Dataset Information

Recognition through GRP78 is enhanced in the UK, South African, and Brazilian variants of SARS-CoV-2; An in silico perspective.

ABSTRACT: New SARS-CoV-2 variants emerged in the United Kingdom and South Africa in December 2020 in concomitant with the Brazillian variant in February 2021 (B.1.1.248 lineage) and currently sparking worldwide during the last few months. The new strain 501.V2 in South Africa bears three mutations in the spike receptor-binding domain (RBD); K417 N, E484K, and N501Y, while the Brazilian B.1.1.248 lineage has 12 mutations. In the current study, we simulate the complex ACE2-SARS-CoV-2 spike RBD system in which the RBD is in the wild-type and mutated isoforms. Additionally, the cell-surface Glucose Regulated Protein 78 (CS-GRP78) associated with the ACE2-SARS-CoV-2 spike RBD complex (ACE2-S RBD) is modeled at the presence of these mutant variants of the viral spike. The results showed that E484K and N501Y are critical in viral spike recognition through either ACE2 or CS-GRP78. The mutated variants (the UK, South African, and Brazilian) of the spike RBD tightly bind to GRP78 more than in the case of the wild-type RBD. These results point to the potent role of GRP78 with ACE2 in the attachment of the new variants, which could be a key for the design of inhibitors to block SARS-CoV-2 attachment and entry to the host cell.

SUBMITTER: Ibrahim IM

PROVIDER: S-EPMC8139235 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundWomen of childbearing age feel great about giving birth, but the pain could be excruciating depending on their pain tolerances. Midwives requires obstetrical knowledge and skills such as pain management during labour and safety. We explored midwives' perspectives on the utilisation of pharmacological pain alleviation interventions during labour in selected hospitals in Matjhabeng Municipality, Free State province, South Africa. A qualitative study was undertaken, involving a sample of ten midwives, using a semi-structured interview guide. The interviews were audio-recorded and transcribed verbatim. Tesch's open coding data analysis method was applied to analyse the data. The midwives were restricted to use Pethidine and Phenergan prescribed by doctors for labour pain relief, which disrupted labour pain management and obliged them either to wait for a physician or follow telephone instructions. According to the midwives, women taking Pethidine and Phenergan encountered adverse effects and discomfort. Midwives identified high workload, inadequate personnel, lack of skill and knowledge, lack of medication availability, and lack of infrastructure as the primary challenges of administering pharmacological methods to women in labour. The lack of standing orders, which delays the administration of medications pending a physician's prescription, constituted an additional difficulty. In the instance that Pethidine and Phenergan were unavailable or ineffective for some women, the midwives recommended that women be administered alternative pharmacological pain relievers. They also advocated for institutionalization of pharmacological guidelines allowing them to use their discretion when treating labour pain. Midwives can only utilise a few standardised and regulated pharmacological medications for labour pain management. The midwives' ability to administer pharmacological pain relief during labour was hampered by a high workload burden, insufficient staff, lack of skill and understanding, drug unavailability, and inadequate infrastructure. Midwives advocated for supported guidelines that would allow them to treat labour pain at their discretion. Intersectoral stakeholders are required to improve midwife skills and attitudes. Health facilities need to train and supply analgesics to midwives. Midwives ought to be familiar with pharmacological pain relievers.

Project description:BackgroundEthnicity data collection has been proven to be important in health care but despite government initiatives remains incomplete and mostly un-validated in the UK. Accurate self-reported ethnicity data would enable experts to assess inequalities in health and access to services and help to ensure resources are targeted appropriately. The aim of this paper is to explore the reasons for the observed gap in ethnicity data by examining the perceptions and experiences of healthy South Asian volunteers. South Asians are the largest ethnic minority group accounting for 50% of all ethnic minorities in the UK 2001 census.MethodsFive focus groups, conducted by trained facilitators in the native language of each group, recruited 36 South Asian volunteers from local community centres and places of worship. The topic guide focused on five key areas:1) general opinions on the collection of ethnicity, 2) experiences of providing ethnicity information, 3) categories used in practice, 4) opinions of other indicators of ethnicity e.g. language, religion and culture and 5) views on how should this information be collected. The translated transcripts were analysed using a qualitative thematic approach.ResultsThe findings of this Cancer Research UK commissioned study revealed that participants felt that accurate recording of ethnicity data was important in healthcare with several stating the increased prevalence of certain diseases in minority ethnic groups as an appropriate justification to improve this data. The overwhelming majority raised no objections to providing this data when the purpose of data collection is fully explained.ConclusionsThis study confirmed that the collection of patients' ethnicity data is deemed important by potential patients but there remains uncertainty and unease as to how the data may be used. A common theme running through the focus groups was the willingness to provide these data, strongly accompanied by a desire to have more information with regard to its use.

Dataset Information

Recognition through GRP78 is enhanced in the UK, South African, and Brazilian variants of SARS-CoV-2; An in silico perspective.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets