ABSTRACT
The ability to estimate protein-protein binding free energy in a computationally efficient via a physics-based approach is beneficial to research focused on the mechanism of viruses binding to their target proteins. Implicit solvation methodology may be particularly useful in the early stages of such research, as it can offer valuable insights into the binding process, quickly. Here we evaluate the potential of the related molecular mechanics generalized Born surface area (MMGB/SA) approach to estimate the binding free energy {Delta}Gbind between the SARS-CoV-2 spike receptor-binding domain and the human ACE2 receptor. The calculations are based on a recent flavor of the generalized Born model, GBNSR6. Two estimates of {Delta}Gbind are performed: one based on standard bondi radii, and the other based on a newly developed set of atomic radii (OPT1), optimized specifically for protein-ligand binding. We take the average of the resulting two {Delta}Gbind values as the consensus estimate. For the well-studied Ras-Raf protein-protein complex, which has similar binding free energy to that of the SARS-CoV-2/ACE2 complex, the consensus {Delta}Gbind = -11.8 {+/-} 1 kcal/mol, vs. experimental -9.7 {+/-} 0.2 kcal/mol. The consensus estimates for the SARS-CoV-2/ACE2 complex is {Delta}Gbind = -9.4 {+/-} 1.5 kcal/mol, which is in near quantitative agreement with experiment (-10.6 kcal/mol). The availability of a conceptually simple MMGB/SA-based protocol for analysis of the SARS-CoV-2 /ACE2 binding may be beneficial in light of the need to move forward fast.
ABSTRACT
BackgroundThis study aimed to describe the population at risk of severe COVID-19 due to underlying health conditions across the United Kingdom in 2019. MethodsWe used anonymised electronic health records from the Clinical Practice Research Datalink GOLD to describe the point prevalence on 5 March 2019 of the at-risk population following national guidance. Prevalence for any risk condition and for each individual condition is given overall and stratified by age and region. We repeated the analysis on 5 March 2014 for full regional representation and to describe prevalence of underlying health conditions in pregnancy. We additionally described the population of cancer survivors, and assessed the value of linked secondary care records for ascertaining COVID-19 at-risk status. FindingsOn 5 March 2019, 24{middle dot}4% of the UK population were at risk due to a record of at least one underlying health condition, including 8{middle dot}3% of school-aged children, 19{middle dot}6% of working-aged adults, and 66{middle dot}2% of individuals aged 70 years or more. 7{middle dot}1% of the population had multimorbidity. The size of the at-risk population was stable over time comparing 2014 to 2019, despite increases in chronic liver disease and diabetes and decreases in chronic kidney disease and current asthma. Separately, 1{middle dot}6% of the population had a new diagnosis of cancer in the past five years. InterpretationThe population at risk of severe COVID-19 (aged [≥]70 years, or with an underlying health condition) comprises 18.5 million individuals in the UK, including a considerable proportion of school-aged and working-aged individuals. FundingNIHR HPRU in Immunisation Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Pubmed for peer-reviewed articles, preprints, and research reports on the size and distribution of the population at risk of severe COVID. We used the terms (1) risk factor or co-morbidity or similar (2) COVID or SARS or similar and (3) prevalence to search for studies aiming to quantify the COVID-19 at-risk UK population published in the previous year to 19 July 2020, with no language restrictions. We found one study which modelled prevalence of risk factors based on the Global Burden of Disease (which included the UK) and one study which estimated that 8.4 million individuals aged [≥]30 years in the UK were at risk based on prevalence of a subset of relevant conditions in England. There were no studies which described the complete COVID-19 at-risk population across the UK. Added value of this studyWe used a large, nationally-representative dataset based on electronic health records to estimate prevalence of increased risk of severe COVID-19 across the United Kingdom, including all conditions in national guidance. We stratified by age, sex and region to enable regionally-tailored prediction of COVID-19-related healthcare burden and interventions to reduce transmission of infection, and planning and modelling of vaccination of the at-risk population. We also quantified the value of linked secondary care records to supplement primary care records. Implications of all the available evidenceIndividuals at moderate or high risk of severe COVID-19 according to current national guidance (aged [≥]70 years, or with a specified underlying health condition) comprise 18{middle dot}5 million individuals in the United Kingdom, rather than the 8.43 million previously estimated. The 8{middle dot}3% of school-aged children and 19{middle dot}6% of working-aged adults considered at-risk according to national guidance emphasises the need to consider younger at-risk individuals in shielding policies and when re-opening schools and workplaces, but also supports prioritising vaccination based on age and condition-specific mortality risk, rather than targeting all individuals with underlying conditions, who form a large population even among younger age groups. Among individuals aged [≥]70 years, 66{middle dot}2% had at least one underlying health condition, suggesting an age-targeted approach to vaccination may efficiently target individuals at risk of severe COVID-19. These national estimates broadly support the use of Global Burden of Disease modelled estimates and age-targeted vaccination strategies in other countries.
Subject(s)
COVID-19ABSTRACT
Electronic health records were used to assess the early impact of COVID-19 on routine childhood vaccination in England to 26 April 2020. MMR vaccination counts fell from February 2020, and in the three weeks after introduction of social distancing measures were 19.8% lower (95% CI -20.7 to -18.9%) than the same period in 2019, before improving in mid-April. A gradual decline in hexavalent vaccination counts throughout 2020 was not accentuated on introduction of social distancing.