id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-010640-s1oqphvn	Baral, Prabin	In-silico identification of the vaccine candidate epitopes against the Lassa virus hemorrhagic fever	2020-05-06		.txt	text/plain	4835	276	51	In an effort to discover new LASV vaccines, we employ several sequence-based computational prediction tools to identify LASV GP major histocompatibility complex (MHC) class I and II T-cell epitopes. In this study, we have identified and characterized T and B-cell epitopes for the LASV GP using different sequence and structure-based computational epitope prediction methods. MHC-I T-cell epitope prediction with the LASV GP sequence was performed using three different methods separately: ProPred-1, CTLPred, and NetCTL1.2, and the results are shown in Supplementary Table S1. MHC-II T-cell epitope prediction with the LASV GP sequence was performed using three different methods separately: ProPred, NetMHCII 2.3, and EpiTOP 3.0, and the results are shown in Supplementary Table S2 . Docking of the four consensus MHC-I epitopes (Table 1 ) was performed using Autodock Vina, which enabled the docking of epitopes obtained from the sequence-based MHC-1 T-cell prediction into the promising allele structures.	./cache/cord-010640-s1oqphvn.txt	./txt/cord-010640-s1oqphvn.txt