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首页> 外文期刊>Journal of Food Biochemistry >Construction of QSAR model based on cysteine‐containing dipeptides and screening of natural tyrosinase inhibitors
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Construction of QSAR model based on cysteine‐containing dipeptides and screening of natural tyrosinase inhibitors

机译:基于含半胱氨酸二肽的QSAR模型构建及天然酪氨酸酶抑制剂筛选

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Abstract Considering that natural products as tyrosinase inhibitors are considered to be safe, with little or no toxic side effects and friendly to the environment, it is urgent to develop a new recognition strategy for natural tyrosinase inhibitors. In current study, an integrated computational analysis was conducted on Cys‐containing dipeptides with high tyrosinase inhibitory activity. Firstly, molecular fingerprint similarity (FS) clustering analysis was performed on the target molecule using machine learning. Secondly, genetic algorithm was used to construct two kinds of highly accurate QSAR models (R2 = .978 and .984, respectively) with Cys at C‐terminal and N‐terminal. Finally, three novel natural candidate inhibitors (NP1, NP2, NP3) were discovered using Molnatsim natural product cluster library, automated screening process and QSAR based on the maximum common substructure (MCS) algorithm, their IC50pre were 260.96, 3.37 and 0.05 μm/mol. Pharmacokinetic predictions showed that NP2 and NP3 had high Bioavailability Score (BS) and Gastrointestinal (GI) absorption, and molecular dynamics simulations further validated the stability of these novel natural candidate inhibitors in binding to tyrosinase. In conclusion, our results provide new ideas for discovering new activities of natural products, and provide an accurate QSAR model for developing novel tyrosinase inhibitors based on MCS Cys‐containing dipeptides. Practical applications Tyrosinase is related to the occurrence of diseases such as excessive melanin deposition such as freckles and chloasma, and studies have shown that neurodegeneration associated with Parkinson's disease and Huntington's disease is also related. In addition, enzymatic browning on the surface of fresh fruit and vegetable slices will shorten the shelf life and affect their quality. Therefore, screening, designing and developing efficient tyrosinase inhibitors is very important in the fields of medicine, cosmetics, food and so on.
机译:摘要考虑到自然的产品酪氨酸酶抑制剂被认为是安全的,很少或根本没有有毒副作用和友好环境,迫在眉睫的是开发一个新的自然酪氨酸酶的识别策略抑制剂。进行了计算分析高半胱氨酸包含二肽与酪氨酸酶抑制活动。指纹图谱相似度(FS)聚类分析对目标分子进行使用吗机器学习。用于构造两种高度精确构象模型(R2 = .978 .984,分别)半胱氨酸在C的终端和N的终端。三个小说自然候选人抑制剂(NP1、使用Molnatsim自然NP2第一版)被发现集群产品库,自动筛选定量构效关系基于过程和最大的共同之处子结构(MCS)算法,他们的IC50pre260.96、3.37和0.05μm /摩尔。预测表明,NP2和NP3高生物利用度得分(BS)和胃肠道(GI)吸收,分子动力学仿真结果进一步验证了稳定性这些小说自然候选人抑制剂酪氨酸酶。为发现新的活动提供新思路自然产品,并提供一个精确的构象模型开发新颖的酪氨酸酶抑制剂基于MCS半胱氨酸包含二肽的量。应用程序中酪氨酸酶有关发生的疾病,如过多的黑色素沉积雀斑和黄褐斑等研究表明,神经退化与帕金森病有关亨廷顿氏舞蹈症也是相关的。此外,表面的酶促褐变新鲜水果和蔬菜片将会缩短保质期和影响其质量。筛选、设计和开发效率酪氨酸酶抑制剂是非常重要的医药、化妆品、食品等。

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