همایش ملی بیوانفورماتیک ایران

صفحه اصلی / 4th international edition and 13th Iranian Conference on Bioinformatics

Insilico study of CD4+ T cells epitopes in ORF1ab protein of SARS-COV-2 for Iranian common MHCII alleles

نویسندگان :

Fatemeh Hajighasem¹ Atefeh Shirkavand²

1- Department of Immunology, Faculty of Medicine, Shahed University, Tehran, Iran 2- Medical Biotechnology Division, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran

کلمات کلیدی :

insilico،SARS-COV-2،epitopes،CD4+ T cells

چکیده :

Introduction: WHO pronounced the corona virus epidemic on January 20, 2020. SARS-COV-2 (as a member of coronavirus family) causes breathing problems in humans. Several vaccines have been produced against SARS-COV-2. However up to now no very safe and high efficient vaccine has been existing. ORF1ab is the main open reading frame of SARS-COV-2. Cell mediated immunity has an important role in defense against corona virus. In this study, CD4+ T cells specific epitopes located on ORF1ab protein of SARS-COV-2 virus for common MHC II alleles in Iranian population, were determined by computational immunology. Methods: The amino acid sequence of ORF1ab protein from SARS-COV-2 virus was got using NCBI database. The most abundant MHC II alleles in the Iranian population were determined by allele frequency net database and the specific epitopes of CD4+ T lymphocytes (connected to MHC II alleles) were predicted by NETMHCPan software. Results: In this study, 1610 CD4+ T cells specific epitopes located on ORF1ab protein of SARS-COV-2 for Iranian common MHC II alleles were predicted by computational immunology. Conclusions: In present study, a lot of CD4+ T cells specific epitopes on ORF1ab protein of SARS-COV-2 for Iranian common MHCII alleles were recognized. Additional studies for recognition of epitopes which induce robust immune response to make effective anti- SARS-COV-2 vaccines are necessary.

لیست مقالات

لیست مقالات بایگانی شده

Exploring the anti-inflammatory potential of the silymarin against IL-17A: in silico molecular docking

Tooba Abdizadeh

Graphene Oxide Nanosheets as Drug Carriers for Erdafitinib in a Targeted Drug Delivery System: A Cutting-Edge Approach to Cancer Therapy

Hooriye Yahyaei - Nahid Shajari - Amirreza Saeni - Ahmadreza Saeni

Combination therapy synergism prediction for virus treatment using machine learning models

Shayan Majidifar - Arash Zabihian - Mohsen Hooshmand

Comprehensive Analysis of DCLK Family Kinases in Gastrointestinal Cancers and Neoplastic Progression

Zahra Salehi - Leili Rejali - Moein Piroozkhah - Pooya Jalali - Ali Aghajani - Mahsa Saeedi Niyasar - Binazir Khanabadi - Amir Sadeghi - Ehsan Nazemalhossein Mojarad

Leveraging Machine Learning Models for Virtual Screening of ZINC Database to Identify JAK1 Inhibitors

Negar Abdolmaleki - Hamid Mahdiuni

DTMP-Prime: A Deep Transformer-based Model for Predicting Prime Editing Efficiency and PegRNA Activity

Roghayyeh Alipanahi - Leila Safari - Alireza Khanteymoori

Tailoring Stability of Keratinocyte Growth Factor Variants for Effective Wound Healing in Acidic Conditions

Mansoureh Shahbazi Dastjerdeh - Mohammadtaghi Borjian Boroujeni

A New Method in Analyzing Drug-Drug Interaction Using Artificial Intelligence: Combination of Channel and Spatial Maps in Deep Attention Networks

Seyed Vahab Shojaedini - AmirReza Moeini

Bioinformatics Analysis of Prostate Cancer by the Construction of circRNA-miRNA-mRNA Regulatory Network

Fatemeh Zamani - Ali Taravati

Drug repurposing using bulk RNA-seq based on key genes involved in inflammatory bowel disease

Nayereh Abdali - Shahram Tahmasebian - Atena Vaghf

بیشتر