Emerging severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants, especially those of concern, may have an impact on the virus's transmissibility and pathogenicity, as well as diagnostic equipment performance and vaccine effectiveness. Even though the SARS-CoV-2 Delta variant (B.1.617.2) emerged during India's second wave of infections, Delta variants have grown dominant internationally and are still evolving. On November 26, 2021, World Health Organization identified the variant B.1.1.529 as a variant of concern, naming it Omicron, based on evidence that Omicron contains numerous mutations that may influence its behavior. However, the mode of transmission and severity of the Omicron variant remains unknown. We used computational studies to examine the Delta and Omicron variants in this study and found that the Omicron variant had a higher affinity for human angiotensin-converting enzyme 2 (ACE2) than the Delta variant due to a significant number of mutations in the SARS-CoV-2 receptor-binding domain (RBD), indicating a higher potential for transmission. Based on docking studies, the Q493R, N501Y, S371L, S373P, S375F, Q498R, and T478K mutations contribute significantly to high binding affinity with human ACE2. In comparison to the Delta variant, both the entire spike protein and the RBD in Omicron include a high proportion of hydrophobic amino acids such as leucine and phenylalanine. These amino acids are located within the protein's core and are required for structural stability. We observed a disorder-order transition in the Omicron variant between spike protein RBD regions 468-473, and it may be significant in the influence of disordered residues/regions on spike protein stability and binding to ACE2. A future study might investigate the epidemiological and biological consequences of the Omicron variant.

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Emerging SARS-CoV-2 variants, especially those of concern, may have an impact on the virus’s transmissibility and pathogenicity, as well as diagnostic equipment performance and vaccine effectiveness. Even though the SARS-CoV-2 Delta variant (B.1.617.2) emerged during India’s second wave of infections, Delta variants have grown dominant internationally and are still evolving. On November 26, 2021, WHO identified the variant B.1.1.529 as a variant of concern, naming it Omicron, based on evidence that Omicron contains numerous mutations that may influence its behaviour. However, the mode of transmission and severity of the Omicron variant remains unknown. We used computational studies to examine the Delta and Omicron variants in this work and found that the Omicron variant had a higher affinity for human ACE2 than the Delta variant due to a significant number of mutations in the SARS-CoV-2 receptor binding domain, indicating a higher potential for transmission. Based on docking studies, the Q493R, N501Y, S371L, S373P, S375F, Q498R, and T478K mutations contribute significantly to high binding affinity with human ACE2. In comparison to the Delta variant, both the entire spike protein and the RBD in Omicron include a high proportion of hydrophobic amino acids such as leucine and phenylalanine. These amino acids are located within the protein’s core and are required for structural stability. Omicron has a higher percentage of alpha-helix structure than the Delta variant in both whole spike protein and RBD, indicating that it has a more stable structure. We observed a disorder-order transition in the Omicron variant between spike protein RBD regions 468-473, and it may be significant in the influence of disordered residues/regions on spike protein stability and binding to ACE2. A future study might investigate the epidemiological and biological consequences of the Omicron variant.

Nature often utilizes molecular oxygen for oxidation reactions through monoxygenases and dioxygenases. In many of these systems, a high-valent iron(IV)-oxo active species is found. In recent years, evidence has accumulated of possible iron(IV)-imido and iron(V)-nitrido intermediates in enzymatic catalysis, although little is known about their activity. In this work, we report a detailed combined kinetics and computational study on the difference in reactivity and chemical properties of nonheme iron(IV)-oxo compared with iron(IV)-tosylimido. We show here that iron(IV)-tosylimido complex is much more reactive with sulfides than the corresponding iron(IV)-oxo complex; however, the reverse trend is obtained for hydrogen atom abstraction reactions. The latter proceed with a relatively small kinetic isotope effect of kH/kD = 7 for the iron(IV)-tosylimido complex. Moreover, a Hammett analysis of hydrogen atom abstraction from para-X-benzyl alcohol reveals a slope of close to zero for the iron(IV)-oxo, whereas a strong negative slope is found for the iron(IV)-tosylimido complex. These studies implicate dramatic changes in the reaction mechanisms and suggest a considerable charge transfer in the transition states. Density functional theory calculations were performed to support the experiments and confirm an initial long-range electron transfer for the iron(IV)-tosylimido complex with substrates, due to a substantially larger electron affinity compared with the iron(IV)-oxo species. As a consequence, it also reacts more efficiently in electrophilic addition reactions such as those with sulfides. By contrast, the long-range electron transfer for the iron(IV)-tosylimido complex results in a rate constant that is dependent on the π*xz → σ*z(2) excitation energy, which raises the hydrogen atom abstraction barrier above that found for the iron(IV)-oxo. On the other hand, sulfimidation has much earlier electron transfer steps with respect to sulfoxidation. All data has been analyzed and rationalized with valence bond models and thermochemical cycles. Our studies highlight the catalytic potential of iron(IV)-tosylimido complexes in chemistry and biology.

Background: Parkinson's disease (PD) is a neurodegenerative disorder. The diagnosis of Parkinsonism is challenging because currently none of the clinical tests have been proven to help in diagnosis. PD may produce characteristic perturbations in the metabolome and such variations can be used as the marker for detection of disease. To test this hypothesis, we used proton NMR and multivariate analysis followed by neural network pattern detection.