Immunoinformatics Approach for Multiepitopes Vaccine Prediction against Glycoprotein B of Avian Infectious Laryngotracheitis Virus

Pendekatan Imunoinformatika untuk Prediksi Vaksin Multiepitop terhadap Glikoprotein B Virus Laringotrakeitis Infeksius Unggas

Clicks: 402
ID: 7718
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #6 of 78 articles by views in advances in bioinformatics

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Infectious laryngotracheitis virus (ILTV) is a gallid herpesvirus type 1, a member of the genus Iltovirus. It causes an infection in the upper respiratory tract mainly trachea which results in significant economic losses in the poultry industry worldwide. Vaccination against ILTV produced latent infected carriers’ birds, which become a source of virus transmission to nonvaccinated flocks. Thus this study aimed to design safe multiepitopes vaccine against glycoprotein B of ILT virus using immunoinformatic tools. Forty-four sequences of complete envelope glycoprotein B were retrieved from GenBank of National Center for Biotechnology Information (NCBI) and aligned for conservancy by multiple sequence alignment (MSA). Immune Epitope Database (IEDB) analysis resources were used to predict and analyze candidate epitopes that could act as a promising peptide vaccine. For B cell epitopes, thirty-one linear epitopes were predicted using Bepipred. However eight epitopes were found to be on both surface and antigenic epitopes using Emini surface accessibility and antigenicity, respectively. Three epitopes (190KKLP193, 386YSSTHVRS393, and 317KESV320) were proposed as B cell epitopes. For T cells several epitopes were interacted with MHC class I with high affinity and specificity, but the best recognized epitopes were 118YVFNVTLYY126, 335VSYKNSYHF343, and 622YLLYEDYTF630. MHC-II binding epitopes, 301FLTDEQFTI309,277FLEIANYQV285, and 743IASFLSNPF751, were proposed as promising epitopes due to their high affinity for MHC-II molecules. Moreover the docked ligand epitopes from MHC-1 molecule exhibited high binding affinity with the receptors; BF chicken alleles (BF2 2101 and 0401) expressed by the lower global energy of the molecules. In this study nine epitopes were predicted as promising vaccine candidate against ILTV. In vivo and in vitro studies are required to support the effectiveness of these predicted epitopes as a multipeptide vaccine through clinical trials.
Virus laringotrakeitis infeksius (*infectious laryngotracheitis virus* atau ILTV) merupakan herpesvirus gallid tipe 1, anggota dari genus *Iltovirus*. Virus ini menyebabkan infeksi pada saluran pernapasan bagian atas, terutama trakea, yang mengakibatkan kerugian ekonomi signifikan dalam industri perunggasan di seluruh dunia. Vaksinasi terhadap ILTV menghasilkan unggas pembawa (*carrier*) terinfeksi laten, yang menjadi sumber penularan virus ke kawanan unggas yang tidak divaksinasi. Oleh karena itu, penelitian ini bertujuan untuk merancang vaksin multiepitop yang aman terhadap glikoprotein B virus ILT menggunakan perangkat imunoinformatika. Empat puluh empat sekuens lengkap glikoprotein B selubung diperoleh dari GenBank National Center for Biotechnology Information (NCBI) dan disejajarkan untuk analisis kekonservasian menggunakan penyejajaran sekuens berganda (*multiple sequence alignment* atau MSA). Sumber daya analisis Immune Epitope Database (IEDB) digunakan untuk memprediksi dan menganalisis kandidat epitop yang berpotensi sebagai vaksin peptida yang menjanjikan. Untuk epitop sel B, tiga puluh satu epitop linier diprediksi menggunakan Bepipred. Namun, delapan epitop ditemukan berada pada permukaan sekaligus bersifat antigenik, masing-masing dievaluasi menggunakan aksesibilitas permukaan Emini dan antigenisitas. Tiga epitop (190KKLP193, 386YSSTHVRS393, dan 317KESV320) diusulkan sebagai epitop sel B. Untuk sel T, beberapa epitop berinteraksi dengan MHC kelas I dengan afinitas dan spesifisitas tinggi, tetapi epitop yang paling baik dikenali adalah 118YVFNVTLYY126, 335VSYKNSYHF343, dan 622YLLYEDYTF630. Epitop pengikat MHC-II, yaitu 301FLTDEQFTI309, 277FLEIANYQV285, dan 743IASFLSNPF751, diusulkan sebagai epitop yang menjanjikan karena memiliki afinitas tinggi terhadap molekul MHC-II. Selain itu, ligan epitop tertambat dari molekul MHC-I menunjukkan afinitas pengikatan yang tinggi dengan reseptor; alel BF ayam (BF2 2101 dan 0401) yang ditunjukkan oleh energi global molekul yang lebih rendah. Dalam penelitian ini, sembilan epitop diprediksi sebagai kandidat vaksin yang menjanjikan terhadap ILTV. Studi *in vivo* dan *in vitro* diperlukan untuk mendukung efektivitas epitop-epitop yang diprediksi ini sebagai vaksin multipeptida melalui uji klinis.
Reference Key
a2019immunoinformaticsadvances Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ali, Sumaia A.;Almofti, Yassir A.;Abd-elrahman, Khoubieb A.;Ali, Sumaia A.;Almofti, Yassir A.;Abd-elrahman, Khoubieb A.;
Journal advances in bioinformatics
Year 2019
DOI
10.1155/2019/1270485
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.