ArticleMicroorganisms2021
Coinfection and Interference Phenomena Are the Results of Multiple Thermodynamic Competitive Interactions.
Article in Microorganisms, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 44 citations in OpenAlex.
- Interaction analysis of non-bacterial respiratory pathogens during and after the coronavirus disease 2019 pandemic in two cities along the eastern coast of China.Pediatric investigation · 2026Article
- Viral Prognosis Using Proteomics.Advances in experimental medicine and biology · 2026Review
- Quantitative Analysis of Virus Adsorption and Co-adsorption Behavior Using BET Modeling and SERS Spectroscopy.The journal of physical chemistry. A · 2025Article
- Pathogen growth and virulence dynamics drive the host evolution against coinfections.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- SARS-CoV-2 strain wars continues: Chemical and thermodynamic characterization of live matter and biosynthesis of Omicron BN.1, CH.1.1 and XBC variants.Microbial risk analysis · 2023Article
- Ghosts of the past: Elemental composition, biosynthesis reactions and thermodynamic properties of Zeta P.2, Eta B.1.525, Theta P.3, Kappa B.1.617.1, Iota B.1.526, Lambda C.37 and Mu B.1.621 variants of SARS-CoV-2.Microbial risk analysis · 2023Article
- Adapting an integrated acute respiratory infections sentinel surveillance to the COVID-19 pandemic requirements, Egypt, 2020-2022.Public health in practice (Oxford, England) · 2023Article
- XBB.1.5 Kraken cracked: Gibbs energies of binding and biosynthesis of the XBB.1.5 variant of SARS-CoV-2.Microbiological research · 2023Article
- The SARS-CoV-2 Hydra, a tiny monster from the 21st century: Thermodynamics of the BA.5.2 and BF.7 variants.Microbial risk analysis · 2023Article
- Never ending story? Evolution of SARS-CoV-2 monitored through Gibbs energies of biosynthesis and antigen-receptor binding of Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants.Microbial risk analysis · 2023Article
- Review
- Beyond COVID-19: Do biothermodynamic properties allow predicting the future evolution of SARS-CoV-2 variants?Microbial risk analysis · 2022Article
- Strain wars 3: Differences in infectivity and pathogenicity between Delta and Omicron strains of SARS-CoV-2 can be explained by thermodynamic and kinetic parameters of binding and growth.Microbial risk analysis · 2022Article
- Why doesn't Ebola virus cause pandemics like SARS-CoV-2?Microbial risk analysis · 2022Article
- Strain wars 5: Gibbs energies of binding of BA.1 through BA.4 variants of SARS-CoV-2.Microbial risk analysis · 2022Article
- Omicron BA.2.75 Subvariant of SARS-CoV-2 Is Expected to Have the Greatest Infectivity Compared with the Competing BA.2 and BA.5, Due to Most Negative Gibbs Energy of Binding.Biotech (Basel (Switzerland)) · 2022Article
- Using thermodynamic equilibrium models to predict the effect of antiviral agents on infectivity: Theoretical application to SARS-CoV-2 and other viruses.Microbial risk analysis · 2022Article
- Strain Wars: Competitive interactions between SARS-CoV-2 strains are explained by Gibbs energy of antigen-receptor binding.Microbial risk analysis · 2022Article
- Strain wars 2: Binding constants, enthalpies, entropies, Gibbs energies and rates of binding of SARS-CoV-2 variants.Virology · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biological, physical and chemical interaction between one (or more) microorganisms and a host organism, causing host cell damage, represents an infection. Infection of a plant, animal or microorganism with a virus can prevent infection with another virus. This phenomenon is known as viral interference. Viral interference is shown to result from two types of interactions, one taking place at the cell surface and the other intracellularly. Various viruses use different receptors to enter the same host cell, but various strains of one virus use the same receptor. The rate of virus-receptor binding can vary between different viruses attacking the same host, allowing interference or coinfection. The outcome of the virus-virus-host competition is determined by the Gibbs energies of binding and growth of the competing viruses and host. The virus with a more negative Gibbs energy of binding to the host cell receptor will enter the host first, while the virus characterized by a more negative Gibbs energy of growth will overtake the host metabolic machine and dominate. Once in the host cell, the multiplication machinery is shared by the competing viruses. Their potential to utilize it depends on the Gibbs energy of growth. Thus, the virus with a more negative Gibbs energy of growth will dominate. Therefore, the outcome can be interference or coinfection, depending on both the attachment kinetics (susceptibility) and the intracellular multiplication machinery (permittivity). The ratios of the Gibbs energies of binding and growth of the competing viruses determine the outcome of the competition. Based on this, a predictive model of virus-virus competition is proposed.
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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.