Identification of promising high-affinity inhibitors of SARS-CoV-2 main protease from African Natural Products Databases by Virtual Screening (preprint)

With the rapid spread of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen agent of COVID-19 pandemic created a serious threat to global public health, requiring the most urgent research for potential therapeutic agents. The availability of genomic data of SARS-CoV-2 and efforts to determine the protein structure of the virus facilitated the identification of potent inhibitors by using structure-based approach and bioinformatics tools. Many pharmaceuticals have been proposed for the treatment of COVID-19, although their effectiveness has not been assessed yet. However, it is important to find out new-targeted drugs to overcome the resistance concern. Several viral proteins such as proteases, polymerases or structural proteins have been considered as potential therapeutic targets. But the virus target must be essential for host invasion match some drugability criterion. In this Work, we selected the highly validated pharmacological target main protease Mpro and we performed high throughput virtual screening of African Natural Products Databases such as NANPDB, EANPDB, AfroDb, and SANCDB to identify the most potent inhibitors with the best pharmacological properties. In total, 8753 natural compounds were virtually screened by AutoDock vina against the main protease of SARS-CoV-2. Two hundred and five (205) compounds showed high-affinity scores (less than − 10.0 Kcal/mol), while fifty-eight (58) filtered through Lipinski’s rules showed better affinity than known Mpro inhibitors (i.e., ABBV-744, Onalespib, Daunorubicin, Alpha-ketoamide, Perampanel, Carprefen, Celecoxib, Alprazolam, Trovafloxacin, Sarafloxacin, Ethyl biscoumacetate…). Those promising compounds could be considered for further investigations toward the developpement of SARS-CoV-2 drug development.

Genomic Determinants of Long COVID (preprint)

Around 5–10% of adults may experience persistence of symptoms/signs beyond 4 to 12 weeks after acute SARS-CoV-2 infection. According to the World Health Organization, up to 40 million people suffer from Long COVID in Europe and the USA alone. The Centers for Disease Control and Prevention have encouraged the recognition of predictors for Long COVID. Any genetic markers associated to the disease have remained elusive to date. Here we explore the potential contribution of genetic traits to Long COVID. We used a well characterized cohort of 50 individuals with definitive diagnostic criteria for Long COVID from an initial set of patients of more than 1,200 with suspected Long COVID. All were attended at Hospital Puerta de Hierro, a large regional hospital in Madrid, Spain. All subjects had tested positive for SARS-CoV-2 RNA and/or antibodies, showed clinical manifestations for more than 6 months, and developed more than 5 persistent symptoms/signs. Low pass whole genome sequencing was performed in blood specimens for our selected cohort. From hundreds of polygenic risk scores (PRS) recorded at the PGS Catalog, we tested in our selected cohort a total of 12 PRS that passed our filtering criteria. Selected PRS encompassed distinct medical conditions, including cancers, hematologic, cardiovascular, endocrine, immunologic and neurological disorders. The calculated PRS in our patients produced a distribution of scores that was compared to a control ancestry-matched general population. We found significant differences for the PRS of traits ‘Tiredness/lethargy in the last 2 weeks’ and suggestive significance for ‘Depression’ when comparing Long COVID patients and controls. Our results strongly support a genetic susceptibility for Long COVID, with those scoring high in genetic predisposition for ‘tiredness’ as more likely to develop the disease. Results shed new light into the physiopathological basis for Long COVID, contrary to opinions considering it a subjective condition.

High-resolution African HLA resource uncoversHLA-DRB1expression effects underlying vaccine response (preprint)

How human genetic variation contributes to vaccine immunogenicity and effectiveness is unclear, particularly in infants from Africa. We undertook genome-wide association analyses of eight vaccine antibody responses in 2,499 infants from three African countries and identified significant associations across the human leukocyte antigen (HLA) locus for five antigens spanning pertussis, diphtheria and hepatitis B vaccines. Using high-resolution HLA typing in 1,706 individuals from 11 African populations we constructed a continental imputation resource to fine-map signals of association across the class II HLA observing genetic variation explaining up to 10% of the observed variance in antibody responses. Using follicular helper T-cell assays, in silico binding, and immune cell eQTL datasets we find evidence of HLA-DRB1 expression correlating with serological response and inferred protection from pertussis following vaccination. This work improves our understanding of molecular mechanisms underlying HLA associations that should support vaccine design and development across Africa with wider global relevance. Teaser High-resolution typing of HLA diversity provides mechanistic insights into differential potency and inferred effectiveness of vaccines across Africa.

Inhibition of SARS-COV-2 Receptor-Binding domain/ACE2 by Bazedoxifene (preprint)

Coronavirus spike glycoprotein (GP)-Receptor Binding Domain (RBD) and its interaction with host receptor angiotensin converting enzyme 2 (ACE2) is one of the most structurally understood but therapeutically untapped aspect of COVID-19 pathogenesis. In this study, Fragment-based lead discovery was conducted to identify potential lead anti-SARS-COV-2 drug candidate acting at RBD/ACE2 interface. From the original 12000 chemical building blocks, benzimidazole (BAZ) scaffold was identified. Fingerprint-based similarity search of the FDA-approved drug library for BAZ-containing compounds identified 12 drugs with the benzimidazole-like substructure. When these compounds were re—docked into GP/ACE2 interface, the consensus docking identified bazedoxifene as the hit. In vitro RBD/ACE2 inhibition kinetics showed micromolar IC50 value (1.237 μM) in the presence of bazedoxifene. Molecular dynamics simulation of RBD/ACE2 in the presence BAZ resulted in loss of contact and specific hydrogen-bond interaction required for RBD/ACE2 stability. Taken together, these findings identified benzimidazole scaffold as a building block for developing novel RBD/ACE2 complex inhibitor and provided mechanistic basis for the use of bazedoxifene as a repurposable drug for the treatment of COVID-19 acting at RBD/ACE2 interface.

SARS-CoV-2 Omicron Spike Glycoprotein Receptor Binding Domain Exhibits Super-Binder Ability with ACE2 but not Convalescent Monoclonal Antibody (preprint)

BackgroundSARS-CoV-2, the causative virus for COVID-19 has now super-mutated into the Omicron (Om) variant. On its spike glycoprotein alone, more than 30 substitutions have been characterized with 15 within the receptor binding domain (RBD); It therefore calls to question the transmissibility and antibody escapability of Omicron. This study was setup to investigate the Omicron RBDs interaction with ACE2 (host receptor) and a SARS-CoV-2 neutralizing monoclonal antibody (mAb). MethodsIn-silico mutagenesis was used to generate the Om-RBD in complex with ACE2 or mAb from the wildtype. All-atom molecular dynamics (MD) simulation trajectories were analyzed for interaction. ResultsMD trajectories showed that Omicron RBD has evolved into an efficient ACE2 binder, via pi-pi (Om-RBD-Y501/ACE2-Y41) and salt-bridge (Om-RBD-K493/ACE2-Y41) interactions. Conversely, in binding mAb, it has become less efficient (Center of mass distance of RBD from mAb complex, wildtype {approx} 30 [A], Omicron {approx} 41 [A]). Disruption of Om-RBD/mAb complex resulted from loose interaction between Om-RBD and the light chain complementarity-determining region residues. ConclusionsOmicron is expected to be better transmissible and less efficiently interacting with neutralizing convalescent mAbs. General significanceOur results elucidate the mechanisms for higher transmissibility in Omicron variant.

Cardiometabolic traits, sepsis and severe covid-19 with respiratory failure: a Mendelian randomization investigation (preprint)

ObjectivesTo investigate whether there is a causal effect of cardiometabolic traits on risk of sepsis and severe covid-19. DesignMendelian randomisation analysis. SettingUK Biobank and HUNT study population-based cohorts for risk of sepsis, and genome-wide association study summary data for risk of severe covid-19 with respiratory failure. Participants12,455 sepsis cases (519,885 controls) and 1,610 severe covid-19 with respiratory failure cases (2,205 controls). ExposureGenetic variants that proxy body mass index (BMI), lipid traits, systolic blood pressure, lifetime smoking score, and type 2 diabetes liability - derived from studies considering between 188,577 to 898,130 participants. Main outcome measuresRisk of sepsis and severe covid-19 with respiratory failure. ResultsHigher genetically proxied BMI and lifetime smoking score were associated with increased risk of sepsis in both UK Biobank (BMI: odds ratio 1.38 per standard deviation increase, 95% confidence interval [CI] 1.27 to 1.51; smoking: odds ratio 2.81 per standard deviation increase, 95% CI 2.09-3.79) and HUNT (BMI: 1.41, 95% CI 1.18 to 1.69; smoking: 1.93, 95% CI 1.02-3.64). Higher genetically proxied BMI and lifetime smoking score were also associated with increased risk of severe covid-19, although with wider confidence intervals (BMI: 1.75, 95% CI 1.20 to 2.57; smoking: 3.94, 95% CI 1.13 to 13.75). There was limited evidence to support associations of genetically proxied lipid traits, systolic blood pressure or type 2 diabetes liability with risk of sepsis or severe covid-19. Similar findings were generally obtained when using Mendelian randomization methods that are more robust to the inclusion of pleiotropic variants, although the precision of estimates was reduced. ConclusionsOur findings support a causal effect of elevated BMI and smoking on risk of sepsis and severe covid-19. Clinical and public health interventions targeting obesity and smoking are likely to reduce sepsis and covid-19 related morbidity, along with the plethora of other health-related outcomes that these traits adversely affect. Summary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LISepsis and severe covid-19 are major contributors to global morbidity and mortality. C_LIO_LICardiometabolic risk factors have been associated with risk of sepsis and severe covid-19, but it is unclear if they are having causal effects. C_LI What this study addsO_LIUsing Mendelian randomization analyses, this study provides evidence to support that higher body mass index and lifetime smoking score both increase risk of sepsis and severe covid-19 with respiratory failure. C_LIO_LIClinical and public health interventions targeting obesity and smoking are likely to reduce sepsis and covid-19 related morbidity, along with the plethora of other health-related outcomes that these traits adversely affect. C_LI