One master and two servants: One Zr(â £) with two ligands of TCPP and NH2-BDC form the MOF as the electrochemiluminescence emitter for the biosensing application.

Here we put forward an innovative "one master and two servants" strategy for enhancing the ECL performance. A novel ECL luminophore named Zr-TCPP/NH2-BDC (TCPP@UiO-66-NH2) was synthesized by self-assembly of meso-tetra(4-carboxyphenyl)porphine (TCPP) and 4-aminobenzoic acid (NH2-BDC) with Zr clusters. TCPP@UiO-66-NH2 has a porous structure and a highly ordered structure, which allows the molecular motion of TCPP to be effectively confined, thereby inhibiting nonradiative energy transfer. Importantly, TCPP@UiO-66-NH2 has a higher and more stable ECL signal. To further improve the sensitivity of the sensor, we use polydopamine-coated manganese dioxide (PDA@MnO2), which has a double quenching effect, as the quencher. The nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2-N) is one of the ideal markers for the early diagnosis of COVID-19, and its sensitivity detection is of great significance for the prevention and treatment of COVID-19. Thus, we constructed a quenching-type ECL sensor for the ultrasensitive detection of the SARS-CoV-2-N. Its linear range is 10 fg/mL∼1 µg/mL and the calculated detection limit is 1.4 fg/mL (S/N = 3). The spiked recoveries are 97.40-103.8%, with the relative standard deviations (RSD) under 3.0%. More importantly, the technique offers a viable way to identify and diagnose viral infections early.

Revolutionizing SARS-CoV-2 omicron variant detection: Towards faster and more reliable methods.

The emergence of the highly contagious Omicron variant of SARS-CoV-2 has inflicted significant damage during the ongoing COVID-19 pandemic. This new variant's significant sequence changes and mutations in both proteins and RNA have rendered many existing rapid detection methods ineffective in identifying it accurately. As the world races to control the spread of the virus, researchers are urgently exploring new diagnostic strategies to specifically detect Omicron variants with high accuracy and sensitivity. In response to this challenge, we have compiled a comprehensive overview of the latest reported rapid detection techniques. These techniques include strategies for the simultaneous detection of multiple SARS-CoV-2 variants and methods for selectively distinguishing Omicron variants. By categorizing these diagnostic techniques based on their targets, which encompass protein antigens and nucleic acids, we aim to offer a comprehensive understanding of the utilization of various recognition elements in identifying these targets. We also highlight the advantages and limitations of each approach. Our work is crucial in providing a more nuanced understanding of the challenges and opportunities in detecting Omicron variants and emerging variants.

A triple-aptamer tetrahedral DNA nanostructures based carbon-nanotube-array transistor biosensor for rapid virus detection.

Outbreaks of infectious viruses cause enormous challenges to global public health. Recently, the coronavirus disease 2019 (COVID-19) induced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has severely threatened human health and resulted in the global pandemic. A strategy to detect SARS-CoV-2 with both fast sensing speed and high accuracy is urgently required. Here, rapid detection of SARS-CoV-2 antigen using carbon-nanotube-array-based thin-film transistor (CNT-array-based TFT) biosensors merged with tetrahedral DNA nanostructures (TDNs) and triple aptamers is demonstrated for the first time. Compared with CNT-network-based TFT biosensors and metal-electrode-based CNT-TFT biosensors, the response of CNT-array-based TFT biosensors can be enhanced up to 102% for SARS-CoV-2 receptor-binding domain (RBD) detection, which is supported by its sensing mechanism. By combining TDNs with triple aptamers, the biosensor has realized the wildtype SARS-CoV-2 RBD detection in a broad detection range spanning eight orders of magnitude with a low limit of detection (LOD) of 10 aM (6 copies/µL) owing to the improved protein capture efficiency. Moreover, the triple-aptamer biosensor platform has achieved the detection of SARS-CoV-2 Omicron RBD in a low LOD of 6 aM (3.6 copies/µL). Additionally, the CNT-array-based TFT biosensors have exhibited excellent specificity, enabling identification among SARS-CoV-2 antigen, SARS-CoV antigen and MERS-CoV antigen. The platform of CNT-array-based TFT biosensors combined with TDNs and triple aptamers provides a high-performance and rapid approach for SARS-CoV-2 detection, and its versatility by altering specific aptamers enables the possibility for rapid virus detection.

Phenol red as electrochemical indicator for highly sensitive quantification of SARS-CoV-2 by loop-mediated isothermal amplification detection.

The current COVID-19 pandemic has made patent the need for rapid and cost-effective diagnostic tests, crucial for future infectious outbreaks. Loop-mediated isothermal amplification (LAMP) is a promising and decentralized alternative to qPCR. In this work we have developed a sensitive, fast, and simple innovative methodology for quantification of SARS-CoV-2 RNA copies, combining reverse-transcription LAMP with electrochemical detection. This is based on the oxidation of phenol red (PR), a visual and electroactive LAMP indicator, which oxidation peak potential (Ep) changes with the progress of the LAMP reaction. Using that Ep shift as analytical signal, a calibration curve was obtained for fragment N1 copies of SARS-CoV2 (which provided better results than N or S fragments), with a potential shift of 16.2 mV per order of magnitude, and a practical limit of detection of 21 copies·µL-1. Moreover, the precision of Ep is excellent (RSD < 2%): 557 ± 5 mV for negative and 602 ± 7 mV for positive (2148 N fragment RNA copies·µL-1·-1) LAMP controls. This methodology has been applied to the analysis of nasopharyngeal swab samples, resulting in total concordance with clinical RT-qPCR results. Advances towards fully decentralization have been achieved by designing and fabricating a small portable heater for isothermal procedures, obtaining comparable results to those from a commercial benchtop thermal cycler.

A facile electrochemical biosensor for coronavirus RNA assay with silver deposition.

Coronaviruses are highly infectious and pose a serious threat to human and animal healths. In this work, a facile electrochemical method based on Exonuclease III (Exo III) catalyzed digestion and silver deposition is developed for coronavirus RNA analysis. A magnetic separation procedure is performed to specifically identify target sequence and release single-stranded DNA modified gold nanoparticles (AuNPs). The nanoparticles can thus be immobilized at a screen-printed electrode and catalyze silver deposition for signal readout. This method allows sensitive analysis of PEDV and SARS-CoV-2 RNAs in the concentration range from 1 to 1000 nM with the limits of detection as low as 0.47 nM and 0.17 nM, respectively. Good specificities are demonstrated. Thus, the proposed method may have great potential use in the applications of coronaviruses analysis.

Characteristics of delirium among COVID-19 patients.

OBJECTIVE: This study estimated delirium incidence in Slovak COVID-19 patients, explored treatment associations and examined the impact on hospitalization and mortality. BACKGROUND: The COVID-19 pandemic caused by SARS-CoV-2 has significantly affected global health. Delirium, a severe form of acute brain dysfunction, is common in hospitalized patients, including those with COVID-19. METHODS: A retrospective study analyzed data from 474 hospitalized patients with confirmed SARS-CoV-2 infection in Kosice, Slovakia. Delirium was diagnosed using standardized ICD-10 criteria. Statistical analyses examined associations between delirium, psychiatric symptoms, treatment modalities, hospitalization duration, and mortality. RESULTS: 29.54 % (140 patients) had delirium. Insomnia, anxiety, and delirium were prevalent psychiatric symptoms. Delirium patients had higher insomnia, anxiety, somnolence, agitation, and aggression rates. Treatments like high-flow nasal oxygen, glucocorticoids, antibiotics, and anakinra were associated with higher delirium incidence. Delirium was more common with antipsychotic use (tiapride, quetiapine, haloperidol), while citalopram seemed protective. No significant associations were found with mortality. Patients using benzodiazepines, hypnotics, or tiapride had longer hospital stays. CONCLUSION: This study provides insights into delirium incidence in Slovak COVID-19 patients, treatment associations, and the importance of managing psychiatric symptoms and treatment choices for optimal outcomes (Tab. 6, Ref. 33).

Fucoidan-based antibody-free magnetic nanoparticle for on-site detection of waterborne SARS-CoV-2.

The portable and sensitive point-of-care-test (POCT) method is in urgent need to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for ensuring public health and safety. However, detection of trace number of pathogens in real water sample from the environment still faces challenges, because complex environment disruptors can rapidly degrade targets. Herein, magnetic beads coated with fucoidan and polydopamine (Fuc-PDA-MBs) were introduced as the capture carrier for pretreatment of samples. Fucoidan, a sulfated polysaccharide, can recognize the SARS-CoV-2 spike (S1) protein receptor-binding domain (S1 RBD) and was chosen for replacement of antibody in enrichment. Environmental water seeded with SARS-CoV-2 spike pseudovirus was applied to test performance of Fuc-PDA-MBs method. Under optimal conditions, the use of Fuc-PDA-MBs showed average 76 % capture efficiency at SARS-CoV-2 spike pseudovirus concentration ranging from 107.62 to 104.34 gene copies (gc)/L. Compared with Electronegative filtration (ENF), Fuc-PDA-MBs showed better virion sorption effectiveness. Fuc-PDA-MBs also validated by raw contaminated urban wastewater and showed high recovery results for SARS-CoV-2 variants. To rapidly detect virus in POCT, nucleic acid extraction-free Loop-Mediated Isothermal Amplification (LAMP) was used for simplifying experimental process. The Fuc-PDA-MBs-LAMP assay showed the quantitation limit of sample (LOQ) was 105.49 gc/L. The whole procedure could be completed within 90 min, including 30 min for virus pre-enrichment, 10 min nucleic acid release and 45 min LAMP analysis. Compared with regular antibody-based immunodetection, this integrated system provides broad-spectrum, economic way to detect SARS-CoV-2 mutants in complex environments and also adaptable for high throughput test, which might be used for on-site early warning of SARS-CoV-2 outbreaks in developing area.

Highly potent dual-targeting angiotensin-converting enzyme 2 (ACE2) and Neuropilin-1 (NRP1) peptides: A promising broad-spectrum therapeutic strategy against SARS-CoV-2 infection.

The efficacy of approved vaccines has been diminishing due to the increasing advent of SARS-CoV-2 variants with diverse mutations that favor sneak entry. Nonetheless, these variants recognize the conservative host receptors angiotensin-converting enzyme 2 (ACE2) and neuropilin-1 (NRP1) for entry, rendering the dual blockade of ACE2 and NRP1 an advantageous pan-inhibition strategy. Here, we identified a highly potent dual-targeting peptide AP-1 using structure-based virtual screening protocol. AP-1 had nanoscale binding affinities for ACE2 (Kd = 6.1 ± 0.2 nM) and NRP1 (Kd = 13.4 ± 1.2 nM) and approximately 102- and 8-fold stronger than positive inhibitors S471-503 and NMTP-5, respectively. Further evidence in pseudovirus cell infection and cytotoxicity assays demonstrated that AP-1 exhibited remarkable entry inhibition of variants of concern (VOCs) of SARS-CoV-2 without impairing host cell viability. Together, our findings suggest that AP-1 with dual-targeting ACE2/NRP1 efficacy could be a promising broad-spectrum agent for treating SARS-CoV-2 emerging VOCs.

Targeting SARS-CoV-2 entry processes: The promising potential and future of host-targeted small-molecule inhibitors.

The COVID-19 pandemic, caused by SARS-CoV-2, has had a huge impact on global health. To respond to rapidly mutating viruses and to prepare for the next pandemic, there is an urgent need to develop small molecule therapies that target critical stages of the SARS-CoV-2 life cycle. Inhibiting the entry process of the virus can effectively control viral infection and play a role in prevention and treatment. Host factors involved in this process, such as ACE2, TMPRSS2, ADAM17, furin, PIKfyve, TPC2, CTSL, AAK1, V-ATPase, HSPG, and NRP1, have been found to be potentially good targets with stability. Through further exploration of the cell entry process of SARS-CoV-2, small-molecule drugs targeting these host factors have been developed. This review focuses on the structural functions of potential host cell targets during the entry of SARS-CoV-2 into host cells. The research progress, chemical structure, structure-activity relationship, and clinical value of small-molecule inhibitors against COVID-19 are reviewed to provide a reference for the development of small-molecule drugs against COVID-19.

Quantifying the Individual Variation in Susceptibility to Endemic Coronavirus and SARS-CoV-2 with Human Challenge Trials.

Human challenge trials reveal how the infection risk depends on a given infectious dose. We propose a mathematical framework to analyze and interpret the outcomes of human challenge trials by incorporating the variability between individuals in susceptibility to infection. We illustrate the framework for two distinctive diseases; endemic diseases where a fraction of the study population has been exposed to the target pathogen previously and is thus immune, and novel diseases where the study population is fully susceptible. Based on available data from published trials, we estimate the immune proportion and the variation in susceptibility to endemic HCoV-229E and present plausible infection risks with SARS-CoV-2 over multiple orders of magnitude of the infectious dose. The results show that the proposed method captures heterogeneous background susceptibility in the study population, and we suggest ways to improve the design of future trials and to translate their outcomes to the general population.

Risk mitigation to healthcare workers against viral and bacterial bioaerosol load in laparoscopic surgical exhaust with a new flow mode in hollow fiber membranes-based filter.

Laparoscopy of COVID-19-infected/suspected patients needs to be performed with the utmost care due to the chances of virus carryover through the pneumoperitoneum gas. In this study, polysulfone/polyvinyl-pyrrolidone hollow fiber membranes (HFMs) were fabricated by phase inversion process, and these HFMs were bundled into a module consisting of tortuous, circular-helical arrangement. Further, copper (Cu) and zinc (Zn) nanoparticles (NPs), known to have antimicrobial and antiviral properties, were flow-coated on the lumen side of the HFMs. To test functional efficiency, the modules were challenged with wet aerosol and bioaerosols. Wet aerosol removal efficiency was ∼98%. Bioaerosol-containing bacteria E. coli strain K-12, showed 2.6 log (∼99.8%), and 2.1 log (∼99.3%) removal efficiency for Cu NPs and Zn NPs coated HFMs modules, respectively, and 1.6 log (∼97%) removal for plain (uncoated) HFMs. Bioaerosols containing SARS-CoV-2 surrogate virus (MS2 bacteriophage) showed ∼5-7 log reduction of bacteriophage for plain HFMs, 3.9 log, and 2.3 log reduction for Cu and Zn coated HFMs, respectively. The flow of aerosols entirely through the HFM lumen helps in attaining a low ΔP of < 1 mm Hg, thus rendering its usefulness, particularly for exhausting pneumoperitoneum gases where high upstream pressures could lead to barotrauma. STATEMENT OF ENVIRONMENTAL IMPLICATION: Surgical smoke is generated during minimally invasive surgical (MIS) procedure such as laparoscopy when electrosurgical devices are used to cut any tissues. This smoke is a hazard as it contains toxic volatile compounds, mutagens, carcinogens, bacteria, and virus-laden aerosols. Infection to healthcare professionals through the bioaerosols containing smoke is well reported in literature. The limitation of using hypochlorite and pleated/HEPA filter, led us to design a low pressure drop bioaerosol filter, which can remove smoke, tissue fragments, and COVID-19 virus. It provides a much safer operation theatre environment during MIS procedures as well as in general for bioaerosol removal.

RNA-dependent RNA polymerase of SARS-CoV-2 regulate host mRNA translation efficiency by hijacking eEF1A factors.

The RNA-dependent RNA polymerase (NSP12) of COVID-19 plays a significant role in the viral infection process, which promotes viral RNA replication by cooperating with NSP7 and NSP8, but little is known about its regulation on the function of host cells. We firstly found that overexpression of NSP12 had little effect on host mRNAs transcription. Using iCLIP technology, we found that NSP12 can bind a series of host RNAs with the conserved binding motif G(C/A/G)(U/G/A)UAG, especially ribosomal RNA. We found that NSP12 could directly bind to eEF1A factor via the NIRAN domain of NSP12 and N-terminal domain of eEF1A. NSP12 colocalized with eEF1A to inhibit type I interferon expression upon virus infection. In order to prove that NSP12 regulates the translation level of host cells, we found that NSP12 significantly affected the translation efficiency of many host mRNAs (such as ISG15, NF-κB2, ILK and SERPINI2) via ribosome profiling experiment, and the genes with significant upregulation in translation efficiency were mainly enriched in positive regulation of ubiquitin-dependent proteasomal process and NIK/NF-κB signaling pathway (such as NF-κB2, ILK), and negative regulation of type I interferon production, protein level of these genes were further confirmed in HEK293T and Calu3 cells upon NSP12 overexpression. These results indicate that NSP12 of SARS-CoV-2 can hijack the eEF1A factor to regulate translation efficiency of host mRNAs, which provides a new idea for us to evaluate the impact of SARS-CoV2 virus on the host and study the potential drug targets.

Social Distancing in the COVID-19 Pandemic: Associated Factors, Health Outcomes, and Implications.

Social distancing has reemerged as a public health measure for containing the spread of COVID-19. This integrative review aims to analyze the historical use of social distancing, the current application during COVID-19, individual factors that affect social distancing practices, and consequential health outcomes. We analyzed relevant literature from searches conducted on Scopus, PubMed, and PsycINFO. We found that resources, culture, age, gender, and personality are associated with the degree to which people practice social distancing. Furthermore, social distancing changes our lifestyles and behavior and results in multifaceted health outcomes, including decreased physical activity and sunlight exposure, increased weight gain, and impaired sleep quality. On the positive side, social distancing has been linked to reduced crime rates and environmental damage, as well as better social and family ties. Future interventions may be utilized to increase adherence to social distancing practices and to mitigate the negative health effects of social distancing.

Effects of mask use on cardiopulmonary functions and coronaphobia in the COVID-19 pandemic: an observational study among university students.

Mask use during the coronavirus disease 2019 (COVID-19) pandemic has been widely recommended and mandated worldwide. However, there is a lack of comprehensive research on the potential adverse health effects of mask usage. This study aimed to investigate and evaluate the negative effects of surgical mask use on scientifically proven cardiopulmonary functions in undergraduate and associate degree students, as well as its impact on coronaphobia. A total of 145 volunteer university students (49 males, 96 females, with a mean age of 20 years) were enrolled in the study, which consisted of two 120-minute sessions. Blood oxygen saturation, heart rate, and blood pressure were assessed before and immediately after each session. The Coronavirus-19 Phobia Scale was utilized to measure levels of COVID-19 phobia. While a time-dependent decrease in oxygen saturation level, blood pressure, and heart rate was measured when vital signs were evaluated at 1 and 120 minutes, none of the values fell outside the reference range. The study also investigated the effects of mask use on various symptoms including headaches, visual impairment, facial discomfort, earaches, shortness of breath, and anxiety. Significantly increased occurrences of all these symptoms were observed at the 60th and 120th minute compared with the baseline. The participants enrolled in the study demonstrated a moderate level of COVID-19 phobia based on the mean total score. Furthermore, high scores were recorded in the psychological and social sub-dimensions, while lower scores were recorded in the economic and psychosomatic sub-dimensions. In the post-COVID-19 normalization phase, the use of a surgical mask during a 120-minute course was found to have no significant impact on cardiopulmonary functions, but moderately affected coronaphobia scores.

SARS-CoV-2 removal in municipal wastewater treatment plants: Focus on conventional activated sludge, membrane bioreactor and anaerobic digestion.

This work focuses on the removal of SARS-CoV-2 RNA in the various stages of a full-scale municipal WWTP characterised by two biological processes in parallel: (i) conventional activated sludge (CAS) and (ii) membrane bioreactor (MBR). The monitoring was carried out during the Omicron wave in 2022, a period characterised by a high concentration of SARS-CoV-2 in influent wastewater. The average concentration of SARS-CoV-2 in influent wastewater was 3.7 × 104 GU/L. In the primary sedimentation, the removal of SARS-CoV-2 was not appreciable. The largest log removal value of SARs-CoV-2 occurred in the biological stages, with 1.8 ± 0.9 and 2.2 ± 0.7 logs in CAS and MBR systems. The mean concentrations of SARS-CoV-2 in the CAS and MBR effluents were 6.8 × 102 GU/L and 6.4 × 102 GU/L, respectively. The MBR effluent showed more negative samples, because small particles are retained by membrane and cake layer. The analysis of the different types of sludge confirmed the accumulation of SARS-CoV-2 in primary (5.2 × 104 GU/L) and secondary sludge (3.5 × 104 GU/L), due to the affinity of enveloped viruses towards biosolids. A SARS-CoV-2 concentration in the digested sludge equal to 4.8 × 104 GU/L denotes a negligible reduction in the mesophilic anaerobic digester at temperature of 31-33 °C.

Targeted community wastewater surveillance for SARS-CoV-2 and Mpox virus during a festival mass-gathering event.

Wastewater surveillance has emerged recently as a powerful approach to understanding infectious disease dynamics in densely populated zones. Wastewater surveillance, while promising as a public health tool, is often hampered by slow turn-around times, complex analytical protocols, and resource-intensive techniques. In this study, we evaluated an affinity capture method and microfluidic digital PCR as a rapid approach to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mpox (formerly known as monkeypox) virus, and fecal indicator, pepper mild mottle virus (PMMoV) in wastewater during a mass-gathering event. Wastewater samples (n = 131) were collected from residential and commercial manholes, pump stations, and a city's wastewater treatment plant. The use of Nanotrap® Microbiome Particles and microfluidic digital PCR produced comparable results to other established methodologies, with reduced process complexity and analytical times, providing same day results for public health preparedness and response. Using indigenous SARS-CoV-2 and PMMoV in wastewater, the average viral recovery efficiency was estimated at 10.1 %. Both SARS-CoV-2 N1 and N2 genes were consistently detected throughout the sampling period, with increased RNA concentrations mainly in wastewater samples collected from commercial area after festival mass gatherings. The mpox virus was sporadically detected in wastewater samples during the surveillance period, without distinct temporal trends. SARS-CoV-2 RNA concentrations in the city's wastewater mirrored the city's COVID-19 cases, confirming the predictive properties of wastewater surveillance. Wastewater surveillance continues to be beneficial for tracking diseases that display gastrointestinal symptoms, including SARS-CoV-2, and can be a powerful tool for sentinel surveillance. However, careful site selection and a thorough understanding of community dynamics are necessary when performing targeted surveillance during temporary mass-gathering events as potential confirmation bias may occur.

Estimating COVID-19 cases on a university campus based on Wastewater Surveillance using machine learning regression models.

Wastewater Surveillance (WS) is a crucial tool in the management of COVID-19 pandemic. The surveillance is based on enumerating SARS-CoV-2 RNA concentrations in the community's sewage. In this study, we used WS data to develop a regression model for estimating the number of active COVID-19 cases on a university campus. Eight univariate and multivariate regression model types i.e. Linear Regression (LM), Polynomial Regression (PR), Generalised Additive Model (GAM), Locally Estimated Scatterplot Smoothing Regression (LOESS), K Nearest Neighbours Regression (KNN), Support Vector Regression (SVR), Artificial Neural Networks (ANN) and Random Forest (RF) were developed and compared. We found that the multivariate RF regression model, was the most appropriate for predicting the prevalence of COVID-19 infections at both a campus level and hostel-level. We also found that smoothing the normalised SARS-CoV-2 data and employing multivariate modelling, using student population as a second independent variable, significantly improved the performance of the models. The final RF campus level model showed good accuracy when tested using previously unseen data; correlation coefficient of 0.97 and a mean absolute error (MAE) of 20 %. In summary, our non-intrusive approach has the ability to complement projections based on clinical tests, facilitating timely follow-up and response.

Immunity testing against COVID-19 from blood by an IoT-enabled and AI-controlled multiplexed microfluidic platform.

Developing herd immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pivotal for changing the course of the coronavirus disease 2019 (COVID-19) pandemic. However, the uncertainty of vaccine-induced immunity development and inequitable distribution of vaccines hinders the global vaccination effort. Therefore, routine serodiagnosis and ensuring effective vaccination on a time-to-time basis are essential for developing sustainable immunity against SARS-CoV-2. Herein, an AI-driven multiplexed point-of-care testing (POCT) platform capable of utilizing a microfluidic lab-on-a-chip (LOC) device has been proposed for analyzing bodily fluid response against SARS-CoV-2. The developed platform has been successfully utilized for the quantification of SARS-CoV-2 S-protein, N-protein, IgM, and IgG from human blood samples with limits of detection (LODs) as low as 0.01, 0.02, 0.69, and 0.61 ng/mL respectively. Finally, a data-receptive web-based dashboard system has been developed and demonstrated to provide real-time, territory-specific analysis of herd immunity progress from the test results. Thus, the proposed platform could be an imperative tool for healthcare authorities to analyze and restrain ongoing COVID-19 outbreaks or similar pandemics in the future by ensuring effective immunization.

Applying the bioisosterism strategy to obtain lead compounds against SARS-CoV-2 cysteine proteases: An in-silico approach.

SARS-CoV-2 cysteine proteases are essential nonstructural proteins due to their role in the formation of the virus multiple enzyme replication-transcription complex. As a result, those functional proteins are extremely relevant targets in the development of a new drug candidate to fight COVID-19. Based on this fact and guided by the bioisosterism strategy, the present work has selected 126 out of 1050 ligands from DrugBank website. Subsequently, 831 chemical analogs containing bioisosteres, some of which became structurally simplified, were created using the MB-Isoster software, and molecular docking simulations were performed using AutoDock Vina. Finally, a study of physicochemical properties, along with pharmacokinetic profiles, was carried out through SwissADME and ADMETlab 2.0 platforms. The promising results obtained with the molecules encoded as DB00549_BI_005, DB04868_BI_003, DB11984_BI_002, DB12364_BI_006 and DB12805_BI_004 must be confirmed by molecular dynamics studies, followed by in vitro and in vivo empirical tests that ratify the advocated in-silico results.