tetano
Editor, Senior Moderator
Sci Rep
. 2024 Jun 20;14(1):14208.
doi: 10.1038/s41598-024-61541-1. Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics
Vaishali P Waman[SUP] 1 [/SUP], Paul Ashford[SUP] 1 [/SUP], Su Datt Lam[SUP] 2 [/SUP], Neeladri Sen[SUP] 1 [/SUP], Mahnaz Abbasian[SUP] 1 [/SUP], Laurel Woodridge[SUP] 1 [/SUP], Yonathan Goldtzvik[SUP] 1 [/SUP], Nicola Bordin[SUP] 1 [/SUP], Jiaxin Wu[SUP] 1 [/SUP], Ian Sillitoe[SUP] 1 [/SUP], Christine A Orengo[SUP] 3 [/SUP]
Affiliations
The COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing these differences are unclear and whilst socioeconomic and cultural differences are likely to be important, human genetic factors could influence susceptibility. Experimental studies indicate SARS-CoV-2 uses innate immune suppression as a strategy to speed-up entry and replication into the host cell. Therefore, it is necessary to understand the impact of variants in immunity-associated human proteins on susceptibility to COVID-19. In this work, we analysed missense coding variants in several SARS-CoV-2 proteins and their human protein interactors that could enhance binding affinity to SARS-CoV-2. We curated a dataset of 19 SARS-CoV-2: human protein 3D-complexes, from the experimentally determined structures in the Protein Data Bank and models built using AlphaFold2-multimer, and analysed the impact of missense variants occurring in the protein-protein interface region. We analysed 468 missense variants from human proteins and 212 variants from SARS-CoV-2 proteins and computationally predicted their impacts on binding affinities for the human viral protein complexes. We predicted a total of 26 affinity-enhancing variants from 13 human proteins implicated in increased binding affinity to SARS-CoV-2. These include key-immunity associated genes (TOMM70, ISG15, IFIH1, IFIT2, RPS3, PALS1, NUP98, AXL, ARF6, TRIMM, TRIM25) as well as important spike receptors (KREMEN1, AXL and ACE2). We report both common (e.g., Y13N in IFIH1) and rare variants in these proteins and discuss their likely structural and functional impact, using information on known and predicted functional sites. Potential mechanisms associated with immune suppression implicated by these variants are discussed. Occurrence of certain predicted affinity-enhancing variants should be monitored as they could lead to increased susceptibility and reduced immune response to SARS-CoV-2 infection in individuals/populations carrying them. Our analyses aid in understanding the potential impact of genetic variation in immunity-associated proteins on COVID-19 susceptibility and help guide drug-repurposing strategies.
Keywords: CATH database; COVID-19; Functional family; Human genetic variation; Immunity; Protein binding affinity prediction; Protein structure complex; SARS-CoV-2: human protein interaction.
. 2024 Jun 20;14(1):14208.
doi: 10.1038/s41598-024-61541-1. Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics
Vaishali P Waman[SUP] 1 [/SUP], Paul Ashford[SUP] 1 [/SUP], Su Datt Lam[SUP] 2 [/SUP], Neeladri Sen[SUP] 1 [/SUP], Mahnaz Abbasian[SUP] 1 [/SUP], Laurel Woodridge[SUP] 1 [/SUP], Yonathan Goldtzvik[SUP] 1 [/SUP], Nicola Bordin[SUP] 1 [/SUP], Jiaxin Wu[SUP] 1 [/SUP], Ian Sillitoe[SUP] 1 [/SUP], Christine A Orengo[SUP] 3 [/SUP]
Affiliations
- PMID: 38902252
- DOI: 10.1038/s41598-024-61541-1
The COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing these differences are unclear and whilst socioeconomic and cultural differences are likely to be important, human genetic factors could influence susceptibility. Experimental studies indicate SARS-CoV-2 uses innate immune suppression as a strategy to speed-up entry and replication into the host cell. Therefore, it is necessary to understand the impact of variants in immunity-associated human proteins on susceptibility to COVID-19. In this work, we analysed missense coding variants in several SARS-CoV-2 proteins and their human protein interactors that could enhance binding affinity to SARS-CoV-2. We curated a dataset of 19 SARS-CoV-2: human protein 3D-complexes, from the experimentally determined structures in the Protein Data Bank and models built using AlphaFold2-multimer, and analysed the impact of missense variants occurring in the protein-protein interface region. We analysed 468 missense variants from human proteins and 212 variants from SARS-CoV-2 proteins and computationally predicted their impacts on binding affinities for the human viral protein complexes. We predicted a total of 26 affinity-enhancing variants from 13 human proteins implicated in increased binding affinity to SARS-CoV-2. These include key-immunity associated genes (TOMM70, ISG15, IFIH1, IFIT2, RPS3, PALS1, NUP98, AXL, ARF6, TRIMM, TRIM25) as well as important spike receptors (KREMEN1, AXL and ACE2). We report both common (e.g., Y13N in IFIH1) and rare variants in these proteins and discuss their likely structural and functional impact, using information on known and predicted functional sites. Potential mechanisms associated with immune suppression implicated by these variants are discussed. Occurrence of certain predicted affinity-enhancing variants should be monitored as they could lead to increased susceptibility and reduced immune response to SARS-CoV-2 infection in individuals/populations carrying them. Our analyses aid in understanding the potential impact of genetic variation in immunity-associated proteins on COVID-19 susceptibility and help guide drug-repurposing strategies.
Keywords: CATH database; COVID-19; Functional family; Human genetic variation; Immunity; Protein binding affinity prediction; Protein structure complex; SARS-CoV-2: human protein interaction.