Structural insights into the effect of mutations in the spike protein of SARS-CoV-2 on the binding with human furin protein.

The SARS COV-2 and its variants are spreading around the world at an alarming speed, due to its higher transmissibility and the conformational changes caused by mutations. The resulting COVID-19 pandemic has imposed severe health consequences on human health. Several countries of the world including Pakistan have studied its genome extensively and provided productive findings. In the current study, the mCSM, DynaMut2, and I-Mutant servers were used to analyze the effect of identified mutations on the structural stability of spike protein however, the molecular docking and simulations approaches were used to evaluate the dynamics of the bonding network between the wild-type and mutant spike proteins with furin. We addressed the mutational modifications that have occurred in the spike protein of SARS-COV-2 that were found in 215 Pakistani's isolates of COVID-19 patients to study the influence of mutations on the stability of the protein and its interaction with the host cell. We found 7 single amino acid substitute mutations in various domains that reside in spike protein. The H49Y, N74K, G181V, and G446V were found in the S1 domain while the D614A, V622F, and Q677H mutations were found in the central helices of the spike protein. Based on the observation, G181V, G446V, D614A, and V622F mutants were found highly destabilizing and responsible for structural perturbation. Protein-protein docking and molecular simulation analysis with that of furin have predicted that all the mutants enhanced the binding efficiency however, the V622F mutant has greatly altered the binding capacity which is further verified by the KD value (7.1 E-14) and therefore may enhance the spike protein cleavage by Furin and increase the rate of infectivity by SARS-CoV-2. On the other hand, the total binding energy for each complex was calculated which revealed -50.57 kcal/mol for the wild type, for G181V -52.69 kcal/mol, for G446V -56.44 kcal/mol, for D614A -59.78 kcal/mol while for V622F the TBE was calculated to be -85.84 kcal/mol. Overall, the current finding shows that these mutations have increased the binding of Furin for spike protein and shows that D614A and V622F have significant effects on the binding and infectivity.

Structural insights into the effect of mutations in the spike protein of SARS-CoV-2 on the binding with human furin protein

The SARS COV-2 and its variants are spreading around the world at an alarming speed, due to its higher transmissibility and the conformational changes caused by mutations. The resulting COVID-19 pandemic has imposed severe health consequences on human health. Several countries of the world including Pakistan have studied its genome extensively and provided productive findings. In the current study, the mCSM, DynaMut2, and I-Mutant servers were used to analyze the effect of identified mutations on the structural stability of spike protein however, the molecular docking and simulations approaches were used to evaluate the dynamics of the bonding network between the wild-type and mutant spike proteins with furin. We addressed the mutational modifications that have occurred in the spike protein of SARS-COV-2 that were found in 215 Pakistani's isolates of COVID-19 patients to study the influence of mutations on the stability of the protein and its interaction with the host cell. We found 7 single amino acid substitute mutations in various domains that reside in spike protein. The H49Y, N74K, G181V, and G446V were found in the S1 domain while the D614A, V622F, and Q677H mutations were found in the central helices of the spike protein. Based on the observation, G181V, G446V, D614A, and V622F mutants were found highly destabilizing and responsible for structural perturbation. Protein-protein docking and molecular simulation analysis with that of furin have predicted that all the mutants enhanced the binding efficiency however, the V622F mutant has greatly altered the binding capacity which is further verified by the KD value (7.1 E−14) and therefore may enhance the spike protein cleavage by Furin and increase the rate of infectivity by SARS-CoV-2. On the other hand, the total binding energy for each complex was calculated which revealed −50.57 kcal/mol for the wild type, for G181V −52.69 kcal/mol, for G446V −56.44 kcal/mol, for D614A −59.78 kcal/mol while for V622F the TBE was calculated to be −85.84 kcal/mol. Overall, the current finding shows that these mutations have increased the binding of Furin for spike protein and shows that D614A and V622F have significant effects on the binding and infectivity.

Predictors and outcomes of acute pulmonary embolism in COVID-19; insights from US National COVID cohort collaborative.

OBJECTIVES: To investigate whether COVID-19 patients with pulmonary embolism had higher mortality and assess the utility of D-dimer in predicting acute pulmonary embolism. PATIENTS AND METHODS: Using the National Collaborative COVID-19 retrospective cohort, a cohort of hospitalized COVID-19 patients was studied to compare 90-day mortality and intubation outcomes in patients with and without pulmonary embolism in a multivariable cox regression analysis. The secondary measured outcomes in 1:4 propensity score-matched analysis included length of stay, chest pain incidence, heart rate, history of pulmonary embolism or DVT, and admission laboratory parameters. RESULTS: Among 31,500 hospitalized COVID-19 patients, 1117 (3.5%) patients were diagnosed with acute pulmonary embolism. Patients with acute pulmonary embolism were noted to have higher mortality (23.6% vs.12.8%; adjusted Hazard Ratio (aHR) = 1.36, 95% CI [1.20-1.55]), and intubation rates (17.6% vs. 9.3%, aHR = 1.38[1.18-1.61]). Pulmonary embolism patients had higher admission D-dimer FEU (Odds Ratio(OR) = 1.13; 95%CI [1.1-1.15]). As the D-dimer value increased, the specificity, positive predictive value, and accuracy of the test increased; however, sensitivity decreased (AUC 0.70). At cut-off D-dimer FEU 1.8 mcg/ml, the test had clinical utility (accuracy 70%) in predicting pulmonary embolism. Patients with acute pulmonary embolism had a higher incidence of chest pain and history of pulmonary embolism or deep vein thrombosis. CONCLUSIONS: Acute pulmonary embolism is associated with worse mortality and morbidity outcomes in COVID-19. We present D-dimer as a predictive risk tool in the form of a clinical calculator for the diagnosis of acute pulmonary embolism in COVID-19.

Pharmacotherapeutic Potential of Natural Products to Target the SARS-CoV-2 PLpro Using Molecular Screening and Simulation Approaches.

Because of the essential role of PLpro in the regulation of replication and dysregulation of the host immune sensing, it is considered a therapeutic target for novel drug development. To reduce the risk of immune evasion and vaccine effectiveness, small molecular therapeutics are the best complementary approach. Hence, we used a structure-based drug-designing approach to identify potential small molecular inhibitors for PLpro of SARS-CoV-2. Initial scoring and re-scoring of the best hits revealed that three compounds NPC320891 (2,2-Dihydroxyindene-1,3-Dione), NPC474594 (Isonarciclasine), and NPC474595 (7-Deoxyisonarciclasine) exhibit higher docking scores than the control GRL0617. Investigation of the binding modes revealed that alongside the essential contacts, i.e., Asp164, Glu167, Tyr264, and Gln269, these molecules also target Lys157 and Tyr268 residues in the active site. Moreover, molecular simulation demonstrated that the reported top hits also possess stable dynamics and structural packing. Furthermore, the residues' flexibility revealed that all the complexes demonstrated higher flexibility in the regions 120-140, 160-180, and 205-215. The 120-140 and 160-180 lie in the finger region of PLpro, which may open/close during the simulation to cover the active site and push the ligand inside. In addition, the total binding free energy was reported to be - 32.65 ± 0.17 kcal/mol for the GRL0617-PLpro, for the NPC320891-PLpro complex, the TBE was - 35.58 ± 0.14 kcal/mol, for the NPC474594-PLpro, the TBE was - 43.72 ± 0.22 kcal/mol, while for NPC474595-PLpro complex, the TBE was calculated to be - 41.61 ± 0.20 kcal/mol, respectively. Clustering of the protein's motion and FEL further revealed that in NPC474594 and NPC474595 complexes, the drug was seen to have moved inside the binding cavity along with the loop in the palm region harboring the catalytic triad, thus justifying the higher binding of these two molecules particularly. In conclusion, the overall results reflect favorable binding of the identified hits strongly than the control drug, thus demanding in vitro and in vivo validation for clinical purposes.

Mutational analysis of the spike protein of SARS-COV-2 isolates revealed atomistic features responsible for higher binding and infectivity.

Introduction: The perpetual appearance of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2), and its new variants devastated the public health and social fabric around the world. Understanding the genomic patterns and connecting them to phenotypic attributes is of great interest to devise a treatment strategy to control this pandemic. Materials and Methods: In this regard, computational methods to understand the evolution, dynamics and mutational spectrum of SARS-CoV-2 and its new variants are significantly important. Thus, herein, we used computational methods to screen the genomes of SARS-CoV-2 isolated from Pakistan and connect them to the phenotypic attributes of spike protein; we used stability-function correlation methods, protein-protein docking, and molecular dynamics simulation. Results: Using the Global initiative on sharing all influenza data (GISAID) a total of 21 unique mutations were identified, among which five were reported as stabilizing while 16 were destabilizing revealed through mCSM, DynaMut 2.0, and I-Mutant servers. Protein-protein docking with Angiotensin-converting enzyme 2 (ACE2) and monoclonal antibody (4A8) revealed that mutation G446V in the receptor-binding domain; R102S and G181V in the N-terminal domain (NTD) significantly affected the binding and thus increased the infectivity. The interaction pattern also revealed significant variations in the hydrogen bonding, salt bridges and non-bonded contact networks. The structural-dynamic features of these mutations revealed the global dynamic trend and the finding energy calculation further established that the G446V mutation increases the binding affinity towards ACE2 while R102S and G181V help in evading the host immune response. The other mutations reported supplement these processes indirectly. The binding free energy results revealed that wild type-RBD has a TBE of -60.55 kcal/mol while G446V-RBD reported a TBE of -73.49 kcal/mol. On the other hand, wild type-NTD reported -67.77 kcal/mol of TBE, R102S-NTD reported -51.25 kcal/mol of TBE while G181V-NTD reported a TBE of -63.68 kcal/mol. Conclusions: In conclusion, the current findings revealed basis for higher infectivity and immune evasion associated with the aforementioned mutations and structure-based drug discovery against such variants.

Do the green bonds overreact to the COVID-19 pandemic?

This paper explores the impacts of the COVID-19 pandemic on the global green bond and conventional assets, including commodity, treasury, stock and clean energy markets, using Diebold and Yilmaz (2012) and Baruník and Krehlík, 2018b spillover framework. The results show that spillover transmitted from COVID-19 is relatively strong over a medium- and long-term horizon, and the spillover effects sharply increased when the pandemic became severe. Furthermore, green bonds are most affected by the COVID-19 pandemic, followed by the treasury, while the other conventional assets are only slightly affected. Additionally, our findings also contain a low-risk portfolio during COVID-19 pandemic.

Mutational analysis of the spike protein of SARS-COV-2 isolates revealed atomistic features responsible for higher binding and infectivity

Introduction: The perpetual appearance of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2), and its new variants devastated the public health and social fabric around the world. Understanding the genomic patterns and connecting them to phenotypic attributes is of great interest to devise a treatment strategy to control this pandemic. Materials and Methods: In this regard, computational methods to understand the evolution, dynamics and mutational spectrum of SARS-CoV-2 and its new variants are significantly important. Thus, herein, we used computational methods to screen the genomes of SARS-CoV-2 isolated from Pakistan and connect them to the phenotypic attributes of spike protein;we used stability-function correlation methods, protein-protein docking, and molecular dynamics simulation. Results: Using the Global initiative on sharing all influenza data (GISAID) a total of 21 unique mutations were identified, among which five were reported as stabilizing while 16 were destabilizing revealed through mCSM, DynaMut 2.0, and I-Mutant servers. Protein-protein docking with Angiotensin-converting enzyme 2 (ACE2) and monoclonal antibody (4A8) revealed that mutation G446V in the receptor-binding domain;R102S and G181V in the N-terminal domain (NTD) significantly affected the binding and thus increased the infectivity. The interaction pattern also revealed significant variations in the hydrogen bonding, salt bridges and non-bonded contact networks. The structural-dynamic features of these mutations revealed the global dynamic trend and the finding energy calculation further established that the G446V mutation increases the binding affinity towards ACE2 while R102S and G181V help in evading the host immune response. The other mutations reported supplement these processes indirectly. The binding free energy results revealed that wild type-RBD has a TBE of −60.55 kcal/mol while G446V-RBD reported a TBE of −73.49 kcal/mol. On the other hand, wild type-NTD reported −67.77 kcal/mol of TBE, R102S-NTD reported −51.25 kcal/mol of TBE while G181V-NTD reported a TBE of −63.68 kcal/mol. Conclusions: In conclusion, the current findings revealed basis for higher infectivity and immune evasion associated with the aforementioned mutations and structure-based drug discovery against such variants.

Roles and functions of SARS-CoV-2 proteins in host immune evasion.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evades the host immune system through a variety of regulatory mechanisms. The genome of SARS-CoV-2 encodes 16 non-structural proteins (NSPs), four structural proteins, and nine accessory proteins that play indispensable roles to suppress the production and signaling of type I and III interferons (IFNs). In this review, we discussed the functions and the underlying mechanisms of different proteins of SARS-CoV-2 that evade the host immune system by suppressing the IFN-ß production and TANK-binding kinase 1 (TBK1)/interferon regulatory factor 3 (IRF3)/signal transducer and activator of transcription (STAT)1 and STAT2 phosphorylation. We also described different viral proteins inhibiting the nuclear translocation of IRF3, nuclear factor-κB (NF-κB), and STATs. To date, the following proteins of SARS-CoV-2 including NSP1, NSP6, NSP8, NSP12, NSP13, NSP14, NSP15, open reading frame (ORF)3a, ORF6, ORF8, ORF9b, ORF10, and Membrane (M) protein have been well studied. However, the detailed mechanisms of immune evasion by NSP5, ORF3b, ORF9c, and Nucleocapsid (N) proteins are not well elucidated. Additionally, we also elaborated the perspectives of SARS-CoV-2 proteins.

Infectious disease and corporate activities

We investigate the effect of equity market volatility due to infectious disease on U.S. firms’ corporate activities from 1985 to 2020. Consistent with the theoretical framework, firms decrease their debt levels, debt maturity, corporate investments and dividend payout, and increase their cash holdings, research and development expenditure.

Roles and functions of SARS-CoV-2 proteins in host immune evasion

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evades the host immune system through a variety of regulatory mechanisms. The genome of SARS-CoV-2 encodes 16 non-structural proteins (NSPs), four structural proteins, and nine accessory proteins that play indispensable roles to suppress the production and signaling of type I and III interferons (IFNs). In this review, we discussed the functions and the underlying mechanisms of different proteins of SARS-CoV-2 that evade the host immune system by suppressing the IFN-β production and TANK-binding kinase 1 (TBK1)/interferon regulatory factor 3 (IRF3)/signal transducer and activator of transcription (STAT)1 and STAT2 phosphorylation. We also described different viral proteins inhibiting the nuclear translocation of IRF3, nuclear factor-κB (NF-κB), and STATs. To date, the following proteins of SARS-CoV-2 including NSP1, NSP6, NSP8, NSP12, NSP13, NSP14, NSP15, open reading frame (ORF)3a, ORF6, ORF8, ORF9b, ORF10, and Membrane (M) protein have been well studied. However, the detailed mechanisms of immune evasion by NSP5, ORF3b, ORF9c, and Nucleocapsid (N) proteins are not well elucidated. Additionally, we also elaborated the perspectives of SARS-CoV-2 proteins.

Investigation of the binding and dynamic features of A.30 variant revealed higher binding of RBD for hACE2 and escapes the neutralizing antibody: A molecular simulation approach.

With the emergence of Delta and Omicron variants, many other important variants of SARS-CoV-2, which cause Coronavirus disease-2019, including A.30, are reported to increase the concern created by the global pandemic. The A.30 variant, reported in Tanzania and other countries, harbors spike gene mutations that help this strain to bind more robustly and to escape neutralizing antibodies. The present study uses molecular modelling and simulation-based approaches to investigate the key features of this strain that result in greater infectivity. The protein-protein docking results for the spike protein demonstrated that additional interactions, particularly two salt-bridges formed by the mutated residue Lys484, increase binding affinity, while the loss of key residues at the N terminal domain (NTD) result in a change to binding conformation with monoclonal antibodies, thus escaping their neutralizing effects. Moreover, we deeply studied the atomic features of these binding complexes through molecular simulation, which revealed differential dynamics when compared to wild type. Analysis of the binding free energy using MM/GBSA revealed that the total binding free energy (TBE) for the wild type receptor-binding domain (RBD) complex was -58.25 kcal/mol in contrast to the A.30 RBD complex, which reported -65.59 kcal/mol. The higher TBE for the A.30 RBD complex signifies a more robust interaction between A.30 variant RBD with ACE2 than the wild type, allowing the variant to bind and spread more promptly. The BFE for the wild type NTD complex was calculated to be -65.76 kcal/mol, while the A.30 NTD complex was estimated to be -49.35 kcal/mol. This shows the impact of the reported substitutions and deletions in the NTD of A.30 variant, which consequently reduce the binding of mAb, allowing it to evade the immune response of the host. The reported results will aid the development of cross-protective drugs against SARS-CoV-2 and its variants.

Blocking key mutated hotspot residues in the RBD of the omicron variant (B.1.1.529) with medicinal compounds to disrupt the RBD-hACE2 complex using molecular screening and simulation approaches† † Electronic supplementary information (ESI) available. See DOI: 10.1039/d2ra00277a

A new variant of SARS-CoV-2 known as the omicron variant (B.1.1.529) reported in South Africa with 30 mutations in the whole spike protein, among which 15 mutations are in the receptor-binding domain, is continuously spreading exponentially around the world. The omicron variant is reported to be highly contagious with antibody-escaping activity. The emergence of antibody-escaping variants is alarming, and thus the quick discovery of small molecule inhibitors is needed. Hence, the current study uses computational drug screening and molecular dynamics simulation approaches (replicated) to identify novel drugs that can inhibit the binding of the receptor-binding domain (RBD) with hACE2. Screening of the North African, East African and North-East African medicinal compound databases by employing a multi-step screening approach revealed four compounds, namely (−)-pipoxide (C1), 2-(p-hydroxybenzyl) benzofuran-6-ol (C2), 1-(4-hydroxy-3-methoxyphenyl)-2-{4-[(E)-3-hydroxy-1-propenyl]-2-methoxyphenoxy}-1,3-propanediol (C3), and Rhein (C4), with excellent anti-viral properties against the RBD of the omicron variant. Investigation of the dynamics demonstrates stable behavior, good residue flexibility profiles, and structural compactness. Validation of the top hits using computational bioactivity analysis, binding free energy calculations and dissociation constant (KD) analysis also indicated the anti-viral properties of these compounds. In conclusion, this study will help in the design and discovery of novel drug therapeutics, which may be used against the emerging omicron variant of SARS-CoV-2. A new variant of SARS-CoV-2 known as the omicron variant (B.1.1.529) reported in South Africa with 30 mutations in the whole spike protein, among which 15 mutations are in the receptor-binding domain, is continuously spreading exponentially around the world.

Global User-Level Perception of COVID-19 Contact Tracing Applications: Data-Driven Approach Using Natural Language Processing.

BACKGROUND: Contact tracing has been globally adopted in the fight to control the infection rate of COVID-19. To this aim, several mobile apps have been developed. However, there are ever-growing concerns over the working mechanism and performance of these applications. The literature already provides some interesting exploratory studies on the community's response to the applications by analyzing information from different sources, such as news and users' reviews of the applications. However, to the best of our knowledge, there is no existing solution that automatically analyzes users' reviews and extracts the evoked sentiments. We believe such solutions combined with a user-friendly interface can be used as a rapid surveillance tool to monitor how effective an application is and to make immediate changes without going through an intense participatory design method. OBJECTIVE: In this paper, we aim to analyze the efficacy of AI and NLP techniques for automatically extracting and classifying the polarity of users' sentiments by proposing a sentiment analysis framework to automatically analyze users' reviews on COVID-19 contact tracing mobile apps. We also aim to provide a large-scale annotated benchmark data set to facilitate future research in the domain. As a proof of concept, we also developed a web application based on the proposed solutions, which is expected to help the community quickly analyze the potential of an application in the domain. METHODS: We propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding with the development and training of artificial intelligence (AI) models for automatic sentiment analysis of users' reviews. In detail, we collected and annotated a large-scale data set of user reviews on COVID-19 contact tracing applications. We used both classical and deep learning methods for classification experiments. RESULTS: We used 8 different methods on 3 different tasks, achieving up to an average F1 score of 94.8%, indicating the feasibility of the proposed solution. The crowd-sourcing activity resulted in a large-scale benchmark data set composed of 34,534 manually annotated reviews. CONCLUSIONS: The existing literature mostly relies on the manual or exploratory analysis of users' reviews on applications, which is tedious and time-consuming. In existing studies, generally, data from fewer applications are analyzed. In this work, we showed that AI and natural language processing techniques provide good results for analyzing and classifying users' sentiments' polarity and that automatic sentiment analysis can help to analyze users' responses more accurately and quickly. We also provided a large-scale benchmark data set. We believe the presented analysis, data set, and proposed solutions combined with a user-friendly interface can be used as a rapid surveillance tool to analyze and monitor mobile apps deployed in emergency situations leading to rapid changes in the applications without going through an intense participatory design method.

Subtractive proteomics assisted therapeutic targets mining and designing ensemble vaccine against Candida auris for immune response induction.

The emergence of variants and the reports of co-infection caused by Candida auris in COVID-19 patients adds a further complication to the global pandemic situation. To date, no effective therapy is available for C. auris infections. Thus, characterization of therapeutic targets and designing effective vaccine candidates using subtractive proteomics and immune-informatics approaches is useful tool in controlling the emerging infections associated with SARS-CoV-2. In the current study, subtractive proteomics-assisted annotation of the vaccine targets was performed, which revealed seven vaccine targets. An immunoinformatic-driven approach was then employed to map protein-specific and proteome-wide immunogenic peptides (CTL, B cell, and HTL) for the design of multi-epitope vaccine candidates (MEVCs). The results demonstrated that the vaccine candidates possess strong antigenic features (>0.4 threshold score) and are classified as non-allergenic. Validation of the designed MEVCs through molecular docking, in-silico cloning, and immune simulation further demonstrated the efficacy of the vaccines by producing immune factor titers (ranging from 2500 to 16000 au/mL) i.e., IgM, IgG, IL-6, and Interferon-α. In conclusion, the current study provides a strong impetus in designing anti-fungal strategies against Candida auris.

The impact of first COVID-19 peak on patient referrals to Liaison Psychiatry Service and staff perception about service provision in Birmingham and Solihull Mental Health Trust Birmingham - a service evaluation project

Aims Based on recommendations from the Royal College of Psychiatrists, this project aimed to evaluate the impact of the first peak of the COVID-19 pandemic on referral patterns to the Queen Elizabeth Hospital Birmingham (QEHB) Liaison Psychiatry (LP) service. Additionally, we aimed to explore staff experiences in LP services across Birmingham and Solihull Mental Health Trust (BSMHFT) in order to generate Trust recommendations promoting optimal healthcare provision amidst the on-going pandemic. Method A mixed method service evaluation was conducted using quantitative and qualitative analysis. Quantitative methods involved reviewing referrals made to the QEHB LP service from March to June 2020, compared with the equivalent time period in 2019. Data were retrospectively extracted from the electronic clinical databases RIO and PICS, and subsequently analysed using Microsoft Office. The number of, and reasons for referrals to LP were identified, whilst focus groups were conducted to explore the subjective experiences of staff working across BSMHFT LP services. Result Between 1st March and 30th June 2020, 984 referrals were made to the QEHB LP service, compared to 1020 referrals in 2019, representing a 3.5% reduction. From 2019 to 2020, referrals due to psychotic symptoms and deliberate self-harm rose by 12.8% and 14.1% respectively, whilst referrals for drug and alcohol-related causes reduced by 28.3%. A significant increase (150%) in referrals for medication or management advice was seen. Focus groups indicated that staff perceived an initial reduction in number of referrals, but an increase in the acuity of patient presentations. Staff reported anxiety around contracting and transmitting SARS-Cov-2, exacerbated by uncertainty around patients’ COVID-19 status. In QEHB, sixty-five of the 984 referrals (7%) had a positive SARS-Cov-2 PCR swab, with the remaining 919 referrals being either negative (68%) or unknown (25%). Ninety-six percent of consultations were conducted face-to-face in QEHB. There were conflicting views amongst staff regarding whether more consultations could have been conducted remotely. Furthermore, varying perceptions of support and communication from both the physical and mental health trust were reported. Conclusion Quantitative data indicates that COVID-19 impacted LP healthcare provision in BSMHFT. Whilst referral numbers remained similar between the equivalent period in 2019 and 2020, a change in the nature of referrals to LP at QEHB was seen. This was corroborated by qualitative data which highlighted a perceived change in acuity of referrals. These findings have been disseminated across the Trust and subsequent recommendations are being implemented during the on-going pandemic.

“Lost between the interface of physical and mental health”: focus groups exploring liaison psychiatry staff's perception about working during the first wave of the COVID-19 pandemic in Birmingham and Solihull Mental Health Foundation Trust

Aims As the COVID-19 pandemic continues, increasing attention is being drawn to the welfare of healthcare providers who have endured many months of sustained exposure to the virus, disrupted working conditions and psychological stress. This project aimed to explore the subjective experiences of staff working in Liaison Psychiatry (LP) in the Birmingham and Solihull Mental Health Foundation Trust, (BSMHFT) during the first wave of the COVID-19 pandemic. These findings have been used to devise recommendations for subsequent waves. Method Data collection occurred as part of a mixed method service evaluation project. We invited all clinical and non-clinical staff from LP departments across BSMHFT to participate in focus groups conducted via Microsoft Teams. The focus groups were video-recorded and facilitated by a moderator and an observer. Subsequent anonymised transcripts were coded and themes were generated by at least two evaluators, using thematic analysis. Result The focus groups, which ranged from 21 to 69 minutes, involved consultants, junior doctors and nurses from four hospitals within BSMHFT. Six major themes emerged including an initial reduction in number yet increase in acuity of patients seen by LP, with some perception that this resulted from reduced face-to-face contact with community mental health services. A feeling that LP was lost at the interface between the physical and mental health trusts emerged as another theme. Uncertainty in adapting to unprecedented working conditions, for example, unclear guidance concerning the use of personal protective equipment, was also described alongside anxiety about contracting and transmitting SARS-Cov-2. Additionally, increased pressure was felt due to staff shortages and inadequate inter-departmental communication. Participants reported differential uptake of remote working, as well as conflicting views regarding the feasibility of remote assessments in LP. Conclusion Liaison psychiatry staff within BSMHFT continued to provide a crucial service during the COVID-19 pandemic. Focus groups with thes staff indicate several recommendations for implementation within the Trust and provoke questions for future research. Due to the unique role that LP plays in providing mental health care within general hospitals, clear guidance for LP staff is key for effective service provision and supporting LP staff. Although used widely across community mental health services, the role of remote working in LP is contentious and requires further exploration. However, there are limitations to the use of focus groups and these findings may not fully represent the experiences of LP staff throughout BSMHFT. Different themes may have emerged through the use of anonymous questionnaires.

The Omicron (B.1.1.529) variant of SARS-CoV-2 binds to the hACE2 receptor more strongly and escapes the antibody response: Insights from structural and simulation data.

As SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) continues to inflict chaos globally, a new variant officially known as B.1.1.529 was reported in South Africa and was found to harbor 30 mutations in the spike protein. It is too early to speculate on transmission and hospitalizations. Hence, more analyses are required, particularly to connect the genomic patterns to the phenotypic attributes to reveal the binding differences and antibody response for this variant, which can then be used for therapeutic interventions. Given the urgency of the required analysis and data on the B.1.1.529 variant, we have performed a detailed investigation to provide an understanding of the impact of these novel mutations on the structure, function, and binding of RBD to hACE2 and mAb to the NTD of the spike protein. The differences in the binding pattern between the wild type and B.1.1.529 variant complexes revealed that the key substitutions Asn417, Ser446, Arg493, and Arg498 in the B.1.1.529 RBD caused additional interactions with hACE2 and the loss of key residues in the B.1.1.529 NTD resulted in decreased interactions with three CDR regions (1-3) in the mAb. Further investigation revealed that B.1.1.529 displayed a stable dynamic that follows a global stability trend. In addition, the dissociation constant (KD), hydrogen bonding analysis, and binding free energy calculations further validated the findings. Hydrogen bonding analysis demonstrated that significant hydrogen bonding reprogramming took place, which revealed key differences in the binding. The total binding free energy using MM/GBSA and MM/PBSA further validated the docking results and demonstrated significant variations in the binding. This study is the first to provide a basis for the higher infectivity of the new SARS-CoV-2 variants and provides a strong impetus for the development of novel drugs against them.

Complement C5a and Clinical Markers as Predictors of COVID-19 Disease Severity and Mortality in a Multi-Ethnic Population.

Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n=33), mild (n=33) and asymptomatic (n=23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help in the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly.

Structural Analysis on the Severe Acute Respiratory Syndrome Coronavirus 2 Non-structural Protein 13 Mutants Revealed Altered Bonding Network With TANK Binding Kinase 1 to Evade Host Immune System.

Mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have made this virus more infectious. Previous studies have confirmed that non-structural protein 13 (NSP13) plays an important role in immune evasion by physically interacting with TANK binding kinase 1 (TBK1) to inhibit IFNß production. Mutations have been reported in NSP13; hence, in the current study, biophysical and structural modeling methodologies were adapted to dissect the influence of major mutations in NSP13, i.e., P77L, Q88H, D260Y, E341D, and M429I, on its binding to the TBK1 and to escape the human immune system. The results revealed that these mutations significantly affected the binding of NSP13 and TBK1 by altering the hydrogen bonding network and dynamic structural features. The stability, flexibility, and compactness of these mutants displayed different dynamic features, which are the basis for immune evasion. Moreover, the binding was further validated using the MM/GBSA approach, revealing that these mutations have higher binding energies than the wild-type (WT) NSP13 protein. These findings thus justify the basis of stronger interactions and evasion for these NSP13 mutants. In conclusion, the current findings explored the key features of the NSP13 WT and its mutant complexes, which can be used to design structure-based inhibitors against the SARS-CoV-2 new variants to rescue the host immune system.

Computational modelling of potentially emerging SARS-CoV-2 spike protein RBDs mutations with higher binding affinity towards ACE2: A structural modelling study.

The spike protein of SARS-CoV-2 and the host ACE2 receptor plays a vital role in the entry to the cell. Among which the hotspot residue 501 is continuously subjected to positive selection pressure and induces unusual virulence. Keeping in view the importance of the hot spot residue 501, we predicted the potentially emerging structural variants of 501 residue. We analyzed the binding pattern of wild type and mutants (Spike RBD) to the ACE2 receptor by deciphering variations in the amino acids' interaction networks by graph kernels along with evolutionary, network metrics, and energetic information. Our analysis revealed that N501I, N501T, and N501V increase the binding affinity and alter the intra and inter-residue bonding networks. The N501T has shown strong positive selection and fitness in other animals. Docking results and repeated simulations (three times) confirmed the structural stability and tighter binding of these three variants, correlated with the previous results following the global stability trend. Consequently, we reported three variants N501I, N501T, and N501V could worsen the situation further if they emerged. The relations between the viral fitness and binding affinity is a complicated game thus the emergence of high affinity mutations in the SARS-CoV-2 RBD brings up the question of whether or not positive selection favours these mutations or not?