Weighted lambda superstrings applied to vaccine design

Martínez, Luis; Milanič, Martin; Malaina, Iker; Alvarez, Carmen; Pérez, María Jesús Fuente; Fuente, Ildefonso M. De la

doi:10.1371/journal.pone.0211714

Cited by 9 publications

(12 citation statements)

References 50 publications

(68 reference statements)

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“…Given two sets and of strings, called host strings and target strings, respectively, and given a mapping , we say that a string is a weighted λ–superstring 21 if, for every , the inequality holds, where is the set of common substrings of and .…”

Section: Methodsmentioning

confidence: 99%

“…The concept of λ-superstring was generalized in our subsequent publication 21 to that of a weighted λ-superstring by allowing the epitopes to be weighted by estimations of their immunogenicities. This generalization entails an important improvement in the applications to vaccine design 22 , as this consideration of an epitope’s immunogenicity more closely models biological and medical practice and increases the likelihood that the obtained CVs are effective.…”

Section: Introductionmentioning

confidence: 99%

“…To address this issue, we used two combined methods in the development of COVID-19 peptide-based vaccines. First, a computational technique that uses advanced tools of artificial intelligence to design the best immunogenic epitopes 20 , 21 . Second, subcutaneous inoculation of DC vaccine platforms loaded with these peptides to test the delayed type hypersensitivity (DTH) reactions in mice, as an in vivo measurement of cellular immune responses that provides easy preparation for the clinic 22 .…”

Section: Introductionmentioning

confidence: 99%

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First computational design using lambda-superstrings and in vivo validation of SARS-CoV-2 vaccine

Martínez

Malaina

Salcines-Cuevas

et al. 2022

Sci Rep

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Coronavirus disease 2019 (COVID-19) is the greatest threat to global health at the present time, and considerable public and private effort is being devoted to fighting this recently emerged disease. Despite the undoubted advances in the development of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, uncertainty remains about their future efficacy and the duration of the immunity induced. It is therefore prudent to continue designing and testing vaccines against this pathogen. In this article we computationally designed two candidate vaccines, one monopeptide and one multipeptide, using a technique involving optimizing lambda-superstrings, which was introduced and developed by our research group. We tested the monopeptide vaccine, thus establishing a proof of concept for the validity of the technique. We synthesized a peptide of 22 amino acids in length, corresponding to one of the candidate vaccines, and prepared a dendritic cell (DC) vaccine vector loaded with the 22 amino acids SARS-CoV-2 peptide (positions 50-71) contained in the NTD domain (DC-CoVPSA) of the Spike protein. Next, we tested the immunogenicity, the type of immune response elicited, and the cytokine profile induced by the vaccine, using a non-related bacterial peptide as negative control. Our results indicated that the CoVPSA peptide of the Spike protein elicits noticeable immunogenicity in vivo using a DC vaccine vector and remarkable cellular and humoral immune responses. This DC vaccine vector loaded with the NTD peptide of the Spike protein elicited a predominant Th1-Th17 cytokine profile, indicative of an effective anti-viral response. Finally, we performed a proof of concept experiment in humans that included the following groups: asymptomatic non-active COVID-19 patients, vaccinated volunteers, and control donors that tested negative for SARS-CoV-2. The positive control was the current receptor binding domain epitope of COVID-19 RNA-vaccines. We successfully developed a vaccine candidate technique involving optimizing lambda-superstrings and provided proof of concept in human subjects. We conclude that it is a valid method to decipher the best epitopes of the Spike protein of SARS-CoV-2 to prepare peptide-based vaccines for different vector platforms, including DC vaccines.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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First computational design using lambda-superstrings and in vivo validation of SARS-CoV-2 vaccine

Martínez

Malaina

Salcines-Cuevas

et al. 2022

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…The problem of epitope assembly has also been considered from a combinatorial optimization perspective, for instance by Martínez et al. [180] , [181] . Their approach can be resumed as follows. Given two sets of strings, a set of host strings, which models a set of instances of a protein, i.e., amino acid sequences of the protein for a given pathogen, and a set of target strings, which models a set of epitopes, a λ-superstring is defined as a string that models a candidate vaccine containing, as substrings, at least λ target strings from each host string.…”

Section: Vaccinesmentioning

confidence: 99%

COVID-19 and SARS-CoV-2. Modeling the present, looking at the future

2020

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Since December 2019 the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has produced an outbreak of pulmonary disease which has soon become a global pandemic, known as COronaVIrus Disease-19 (COVID-19). The new coronavirus shares about 82% of its genome with the one which produced the 2003 outbreak (SARS CoV-1). Both coronaviruses also share the same cellular receptor, which is the angiotensin-converting enzyme 2 (ACE2) one. In spite of these similarities, the new coronavirus has expanded more widely, more faster and more lethally than the previous one. Many researchers across the disciplines have used diverse modeling tools to analyze the impact of this pandemic at global and local scales. This includes a wide range of approaches – deterministic, data-driven, stochastic, agent-based, and their combinations – to forecast the progression of the epidemic as well as the effects of non-pharmaceutical interventions to stop or mitigate its impact on the world population. The physical complexities of modern society need to be captured by these models. This includes the many ways of social contacts – (multiplex) social contact networks, (multilayers) transport systems, metapopulations, etc. – that may act as a framework for the virus propagation. But modeling not only plays a fundamental role in analyzing and forecasting epidemiological variables, but it also plays an important role in helping to find cures for the disease and in preventing contagion by means of new vaccines. The necessity for answering swiftly and effectively the questions: could existing drugs work against SARS CoV-2? and can new vaccines be developed in time? demands the use of physical modeling of proteins, protein-inhibitors interactions, virtual screening of drugs against virus targets, predicting immunogenicity of small peptides, modeling vaccinomics and vaccine design, to mention just a few. Here, we review these three main areas of modeling research against SARS CoV-2 and COVID-19: (1) epidemiology; (2) drug repurposing; and (3) vaccine design. Therefore, we compile the most relevant existing literature about modeling strategies against the virus to help modelers to navigate this fast-growing literature. We also keep an eye on future outbreaks, where the modelers can find the most relevant strategies used in an emergency situation as the current one to help in fighting future pandemics.

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“…Vaccines for adults is one of the biggest challenges of current vaccinology and several methodologies have been proposed for this purpose such as reverse vaccinology, a genome-based approach to vaccine development (1), or immune algorithm approaches (2)(3)(4). One of the main issues regarding vaccines for adults is the possibility to prepare bacterial vaccines that induce cross-protection against infections caused by different pathogens that provide cellular specific immunity, involving both T and B cells, known as cross-reactive vaccines (CRV).…”

Section: Introductionmentioning

confidence: 99%

A Comparison Between Recombinant Listeria GAPDH Proteins and GAPDH Encoding mRNA Conjugated to Lipids as Cross-Reactive Vaccines for Listeria, Mycobacterium, and Streptococcus

et al. 2021

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Cross-reactive vaccines recognize common molecular patterns in pathogens and are able to confer broad spectrum protection against different infections. Antigens common to pathogenic bacteria that induce broad immune responses, such as the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) of the genera Listeria, Mycobacterium, or Streptococcus, whose sequences present more than 95% homology at the N-terminal GAPDH1−22 peptide, are putative candidates for universal vaccines. Here, we explore vaccine formulations based on dendritic cells (DC) loaded with two molecular forms of Listeria monocytogenes GAPDH (LM-GAPDH), such as mRNA carriers or recombinant proteins, and compare them with the same molecular forms of three other antigens used in experimental vaccines, listeriolysin O of Listeria monocytogeness, Ag85A of Mycobacterium marinum, and pneumolysin of Streptococcus pneumoniae. DC loaded with LM-GAPDH recombinant proteins proved to be the safest and most immunogenic vaccine vectors, followed by mRNA encoding LM-GAPDH conjugated to lipid carriers. In addition, macrophages lacked sufficient safety as vaccines for all LM-GAPDH molecular forms. The ability of DC loaded with LM-GAPDH recombinant proteins to induce non-specific DC activation explains their adjuvant potency and their capacity to trigger strong CD4+ and CD8+ T cell responses explains their high immunogenicity. Moreover, their capacity to confer protection in vaccinated mice against challenges with L. monocytogenes, M. marinum, or S. pneumoniae validated their efficiency as cross-reactive vaccines. Cross-protection appears to involve the induction of high percentages of GAPDH1−22 specific CD4+ and CD8+ T cells stained for intracellular IFN-γ, and significant levels of peptide-specific antibodies in vaccinated mice. We concluded that DC vaccines loaded with L. monocytogenes GAPDH recombinant proteins are cross-reactive vaccines that seem to be valuable tools in adult vaccination against Listeria, Mycobacterium, and Streptococcus taxonomic groups.

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Weighted lambda superstrings applied to vaccine design

Cited by 9 publications

References 50 publications

First computational design using lambda-superstrings and in vivo validation of SARS-CoV-2 vaccine

First computational design using lambda-superstrings and in vivo validation of SARS-CoV-2 vaccine

COVID-19 and SARS-CoV-2. Modeling the present, looking at the future

A Comparison Between Recombinant Listeria GAPDH Proteins and GAPDH Encoding mRNA Conjugated to Lipids as Cross-Reactive Vaccines for Listeria, Mycobacterium, and Streptococcus

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