vaccines and immunoinformatics approaches

Joint epitope selection and spacer design for string-of-beads vaccines

This paper presents a computational method that jointly selects epitopes and designs spacers for string-of-beads vaccines to improve immunogenicity and processing efficiency.

COVIEdb: A database for potential immune epitopes of coronaviruses

The paper predicts potential B/T-cell epitopes for multiple coronaviruses and stores the results in a database for vaccine development.

EpiDope: A Deep neural network for linear B-cell epitope prediction

EpiDope uses a deep neural network to predict linear B-cell epitopes with higher accuracy than existing tools, reducing laboratory costs and time.

Designing of Epitope-Based Vaccine from the Conserved Region of the Spike Glycoprotein of SARS-CoV-2

This study predicts a novel T cell epitope from the conserved spike glycoprotein of SARS-CoV-2 for an epitope-based vaccine using in-silico methods.

EPIP: MHC-I epitope prediction integrating mass spectrometry derived motifs and tissue-specific expression profiles

EPIP predicts MHC-I epitope presentation by integrating mass spectrometry-derived motifs and tissue-specific RNA-seq data, outperforming existing methods in independent validation.

Sequence-based prediction of vaccine targets for inducing T cell responses to SARS-CoV-2 utilizing the bioinformatics predictor RECON

This paper uses RECON to predict SARS-CoV-2 T cell epitopes for HLA-I and HLA-II alleles, identifying candidate peptides with broad population coverage.

Immuno-informatics approach for multi-epitope vaccine designing against SARS-CoV-2

This paper designs a multi-epitope vaccine against SARS-CoV-2 using immuno-informatics, showing it is stable, non-allergic, and antigenic with strong immune responses.

proABC-2: PRediction Of AntiBody Contacts v2 and its application to information-driven docking

proABC-2 predicts antibody-antigen contacts using a convolutional neural network and integrates with HADDOCK for docking.

COVID-19 coronavirus vaccine design using reverse vaccinology and machine learning

The paper predicts COVID-19 vaccine candidates using reverse vaccinology and machine learning, identifying the N and nsp3 proteins as potential targets.

Identification of peptide candidate against COVID-19 through reverse vaccinology: An immunoinformatics approach

The paper identifies a potential peptide vaccine candidate against COVID-19 using immunoinformatics by predicting a 9-mer peptide with B-cell and T-cell epitopes and favorable properties.

An in-silico based clinical insight on the effect of noticeable CD4 conserved residues of SARS-CoV-2 on the CD4-MHC-I interactions

The paper compares CD4-MHC-II interactions between SARS-CoV-2 RBD and HIV-1 Env gp120, finding HIV-1 has higher binding affinity and more salt bridge formations.

Structural basis to design multi-epitope vaccines against Novel Coronavirus 19 (COVID19) infection, the ongoing pandemic emergency: an in silico approach

This paper designs two multi-epitope vaccines against SARS-CoV-2 using in silico methods, validated for stability and immune response potential.

COVIDep platform for real-time reporting of vaccine target recommendations for SARS-CoV-2: Description and connections with COVID-19 immune responses and preclinical vaccine trials

The paper introduces a web-based platform called COVIDep that provides immune target recommendations for SARS-CoV-2 vaccine development by integrating genetic and epitope data.

Immuno-informatics Characterization SARS-CoV-2 Spike Glycoprotein for Prioritization of Epitope based Multivalent Peptide Vaccine

The paper uses immune-informatics to identify B and T cell epitopes from SARS-CoV-2 spike glycoprotein and designs a multi-epitope peptide vaccine construct that shows strong immune response and stability with TLR3.

Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach

This study designs a multi-epitope peptide vaccine against SARS-CoV-2 using immunoinformatics tools, identifying three epitopes with high binding affinity and global population coverage.

Bio-informed Protein Sequence Generation for Multi-class Virus Mutation Prediction

This paper introduces a GAN-based model to generate protein sequences for predicting virus mutations across multiple classes.

In silico multi-epitope vaccine against covid19 showing effective interaction with HLA-B*15:03

This paper designs an in silico multi-epitope vaccine against SARS-CoV-2 that interacts with HLA-B*15:03, showing potential for cross-protection against SARS and MERS.

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation

The paper introduces CAMAP, an artificial neural network that predicts MHC-I peptide presentation by analyzing codon arrangement in mRNA sequences, improving prediction accuracy beyond traditional methods.

Epitope-Based Peptide Vaccine Against Severe Acute Respiratory Syndrome-Coronavirus-2 Nucleocapsid Protein: An in silico Approach

The paper identifies an immunogenic epitope for a peptide vaccine against SARS-CoV-2 N protein using in silico methods and phylogenetic analysis.

EpitoCore: mining conserved epitope vaccine candidates in the core proteome of multiple bacteria strains

EpitoCore identifies conserved epitopes in bacterial core proteomes across multiple strains to prioritize vaccine candidates.

Improved prediction of MHC II antigen presentation throughintegration and motif deconvolution of mass spectrometryMHC eluted ligand data

The paper improves MHC II epitope prediction by integrating mass spectrometry data with a new machine learning framework, achieving better performance than existing methods.

Identification of potential vaccine candidates against SARS-CoV-2, A step forward to fight COVID-19: A Reverse Vaccinology Approach

This study identifies a potential SARS-CoV-2 antigenic peptide using reverse vaccinology, showing high conservation and predicted MHC interaction for vaccine development.

ProGeo-neo: a Customized Proteogenomic Workflow for Neoantigen Prediction and Selection

ProGeo-neo integrates genomic and proteomic data to improve neoantigen prediction by incorporating mass spectrometry validation and MHC binding prediction.

In silico approach for designing of a multi-epitope based vaccine against novel Coronavirus (SARS-COV-2)

This study designs a multi-epitope vaccine against SARS-COV-2 using computational methods, identifying immunogenic epitopes and validating the vaccine construct's safety and immunogenicity through in silico analysis.

Towards a Chimeric Vaccine against Multiple Isolates of Mycobacteroides - An Integrative Approach

The paper identifies a chimeric vaccine construct, V6, against Mycobacteroides through genomic and proteomic analysis, epitope prediction, and molecular docking.

immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking

immuneSIM simulates B- and T-cell receptor repertoires with tunable features to benchmark immunoinformatics tools.

Multi-epitope vaccine design using an immunoinformatics approach for 2019 novel coronavirus (SARS-CoV-2)

This paper designs multi-epitope peptide vaccines against SARS-CoV-2 using immunoinformatics, showing they elicit strong humoral and cellular immune responses in mice.

Structural Basis and Designing of Peptide Vaccine using PE-PGRS Family Protein of Mycobacterium ulcerans - An Integrated Vaccinomics Approach

The paper designs a multi-epitope peptide vaccine against Mycobacterium ulcerans using vaccinomics, showing strong TLR2 binding and potential immune responses.

A 3D structural affinity model for multi-epitope in silico germinal center simulations

This paper introduces a 3D structural model for simulating germinal center responses to multi-epitope vaccines, showing that epitope cocktails enhance cross-reactive antibody development.

Preliminary identification of potential vaccine targets for the COVID-19 coronavirus (SARS-CoV-2) based on SARS-CoV immunological studies

This study identifies conserved B and T cell epitopes between SARS-CoV and SARS-CoV-2 to guide vaccine development against the novel coronavirus.