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1.
Computers in Biology and Medicine ; : 105574, 2022.
Article in English | ScienceDirect | ID: covidwho-1814282

ABSTRACT

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.

2.
RSC advances ; 12(12):7318-7327, 2022.
Article in English | EuropePMC | ID: covidwho-1787253

ABSTRACT

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.

3.
JMIR Form Res ; 2022 Mar 16.
Article in English | MEDLINE | ID: covidwho-1779877

ABSTRACT

BACKGROUND: Contact tracing has been globally adopted in the fight to control the infection rate of COVID-19. Thanks to digital technologies, such as smartphones and wearable devices, contacts of COVID-19 patients can be easily traced and informed about their potential exposure to the virus. To this aim, several mobile applications 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 which, although in normal circumstances is optimal, but not optimal in emergency situations where a mobile device needs to be deployed immediately with little to no user input from the beginning for the greater public good. OBJECTIVE: In this paper, we aim to analyze the efficacy of AI models and Natural Language Processing (NLP) techniques in 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 applications. We also aim to provide a large-scale annotated benchmark dataset to facilitate future research in the domain. As a proof of concepts, we also develop a potential web application, based on the proposed solutions, with a user-friendly interface to automatically analyze and classify users' reviews on the COVID-19 contact tracing applications. The proposed framework combined with the interface which is expected to help the community in quickly analyzing users' perception about such mobile applications and can be used as a rapid surveillance tool to monitor effectiveness of mobile applications and to make immediate changes without going through an intense participatory design method in emergency situations. METHODS: We propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding on the development and training of AI models for automatic sentiment analysis of users' reviews. In detail, we collected and annotated a large- scale dataset of Android and iOS mobile applications users' reviews for COVID-19 contact tracing. After manually analyzing and annotating users' reviews, we employed both classical (i.e., Naïve Bayes, SVM, Random Forest) and deep learning (i.e., fastText, and different transformers) methods for classification experiments. This resulted in eight different classification models. RESULTS: We employed eight different methods on three different tasks achieving up to an average F1-Scores 94.8% indicating the feasibility and applicability of automatic sentiment analysis of users' reviews on the COVID-19 contact tracing applications. Moreover, the crowd-sourcing activity resulted in a large-scale benchmark dataset composed of 34,534 reviews manually annotated from the contract tracing applications of 46 distinct countries. The resulted dataset is also made publicly available for research usage. CONCLUSIONS: The existing literature mostly relies on the manual/exploratory analysis of users' reviews on the application, which is a tedious and time-consuming process. Moreover, in the existing studies, generally, data from fewer applications are analyzed. In this work, we showed that AI and NLP techniques provide good results in analyzing and classifying users' sentiments' polarity, and that the automatic sentiment analysis can help in analyzing users' responses to the application more quickly with a significant accuracy. Moreover, we also provided a large-scale benchmark dataset composed of 34,534 reviews from 47 different applications. We believe the presented analysis, dataset, and the proposed solutions combined with a user-friendly interface can be used as a rapid surveillance tool to analyze and monitor mobile applications deployed in emergency situations leading to rapid changes in the applications without going through an intense participatory design method.

4.
Comput Biol Med ; 145: 105462, 2022 Apr 01.
Article in English | MEDLINE | ID: covidwho-1768008

ABSTRACT

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.

5.
RSC Adv ; 12(12): 7318-7327, 2022 Mar 01.
Article in English | MEDLINE | ID: covidwho-1747166

ABSTRACT

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 (K D) 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.

6.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-308961

ABSTRACT

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 novel 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 the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly.

7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-304960

ABSTRACT

Contact tracing has been globally adopted in the fight to control the infection rate of COVID-19. Thanks to digital technologies, such as smartphones and wearable devices, contacts of COVID-19 patients can be easily traced and informed about their potential exposure to the virus. To this aim, several interesting mobile applications 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. In this work, we propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding on the development and training of AI models for automatic sentiment analysis of users' reviews. In total, we employ eight different methods achieving up to an average F1-Scores 94.8% indicating the feasibility of automatic sentiment analysis of users' reviews on the COVID-19 contact tracing applications. We also highlight the key advantages, drawbacks, and users' concerns over the applications. Moreover, we also collect and annotate a large-scale dataset composed of 34,534 reviews manually annotated from the contract tracing applications of 46 distinct countries. The presented analysis and the dataset are expected to provide a baseline/benchmark for future research in the domain.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-314041

ABSTRACT

Background: The prolific spread of COVID-19 caused by a novel coronavirus (SARS-CoV-2) from its epicenter in Wuhan, China, to every nook and cranny of the world after December 2019, jeopardize the prevailing health system in the world and has raised serious concerns about human safety. To date efforts are continuing to design small molecule inhibitor, vaccines and many other therapeutic options are practiced but their final therapeutic potential is still to be tested. Using the old drug or vaccine or peptides could aid this process to avoid such long experimental procedure. Results: : Hence, here we have repurposed a small peptide (ATLQAIAS) from the previous study which reported the inhibitory effects of this peptide. We used in silico mutagenesis approach to design more peptides from the native wild peptide, which revealed that substitutions (T2W, T2Y, L3R and A5W) could increase the binding affinity of the peptide towards the 3CLpro. Furthermore, using MD simulation and free energy calculation confirmed its dynamics stability and stronger binding affinities. Per-residues energy decomposition analysis revealed that the specified substitution significantly increased the binding affinity at residue level. Conclusion: Our wide-ranging analyses of binding affinities disclosed that our designed peptide owns the potential to hinder the SARS-CoV-2 and will reduce the progression of SARs-CoV-2-borne pneumonia. Our analysis strongly suggests the experimental and clinical validation of these peptides to curtail the recent corona outbreak.

9.
BJPsych open ; 7(Suppl 1):S329-S329, 2021.
Article in English | EuropePMC | ID: covidwho-1661173

ABSTRACT

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.

10.
BJPsych open ; 7(Suppl 1):S329-S329, 2021.
Article in English | EuropePMC | ID: covidwho-1661172

ABSTRACT

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.

11.
Int J Biol Macromol ; 200: 438-448, 2022 Mar 01.
Article in English | MEDLINE | ID: covidwho-1633972

ABSTRACT

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.


Subject(s)
Angiotensin-Converting Enzyme 2/chemistry , Angiotensin-Converting Enzyme 2/metabolism , Antibodies/chemistry , Antibodies/metabolism , SARS-CoV-2/chemistry , SARS-CoV-2/metabolism , Antibodies, Monoclonal/chemistry , Antibodies, Monoclonal/metabolism , Humans , Hydrogen Bonding , Immune Evasion , Molecular Docking Simulation , Molecular Dynamics Simulation , Protein Binding/immunology , Protein Domains/immunology , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/immunology , Spike Glycoprotein, Coronavirus/metabolism
12.
Comput Biol Med ; 141: 105163, 2022 02.
Article in English | MEDLINE | ID: covidwho-1588032

ABSTRACT

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?


Subject(s)
SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus , Angiotensin-Converting Enzyme 2 , Animals , COVID-19/virology , Humans , Molecular Dynamics Simulation , Mutation , Protein Binding , Protein Domains , Spike Glycoprotein, Coronavirus/genetics
13.
Front Immunol ; 12: 707159, 2021.
Article in English | MEDLINE | ID: covidwho-1581347

ABSTRACT

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.


Subject(s)
Biomarkers/blood , COVID-19/blood , COVID-19/mortality , Complement C5a/analysis , Patient Acuity , Adult , Aged , COVID-19/complications , Cohort Studies , Female , Humans , Hypoalbuminemia/mortality , Hypoalbuminemia/virology , Lymphocyte Count , Lymphopenia/mortality , Lymphopenia/virology , Male , Middle Aged , Prognosis , Prospective Studies , Qatar , SARS-CoV-2
14.
Front Microbiol ; 12: 789062, 2021.
Article in English | MEDLINE | ID: covidwho-1581272

ABSTRACT

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.

15.
J Biomol Struct Dyn ; 39(13): 4659-4670, 2021 08.
Article in English | MEDLINE | ID: covidwho-1521979

ABSTRACT

The current coronavirus (SARS-COV-2) pandemic and phenomenal spread to every nook and cranny of the world has raised major apprehensions about the modern public health care system. So far as a result of this epidemic, 4,434,653 confirmed cases and 302,169 deaths are reported. The growing infection rate and death toll demand the use of all possible approaches to design novel drugs and vaccines to curb this disease. In this study, we combined drugs repurposing and virtual drug screening strategies to target 3CLpro, which has an essential role in viral maturation and replication. A total of 31 FDA approved anti-HIV drugs, and Traditional Chinese medicines (TCM) database were screened to find potential inhibitors. As a result, Saquinavir, and five drugs (TCM5280805, TCM5280445, TCM5280343, TCM5280863, and TCM5458190) from the TCM database were found as promising hits. Furthermore, results from molecular dynamics simulation and total binding free energy revealed that Saquinavir and TCM5280805 target the catalytic dyad (His41 and Cys145) and possess stable dynamics behavior. Thus, we suggest that these compounds should be tested experimentally against the SARS-COV-2 as Saquinavir has been reported to inhibit HIV protease experimentally. Considering the intensity of coronavirus dissemination, the present research is in line with the idea of discovering the latest inhibitors against the coronavirus essential pathways to accelerate the drug development cycle.Communicated by Ramaswamy H. Sarma.


Subject(s)
COVID-19 , Drug Repositioning , Humans , Molecular Docking Simulation , Molecular Dynamics Simulation , Peptide Hydrolases , Protease Inhibitors/pharmacology , SARS-CoV-2
16.
Gene Rep ; 26: 101441, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1520981

ABSTRACT

Ongoing Coronavirus epidemic (COVID-19) identified first in Wuhan, China posed huge impact on public health and economy around the globe. Both cough and sneeze based droplets or aerosols encapsulated COVID-19 particles are responsible for airborne transmission of this virus and caused an unexpected escalation and high mortality worldwide. Current study intends to investigate the correlation of COVID-19 epidemic with meteorological parameters, particularly temperature and humidity. A data set of Epidemiological data of COVID-19 for highly infected provinces of Pakistan was collected from the official website of (https://www.covid.gov.pk/) and weather data was collected from (https://www.timeanddate.com/) during the time period of 1st March to 30th September 2020. The GrapPad prism 5 Software was used to calculate the mean and standard error of mean (SEM). In the current study the incident of daily covid cases is recorded higher in the month of June while the less number of case were reported in the month of May as compared to the other months (April, May, June, July, September and August) in the four province of Pakistan. We also find out that the incident of Covid19 were high at higher temperature (like the average temperature in the month of June 37 °C) while less cases were reported in May the average temperature was 29.5 °C. Furthermore the incident of covid cases were less reported at low humidity while more intendant with high humidity. Pearson's (r) determine the strength of the relationship between the variables. Pearson's correlation coefficient test employed for data analysis revealed that temperature average (TA) and average humidity is not a significant correlated with COVID-19 pandemic. The results obtained from the current analysis for selected parameters indirect correlation of COVID-19 transmission with temperature variation, and humidity. In the present study association of parameters is not correlated with COVID-19 pandemic, suggested need of more strict actions and control measures for highly populated cities. These findings will be helpful for health regulatory authorities and policy makers to take specific measures to combat COVID-19 epidemic in Pakistan.

17.
Microorganisms ; 9(11)2021 Nov 11.
Article in English | MEDLINE | ID: covidwho-1512502

ABSTRACT

Glucose-regulated protein 78 (GRP78) might be a receptor for SARS-CoV-2 to bind and enter the host cell. Recently reported mutations in the spike glycoprotein unique to the receptor-binding domain (RBD) of different variants might increase the binding and pathogenesis. However, it is still not known how these mutations affect the binding of RBD to GRP78. The current study provides a structural basis for the binding of GRP78 to the different variants, i.e., B.1.1.7, B.1.351, B.1.617, and P.1 (spike RBD), of SARS-CoV-2 using a biomolecular simulation approach. Docking results showed that the new variants bound stronger than the wild-type, which was further confirmed through the free energy calculation results. All-atom simulation confirmed structural stability, which was consistent with previous results by following the global stability trend. We concluded that the increased binding affinity of the B.1.1.7, B.1.351, and P.1 variants was due to a variation in the bonding network that helped the virus induce a higher infectivity and disease severity. Consequently, we reported that the aforementioned new variants use GRP78 as an alternate receptor to enhance their seriousness.

18.
Comput Biol Med ; 138: 104936, 2021 11.
Article in English | MEDLINE | ID: covidwho-1458824

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). Reports of new variants that potentially increase virulence and viral transmission, as well as reduce the efficacy of available vaccines, have recently emerged. In this study, we computationally analyzed the N439K, S477 N, and T478K variants for their ability to bind Angiotensin-converting enzyme 2 (ACE2). We used the protein-protein docking approach to explore whether the three variants displayed a higher binding affinity to the ACE2 receptor than the wild type. We found that these variants alter the hydrogen bonding network and the cluster of interactions. Additional salt bridges, hydrogen bonds, and a high number of non-bonded contacts (i.e., non-bonded interactions between atoms in the same molecule and those in other molecules) were observed only in the mutant complexes, allowing efficient binding to the ACE2 receptor. Furthermore, we used a 2.0-µs all-atoms simulation approach to detect differences in the structural dynamic features of the resulting protein complexes. Our findings revealed that the mutant complexes possessed stable dynamics, consistent with the global trend of mutations yielding variants with improved stability and enhanced affinity. Binding energy calculations based on molecular mechanics/generalized Born surface area (MM/GBSA) further revealed that electrostatic interactions principally increased net binding energies. The stability and binding energies of N439K, S477 N, and T478K variants were enhanced compared to the wild-type-ACE2 complex. The net binding energy of the systems was -31.86 kcal/mol for the wild-type-ACE2 complex, -67.85 kcal/mol for N439K, -69.82 kcal/mol for S477 N, and -69.64 kcal/mol for T478K. The current study provides a basis for exploring the enhanced binding abilities and structural features of SARS-CoV-2 variants to design novel therapeutics against the virus.


Subject(s)
Angiotensin-Converting Enzyme 2/genetics , COVID-19 , Spike Glycoprotein, Coronavirus , Angiotensin-Converting Enzyme 2/chemistry , Angiotensin-Converting Enzyme 2/metabolism , Computational Biology , Humans , Molecular Dynamics Simulation , Protein Binding , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/metabolism
19.
Biomed Pharmacother ; 143: 112176, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1412768

ABSTRACT

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its new variants reported in different countries have posed a serious threat to human health and social fabrics worldwide. In addition, these new variants hindered the efforts of vaccines and other therapeutic developments. In this review article, we explained the emergence of new variants of SARS-CoV-2, their transmission risk, mortality rate, and, more importantly, the impact of each new variant on the efficacy of the developed vaccines reported in different literature and findings. The literature reported that with the emergence of new variants, the efficacy of different vaccines is declined, hospitalization and the risk of reinfection is increased. The reports concluded that the emergence of a variant that entirely evades the immune response triggered by the vaccine is improbable. The emergence of new variants and reports of re-infections are creating a more distressing situation and therefore demands further investigation to formulate an effective therapeutic strategy.


Subject(s)
COVID-19 Vaccines , COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/virology , COVID-19 Vaccines/classification , COVID-19 Vaccines/pharmacology , Humans , Immunogenicity, Vaccine , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity , SARS-CoV-2/physiology , Treatment Outcome
20.
Comput Biol Med ; 133: 104420, 2021 06.
Article in English | MEDLINE | ID: covidwho-1385348

ABSTRACT

Reports of the novel and more contagious strains of SARS-CoV-2 originating in different countries have further aggravated the pandemic situation. The recent substitutions in spike protein may be critical for the virus to evade the host's immune system and therapeutics that have already been developed. Thus, this study has employed an immunoinformatics pipeline to target the spike protein of this novel strain to construct an immunogenic epitope (CTL, HTL, and B cell) vaccine against the new variant. Our investigation revealed that 12 different epitopes imparted a critical role in immune response induction. This was validated by an exploration of physiochemical properties and experimental feasibility. In silico and host immune simulation confirmed the expression and induction of both primary and secondary immune factors such as IL, cytokines, and antibodies. The current study warrants further lab experiments to demonstrate its efficacy and safety.


Subject(s)
COVID-19 , Viral Vaccines , Cloning, Molecular , Computer Simulation , Epitopes, B-Lymphocyte , Epitopes, T-Lymphocyte , Humans , Immunity , Molecular Docking Simulation , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/genetics , Vaccines, Subunit
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