Institute of Microbiology and Molecular Genetics, University of the Punjab, Lahore 54590, Pakistan.
Department of Biotechnology, University of Central Punjab, Lahore, Pakistan.
J Infect Public Health. 2023 Oct;16(10):1544-1555. doi: 10.1016/j.jiph.2023.07.011. Epub 2023 Jul 24.
The SARS-CoV-2 pandemic, caused by the novel coronavirus, has posed a significant global health threat since its emergence in late 2019. The World Health Organization declared the outbreak a pandemic on March 11, 2020, due to its rapid global spread and impact on public health. New variants have raised concerns about their potential impact on the transmission of the virus and the effectiveness of current diagnostic tools, treatments, and vaccines. This study aims to investigate the effect of new variants in Pakistani virus strains on human receptors, specifically ACE2 and NRP1. In-silico analysis provides a powerful tool to analyze the potential impact of new variants on protein structure, function, and interactions.
The SARS-CoV-2 virus is evolving quickly. After being exposed in Wuhan, SARS-CoV-2 underwent numerous mutations, leading to several variants' emergence. These variants stabilize the interaction of spike protein with human receptors ACE2 and NRP1. The study aims to check the molecular effect of these variants on human receptors using the in-silico approach.
We use in-silico mutational tools to analyze new variants in SARS-CoV-2 and to check the molecular interaction of spike protein with human receptors (ACE2 and NRP1). Genomic sequences of 41 SARS-CoV-2 strains were sequenced using Ion Torrent (NGS) and submitted to the GISAID database. Spike protein of SARS-CoV-2 sequence trimmed and translated into a protein sequence using ExPasy. We used multiple sequence alignments to check for variants in the spike protein of strains. We utilized mutation tools such as Mupro, SIFT, SNAP2, and Mutpred2.3D structures of SARS-CoV-2 spike proteins (wild and mutated) to analyze further the mutations, ACE2 and NRP1 modelled by the ITASSER protein modelling server. Interactions of spike proteins (wild and mutant) analyzed by MD Docking, Simulation, and MMGBSA RESULTS: Variants I210T, V213G, S371F, S373P, T478K, F486V, Y505H, and D796Y were identified in SARS-CoV-2 Pakistani strains' spike protein. Variant Y505H were found to affect protein function. MD Docking, MMGBSA and MD simulation revealed that these variants increased spike protein's binding affinity with human receptors (ACE2 and NRP1). MD simulation revealed that mutated spike protein stabilized earlier than wild when interacting with ACE2 after 40 ns and interaction with NRP1 stabilized after 30 ns for mutated spike protein compared to wild.
These variants in Pakistani strains of SARS-CoV-2 are increasing the stability of spike protein with human receptors. These findings provide insight into how the SARS-CoV-2 virus evolves and adapts to human hosts. This information may help develop strategies to control the virus's spread and develop effective treatments and vaccines in the future.
新型冠状病毒引起的 SARS-CoV-2 大流行自 2019 年底出现以来，对全球健康构成了重大威胁。由于其在全球范围内的迅速传播和对公共卫生的影响，世界卫生组织于 2020 年 3 月 11 日宣布疫情为大流行。新变体引发了人们对其潜在传播风险和对当前诊断工具、治疗方法和疫苗有效性的影响的担忧。本研究旨在研究新变体对巴基斯坦病毒株中人类受体 ACE2 和 NRP1 的影响。计算机模拟分析为分析新变体对蛋白质结构、功能和相互作用的潜在影响提供了一种强大的工具。
SARS-CoV-2 病毒正在迅速进化。在武汉暴露后，SARS-CoV-2 经历了多次突变，导致了几种变体的出现。这些变体稳定了刺突蛋白与人类受体 ACE2 和 NRP1 的相互作用。该研究旨在使用计算机模拟方法检查这些变体对人类受体的分子影响。
我们使用计算机模拟突变工具来分析 SARS-CoV-2 中的新变体，并检查刺突蛋白与人类受体（ACE2 和 NRP1）的分子相互作用。使用 Ion Torrent（NGS）对 41 株 SARS-CoV-2 进行基因组序列测序，并将其提交到 GISAID 数据库。使用 ExPasy 对 SARS-CoV-2 序列进行修剪并翻译成蛋白质序列。我们使用多重序列比对来检查菌株中刺突蛋白的变体。我们使用突变工具，如 Mupro、SIFT、SNAP2 和 Mutpred2.3D。使用 ITASSER 蛋白质建模服务器分析 SARS-CoV-2 刺突蛋白（野生型和突变型）的结构，进一步分析突变、ACE2 和 NRP1 建模。使用 MD 对接、模拟和 MMGBSA 分析刺突蛋白（野生型和突变型）的相互作用。
在 SARS-CoV-2 巴基斯坦株的刺突蛋白中发现了 I210T、V213G、S371F、S373P、T478K、F486V、Y505H 和 D796Y 等变体。变体 Y505H 被发现影响蛋白功能。MD 对接、MMGBSA 和 MD 模拟表明，这些变体增加了刺突蛋白与人类受体（ACE2 和 NRP1）的结合亲和力。MD 模拟表明，与野生型相比，突变型刺突蛋白在与 ACE2 相互作用后 40ns 时比野生型更早地稳定，而与 NRP1 相互作用后 30ns 时突变型刺突蛋白稳定。
这些在巴基斯坦 SARS-CoV-2 株中的变体增加了刺突蛋白与人类受体的稳定性。这些发现提供了关于 SARS-CoV-2 病毒如何进化和适应人类宿主的见解。这些信息可能有助于制定控制病毒传播的策略，并在未来开发有效的治疗方法和疫苗。
