Computational design of a multi-epitope vaccine candidate against Langya henipavirus using surface proteins

表位 抗原性 佐剂 免疫原性 生物信息学 对接(动物) 病毒学 反向疫苗学 抗原 免疫系统 计算生物学 生物 化学 医学 免疫学 基因 遗传学 护理部
作者
Sajjad Ahmad,Shahin Nazarian,Akram Alizadeh,Maryam Pashapour Hajialilou,Shahram Tahmasebian,Metab Alharbi,Abdullah F. Alasmari,Ali Shojaeian,Mahdi Ghatrehsamani,Muhammad Irfan,Hamidreza Pazoki‐Toroudi,Samira Sanami
出处
期刊:Journal of Biomolecular Structure & Dynamics [Taylor & Francis]
卷期号:: 1-18 被引量:10
标识
DOI:10.1080/07391102.2023.2258403
摘要

In July 2022, Langya henipavirus (LayV) was identified in febrile patients in China. There is currently no approved vaccine against this virus. Therefore, this research aimed to design a multi-epitope vaccine against LayV using reverse vaccinology. The best epitopes were selected from LayV's fusion protein (F) and glycoprotein (G), and a multi-epitope vaccine was designed using these epitopes, adjuvant, and appropriate linkers. The physicochemical properties, antigenicity, allergenicity, toxicity, and solubility of the vaccine were evaluated. The vaccine's secondary and 3D structures were predicted, and molecular docking and molecular dynamics (MD) simulations were used to assess the vaccine's interaction and stability with toll-like receptor 4 (TLR4). Immune simulation, codon optimization, and in silico cloning of the vaccine were also performed. The vaccine candidate showed good physicochemical properties, as well as being antigenic, non-allergenic, and non-toxic, with acceptable solubility. Molecular docking and MD simulation revealed that the vaccine and TLR4 have stable interactions. Furthermore, immunological simulation of the vaccine indicated its ability to elicit immune responses against LayV. The vaccine's increased expression was also ensured using codon optimization. This study's findings were encouraging, but in vitro and in vivo tests are needed to confirm the vaccine's protective effect.Communicated by Ramaswamy H. Sarma.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
shirouer发布了新的文献求助10
刚刚
清脆的一一完成签到,获得积分10
1秒前
小李完成签到,获得积分10
1秒前
suxiang应助sunshine采纳,获得30
2秒前
sunzyu发布了新的文献求助10
2秒前
陈念完成签到,获得积分10
2秒前
2秒前
jingle完成签到,获得积分10
2秒前
希望天下0贩的0应助夏璃采纳,获得10
3秒前
3秒前
zyzhnu发布了新的文献求助30
3秒前
Eden发布了新的文献求助10
3秒前
4秒前
追寻完成签到,获得积分10
4秒前
4秒前
施柔发布了新的文献求助10
5秒前
含蓄冰彤发布了新的文献求助10
5秒前
orixero应助合适诗蕾采纳,获得10
5秒前
Owen应助欢喜的梦旋采纳,获得10
6秒前
7秒前
友好晓蓝完成签到,获得积分10
7秒前
光亮蜗牛完成签到,获得积分10
7秒前
8秒前
TT发布了新的文献求助50
8秒前
8秒前
MP应助sunshine采纳,获得30
8秒前
8秒前
8秒前
博远发布了新的文献求助10
8秒前
8秒前
执着的傲蕾完成签到 ,获得积分10
9秒前
充电小子发布了新的文献求助10
9秒前
道天发布了新的文献求助10
9秒前
初景发布了新的文献求助10
9秒前
9秒前
9秒前
9秒前
听着风吹啊完成签到,获得积分10
10秒前
情怀应助chigga采纳,获得10
10秒前
晴晴晴发布了新的文献求助10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Picture this! Including first nations fiction picture books in school library collections 2000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1500
Cowries - A Guide to the Gastropod Family Cypraeidae 1200
ON THE THEORY OF BIRATIONAL BLOWING-UP 666
Signals, Systems, and Signal Processing 610
“美军军官队伍建设研究”系列(全册) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6386273
求助须知:如何正确求助?哪些是违规求助? 8199908
关于积分的说明 17346612
捐赠科研通 5439973
什么是DOI,文献DOI怎么找? 2876832
邀请新用户注册赠送积分活动 1853261
关于科研通互助平台的介绍 1697349