Vaxi-DL: A web-based deep learning server to identify potential vaccine candidates

Rawal, Kamal; Sinha, Robin; Nath, Swarsat Kaushik; Preeti, P.; Kumari, Priya; Gupta, Sandeep K.; Sharma, Trapti; Strych, Ulrich; Hotez, Peter J.; Bottazzi, María Elena

doi:10.1016/j.compbiomed.2022.105401

Cited by 18 publications

(17 citation statements)

References 35 publications

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“…Vax-DL is a computational method that reveals potential vaccine candidates. 19 Rawal, Kamal, et al The production of a novel vaccination is a difficult process that includes computational analyses, experimental work, and animal investigations, all of which are followed by clinical trials. In silico screening is commonly used for antigen identification to speed up the process.…”

Section: Results Obtained For Thementioning

confidence: 99%

Evaluation of LigA as a potential vaccine candidate using computational tools

Angaleshwari¹,

Dixit²,

Preeti³

et al. 2022

Preprint

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Leptospirosis vaccine candidates still need to be identified, which was a challenge. One such candidate, however, is OmpL37, a potential surface-exposed antigen with the highest elastin-binding capacity yet observed, indicating that it likely contributes significantly to host colonization. Cell viability is frequently evaluated using high throughput metabolic viability assays like MTT and MTS. Utilizing genomic, proteomic data, and computational methods, particularly deep learning systems, can be crucial in identifying vaccine targets. A new computational method for identifying and evaluating novel vaccination targets, which paves the way for the creation of a multi-epitope subunit vaccine candidate was using Vax-Elan. In order to uncover prospective vaccine candidates, the system screens genomic and proteomic datasets of multiple diseases, including leptospirosis species, using reverse vaccination and immuno-informatics. It uses supervised machine learning-based methods for vaccine discovery and an immuno-informatics approach. To computationally analyze and assess the pathogenic proteomes that were developed followed by narrowing down proteins that exhibit particular traits in order to rank them as prospective vaccination candidates. In this study, we developed new leptospirosis vaccine targets. Where the protein sequence of ligA [Id-ach98094.1] was extracted from the NCBI protein database. And the predicted amino acid sequence for LigA is a set of 90-amino-acid tandem repeats encoded by a 3,675-bp open reading frame. By using the Vax-Elan server to evaluate important properties, to check the suitability of this protein as a potential vaccine candidate. As per VaxElan, the protein is predicted to be 1 for Target p, if it is a signal peptide ligA is predicted to be a signal peptide and hence scored 1 as being a signal peptide is a criterion for a potential vaccine candidate. In the case of mTP and cTP, VaxElan gives a score of 0 and for 1TP VaxElan gives 0.05 which is followed by various research studies.

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Section: Results Obtained For Thementioning

confidence: 99%

Evaluation of LigA as a potential vaccine candidate using computational tools

Angaleshwari¹,

Dixit²,

Preeti³

et al. 2022

Preprint

Self Cite

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“…The first part had 170 equally weighted examples as used during training and 30 examples were used in testing or cross validation purposes. Our group has recently deployed a user-friendly cloud-based Vaxi-DL server for potential vaccine prediction ( Rawal et al, 2022 ).…”

Section: Methodsmentioning

confidence: 99%

Identification of vaccine targets & design of vaccine against SARS-CoV-2 coronavirus using computational and deep learning-based approaches

Abbasi¹,

Saraf²,

Sharma³

et al. 2022

PeerJ

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An unusual pneumonia infection, named COVID-19, was reported on December 2019 in China. It was reported to be caused by a novel coronavirus which has infected approximately 220 million people worldwide with a death toll of 4.5 million as of September 2021. This study is focused on finding potential vaccine candidates and designing an in-silico subunit multi-epitope vaccine candidates using a unique computational pipeline, integrating reverse vaccinology, molecular docking and simulation methods. A protein named spike protein of SARS-CoV-2 with the GenBank ID QHD43416.1 was shortlisted as a potential vaccine candidate and was examined for presence of B-cell and T-cell epitopes. We also investigated antigenicity and interaction with distinct polymorphic alleles of the epitopes. High ranking epitopes such as DLCFTNVY (B cell epitope), KIADYNKL (MHC Class-I) and VKNKCVNFN (MHC class-II) were shortlisted for subsequent analysis. Digestion analysis verified the safety and stability of the shortlisted peptides. Docking study reported a strong binding of proposed peptides with HLA-A*02 and HLA-B7 alleles. We used standard methods to construct vaccine model and this construct was evaluated further for its antigenicity, physicochemical properties, 2D and 3D structure prediction and validation. Further, molecular docking followed by molecular dynamics simulation was performed to evaluate the binding affinity and stability of TLR-4 and vaccine complex. Finally, the vaccine construct was reverse transcribed and adapted for E. coli strain K 12 prior to the insertion within the pET-28-a (+) vector for determining translational and microbial expression followed by conservancy analysis. Also, six multi-epitope subunit vaccines were constructed using different strategies containing immunogenic epitopes, appropriate adjuvants and linker sequences. We propose that our vaccine constructs can be used for downstream investigations using in-vitro and in-vivo studies to design effective and safe vaccine against different strains of COVID-19.

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“…Here, we are using computational tools Vaxi-DL and VaxELAN to analyze a potential vaccine candidate i.e, N-acetylmuramoyl-L-alanine amidase as identified by Vaxign program [4]. VaxELAN which helps a researcher to determine and examine the potential vaccine candidates using their genomic and proteomic information [5,6,8]. Here, we were able to analyze PVC i.e., N-acetylmuramoyl-L-alanine amidase for development of vaccine against IPSID (Immuno proliferative small intestine disease) which was selected as a PVC by vaxign program [4], with the help of Vaxi-DL and VaxELAN [5,6] in terms of adhesion, secretory nature, trans-membrane helices, cleavage sites, MHC-I binding, CTL epitope prediction, essential genes, molecular weight, non-bacterial pathogen, non-homology with human genome, virulence factors, allergenicity, cellular localization and probability of being a PVC.…”

Section: Symptoms and Diagnosismentioning

confidence: 99%

“…VaxELAN which helps a researcher to determine and examine the potential vaccine candidates using their genomic and proteomic information [5,6,8]. Here, we were able to analyze PVC i.e., N-acetylmuramoyl-L-alanine amidase for development of vaccine against IPSID (Immuno proliferative small intestine disease) which was selected as a PVC by vaxign program [4], with the help of Vaxi-DL and VaxELAN [5,6] in terms of adhesion, secretory nature, trans-membrane helices, cleavage sites, MHC-I binding, CTL epitope prediction, essential genes, molecular weight, non-bacterial pathogen, non-homology with human genome, virulence factors, allergenicity, cellular localization and probability of being a PVC. IPSID is a disease emerging from the low socio-economic background areas such as in mediterranean regions and later spread as sporadic cases increased in European and American countries [1].…”

Section: Symptoms and Diagnosismentioning

confidence: 99%

N-acetylmuramoyl-L-alanine amidase : A competent vaccine candidate against IPSID

sabikhi¹,

Surabhi²,

Dixit³

et al. 2022

Preprint

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Immunoproliferative small intestine disease (IPSID) is a collective name for a range of diseases caused by various microorganisms but the major and persistent organism is Campylobacter Jejuni. IPSID can lead to minor symptoms like diarrhea, nausea, imbalance of electrolytes in the body etc. to major consequences that may lead to death in case of prolonged untreated condition. IPSID leads to infiltration of lymphocytes as a consequence of an immune response to invasion by microbes, which eventually leads to the evolvement of IgA producing bodies and to the selection of a body that produces α heavy chains. Hence, it is also called “α- Heavy chain disease”. Until now there has been no successful development of a vaccine for this disease. N-acetylmuramoyl-L-alanine amidase is one of the proteins in Campylobacter Jejuni ssp. Jejuni which is also a Potential vaccine candidate (PVC) against IPSID as identified by Vaxigen. Here, we are utilizing deep learning softwares i.e, Vaxi-DL and VaxELAN for analyzing the given protein in terms of adhesion, secretory nature, trans-membrane helices, cleavage sites, MHC-I binding, CTL epitope prediction, essential genes, molecular weight, non-bacterial pathogen, non-homology with human genome, virulence factors, allergenicity, cellular localization and probability of being a PVC.

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Vaxi-DL: A web-based deep learning server to identify potential vaccine candidates

Cited by 18 publications

References 35 publications

Evaluation of LigA as a potential vaccine candidate using computational tools

Evaluation of LigA as a potential vaccine candidate using computational tools

Identification of vaccine targets & design of vaccine against SARS-CoV-2 coronavirus using computational and deep learning-based approaches

N-acetylmuramoyl-L-alanine amidase : A competent vaccine candidate against IPSID

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