Evidence map›Paper›PMID 29297294›Full record

ArticleBMC bioinformatics2017

Combining agent based-models and virtual screening techniques to predict the best citrus-derived vaccine adjuvants against human papilloma virus.

Marzio Pennisi, Giulia Russo, Silvia Ravalli, Francesco Pappalardo

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In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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  11. A bioinformatics potpourri.BMC genomics · 2018
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Marzio PennisiDepartment of Mathematics and Computer Science, University of Catania, 95125, Catania, Italy.
Giulia RussoDepartment of Biomedical and Biotechnological Sciences, University of Catania, 95123, Catania, Italy.
Silvia RavalliDepartment of Drug Sciences, University of Catania, 95125, Catania, Italy.
Francesco PappalardoDepartment of Drug Sciences, University of Catania, 95125, Catania, Italy. francesco.pappalardo@unict.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman papillomavirus infection is a global social burden that, every year, leads to thousands new diagnosis of cancer. The introduction of a protocol of immunization, with Gardasil and Cervarix vaccines, has radically changed the way this infection easily spreads among people. Even though vaccination is only preventive and not therapeutic, it is a strong tool capable to avoid the consequences that this pathogen could cause. Gardasil vaccine is not free from side effects and the duration of immunity is not always well determined. This work aim to enhance the effects of the vaccination by using a new class of adjuvants and a different administration protocol. Due to their minimum side effects, their easy extraction, their low production costs and their proven immune stimulating activity, citrus-derived molecules are valid candidates to be administered as adjuvants in a vaccine formulation against Hpv.

resultsWith the aim to get a stronger immune response against Hpv infection we built an in silico model that delivers a way to predict the best adjuvants and the optimal means of administration to obtain such a goal. Simulations envisaged that the use of Neohesperidin elicited a strong immune response that was then validated in vivo.

conclusionsWe built up a computational infrastructure made by a virtual screening approach able to preselect promising citrus derived compounds, and by an agent based model that reproduces HPV dynamics subject to vaccine stimulation. This integrated methodology was able to predict the best protocol that confers a very good immune response against HPV infection. We finally tested the in silico results through in vivo experiments on mice, finding good agreement.

Indexed as

Adjuvants, PharmaceuticAnimalsCitrusFemaleHumansMass ScreeningPapillomaviridaePapillomavirus InfectionsPapillomavirus VaccinesVaccinationAdjuvants, Pharmaceutichuman papillomavirus vaccine, L1 type 16, 18Papillomavirus VaccinesAdjuvantsHPVMulti agent systems, vaccinesVirtual screening

Identifiers

PMID29297294
PMCPMC5751416

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.