Qamar Fouzia, Sharif Zubair, Idrees Jawaria, Wasim Asif, Haider Sana, Salman Saad
Department of Biology, Lahore Garrison University, Lahore-54000, Punjab, Pakistan.
Faculty of Medical Laboratory Sciences, Superior University, Lahore-54000, Punjab, Pakistan.
Future Sci OA. 2024 May 15;10(1):FSO917. doi: 10.2144/fsoa-2023-0112. eCollection 2024.
To investigate the role of phosphorylation in SARS-CoV-2 infection, potential therapeutic targets and its harmful genetic sequences. Data mining techniques were employed to identify upregulated kinases responsible for proteomic changes induced by SARS-CoV-2. Spike and nucleocapsid proteins' sequences were analyzed using predictive tools, including SNAP2, MutPred2, PhD-SNP, SNPs&Go, MetaSNP, Predict-SNP and PolyPhen-2. Missense variants were identified using ensemble-based algorithms and homology/structure-based models like SIFT, PROVEAN, Predict-SNP and MutPred-2. Eight missense variants were identified in viral sequences. Four damaging variants were found, with SNPs&Go and PolyPhen-2. Promising therapeutic candidates, including gilteritinib, pictilisib, sorafenib, RO5126766 and omipalisib, were identified. This research offers insights into SARS-CoV-2 pathogenicity, highlighting potential treatments and harmful variants in viral proteins.
为了研究磷酸化在严重急性呼吸综合征冠状病毒2（SARS-CoV-2）感染、潜在治疗靶点及其有害基因序列中的作用。采用数据挖掘技术来识别导致SARS-CoV-2诱导的蛋白质组变化的上调激酶。使用包括SNAP2、MutPred2、PhD-SNP、SNPs&Go、MetaSNP、Predict-SNP和PolyPhen-2在内的预测工具分析刺突蛋白和核衣壳蛋白的序列。使用基于集成的算法以及基于同源性/结构的模型（如SIFT、PROVEAN、Predict-SNP和MutPred-2）来识别错义变体。在病毒序列中鉴定出八个错义变体。使用SNPs&Go和PolyPhen-2发现了四个有害变体。确定了有前景的治疗候选药物，包括吉列替尼、匹西利司、索拉非尼、RO5126766和奥米帕利司。这项研究为SARS-CoV-2的致病性提供了见解，突出了病毒蛋白中的潜在治疗方法和有害变体。
