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GP63蛋白衍生肽对黑色素瘤癌MMP2蛋白抗癌特性的生物信息学评估。

Bioinformatics evaluation of anticancer properties of GP63 protein-derived peptides on MMP2 protein of melanoma cancer.

作者信息

Sharifi Fatemeh, Sharifi Iraj, Babaei Zahra, Alahdin Sodabeh, Afgar Ali

机构信息

Research Center of Tropical and Infectious Diseases, Kerman University of Medical Sciences, Kerman, Iran.

Leishmaniasis Research Center, Kerman University of Medical Sciences, Kerman, Iran.

出版信息

J Pathol Inform. 2023 Jan 12;14:100190. doi: 10.1016/j.jpi.2023.100190. eCollection 2023.

Abstract

BACKGROUND

GP63, also known as Leishmanolysin, is a multifunctional virulence factor abundant on the surface of spp. small peptides with anticancer capabilities that are selective and toxic to cancer cells are known as anticancer peptides. We aimed to demonstrate the activity of GP63 and its anticancer properties on melanoma using a range of tools and screening methods to identify predicted and designed anticancer peptides.

METHODS

Various modeling methodologies are used to establish the three-dimensional (3D) structure of GP63. Refinement and re-evaluation of the modeled structures and the built models' quality evaluated using the different docking used to find the interacting amino acids between MMP2 and GP63 and its anticancer peptides. AntiCP2.0 is used for screening anticancer peptides. 2D interaction plots of protein-ligand complexes evaluated by Protein-Ligand Interaction Profiler server. It is for the first time that used anticancer peptides of GP63 and the predicted and designed peptides.

RESULTS

We used 3 peptides of GP63 based on the AntiCP 2.0 server with scores of 0.63, 0.53, and 0.49, and common peptides of GP63/MMP2 (continues peptide: mean the completely selected peptide after docking with non-anticancer effect, predicted with 0.58 score and designed peptides with 0.47 and 0.45 scores by AntiCP 2.0 server).

CONCLUSIONS

The antileishmanial and anticancer peptide research topics exemplify the multidisciplinary nature of peptide research. The advancement of therapeutics targeting cancer and/or requires an interconnected research strategy shown in this work.

摘要

背景

GP63,也被称为利什曼溶素,是一种在 物种表面丰富的多功能毒力因子。具有抗癌能力的小肽对癌细胞具有选择性和毒性,被称为抗癌肽。我们旨在使用一系列工具和筛选方法来证明GP63的活性及其对黑色素瘤的抗癌特性,以鉴定预测和设计的抗癌肽。

方法

使用各种建模方法来建立GP63的三维(3D)结构。对建模结构进行优化和重新评估,并使用不同的对接方法评估构建模型的质量,以找到MMP2与GP63及其抗癌肽之间相互作用的氨基酸。使用AntiCP2.0筛选抗癌肽。通过蛋白质-配体相互作用分析服务器评估蛋白质-配体复合物的二维相互作用图。这是首次使用GP63的抗癌肽以及预测和设计的肽。

结果

我们基于AntiCP 2.0服务器使用了3种GP63肽,得分分别为0.63、0.53和0.49,以及GP63/MMP2的常见肽(连续肽:指对接后完全选择的无抗癌作用的肽,通过AntiCP 2.0服务器预测得分为0.58,设计肽得分为0.47和0.45)。

结论

抗利什曼原虫和抗癌肽的研究主题体现了肽研究的多学科性质。针对癌症和/或 的治疗进展需要本研究中所示的相互关联的研究策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a82/9867975/14fdefdecb37/gr1.jpg

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