A computational simulation appraisal of banana lectin as a potential anti-SARS-CoV-2 candidate by targeting the receptor-binding domain.

IF 3.6 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Journal, genetic engineering & biotechnology Pub Date : 2023-11-28 DOI:10.1186/s43141-023-00569-8
Sofia Safitri Hessel, Fenny Martha Dwivany, Ima Mulyama Zainuddin, Ketut Wikantika, Ismail Celik, Talha Bin Emran, Trina Ekawati Tallei
{"title":"A computational simulation appraisal of banana lectin as a potential anti-SARS-CoV-2 candidate by targeting the receptor-binding domain.","authors":"Sofia Safitri Hessel, Fenny Martha Dwivany, Ima Mulyama Zainuddin, Ketut Wikantika, Ismail Celik, Talha Bin Emran, Trina Ekawati Tallei","doi":"10.1186/s43141-023-00569-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The ongoing concern surrounding coronavirus disease 2019 (COVID-19) primarily stems from continuous mutations in the genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), leading to the emergence of numerous variants. The receptor-binding domain (RBD) in the S1 subunit of the S protein of the virus plays a crucial role in recognizing the host's angiotensin-converting enzyme 2 (hACE2) receptor and facilitating cell membrane fusion processes, making it a potential target for preventing viral entrance into cells. This research aimed to determine the potential of banana lectin (BanLec) proteins to inhibit SARS-CoV-2 attachment to host cells by interacting with RBD through computational modeling.</p><p><strong>Materials and methods: </strong>The BanLecs were selected through a sequence analysis process. Subsequently, the genes encoding BanLec proteins were retrieved from the Banana Genome Hub database. The FGENESH online tool was then employed to predict protein sequences, while web-based tools were utilized to assess the physicochemical properties, allergenicity, and toxicity of BanLecs. The RBDs of SARS-CoV-2 were modeled using the SWISS-MODEL in the following step. Molecular docking procedures were conducted with the aid of ClusPro 2.0 and HDOCK web servers. The three-dimensional structures of the docked complexes were visualized using PyMOL. Finally, molecular dynamics simulations were performed to investigate and validate the interactions of the complexes exhibiting the highest interactions, facilitating the simulation of their dynamic properties.</p><p><strong>Results: </strong>The BanLec proteins were successfully modeled based on the RNA sequences from two species of banana (Musa sp.). Moreover, an amino acid modification in the BanLec protein was made to reduce its mitogenicity. Theoretical allergenicity and toxicity predictions were conducted on the BanLecs, which suggested they were likely non-allergenic and contained no discernible toxic domains. Molecular docking analysis demonstrated that both altered and wild-type BanLecs exhibited strong affinity with the RBD of different SARS-CoV-2 variants. Further analysis of the molecular docking results showed that the BanLec proteins interacted with the active site of RBD, particularly the key amino acids residues responsible for RBD's binding to hACE2. Molecular dynamics simulation indicated a stable interaction between the Omicron RBD and BanLec, maintaining a root-mean-square deviation (RMSD) of approximately 0.2 nm for a duration of up to 100 ns. The individual proteins also had stable structural conformations, and the complex demonstrated a favorable binding-free energy (BFE) value.</p><p><strong>Conclusions: </strong>These results confirm that the BanLec protein is a promising candidate for developing a potential therapeutic agent for combating COVID-19. Furthermore, the results suggest the possibility of BanLec as a broad-spectrum antiviral agent and highlight the need for further studies to examine the protein's safety and effectiveness as a potent antiviral agent.</p>","PeriodicalId":74026,"journal":{"name":"Journal, genetic engineering & biotechnology","volume":"21 1","pages":"148"},"PeriodicalIF":3.6000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684481/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal, genetic engineering & biotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s43141-023-00569-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Background: The ongoing concern surrounding coronavirus disease 2019 (COVID-19) primarily stems from continuous mutations in the genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), leading to the emergence of numerous variants. The receptor-binding domain (RBD) in the S1 subunit of the S protein of the virus plays a crucial role in recognizing the host's angiotensin-converting enzyme 2 (hACE2) receptor and facilitating cell membrane fusion processes, making it a potential target for preventing viral entrance into cells. This research aimed to determine the potential of banana lectin (BanLec) proteins to inhibit SARS-CoV-2 attachment to host cells by interacting with RBD through computational modeling.

Materials and methods: The BanLecs were selected through a sequence analysis process. Subsequently, the genes encoding BanLec proteins were retrieved from the Banana Genome Hub database. The FGENESH online tool was then employed to predict protein sequences, while web-based tools were utilized to assess the physicochemical properties, allergenicity, and toxicity of BanLecs. The RBDs of SARS-CoV-2 were modeled using the SWISS-MODEL in the following step. Molecular docking procedures were conducted with the aid of ClusPro 2.0 and HDOCK web servers. The three-dimensional structures of the docked complexes were visualized using PyMOL. Finally, molecular dynamics simulations were performed to investigate and validate the interactions of the complexes exhibiting the highest interactions, facilitating the simulation of their dynamic properties.

Results: The BanLec proteins were successfully modeled based on the RNA sequences from two species of banana (Musa sp.). Moreover, an amino acid modification in the BanLec protein was made to reduce its mitogenicity. Theoretical allergenicity and toxicity predictions were conducted on the BanLecs, which suggested they were likely non-allergenic and contained no discernible toxic domains. Molecular docking analysis demonstrated that both altered and wild-type BanLecs exhibited strong affinity with the RBD of different SARS-CoV-2 variants. Further analysis of the molecular docking results showed that the BanLec proteins interacted with the active site of RBD, particularly the key amino acids residues responsible for RBD's binding to hACE2. Molecular dynamics simulation indicated a stable interaction between the Omicron RBD and BanLec, maintaining a root-mean-square deviation (RMSD) of approximately 0.2 nm for a duration of up to 100 ns. The individual proteins also had stable structural conformations, and the complex demonstrated a favorable binding-free energy (BFE) value.

Conclusions: These results confirm that the BanLec protein is a promising candidate for developing a potential therapeutic agent for combating COVID-19. Furthermore, the results suggest the possibility of BanLec as a broad-spectrum antiviral agent and highlight the need for further studies to examine the protein's safety and effectiveness as a potent antiviral agent.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于受体结合域的香蕉凝集素抗sars - cov -2候选物的计算模拟评价
背景:对2019冠状病毒病(COVID-19)的持续关注主要源于严重急性呼吸综合征冠状病毒2 (SARS-CoV-2)基因组的连续突变,导致大量变体的出现。病毒S蛋白S1亚基的受体结合域(RBD)在识别宿主血管紧张素转换酶2 (hACE2)受体和促进细胞膜融合过程中起着至关重要的作用,使其成为阻止病毒进入细胞的潜在靶点。本研究旨在通过计算模型确定香蕉凝集素(BanLec)蛋白通过与RBD相互作用抑制SARS-CoV-2附着宿主细胞的潜力。材料和方法:BanLecs通过序列分析筛选。随后,从香蕉基因组中心数据库中检索编码BanLec蛋白的基因。然后使用FGENESH在线工具预测蛋白质序列,同时使用基于网络的工具评估BanLecs的物理化学特性、过敏原性和毒性。在接下来的步骤中,使用SWISS-MODEL对SARS-CoV-2的rbd进行建模。分子对接程序借助ClusPro 2.0和HDOCK web服务器进行。利用PyMOL对对接物的三维结构进行可视化分析。最后,进行了分子动力学模拟,以研究和验证具有最高相互作用的配合物的相互作用,从而促进其动力学性质的模拟。结果:基于两种香蕉(Musa sp.)的RNA序列成功构建了BanLec蛋白模型。此外,对BanLec蛋白进行氨基酸修饰以降低其有丝分裂性。对BanLecs进行了理论上的致敏性和毒性预测,这表明它们可能是非致敏性的,并且不包含可识别的毒性结构域。分子对接分析表明,改变的BanLecs和野生型BanLecs都与不同SARS-CoV-2变体的RBD具有很强的亲和力。进一步的分子对接分析结果表明,BanLec蛋白与RBD的活性位点相互作用,特别是与RBD与hACE2结合的关键氨基酸残基。分子动力学模拟表明,Omicron RBD和BanLec之间的相互作用稳定,在长达100 ns的持续时间内保持约0.2 nm的均方根偏差(RMSD)。单个蛋白具有稳定的结构构象,复合物具有良好的无结合能(BFE)值。结论:这些结果证实,BanLec蛋白是开发抗COVID-19潜在治疗剂的有希望的候选蛋白。此外,这些结果表明BanLec作为一种广谱抗病毒药物的可能性,并强调需要进一步研究该蛋白作为一种强效抗病毒药物的安全性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Physiochemical analyses and molecular characterization of heavy metal-resistant bacteria from Ilesha gold mining sites in Nigeria. Whole genome sequence and comparative genomics analysis of multidrug-resistant Staphylococcus xylosus NM36 isolated from a cow with mastitis in Basrah city. Immunoinformatics-aided rational design of multiepitope-based peptide vaccine (MEBV) targeting human parainfluenza virus 3 (HPIV-3) stable proteins. Isolation of plant growth-promoting rhizobacteria from the agricultural fields of Tattiannaram, Telangana. Short tandem repeat (STR) variation from 6 cities in Iraq based on 15 loci.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1