In Silico Analysis of Novel DPP-IV Inhibitory Peptides Released from Camel Milk Lactoferrin and the Possible Pathways Involved in Diabetes Protection
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摘要: 目的：结合生物信息学，从驼乳乳铁蛋白（Lactoferrin，LF）中筛选DPP-IV（Dipeptidyl peptidase IV，DPP-IV）抑制肽，并利用网络药理学探讨筛选肽段对糖尿病的潜在作用机制。方法：利用BIOPEP网站模拟酶切LF序列产生多条肽段，结合多肽数据库及分子对接筛选潜在的DPP-IV抑制肽，选择其中四条进行人工合成，验证其DPP-IV抑制活性，通过分子对接分析肽段与DPP-IV分子间相互作用方式，Lineweaver-Burk方法分析肽段抑制模式。选择抑制作用较强的GPQY进行网络药理学分析，预测其对糖尿病的潜在作用机制。采用Swiss Target Prediction和GeneCards数据库挖掘GPQY及糖尿病的作用靶点，String数据库获取蛋白与蛋白互作关系，Cytoscape 3.9.0软件构建PPI网络，DAVID数据库对靶点进行GO与KEGG通路富集分析。结果：筛选验证获得2条DPP-IV抑制GPQY和EACAF，其半抑制浓度（IC50）值分别为348.27±16.11和1024.89±19.67 μmol/L，抑制模式分析表明GPQY为竞争性抑制，EACAF为混合型抑制。分子对接结果显示两条肽段通过氢键、疏水作用和静电作用与DPP-IV结合。由PPI网络筛选到GPQY有STAT3、MMP9、SRC、MAPK1等25个核心作用靶点，KEGG通路富集显示GPQY防治糖尿病通路涉及IL-17信号通路、肿瘤坏死因子（TNF）信号通路、肾素-血管紧张素系统、细胞凋亡等。 结论：驼乳LF是DPP-IV抑制肽的良好来源，由其获得的四肽GPQY可通过多靶点、多通路参与炎症反应，影响细胞增殖分化等多方面防治糖尿病及其并发症。Abstract: Objective: To screen novel dipeptidyl peptidase IV (DPP-IV) inhibitory peptides from camel milk lactoferrin (LF) combined with bioinformatics. Network pharmacology was used to explore the potential mechanism of action of screened peptides on diabetes. Methods: Multiple peptides were generated by simulated enzymatic cleavage of lactoferrin using the BIOPEP website. Screening target peptides by combining peptide databases and molecular docking. Four of them were selected for solid-phase synthesis to verify their DPP-IV inhibitory activity. Molecular docking was performed to analyze the interaction between the peptide and DPP-IV molecules, and the Lineweaver-Burk method was used to analyze the inhibition mode of the peptide. Then, GPQY with stronger inhibition was selected for network pharmacological analysis to predict its potential mechanism of action on diabetes. Furthermore, the active targets of GPQY and diabetes were mined from the Swiss Target Prediction and Gene Cards databases, and the String database was used to obtain protein-protein interaction relationships. The PPI networks were built by Cytoscape 3.9.0 software, and the DAVID database was exploited for enrichment analysis of GO and KEGG signaling pathways for key targets. Results: Two DPP-IV inhibitory peptides were obtained with semi-inhibitory concentration (IC50) values of 348.27±16.11 and 1024.89±19.67 μmol/L. Inhibition pattern analysis indicated competitive inhibition of GPQY and mixed-type inhibition of EACAF. Molecular docking results revealed two peptides bound to the active pocket of DPP-IV through hydrogen bonding, hydrophobic interactions and electrostatic interactions. From the PPI network analysis, GPQY had 25 core-acting targets, including STAT3, MMP9, SRC, and MAPK1. The enrichment results were based on KEGG pathways, which showed that GPQY was involved in the IL-17 signaling pathway, tumor necrosis factor (TNF) signaling pathway, renin-angiotensin system, apoptosis, etc. Conclusion: Camel milk lactoferrin is a good source of DPP-IV inhibitor peptide. GPQY could prevent diabetes and its complications through multiple targets and pathways involved in the inflammatory response and cell proliferation and differentiation.
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图 1 肽段HPLC图和LC-MS图
Figure 1. HPLC spectrum and LC-MS spectrum of peptides
注：A、B、C和D分别代表 EACAF、GPQY、IWKL和 FGR。
图 2 GPQY（A）和EACAF（B）的DPP-IV抑制活性
Figure 2. DPP-IV inhibitory activity of GPQY (A) and EACAF (B)
图 3 DPP-IV抑制肽 GPQY（A）与EACAF（B）的Lineweaver-Buck双倒数图
Figure 3. Lineweaver-Buck double inverse plot of DPP-IV inhibitory peptide GPQY (A) and EACAF (B)
图 4 分子对接模式图
Figure 4. Molecular docking pattern diagram
注：A、B、C分别表示IPI（对照）、GQPY和EACAF；下标1、2、3分别表示肽段与DPP-IV对接最佳构象3D视图，局部图和相互作用2D图。
图 5 GPQY潜在作用靶点分布（A）和GPQY与糖尿病交集靶点韦恩图（B）
Figure 5. Distribution of potential targets of GPQY action (A) and Venn diagram of GPQY and diabetes intersection targets (B)
图 7 GPQY与糖尿病相关的82个靶点KEGG富集分析（A）及GO富集分析（B）
Figure 7. KEGG enrichment analysis (A) and GO enrichment analysis (B) of 82 targets associated with GPQY and diabetes
表 1 模拟酶切结果
Table 1. Simulation of digestion results
蛋白酶种类 模拟酶解产
生肽段数目去除重复肽
段后数目特有肽
段数Peptide ranker
得分>0.5胰蛋白酶Trypsin
（EC3.4.21.4）75 73 72 23（32%） 胃蛋白酶pepsinpH1.3
（EC3.4.23.1）82 77 26 32（42%） 胰凝乳蛋白酶
Chymotrypsin
（EC3.4.21.1）125 110 49 33（30%） 木瓜蛋白酶papain
（EC3.4.22.2）186 144 114 35（24%） 碱性蛋白酶Subtilisin
（3.4.2.34）167 148 93 45（30%） 蛋白酶K proteinase K
（EC3.4.21.67）154 133 85 38（29%） 
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表 2 筛选肽段Peptide ranker评分
Table 2. Peptide ranker score for screening peptides
序号 肽段 Peptide ranker评分 序号 肽段 Peptide ranker评分 1 GF1 0.994712 16 SGF 0.947492 2 RF1 0.986556 17 GDF 0.941533 3 AF1 0.973259 18 IPM1 0.845096 4 IW 0.944175 19 DAF 0.804969 5 CP 0.943255 20 CPN 0.780467 6 DW 0.933025 21 APG1 0.745179 7 GP1 0.905487 22 SPL 0.665423 8 CL 0.879917 23 PAL 0.631952 9 VW 0.802223 24 GAL 0.594888 10 AP1 0.626856 25 DPY 0.586633 11 SP1 0.514894 26 IWKL 0.733588 12 CRF 0.98469 27 GPQY 0.643377 13 RPF 0.977766 28 PPEPL 0.684494 14 FGR 0.967011 29 DPYKL 0.579245 15 GAF 0.954769 30 EACAF 0.634993 注：1为已报道的肽。 
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表 3 分子对接打分表
Table 3. Molecular docking scoring
序号 肽段 -CDOCKER_ENERGY -CDOCKER_INTERACTION_
ENERGY1 EACAF 102.042 68.9447 2 IWKL 88.9743 79.7752 3 GPQY 84.6352 71.8239 4 DAF 81.4763 59.859 5 FGR 81.046 75.6303 6 GDF 80.4749 64.0784 7 DPYKL 75.5242 76.8073 8 GAF 74.7882 64.8822 9 GAL 73.5947 61.7327 10 SGF 73.5308 63.686 11 CRF 72.4341 68.7239 12 DPY 71.4961 63.9571 13 DW 68.2476 53.2253 14 IW 66.5734 63.7061 15 CPN 63.3028 65.4616 16 RPF 61.2769 71.9084 17 SPL 60.3406 67.1524 18 VW 60.2456 55.2833 19 IPI 60.1427 62.6373 20 PAL 57.1327 65.2958 21 PPEPL 54.4414 72.4935 22 CP 48.4354 53.0389 
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表 4 已报道的DPP-IV抑制肽的IC50值
Table 4. IC50 values of the reported DPP-IV inhibitory peptides
肽段 来源 DPP-IV IC50 参考文献 VPF 驼乳β-酪蛋白 55.1±5.8 μmol/L [3] YP 酪蛋白 658.1±8.0 μmol/L [20] LP 酪蛋白 712.5±11.0 μmol/L [20] LPLPL 酪蛋白 325.0±15.2 μmol/L [20] MPPLP 乳制品 490 μmol/L [23] ADF 鸡蛋肌球蛋白 16.83 mmol/L [24] MIR 鸡蛋肌球蛋白 4.86 mmol/L [24] MPVQA 驼乳蛋白 93.3±8.0 μmol/L [25] IPI κ-酪蛋白 3.5 μmol/L [26] IPV 鱼蛋白 5.61±0.20 μmol/L [27] LQP β-酪蛋白 118.1 μmol/L [28] GPFPILV 山羊乳酪蛋白 163.7±1.33 mmol/L [29] 
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表 5 肽段与DPP-IV对接最佳构象相互作用力
Table 5. Optimal conformational interaction force of peptide docking with DPP-IV
Peptides
（肽键）-CDOCKER_ENERGY
（亲和力）Residues with Hydrogen bonds
（氢键）Residues with Hydrophobic
（疏水相互作用）Residues with Electrostatic
（静电相互作用）IPI 60.1427 Asn 710（2.85 ?）
Arg 125（2.67?，2.59 ?）
Tyr 662 （2.04 ?）Phe 357（5.21 ?）
Tyr 547（5.06?, 5.21?, 5.01 ?）
Tyr 666（5.10?, 5.15?）Arg 125（2.07 ?）
Glu 205（1.76 ?）
Glu 206（2.59 ?）
Asp 663（4.68 ?）GPQY 84.6352 Arg 125（1.93 ?）
Glu 205（1.90?，2.75 ?）
Tyr 547（2.65?）
Ser 630（2.97 ?）
Tyr 631（1.89 ?）
Tyr 662（1.81 ?, 2.33 ?）
His740（2.38 ?）His 740（5.34 ?）
Val 711（5.23 ?）
Tyr 662（4.37 ?）Glu 205（1.95 ?）
Glu 206（1.99 ?）
Asp 663（4.63 ?）EACAF
10102.042 Arg125（1.90?, 2.09 ?,
2.38 ?, 2.49 ?）
Glu205（2.58 ?）
Glu206（3.00 ?）
Ser209（1.83 ?）
Ser630（2.69 ?）
Tyr631（2.97 ?）
Tyr662（1.93?, 2.34 ?）Phe357（4.12 ?） Arg 125（5.06 ?）
Glu 205（1.94 ?）
Glu 206（2.60 ?）
Tyr 662（4.41 ?）
Asp 663（5.12 ?）
Tyr 666（4.18 ?）
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表 6 核心靶点拓扑参数
Table 6. Core targets and topological parameters
序号 靶点 Degree 序号 靶点 Degree 1 STAT3 15 14 MME 6 2 MMP9 13 15 MMP3 5 3 SRC 13 16 MMP2 5 4 PLG 10 17 CTSL 5 5 MAPK1 10 18 DPP4 5 6 CXCR4 8 19 MMP10 4 7 MMP1 7 20 NOS2 4 8 FYN 7 21 DLG4 4 9 LCK 7 22 CPB2 4 10 F2 7 23 HDAC1 4 11 CASP3 7 24 PTGS2 4 12 SHC1 6 25 BACE1 4 13 CTSB 6 
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