How virus size and attachment parameters affect the temperature sensitivity of virus binding to host cells: Predictions of a thermodynamic model for arboviruses and HIV

DNA-based assay for calorimetric determination of protein concentrations in pure or mixed solutions

It was recently reported that values of the transition heat capacities, as measured by differential scanning calorimetry, for two globular proteins and a short DNA hairpin in NaCl buffer are essentially equivalent, at equal concentrations (mg/mL). To validate the broad applicability of this phenomenon, additional evidence for this equivalence is presented that reveals it does not depend on DNA sequence, buffer salt, or transition temperature (Tm). Based on the equivalence of transition heat capacities, a calorimetric method was devised to determine protein concentrations in pure and complex solutions. The scheme uses direct comparisons between the thermodynamic stability of a short DNA hairpin standard of known concentration, and thermodynamic stability of protein solutions of unknown concentrations. Sequences of two DNA hairpins were designed to confer a near 20°C difference in their Tm values. In all cases, evaluated protein concentrations determined from the DNA standard curves agreed with the UV-Vis concentration for monomeric proteins. For multimeric proteins evaluated concentrations were greater than determined by UV-Vis suggesting the calorimetric approach can also be an indicator of molecular stoichiometry.

Thermodynamics of microbial consortia: Enthalpies and Gibbs energies of microorganism live matter and macromolecules of E. coli, G. oxydans, P. fluorescens, S. thermophilus and P. chrysogenum

Every microorganism represents a biothermodynamic system, characterized by an empirical formula and thermodynamic properties of biosynthesis. Gibbs energy of biosynthesis influences the multiplication rate of a microorganism. In case of a mixed culture (microbial consortia) biosynthesis processes of microbial species are competitive. This is why Gibbs energy of biosynthesis determines the growth in a mixed culture. This paper gives a mechanistic model that explains growth of microorganisms in mixed culture and ability to grow in microbial consortia. Detailed biosynthesis reactions were formulated for the first time for five microorganism species, which include metallic elements. Moreover, thermodynamic properties of live matter and biosynthesis were calculated for the first time for five microorganism species and macromolecules.

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

SARS-CoV-2 has during the last 3 years mutated several dozen times. Most mutations in the newly formed variants have been chemically and thermodynamically characterized. New variants have been declared as variants under monitoring. The European Centre for Disease Prevention and Control has suggested the hypothesis that the new BN.1, CH.1.1 and XBC variants could have properties similar to those of VOC. Thermodynamic properties of new variants have been reported in this manuscript for the first time. Gibbs energy of biosynthesis, as the driving force for viral multiplication, is less negative for the new variants than for the earlier variants. This indicates that the virus has evolved towards decrease in pathogenicity, which leads to less severe forms of COVID-19.

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

From the perspectives of molecular biology, genetics and biothermodynamics, SARS-CoV-2 is the among the best characterized viruses. Research on SARS-CoV-2 has shed a new light onto driving forces and molecular mechanisms of viral evolution. This paper reports results on empirical formulas, biosynthesis reactions and thermodynamic properties of biosynthesis (multiplication) for the 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. Thermodynamic analysis has shown that the physical driving forces for evolution of SARS-CoV-2 are Gibbs energy of biosynthesis and Gibbs energy of binding. The driving forces have led SARS-CoV-2 through the evolution process from the original Hu-1 to the newest variants in accordance with the expectations of the evolution theory.

Clinical features and transmission risk analysis of dengue virus infections in Shenzhen, During 2014-2019

Dengue fever (DF) and dengue hemorrhagic fever (DHF) are among the most common tropical diseases affecting humans. To analyze the risk of clinical and transmission of DF/DHF in Shenzhen, the surveillance on patients of all-age patients with dengue virus (DENV) infections was conducted. Our findings revealed that the majority of DENV-infected patients are young to middle-aged males, and the development of the disease is accompanied by abnormal changes in the percentages of neutrophils, lymphocytes, and basophils. Demographic analysis revealed that these patients is concentrated in areas such as Futian District, which may be due to the higher mosquito density and temperature than that in other area. Subsequent, mosquito infection experiments confirmed that the effect of temperature shift on DENV proliferation and transmission. Not only that, constant temperatures can enhance the spread of DENV, even increase the risk of epidemic. Thus, the role of innate immune response should be highlighted in the prediction of severe severity of DENV-infected patients, and temperature should be taken into account in the prevention and control of DENV.

INTRODUCTION

Dengue fever (DF) and dengue hemorrhagic fever (DHF) are among the most common tropical diseases affecting humans, and which caused by the four dengue virus serotypes (DENV 1-4).

OBJECTIVES

To analyze the risk of clinical and transmission of DF/DHF in Shenzhen.

METHODS

The surveillance on patients of all-age patients with dengue virus (DENV) infections was conducted.

RESULTS

Our findings revealed that the majority of DENV-infected patients are young to middle-aged males, and the development of the disease is accompanied by abnormal changes in the percentages of neutrophils, lymphocytes, and basophils. Demographic analysis revealed that these patients is concentrated in areas such as Futian District, which may be due to the higher mosquito density and temperature than that in other area. Subsequent, mosquito infection experiments confirmed that the effect of temperature shift on DENV proliferation and transmission. Not only that, constant temperatures can enhance the spread of DENV, even increase the risk of epidemic.

CONCLUSION

1. Elevated levels of neutrophils, lymphocytes, basophils, and temperature are all significant risk factors for dengue transmission and pathogenesis; 2. Temperature increasing is associated with a higher risk of dengue transmission; 3. Fluctuations in temperature around 28 °C (28 ± 5 °C) would increase dengue transmission.

XBB.1.5 Kraken cracked: Gibbs energies of binding and biosynthesis of the XBB.1.5 variant of SARS-CoV-2

The SARS-CoV-2 Hydra with many heads (variants) has been causing the COVID-19 pandemic for 3 years. The appearance of every new head (SARS-CoV-2 variant) causes a new pandemic wave. The last in the series is the XBB.1.5 "Kraken" variant. In the general public (social media) and in the scientific community (scientific journals), during the last several weeks since the variant has appeared, the question was raised of whether the infectivity of the new variant will be greater. This article attempts to provide the answer. Analysis of thermodynamic driving forces of binding and biosynthesis leads to the conclusion that infectivity of the XBB.1.5 variant could be increased to a certain extent. The pathogenicity of the XBB.1.5 variant seems to be unchanged compared to the other Omicron variants.

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

RNA viruses exhibit a great tendency to mutate. Mutations occur in the parts of the genome that encode the spike glycoprotein and less often in the rest of the genome. This is why Gibbs energy of binding changes more than that of biosynthesis. Starting from 2019, the wild type that was labeled Hu-1 has during the last 3 years evolved to produce several dozen new variants, as a consequence of mutations. Mutations cause changes in empirical formulas of new virus strains, which lead to change in thermodynamic properties of biosynthesis and binding. These changes cause changes in the rate of reactions of binding of virus antigen to the host cell receptor and the rate of virus multiplication in the host cell. Changes in thermodynamic and kinetic parameters lead to changes in biological parameters of infectivity and pathogenicity. Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has been evolving towards increase in infectivity and maintaining constant pathogenicity, or for some variants a slight decrease in pathogenicity. In the case of Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants pathogenicity is identical as in the Omicron BA.2.75 variant. On the other hand, infectivity of the Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants is greater than those of previous variants. This will most likely result in the phenomenon of asymmetric coinfection, that is circulation of several variants in the population, some being dominant.

Biothermodynamics of Viruses from Absolute Zero (1950) to Virothermodynamics (2022)

Biothermodynamics of viruses is among the youngest but most rapidly developing scientific disciplines. During the COVID-19 pandemic, it closely followed the results published by molecular biologists. Empirical formulas were published for 50 viruses and thermodynamic properties for multiple viruses and virus variants, including all variants of concern of SARS-CoV-2, SARS-CoV, MERS-CoV, Ebola virus, Vaccinia and Monkeypox virus. A review of the development of biothermodynamics of viruses during the last several decades and intense development during the last 3 years is described in this paper.

Why doesn't Ebola virus cause pandemics like SARS-CoV-2?

Ebola virus is among the most dangerous, contagious and deadly etiological causes of viral diseases. However, Ebola virus has never extensively spread in human population and never have led to a pandemic. Why? The mechanistic biophysical model revealing the biothermodynamic background of virus-host interaction) could help us to understand pathogenesis of Ebola virus disease (earlier known as the Ebola hemorrhagic fever). In this paper for the first time the empirical formula, thermodynamic properties of biosynthesis (including the driving force of virus multiplication in the susceptible host), binding constant and thermodynamic properties of binding are reported. Thermodynamic data for Ebola virus were compared with data for SARS-CoV-2 to explain why SARS-CoV-2 has caused a pandemic, while Ebola remains on local epidemic level. The empirical formula of the Ebola virus was found to be CH_1.569O_0.3281N_0.2786P_0.00173S_0.00258. Standard Gibbs energy of biosynthesis of the Ebola virus nucleocapsid is -151.59 kJ/C-mol.

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

In this paper, for the first time, empirical formulas have been reported of the Delta and Omicron strains of SARS-CoV-2. The empirical formula of the Delta strain entire virion was found to be CH1.6383O0.2844N0.2294P0.0064S0.0042, while its nucleocapsid has the formula CH1.5692O0.3431N0.3106P0.0060S0.0043. The empirical formula of the Omicron strain entire virion was found to be CH1.6404O0.2842N0.2299P0.0064S0.0038, while its nucleocapsid has the formula CH1.5734O0.3442N0.3122P0.0060S0.0033. Based on the empirical formulas, standard thermodynamic properties of formation and growth have been calculated and reported for the Delta and Omicron strains. Moreover, standard thermodynamic properties of binding have been reported for Wild type (Hu-1), Alpha, Beta, Gamma, Delta and Omicron strains. For all the strains, binding phenomenological coefficients and antigen-receptor (SGP-ACE2) binding rates have been determined and compared, which are proportional to infectivity. The results show that the binding rate of the Omicron strain is between 1.5 and 2.5 times greater than that of the Delta strain. The Omicron strain is characterized by a greater infectivity, based on the epidemiological data available in the literature. The increased infectivity was explained in this paper using Gibbs energy of binding. However, no indications exist for decreased pathogenicity of the Omicron strain. Pathogenicity is proportional to the virus multiplication rate, while Gibbs energies of multiplication are very similar for the Delta and Omicron strains. Thus, multiplication rate and pathogenicity are similar for the Delta and Omicron strains. The lower number of severe cases caused by the Omicron strain can be explained by increased number of immunized people. Immunization does not influence the possibility of occurrence of infection, but influences the rate of immune response, which is much more efficient in immunized people. This leads to prevention of more severe Omicron infection cases.

Strain wars 5: Gibbs energies of binding of BA.1 through BA.4 variants of SARS-CoV-2

This paper reports, for the first time, standard Gibbs energies of binding of the BA.1, BA.2, BA.3, BA.2.13, BA.2.12.1 and BA.4 Omicron variants of SARS-CoV-2, to the Human ACE2 receptor. Variants BA.1 through BA.3 exhibit a trend of decreasing standard Gibbs energy of binding and hence increased infectivity. The BA.4 variant exhibits a less negative standard Gibbs energy of binding, but also more efficient evasion of the immune response. Therefore, it was concluded that all the analyzed strains evolve in accordance with expectations of the theory of evolution, albeit using different strategies.

Beyond COVID-19: Do biothermodynamic properties allow predicting the future evolution of SARS-CoV-2 variants?

During the COVID-19 pandemic, many statistical and epidemiological studies have been published, trying to predict the future development of the SARS-CoV-2 pandemic. However, it would be beneficial to have a specific, mechanistic biophysical model, based on the driving forces of processes performed during virus-host interactions and fundamental laws of nature, allowing prediction of future evolution of SARS-CoV-2 and other viruses. In this paper, an attempt was made to predict the development of the pandemic, based on biothermodynamic parameters: Gibbs energy of binding and Gibbs energy of growth. Based on analysis of biothermodynamic parameters of various variants of SARS-CoV-2, SARS-CoV and MERS-CoV that appeared during evolution, an attempt was made to predict the future directions of evolution of SARS-CoV-2 and potential occurrence of new strains that could lead to new pandemic waves. Possible new mutations that could appear in the future could lead to changes in chemical composition, biothermodynamic properties (driving forces of new virus strains) and biological properties of SARS CoV-2 that represent a risk for humanity.

Omicron BA.2.75 Sublineage (Centaurus) Follows the Expectations of the Evolution Theory: Less Negative Gibbs Energy of Biosynthesis Indicates Decreased Pathogenicity

SARS-CoV-2 belongs to the group of RNA viruses with a pronounced tendency to mutate. Omicron BA.2.75 is a subvariant believed to be able to suppress the currently dominant BA.5 and cause a new winter wave of the COVID-19 pandemic. Omicron BA.2.75 is characterized by a greater infectivity compared to earlier Omicron variants. However, the Gibbs energy of the biosynthesis of virus particles is slightly less negative compared to those of other variants. Thus, the multiplication rate of Omicron BA.2.75 is lower than that of other SARS-CoV-2 variants. This leads to slower accumulation of newly formed virions and less damage to host cells, indicating evolution of SARS-CoV-2 toward decreasing pathogenicity.

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

Omicron BA.2.75 may become the next globally dominant strain of COVID-19 in 2022. The BA.2.75 sub-variant has acquired more mutations (9) in spike protein and other genes of SARS-CoV-2 than any other variant. Thus, its chemical composition and thermodynamic properties have changed compared with earlier variants. In this paper, the Gibbs energy of the binding and antigen-receptor binding rate was reported for the BA.2.75 variant. Gibbs energy of the binding of the Omicron BA.2.75 variant is more negative than that of the competing variants BA.2 and BA.5.

Strain Wars: Competitive interactions between SARS-CoV-2 strains are explained by Gibbs energy of antigen-receptor binding

Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has mutated several times into new strains, with an increased infectivity. Infectivity of SARS-CoV-2 strains depends on binding affinity of the virus to its host cell receptor. In this paper, we quantified the binding affinity using Gibbs energy of binding and analyzed the competition between SARS-CoV-2 strains as an interference phenomenon. Gibbs energies of binding were calculated for several SARS-SoV-2 strains, including Hu-1 (wild type), B.1.1.7 (alpha), B.1.351 (beta), P.1 (Gamma), B.1.36 and B.1.617 (Delta). The least negative Gibbs energy of binding is that of Hu-1 strain, -37.97 kJ/mol. On the other hand, the most negative Gibbs energy of binding is that of the Delta strain, -49.50 kJ/mol. We used the more negative Gibbs energy of binding to explain the increased infectivity of newer SARS-CoV-2 strains compared to the wild type. Gibbs energies of binding was found to decrease chronologically, with appearance of new strains. The ratio of Gibbs energies of binding of mutated strains and wild type was used to define a susceptibility coefficient, which is an indicator of viral interference, where a virus can prevent or partially inhibit infection with another virus.

Using thermodynamic equilibrium models to predict the effect of antiviral agents on infectivity: Theoretical application to SARS-CoV-2 and other viruses

Thermodynamic equilibrium models predict the infectivity of novel and emerging viruses using molecular data including the binding affinity of the virus to the host cell (as represented by the association constant K_{a_virus_T}) and the probability, p_virogenesis, of the virus replicating after entry to the cell. Here those models are adapted based on the principles of ligand binding to macromolecules to assess the effect on virus infectivity of inhibitor molecules which target specific proteins of the virus. Three types of inhibitor are considered using the thermodynamic equilibrium model for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection of the human lung with parameters for the strength and nature of the interaction between the target virus protein and the inhibitor molecule. The first is competitive inhibition of the SARS-CoV-2 spike glycoprotein (SGP) trimer binding to its human angiotensin converting enzyme 2 (ACE2) receptor by unfractionated heparin (UFH). Using a novel approach presented here, a value of K_{a_virus_T} = 3.53 × 10¹⁷ M^-1 is calculated for SARS-CoV-2 from the IC₅₀ for inhibition by UFH of SARS-CoV-2 plaque formation in cell culture together with the dissociation constant K_VI of 0.73 × 10^-10 M reported for heparin binding to SARS-CoV-2 SGP trimer. Such a high K_{a_virus_T} limits the effectiveness of competitive inhibitors such as UFH. The second is the attachment of a nanoparticle such as a zinc oxide tetrapod (ZnOT) to the virus shell as for herpes simplex virus (HSV). The increase in molecular weight through ZnOT attachment is predicted to decrease K_{a_virus_T} by orders of magnitude by making the entropy change (ΔS_{a_immob}) on immobilisation of the ZnOT:virus complex on cell binding more negative than for the virus alone. According to the model, ZnOT acts synergistically with UFH at the IC₅₀ of 33 μg/cm³ which together decrease viral infectivity by 61,000-fold compared to the two-fold and three-fold decreases predicted for UFH alone at the IC₅₀ and for ZnOT alone respectively. According to the model here, UFH alone at its peak deliverable dose to the lung of 1,000 μg/cm³ only decreases infectivity by 31-fold. Practicable approaches to target and decrease ΔS_{a_immob} for respiratory viruses should therefore be considered. The combination of decreasing ΔS_{a_immob} together with blocking the interaction of virus surface protein with its host cell receptor may achieve synergistic effects for faecal-oral viruses and HSV. The third is reversible noncompetitive inhibition of the viral main protease (M^pro) for which the decrease in p_virogenesis is assumed to be proportional to the decrease in enzyme activity as predicted by enzyme kinetic equations for a given concentration of inhibitor which binds to M^pro with dissociation constant K_i. Virologists reporting viral inhibition studies are urged to report the concentration of cells in the cell culture experiment as this is a key parameter in estimating K_{a_virus_T} here.

Thermoresponsive C22 phage stiffness modulates the phage infectivity

Bacteriophages offer a sustainable alternative for controlling crop disease. However, the lack of knowledge on phage infection mechanisms makes phage-based biological control varying and ineffective. In this work, we interrogated the temperature dependence of the infection and thermo-responsive behavior of the C22 phage. This soilborne podovirus is capable of lysing Ralstonia solanacearum, causing bacterial wilt disease. We revealed that the C22 phage could better infect the pathogenic host cell when incubated at low temperatures (25, 30 °C) than at high temperatures (35, 40 °C). Measurement of the C22 phage stiffness revealed that the phage stiffness at low temperatures was 2–3 times larger than at high temperatures. In addition, the imaging results showed that more C22 phage particles were attached to the cell surface at low temperatures than at high temperatures, associating the phage stiffness and the phage attachment. The result suggests that the structure and stiffness modulation in response to temperature change improve infection, providing mechanistic insight into the C22 phage lytic cycle. Our study signifies the need to understand phage responses to the fluctuating environment for effective phage-based biocontrol implementation.

Phase transitions may explain why SARS-CoV-2 spreads so fast and why new variants are spreading faster

The novel coronavirus SARS CoV-2 responsible for the COVID-19 pandemic and SARS CoV-1 responsible for the SARS epidemic of 2002-2003 share an ancestor yet evolved to have much different transmissibility and global impact ¹. A previously developed thermodynamic model of protein conformations hypothesized that SARS CoV-2 is very close to a new thermodynamic critical point, which makes it highly infectious but also easily displaced by a spike-based vaccine because there is a tradeoff between transmissibility and robustness ². The model identified a small cluster of four key mutations of SARS CoV-2 that predicts much stronger viral attachment and viral spreading compared to SARS CoV-1. Here we apply the model to the SARS-CoV-2 variants Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1) and Delta (B.1.617.2)³ and predict, using no free parameters, how the new mutations will not diminish the effectiveness of current spike based vaccines and may even further enhance infectiousness by augmenting the binding ability of the virus.

Coinfection and Interference Phenomena Are the Results of Multiple Thermodynamic Competitive Interactions

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.

Thermodynamic equilibrium dose-response models for MERS-CoV infection reveal a potential protective role of human lung mucus but not for SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome coronavirus (MERS-CoV) infect the human respiratory tract. A prototype thermodynamic equilibrium model is presented here for the probability of the virions getting through the mucus barrier and infecting epithelial cells based on the binding affinity (Kmucin) of the virions to mucin molecules in the mucus and parameters for binding and infection of the epithelial cell. Both MERS-CoV and SARS-CoV-2 bind strongly to their cellular receptors, DDP4 and ACE2, respectively, and infect very efficiently both bronchus and lung ex vivo cell cultures which are not protected by a mucus barrier. According to the model, mucin binding could reduce the infectivity for MERS-CoV compared to SARS-CoV-2 by at least 100-fold depending on the magnitude of Kmucin. Specifically Kmucin values up to 106 M-1 have little protective effect and thus the mucus barrier would not remove SARS-CoV-2 which does not bind to sialic acids (SA) and hence would have a very low Kmucin. Depending on the viability of individual virions, the ID50 for SARS-CoV-2 is estimated to be ~500 virions (viral RNA genomic copies) representing 1 to 2 pfu. In contrast MERS-CoV binds both SA and human mucin and a Kmucin of 5 × 109 M-1 as reported for lectins would mop up 99.83% of the virus according to the model with the ID50 for MERS-CoV estimated to be ~295,000 virions (viral RNA genomic copies) representing 819 pfu. This could in part explain why MERS-CoV is poorly transmitted from human to human compared to SARS-CoV-2. Some coronaviruses use an esterase to escape the mucin, although MERS-CoV does not. Instead, it is shown here that "clustering" of virions into single aerosol particles as recently reported for rotavirus in extracellular vesicles could provide a co-operative mechanism whereby MERS-CoV could theoretically overcome the mucin barrier locally and a small proportion of 10 μm diameter aerosol particles could contain ~70 virions based on reported maximum levels in saliva. Although recent evidence suggests SARS-CoV-2 initiates infection in the nasal epithelium, the thermodynamic equilibrium models presented here could complement published approaches for modelling the physical entry of pathogens to the lung based on the fate and transport of the pathogen particles (as for anthrax spores) to develop a dose-response model for aerosol exposure to respiratory viruses. This would enable the infectivity through aerosols to be defined based on molecular parameters as well as physical parameters. The role of the spike proteins of MERS-CoV and SARS-CoV-2 binding to SA and heparan sulphate, respectively, may be to aid non-specific attachment to the host cell. It is proposed that a high Kmucin is the cost for subsequent binding of MERS-CoV to SAs on the cell surface to partially overcome the unfavourable entropy of immobilisation as the virus adopts the correct orientation for spike protein interactions with its protein cellular receptor DPP4.

Thermodynamic insight into viral infections 2: empirical formulas, molecular compositions and thermodynamic properties of SARS, MERS and SARS-CoV-2 (COVID-19) viruses

The current situation with the SARS-CoV-2 pandemic indicates the importance of new approaches in vaccine design. In order to design new attenuated vaccines, to decrease virulence of virus wild types, it is important to understand what allows a virus to hijack its host cell's metabolism, a property of all viruses. RNA and protein sequences obtained from databases were used to count the number of atoms of each element in the virions of SARS, MERS and SARS-CoV-2. The number of protein copies and carbohydrate composition were taken from the literature. The number of lipid molecules was estimated from the envelope surface area. Based on elemental composition, growth equations were balanced, and thermodynamic properties of the viruses were determined using Patel-Erickson and Battley equations. Elemental and molecular compositions of SARS, MERS and SARS-CoV-2 were found, as well as their standard thermodynamic properties of formation and growth. Standard Gibbs energy of growth of virus nucleocapsids was found to be significantly more negative than that of their host tissue. The ratio of Gibbs energies of growth of virus nucleocapsids and host cell is greater than unity. The more negative Gibbs energy of growth of viruses implies that virus multiplication has a greater driving force than synthesis of host cell components, giving a physical explanation of why viruses are able to hijack their host cell's metabolism. Knowing the mechanism of viral metabolism hijacking can open new paths for vaccine design. By manipulating chemical composition of viruses, virulence can be decreased by making the Gibbs energy of their growth less negative, resulting in decreased multiplication rate, while preserving antigenic properties.