The γ-aminobutyric acid type A receptor (GABA (A) receptor) is a membrane protein activated by the neurotransmitter GABA. Structurally, this major inhibitory neurotransmitter receptor in the human central nervous system is a pentamer that can be built from a selection of 19 subunits consisting of α(1,2,3,4,5 or 6), β (1,2 or 3), γ (1,2 or 3), ρ (1,2 or 3), and δ, π, θ, and ε. This creates several possible pentameric arrangements, which also influence the pharmacological and physiological properties of the receptor. The complexity and heterogeneity of the receptors are further increased by the addition of short and long splice variants in several subunits and the existence of multiple allosteric binding sites and expansive ligands that can bind to the receptors. Therefore, a comprehensive understanding of the structure and function of the receptors is required to gain novel insights into the consequences of receptor dysfunction and subsequent drug development studies. Notably, advancements in computational-aided studies have facilitated the elucidation of residual interactions and exploring energy binding, which may otherwise be challenging to investigate. In this review, we aim to summarize the current understanding of the structure and function of GABA (A) receptors obtained from advancements in computational-aided applications.
Genomic surveillance is crucial for tracking emergence and spread of novel variants of pathogens, such as SARS-CoV-2, to inform public health interventions and to enforce control measures. However, in some settings especially in low- and middle- income counties, where sequencing platforms are limited, only certain patients get to be selected for sequencing surveillance. Here, we show that patients with multiple comorbidities potentially harbour SARS-CoV-2 with higher mutation rates and thus deserve more attention for genomic surveillance. The relationship between the patient comorbidities, and type of amino acid mutations was assessed. Correlation analysis showed that there was a significant tendency for mutations to occur within the ORF1a region for patients with higher number of comorbidities. Frequency analysis of the amino acid substitution within ORF1a showed that nsp3 P822L of the PLpro protease was one of the highest occurring mutations. Using molecular dynamics, we simulated that the P822L mutation in PLpro represents a system with lower Root Mean Square Deviation (RMSD) fluctuations, and consistent Radius of gyration (Rg), Solvent Accessible Surface Area (SASA) values-indicate a much stabler protein than the wildtype. The outcome of this study will help determine the relationship between the clinical status of a patient and the mutations of the infecting SARS-CoV-2 virus.