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 [Informa]
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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。
建议保存本图,每天支付宝扫一扫(相册选取)领红包
实时播报
刚刚
222完成签到,获得积分10
2秒前
叶子完成签到 ,获得积分10
3秒前
4秒前
不安的可乐完成签到,获得积分10
5秒前
Soda8513完成签到,获得积分10
6秒前
11秒前
14秒前
yyy111完成签到,获得积分20
17秒前
ColinWine完成签到 ,获得积分10
17秒前
UniTTEC9560完成签到,获得积分10
21秒前
yyy111发布了新的文献求助10
21秒前
lucia5354完成签到,获得积分10
21秒前
邱佩群完成签到 ,获得积分10
22秒前
22秒前
Bingo完成签到,获得积分10
24秒前
Chong完成签到,获得积分10
24秒前
渺渺完成签到 ,获得积分10
26秒前
浮游应助阜睿采纳,获得10
26秒前
奕妘完成签到,获得积分10
31秒前
Cyber_relic完成签到,获得积分10
32秒前
ZXD1989完成签到 ,获得积分10
32秒前
李宗洋完成签到,获得积分10
33秒前
无语的翠柏完成签到,获得积分10
35秒前
沙克几十块完成签到,获得积分0
36秒前
午盏完成签到 ,获得积分10
37秒前
maxthon完成签到,获得积分10
38秒前
39秒前
adamchris完成签到,获得积分10
40秒前
xiekunwhy完成签到,获得积分10
51秒前
清风徐来完成签到 ,获得积分10
54秒前
wuta完成签到,获得积分10
55秒前
土土完成签到,获得积分10
55秒前
adeno完成签到,获得积分10
55秒前
56秒前
56秒前
天真醉波完成签到 ,获得积分10
56秒前
Muran完成签到,获得积分10
59秒前
Pepsi完成签到 ,获得积分10
1分钟前
Muncy完成签到 ,获得积分10
1分钟前
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
List of 1,091 Public Pension Profiles by Region 1541
Binary Alloy Phase Diagrams, 2nd Edition 600
Atlas of Liver Pathology: A Pattern-Based Approach 500
A Technologist’s Guide to Performing Sleep Studies 500
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
Using Genomics to Understand How Invaders May Adapt: A Marine Perspective 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5498687
求助须知:如何正确求助?哪些是违规求助? 4595838
关于积分的说明 14450057
捐赠科研通 4528831
什么是DOI,文献DOI怎么找? 2481735
邀请新用户注册赠送积分活动 1465732
关于科研通互助平台的介绍 1438581