分析 VEGFA/VEGFR1 相互作用:应用共振识别模型-斯托克韦尔变换法探索血管生成相关疾病的潜在治疗方法

The protein journal Pub Date : 2024-08-01 Epub Date: 2024-07-16 DOI:10.1007/s10930-024-10219-8
Tuhin Mukherjee, Ashok Pattnaik, Sitanshu Sekhar Sahu
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引用次数: 0

摘要

血管内皮生长因子 A(VEGFA)和血管内皮生长因子受体 1(VEGFR1)之间的相互作用是病理血管生成药物开发的核心重点。识别这些蛋白的热点对于开发新的疗法至关重要。尽管机器学习技术在预测任务中取得了巨大成功,但它们却难以准确定位与血管生成活性相关的热点。本研究通过 UniProt 数据库收集了不同物种的 VEGFA 和 VEGFR1 蛋白序列。电子-离子相互作用电位(EIIP)值被分配给各个氨基酸,并通过离散快速傅立叶变换(FFT)转换成频域表示。通过整合来自多个序列的 FFT 数据,形成了一个共识频谱,揭示了特定的特征频率。随后,利用斯托克韦尔变换(ST)得出热点。共振识别模型(RRM)识别出特征频率为 0.128007,相关波长为 1570 nm,RRM-ST 识别出 VEGFA(人类 36、46、48、67、71、74、82、86、89、93)和 VEGFR1(人类 224、259、263、290、807、841、877、881、885、892、894、909、913、1018、1022、1026、1043)的热点。这些发现通过热点向导 3.0 网络服务器和蛋白质数据库(PDB)进行了交叉验证。该研究建议使用 1570 nm 波长的光生物调制来促进 VEGFA/VEGFR1 在所需条件下的相互作用。它还旨在减少 VEGFA/VEGFR2 的相互作用,限制糖尿病视网膜病变等情况下的有害血管生成。此外,确定的热点还有助于设计激动肽或拮抗肽,以满足血管异常生成的特定医疗要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Analyzing VEGFA/VEGFR1 Interaction: Application of the Resonant Recognition Model-Stockwell Transform Method to Explore Potential Therapeutics for Angiogenesis-Related Diseases.

Analyzing VEGFA/VEGFR1 Interaction: Application of the Resonant Recognition Model-Stockwell Transform Method to Explore Potential Therapeutics for Angiogenesis-Related Diseases.

The interaction between vascular endothelial growth factor A (VEGFA) and VEGF receptor 1(VEGFR1) is a central focus for drug development in pathological angiogenesis, where aberrant angiogenesis underlies various anomalies necessitating therapeutic intervention. Identifying hotspots of these proteins is crucial for developing new therapeutics. Although machine learning techniques have succeeded significantly in prediction tasks, they struggle to pinpoint hotspots linked to angiogenic activity accurately. This study involves the collection of diverse VEGFA and VEGFR1 protein sequences from various species via the UniProt database. Electron-ion interaction Potential (EIIP) values were assigned to individual amino acids and transformed into frequency-domain representations using discrete Fast Fourier Transform (FFT). A consensus spectrum emerged by consolidating FFT data from multiple sequences, unveiling specific characteristic frequencies. Subsequently, the Stockwell Transform (ST) was employed to yield the hotspots. The Resonant Recognition Model (RRM) identified a characteristic frequency of 0.128007 with an associated wavelength of 1570 nm and RRM-ST identified hotspots for VEGFA (Human 36, 46, 48, 67, 71, 74, 82, 86, 89, 93) and VEGFR1 (Human 224, 259, 263, 290, 807, 841, 877, 881, 885, 892, 894, 909, 913, 1018, 1022, 1026, 1043). These findings were cross-validated by Hotspots Wizard 3.0 webserver and Protein Data Bank (PDB). The study proposes using a 1570 nm wavelength for photo bio modulation to boost VEGFA/VEGFR1 interaction in the condition that is needed. It also aims to reduce VEGFA/VEGFR2 interaction, limiting harmful angiogenesis in conditions like diabetic retinopathy. Also, the identified hotspots assist in designing agonistic or antagonistic peptides tailored to specific medical requirements with abnormal angiogenesis.

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