ABSTRACT
Background/Objectives: Chemosensory dysfunction is a hallmark of SARS-CoV-2 infection;nevertheless, the genetic factors predisposing to long-term smell and taste loss are still unknown. This study aims to identify candidate genes possibly involved in persistent smell/taste loss through Whole Genome Sequencing (WGS) analysis of a large cohort of 130 fully characterised Italian individuals, previously diagnosed with COVID-19. Method(s): DNA of all analysed patients was used to perform WGS analysis, and a detailed personal anamnesis was collected. Moreover, orthonasal function was assessed through the extended Sniffin' Sticks test, retronasal function was tested with 20 powdered tasteless aromas, and taste was determined with validated Taste Strips. Self-reported smell and taste alterations were assessed via Visual Analog Scales plus questionnaires. Result(s): The clinical evaluation allowed to classify the patients in two groups: 88 cases affected by persistent smell dysfunction (median age, 49) and 42 controls (median age, 51). Among cases, 26.1% (n = 23) were functionally anosmic and 73.9% (n = 65) were hyposmic. Within cases, 77 underwent the taste strip test: 53.2% (n = 41) presented hypogeusia and 46.8% (n = 36) were normogeusic. Preliminary WGS results on a first subset of 76 samples confirmed the important role of UGT2A1 gene, previously described as involved in smell loss. Interestingly, we identified a nonsense variant (rs111696697, MAF 0.046) significantly associated with anosmia in males (p-value: 0.0183). Conclusion(s): Here, for the first time a large cohort of patients, fully characterised through a comprehensive psychophysical evaluation of smell and taste, have been analysed to better define the genetic bases of COVID-19-related persistent chemosensory dysfunction.
ABSTRACT
The main protease of SARS-CoV-2 (called Mpro or 3CLpro) is essential for processing polyproteins encoded by viral RNA. Several Mpro mutations were found in SARS-CoV-2 variants, which are related to higher transmissibility, pathogenicity, and resistance to neutralization antibodies. Macromolecules adopt several favored conformations in solution depending on their structure and shape, determining their dynamics and function. In this study, we used a hybrid simulation method to generate intermediate structures along the six lowest frequency normal modes and sample the conformational space and characterize the structural dynamics and global motions of WT SARS-CoV-2 Mpro and 48 mutations, including mutations found in P.1, B.1.1.7, B.1.351, B.1.525 and B.1.429+B.1.427 variants. We tried to contribute to the elucidation of the effects of mutation in the structural dynamics of SARS-CoV-2 Mpro. A machine learning analysis was performed following the investigation regarding the influence of the K90R, P99L, P108S, and N151D mutations on the dimeric interface assembling of the SARS-CoV-2 Mpro. The parameters allowed the selection of potential structurally stable dimers, which demonstrated that some single surface aa substitutions not located at the dimeric interface (K90R, P99L, P108S, and N151D) are able to induce significant quaternary changes. Furthermore, our results demonstrated, by a Quantum Mechanics method, the influence of SARS-CoV-2 Mpro mutations on the catalytic mechanism, confirming that only one of the chains of the WT and mutant SARS-CoV-2 Mpros are prone to cleave substrates. Finally, it was also possible to identify the aa residue F140 as an important factor related to the increasing enzymatic reactivity of a significant number of SARS-CoV-2 Mpro conformations generated by the normal modes-based simulations. Graphical Image 1
ABSTRACT
The main protease of SARS-CoV-2 (called Mpro or 3CLpro) is essential for processing polyproteins encoded by viral RNA. Several Mpro mutations were found in SARS-CoV-2 variants, which are related to higher transmissibility, pathogenicity, and resistance to neutralization antibodies. Macromolecules adopt several favored conformations in solution depending on their structure and shape, determining their dynamics and function. In this study, we used a hybrid simulation method to generate intermediate structures along the six lowest frequency normal modes and sample the conformational space and characterize the structural dynamics and global motions of WT SARS-CoV-2 Mpro and 48 mutations, including mutations found in P.1, B.1.1.7, B.1.351, B.1.525 and B.1.429+B.1.427 variants. We tried to contribute to the elucidation of the effects of mutation in the structural dynamics of SARS-CoV-2 Mpro. A machine learning analysis was performed following the investigation regarding the influence of the K90R, P99L, P108S, and N151D mutations on the dimeric interface assembling of the SARS-CoV-2 Mpro. The parameters allowed the selection of potential structurally stable dimers, which demonstrated that some single surface aa substitutions not located at the dimeric interface (K90R, P99L, P108S, and N151D) are able to induce significant quaternary changes. Furthermore, our results demonstrated, by a Quantum Mechanics method, the influence of SARS-CoV-2 Mpro mutations on the catalytic mechanism, confirming that only one of the chains of the WT and mutant SARS-CoV-2 Mpros are prone to cleave substrates. Finally, it was also possible to identify the aa residue F140 as an important factor related to the increasing enzymatic reactivity of a significant number of SARS-CoV-2 Mpro conformations generated by the normal modes-based simulations.