A Computational Approach to Characterize the Protein S-Mer Tyrosine Kinase (PROS1-MERTK) Protein-Protein Interaction Dynamics.

IF 1.8 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Mak B Djulbegovic, David J Taylor Gonzalez, Luciano Laratelli, Michael Antonietti, Vladimir N Uversky, Carol L Shields, Carol L Karp
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引用次数: 0

Abstract

Protein S (PROS1) has recently been identified as a ligand for the TAM receptor MERTK, influencing immune response and cell survival. The PROS1-MERTK interaction plays a role in cancer progression, promoting immune evasion and metastasis in multiple cancers by fostering a tumor-supportive microenvironment. Despite its importance, limited structural insights into this interaction underscore the need for computational studies to explore their binding dynamics, potentially guiding targeted therapies. In this study, we investigated the PROS1-MERTK interaction using advanced computational analyses to support immunotherapy research. High-resolution structural models from ColabFold, an AlphaFold2 adaptation, provided a baseline structure, allowing us to examine the PROS1-MERTK interface with ChimeraX and map residue interactions through Van der Waals criteria. Molecular dynamics (MD) simulations were conducted in GROMACS over 100 ns to assess stability and conformational changes using RMSD, RMSF, and radius of gyration (Rg). The PROS1-MERTK interface was predicted to contain a heterogeneous mix of amino acid contacts, with lysine and leucine as frequent participants. MD simulations demonstrated prominent early structural shifts, stabilizing after approximately 50 ns with small conformational shifts occurring as the simulation completed. In addition, there are various regions in each protein that are predicted to have greater conformational fluctuations as compared to others, which may represent attractive areas to target to halt the progression of the interaction. These insights deepen our understanding of the PROS1-MERTK interaction role in immune modulation and tumor progression, unveiling potential targets for cancer immunotherapy.

表征蛋白 S-Mer 酪氨酸激酶 (PROS1-MERTK) 蛋白-蛋白相互作用动力学的计算方法。
蛋白 S(PROS1)最近被确认为 TAM 受体 MERTK 的配体,可影响免疫反应和细胞存活。PROS1-MERTK 相互作用在癌症进展中发挥着作用,通过促进肿瘤支持性微环境,促进多种癌症的免疫逃避和转移。尽管这种相互作用非常重要,但由于对其结构的了解有限,因此需要通过计算研究来探索其结合动力学,从而为靶向治疗提供潜在指导。在这项研究中,我们利用先进的计算分析方法研究了 PROS1-MERTK 的相互作用,以支持免疫疗法研究。来自 AlphaFold2 适配版 ColabFold 的高分辨率结构模型提供了一个基线结构,使我们能够用 ChimeraX 检查 PROS1-MERTK 接口,并通过范德华标准绘制残基相互作用图。我们在 GROMACS 中进行了 100 ns 的分子动力学(MD)模拟,利用 RMSD、RMSF 和回旋半径(Rg)评估稳定性和构象变化。据预测,PROS1-MERTK 界面包含多种氨基酸接触,其中赖氨酸和亮氨酸经常参与。MD 模拟显示了明显的早期结构转变,在大约 50 毫微秒后趋于稳定,随着模拟的完成,会发生小的构象转变。此外,与其他区域相比,每个蛋白质中都有不同的预测构象波动较大的区域,这些区域可能是阻止相互作用进展的有吸引力的目标区域。这些见解加深了我们对 PROS1-MERTK 相互作用在免疫调节和肿瘤进展中的作用的理解,揭示了癌症免疫疗法的潜在靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cell Biochemistry and Biophysics
Cell Biochemistry and Biophysics 生物-生化与分子生物学
CiteScore
4.40
自引率
0.00%
发文量
72
审稿时长
7.5 months
期刊介绍: Cell Biochemistry and Biophysics (CBB) aims to publish papers on the nature of the biochemical and biophysical mechanisms underlying the structure, control and function of cellular systems The reports should be within the framework of modern biochemistry and chemistry, biophysics and cell physiology, physics and engineering, molecular and structural biology. The relationship between molecular structure and function under investigation is emphasized. Examples of subject areas that CBB publishes are: · biochemical and biophysical aspects of cell structure and function; · interactions of cells and their molecular/macromolecular constituents; · innovative developments in genetic and biomolecular engineering; · computer-based analysis of tissues, cells, cell networks, organelles, and molecular/macromolecular assemblies; · photometric, spectroscopic, microscopic, mechanical, and electrical methodologies/techniques in analytical cytology, cytometry and innovative instrument design For articles that focus on computational aspects, authors should be clear about which docking and molecular dynamics algorithms or software packages are being used as well as details on the system parameterization, simulations conditions etc. In addition, docking calculations (virtual screening, QSAR, etc.) should be validated either by experimental studies or one or more reliable theoretical cross-validation methods.
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