In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform

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Abstract

Background

SARS-CoV-2 is a severe respiratory infection that infects humans. Its outburst entitled it as a pandemic emergence. To get a grip on this outbreak, specific preventive and therapeutic interventions are urgently needed. It must be said that, until now, there are no existing vaccines for coronaviruses. To promptly and rapidly respond to pandemic events, the application of in silico trials can be used for designing and testing medicines against SARS-CoV-2 and speed-up the vaccine discovery pipeline, predicting any therapeutic failure and minimizing undesired effects.

Results

We present an in silico platform that showed to be in very good agreement with the latest literature in predicting SARS-CoV-2 dynamics and related immune system host response. Moreover, it has been used to predict the outcome of one of the latest suggested approach to design an effective vaccine, based on monoclonal antibody. Universal Immune System Simulator (UISS) in silico platform is potentially ready to be used as an in silico trial platform to predict the outcome of vaccination strategy against SARS-CoV-2.

Conclusions

In silico trials are showing to be powerful weapons in predicting immune responses of potential candidate vaccines. Here, UISS has been extended to be used as an in silico trial platform to speed-up and drive the discovery pipeline of vaccine against SARS-CoV-2.

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Most cited references 55

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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Chaolin Huang, Yeming Wang, Xingwang Li … (2020)

Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.

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SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

Markus Hoffmann, Hannah Kleine-Weber, Simon Schroeder … (2020)

Summary The recent emergence of the novel, pathogenic SARS-coronavirus 2 (SARS-CoV-2) in China and its rapid national and international spread pose a global health emergency. Cell entry of coronaviruses depends on binding of the viral spike (S) proteins to cellular receptors and on S protein priming by host cell proteases. Unravelling which cellular factors are used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal therapeutic targets. Here, we demonstrate that SARS-CoV-2 uses the SARS-CoV receptor ACE2 for entry and the serine protease TMPRSS2 for S protein priming. A TMPRSS2 inhibitor approved for clinical use blocked entry and might constitute a treatment option. Finally, we show that the sera from convalescent SARS patients cross-neutralized SARS-2-S-driven entry. Our results reveal important commonalities between SARS-CoV-2 and SARS-CoV infection and identify a potential target for antiviral intervention.

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Is Open Access

A new coronavirus associated with human respiratory disease in China

Fan Wu, Su Zhao, Bin Yu … (2020)

Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health 1–3 . Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing 4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China 5 . This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.

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Author and article information

Contributors

Giulia Russo: giulia.russo@unict.it

Marzio Pennisi: marzio.pennisi@uniupo.it

Epifanio Fichera: epifanio.fichera@etnabiotech.it

Santo Motta: s.motta@iac.cnr.it

Giuseppina Raciti: racitigi@unict.it

Marco Viceconti: marco.viceconti@unibo.it

Francesco Pappalardo: francesco.pappalardo@unict.it

Conference

Journal ID (nlm-ta): BMC Bioinformatics

Journal ID (iso-abbrev): BMC Bioinformatics

Title: BMC Bioinformatics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2105

Publication date (Electronic): 14 December 2020

Publication date PMC-release: 14 December 2020

Publication date Collection: 2020

Volume: 21

Issue : Suppl 17 Issue sponsor : Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. Supplement Editors did not handle peer review on any articles that they have co-authored. The Supplement Editors declare that they have no other competing interests.

Electronic Location Identifier: 527

Affiliations

[1 ]GRID grid.8158.4, ISNI 0000 0004 1757 1969, Department of Drug Sciences, , University of Catania, ; 95125 Catania, Italy

[2 ]GRID grid.16563.37, ISNI 0000000121663741, Computer Science Institute, DiSIT, , University of Eastern Piedmont, ; 15125 Alessandria, Italy

[3 ]GRID grid.434329.b, ISNI 0000 0004 7402 7724, Etna Biotech S.R.L., ; 95121 Catania, Italy

[4 ]GRID grid.5326.2, ISNI 0000 0001 1940 4177, National Research Council of Italy, ; 00185 Rome, Italy

[5 ]GRID grid.6292.f, ISNI 0000 0004 1757 1758, Department of Industrial Engineering, , Alma Mater Studiorum – University of Bologna, ; 40136 Bologna, Italy

Article

Publisher ID: 3872

DOI: 10.1186/s12859-020-03872-0

PMC ID: 7733700

PubMed ID: 33308153

SO-VID: 752d342a-611e-4ae3-b7ed-a73b00d19e1f

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Conference name: 3rd International Workshop on Computational Methods for the Immune System Function (CMISF 2019)

Conference acronym: CMISF 2019

Conference location: San Diego, CA, USA

Conference date: 18-21 November 2019

History

Date received : 29 October 2020

Date accepted : 9 November 2020

Custom metadata

ScienceOpen disciplines: Bioinformatics & Computational biology

Keywords: agent-based model,human monoclonal antibodies,in silico trials,sars-cov-2,vaccines

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ScienceOpen disciplines: Bioinformatics & Computational biology

Keywords: agent-based model, human monoclonal antibodies, in silico trials, sars-cov-2, vaccines

In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform

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Abstract

Background

Results

Conclusions

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Novel Coronavirus Disease COVID-19

Most cited references 55

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

A new coronavirus associated with human respiratory disease in China

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