Data on the cytotoxic T lymphocyte epitopes identified from the SARS-CoV-2 isolated in India

This fileset consists of the following datasets: <b>18670_NetCTLpan.xls </b>in xls file format <b>epitope_immunogenicity_score.txt</b> in .txt file format <b>NetCTLpan_out_sorted.txt</b> in .txt file format The zipped folder <b>BatchPeptideMatch-202003311256376185117084.zip </b>contains the following datasets: <b>log.txt</b> in .txt file format <b>perPeptideMatchDetails.txt</b> in .txt file format <b>139 .txt files</b> contained within the folder “<b>PerPeptideMatchResults</b>” The <b>3 zipped folders HPEPDOCK_results_3kps.tar.gz</b>, <b>HPEPDOCK_results_6at5.tar.gz</b> and <b>HPEPDOCK_results_6o9c.tar.gz</b>, each contain <b>101 data files</b> in <b>.pdb file format</b>.<br> Dataset <b>18670_NetCTLpan.xls </b>contains data on<b> </b>the cytotoxic T lymphocyte epitopes identified from the SARS-CoV-2 isolated in India as predicted by NetCTLpan. Dataset <b>epitope_immunogenicity_score.txt </b>contains the immunogenicity scores of all the predicted epitopes, after these were subjected to the Immune Epitope Database (IEDB) immunogenicity tool.Dataset <b>NetCTLpan_out_sorted.txt </b>contains the<b> </b>NetCTLpan predictions for the HLA-A*03:01 allele.<br> Datasets <b>log.txt </b>and the<b> 139 .txt </b>files contained within the folder “<b>PerPeptideMatchResults</b>”, contain data from the peptide matching step, that was performed on sequence dataset ‘UniProtKB release 2020_01 plus isoforms | SwissProt | Isoform’ with target organism set as ‘Homo sapiens [9606]’. <b>.pdb</b> files contained in the three zipped folders <b>HPEPDOCK_results_3kps.tar.gz</b>, <b>HPEPDOCK_results_6at5.tar.gz</b> and <b>HPEPDOCK_results_6o9c.tar.gz: </b>To further confirm the candidacy of the foreign epitopes as a vaccine, the top three foreign epitopes based on immunogenicity scores were subjected to molecular docking studies to confirm their interactions with the specified HLA at the peptide-binding groove. The molecular docking of the peptide epitope with the HLA structure was performed using HPEPDOCK Server. Each of the zipped folders therefore contains the results of the molecular docking studies using HPEPDOCK Server for the top three vaccine candidates (3kps, 6at5 and 6o9c). <br> <b>Study aims and methodology: </b>This study aimed to identify cytotoxic T cell (CTL) epitopes of SARS-CoV-2 Indian isolate for designing potential vaccine candidates which are effective on Indian population using an <i>in-silico </i>approach. The authors predicted the CTL epitopes for all those human leukocyte antigen supertypes (HLA) which have high allelic frequently in Indian population. Additionally, they further studied the immunogenicity, foreignness, and interactions between the epitopes and the HLA molecules by the means of molecular docking studies. The amino acid sequence of the complete genome of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolate of India (MT050493.1) with 9950 AA was retrieved from NCBI. NetCTLpan version 1.1 was used to predict the CTL epitopes across the proteins coded by the SARS-CoV-2 Indian isolate. All the predicted epitopes were subjected to the Immune Epitope Database (IEDB) immunogenicity tool to predict their immunogenicity score.<b></b> To filter out the vaccine candidates which are foreign to the human body, all the epitopes that showed positive immunogenicity, were subjected to Multiple Peptide Match tool against human reference proteome. To further confirm the candidacy of the foreign epitopes as a vaccine, the top three foreign epitopes based on immunogenicity scores were subjected to molecular docking studies to confirm their interactions with the specified HLA at the peptide-binding groove. The molecular docking of the peptide epitope with the HLA structure was performed using the HPEPDOCK Server. For more details on the methodology, please read the published article. <br>

本数据集组包含以下文件：格式为XLS的<b>18670_NetCTLpan.xls</b>、格式为TXT的<b>epitope_immunogenicity_score.txt</b>与<b>NetCTLpan_out_sorted.txt</b>。压缩文件夹<b>BatchPeptideMatch-202003311256376185117084.zip</b>内含以下数据集：格式为TXT的<b>log.txt</b>与<b>perPeptideMatchDetails.txt</b>，以及位于“<b>PerPeptideMatchResults</b>”文件夹内的139个TXT文件。3个压缩文件夹<b>HPEPDOCK_results_3kps.tar.gz</b>、<b>HPEPDOCK_results_6at5.tar.gz</b>与<b>HPEPDOCK_results_6o9c.tar.gz</b>各自内含101个格式为PDB的数据文件。

<b>18670_NetCTLpan.xls</b>包含由NetCTLpan预测得到的、从印度分离的严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）中鉴定出的细胞毒性T淋巴细胞（cytotoxic T lymphocyte, CTL）表位相关数据。<b>epitope_immunogenicity_score.txt</b>包含所有预测表位经免疫表位数据库（Immune Epitope Database, IEDB）免疫原性工具分析后得到的免疫原性得分。<b>NetCTLpan_out_sorted.txt</b>包含针对HLA-A*03:01等位基因的NetCTLpan预测结果。

<b>log.txt</b>与“PerPeptideMatchResults”文件夹内的139个TXT文件，包含针对序列数据集“UniProtKB release 2020_01 plus isoforms | SwissProt | Isoform”、以智人（Homo sapiens [9606]）为目标生物进行肽段匹配步骤所得的数据。

上述3个HPEPDOCK结果压缩文件夹内的PDB文件相关说明：为进一步验证外源表位作为疫苗候选的潜力，研究人员选取免疫原性得分前三的外源表位进行分子对接实验，以验证其在肽结合槽与指定人类白细胞抗原（human leukocyte antigen, HLA）分子的相互作用。本研究通过HPEPDOCK服务器完成肽表位与HLA结构的分子对接，因此每个压缩文件夹均包含针对3个候选疫苗（3kps、6at5与6o9c）的HPEPDOCK服务器分子对接实验结果。

<b>研究目标与方法</b>：本研究旨在通过计算机模拟（in-silico）方法，鉴定印度分离株SARS-CoV-2的细胞毒性T细胞表位，以设计针对印度人群的潜在疫苗候选物。研究人员针对印度人群等位基因频率较高的所有HLA超型预测CTL表位。此外，研究人员还通过分子对接实验分析了表位的免疫原性、外源性以及表位与HLA分子间的相互作用。
研究人员从NCBI数据库获取了印度分离株SARS-CoV-2（登录号MT050493.1）的完整基因组氨基酸序列，该序列全长9950个氨基酸。使用NetCTLpan 1.1版本预测该印度分离株编码蛋白的全部CTL表位。将所有预测得到的表位提交至IEDB免疫原性工具，以预测其免疫原性得分。
为筛选出对人体而言的外源疫苗候选物，研究人员将所有免疫原性为阳性的表位提交至多重肽段匹配工具，与人类参考蛋白质组进行比对。为进一步验证外源表位作为疫苗候选的潜力，研究人员选取免疫原性得分前三的外源表位进行分子对接实验，以验证其在肽结合槽与指定HLA分子的相互作用。本研究通过HPEPDOCK服务器完成肽表位与HLA结构的分子对接。如需了解方法细节，请查阅已发表的相关论文。