomphostema niveum) as well as synthetic chemicals (5-aminolevulinic acid) have been reported in recent patents. Plasmodium falciparum leucyl aminopeptidase (PfA-M17) is a validated target for antimalarial drug development. However, known aminopeptidase inhibitors beset with the problem of non-specificity. Therefore, 3D structural models of PfA-M17 human homologs, Leucine aminopeptidase3 (hLAP3) and probable leucine aminopeptidase (hNPEPL1) were predicted for molecular docking based screening of potential inhibitors for their off target activity. Comparison of IC50 and docking scores of highly active hLAP3 inhibitors shows good correlation (r(2)≈ 0.8). Further, docking analysis with potential PfA-M17 inhibitor Compound-X (identified through virtual screening) shows much higher binding affinity towards PfA-M17 (docking score -11.44) than hLAP3 (docking score -4.26) and hNPEPL1 (docking score -5.08). This lead compound, Compound-X can act as a scaffold for further increasing PfA-M17 binding affinity and hLAP3 and hNPEPL1 3D structure models will be useful for screening of PfA-M17 specific inhibitors.

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