Quantitative probability estimation of light-induced inactivation of SARS-CoV-2

Abstract

During the COVID pandemic caused by the SARS-CoV-2 virus, studies have shown the efficiency of deactivating this virus via ultraviolet light. The damage mechanism is well understood: UV light disturbs the integrity of the RNA chain at those locations where specific nucleotide neighbors occur. In this contribution, we present a model to address certain gaps in the description of the interaction between UV photons and the RNA sequence for virus inactivation. We begin by exploiting the available information on the pathogen's morphology, physical, and genomic characteristics, enabling us to estimate the average number of UV photons required to photochemically damage the virus's RNA. To generalize our results, we have numerically generated random RNA sequences and checked that the distribution of pairs of nucleotides susceptible of damage for the SARS-CoV-2 is within the expected values for a random-generated RNA chain. After determining the average number of photons reaching the RNA for a preset level of fluence (or photon density), we applied the binomial probability distribution to evaluate the damage of nucleotide pairs in the RNA chain due to UV radiation. Our results describe this interaction in terms of the probability of damaging a single pair of nucleotides, and the number of available photons. The cumulative probability exhibits a steep sigmoidal shape, implying that a relatively small change in the number of affected pairs may trigger the inactivation of the virus. Our light-RNA interaction model quantitatively describes how the fraction of affected pairs of nucleotides in the RNA sequence depends on the probability of damaging a single pair and the number of photons impinging on it. A better understanding of the underlying inactivation mechanism would help in the design of optimum experiments and UV sanitization methods. Although this paper focuses on SARS-CoV-2, these results can be adapted for any other type of pathogen susceptible of UV damage.

Keywords: Light-virus interaction; Optical disinfection; Ultraviolet light.

Figure 1

Left: structure of the SARS-Cov-2. Right: comparative representation of the geometrical cross section of the capsule ($r_{\text{capsule}}$), the individual RNA bundle ($r_{\mathrm{RNA}-\mathrm{bundle}}$), and the equivalent RNA bundle ($r_{\text{RNA}}$), as presented in Table 1.

Figure 2

Left: normalized probability of occurrence as a function of the percentage of neighbors susceptible to UV light damage (blue dots). We have generated 5000 times a RNA chain of 30,000 bases randomly arranged. The red line represents the fitting of this distribution to a Gaussian curve with a mean equal to 25% and $\sigma =0.3$%. The large red dot corresponds with the case of the SARS-CoV-2 pathogen. Right: Distribution of the 16 combinations of neighbors for the SARS-CoV-2 RNA chain. The numbers in red correspond to the nucleotide pairs that are affected by the UV radiation and generate a disturbance in the base functionality: CC, CU, UC, and UU. These four nucleotide combinations represent 25.5% of the total number of neighbors.

Figure 3

Probability (upper row in semilog scale), and cumulative probability (lower row) of having a given percentage of neighboring pairs damaged by radiation. The lines in color correspond to different values of $\alpha$ (0.2, 0.5 and 0.8 for blue, orange, and green, respectively), and each column represents a different number of interacting photons per pair, $n=1,2,$ and 3.

Figure 4

Percentage of affected pairs as a function of $\alpha$ for several values of the average number of photons, n, interacting with each pair. The solid lines represent the 50% cumulative probability, and the shaded region around them covers the portion between 0.1 and 99.9% in cumulative percentage (see bottom row in Fig. 3).