Determinant of stunting in children aged 12-24 months during the COVID-19 pandemic era in Makassar City

Objective: The prevalence of stunting in Sulawesi Selatan after the pandemic has decreased. This is because the COVID-19 pandemic situation has made it difficult to conduct anthropometric measurements owing to a number of regulations enacted by the government to suppress the cases of COVID-19. The Sudiang Public Health Center is one of the biggest contributors to stunting in Makassar City with a prevalence of 11.06 %. This study aimed to assess the degree of risk of Low Body Weight (LBW), pregnancy checkups <4 times, incomplete basic vaccinations, nonexclusive breastfeeding, Acute Respiratory Infection (ARI)/ diarrhea infections, household income, and contaminated water sources on stunting during the pandemic. Methods: This study was an observational study with a control case epidemiology design. The sample was 140 respondents, namely 70 case children (stunting) and 70 control children (non-stunting). The statistical analysis used was the Chi-Square test and multiple logistic regression test. The results were expressed in the ODDS ratio. Results: The results of this study showed that there is a relationship between LBW (OR=4.0, 1.502-10.911, CI=95 %;ρ=0.006), pregnancy checkups <4 times (OR=3.3, 1.319-8.753, CI=95 %;ρ=0.011), non-exclusive breastfeeding (OR=2.4, 1.045-5.645, CI=95 %;ρ=0.039), and ARI/ diarrhea infections (OR=4.3, 1.839-10.222, CI=95 %;ρ=0.001) and stunting in children aged 12-24 months during the COVID-19 pandemic in Makassar City. The history of infectious disease is the most influential variable in the incidence of stunting. Conclusions: It is concluded that the risk of stunting is the highest in LBW children, with pregnancy checkups less than 4 times, non-exclusive breastfeeding, and infectious diseases such as ARI/diarrhea in the last three months. © 2023 Academia Nacional de Medicina. All rights reserved.

Evaluation of RT-PCR assays for detection of SARS-CoV-2 variants of concern.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic has been considered with great importance on correct screening procedure. The detection efficiency of recent variants of concern were observed by comparing 5 commercial RT-PCR kits and a SYBR-green method developed and validated in our laboratory. The RNA was extracted from nasopharyngeal samples from suspected COVID-19 patients and RT-PCR assay was performed according to the instruction of the respective manufacturers. The specificity and sensitivity of Maccura kit was 81.8% and 82.5%, A*Star kit was 100% and 75.4%, Da An Gene kit was 100% and 68.4%, Sansure kit was 54.5% and 91.2% and TaqPath kit was 100% and 70.2% respectively. Our in house SYBR-Green method showed a consistent detection result with 90.9% specificity and 91.2% sensitivity. We also found that detection kits targeting more genes showed better accuracy which facilitates less false positive results (< 20%). Our study found a significant difference (p < 0.005) in Ct value reported for common target genes shared by the RT-PCR kits in relation with different variants of COVID-19 infection. Recent variants of concerns contain more than 30 mutations in the spike proteins including 2 deletion and a unique insertion mutation by which makes detection of these variants difficult and these facilitates the variants to escape from being detected.

Preparedness of Students for Future Teaching and Learning in Higher Education: A Bangladeshi Perspective

The COVID-19 pandemic has had a significant impact on higher education (HE) across the globe, including in Bangladesh. The Bangladeshi HE system is going through an abrupt transition and transformation to cope with the crisis. This chapter is based on data collected from teachers and students of Bangladeshi public and private HE institutions regarding teaching and learning during the COVID-19 lockdown. In Bangladesh, some universities switched to online distance teaching and learning quickly during this period, and others lagged behind in this regard. Teachers and students from both groups of public and private universities participated in the study, including those who attended online teaching and learning activities and those who did not participate. This chapter highlights both teachers' and students' perspectives regarding students' future preparedness for participating fully in the changing landscape of HE, especially technology-enhanced teaching and learning. Understanding these perspectives of teachers and students is important to address the digital divide and social justice issues in the policy and practice. Within the HE sector in Bangladesh, it is especially vital while transforming its education system and adapting emerging technologies to address the challenges of education in future emergencies.

Unique mutations in SARS-CoV-2 Omicron subvariants' non-spike proteins: Potential impacts on viral pathogenesis and host immune evasion.

SARS-CoV-2 is the causative agent behind the ongoing COVID-19 pandemic. This virus is a cumulative outcome of mutations, leading to frequent emergence of new variants and their subvariants. Some of them are a matter of high concern, while others are variants of interest for studying the mutational effect. The major five variants of concern (VOCs) are Alpha (B.1.1.7), Beta (B.1.315), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529.*/BA.*). Omicron itself has >100 subvariants at present, among which BA.1 (21K), BA.2 (21L), BA.4 (22A), BA.5 (22B), and BA.2.12.1 (22C) are the dominant ones. Undoubtedly, these variants and sometimes their progeny subvariants have significant differences in their spike region that impart them the unique properties they harbor. But alongside, the mutations in their non-spike regions could also be responsible elements behind their characteristics, such as replication time, virulence, survival, host immune evasion, and such. There exists a probability that these mutations of non-spike proteins may also impart epistatic effects that are yet to be brought to light. The focus of this review encompasses the non-spike mutations of Omicron, especially in its widely circulating subvariants (BA.1, BA.2, BA.4, BA.5, and BA.2.12.1). The mutations such as in NSP3, NSP6, NSP13, M protein, ORF7b, and ORF9b are mentioned few of all, which might have led to the varying properties, including growth advantages, higher transmission rate, lower infectivity, and most importantly better host immune evasion through natural killer cell inactivation, autophagosome-lysosome fusion prevention, host protein synthesis disruption, and so on. This aspect of Omicron subvariants has not yet been explored. Further study of alteration of expression or interaction profile of these non-spike mutations bearing proteins, if present, can add a great deal of knowledge to the current understanding of the viral properties and thus effective prevention strategies.

Development and validation of cost-effective one-step multiplex RT-PCR assay for detecting the SARS-CoV-2 infection using SYBR Green melting curve analysis.

TaqMan probe-based commercial real-time (RT) PCR kits are expensive but most frequently used in COVID-19 diagnosis. The unprecedented scale of SARS-CoV-2 infections needs to meet the challenge of testing more persons at a reasonable cost. This study developed a simple and cost-effective alternative diagnostic method based on melting curve analysis of SYBR green multiplex assay targeting two virus-specific genes along with a host-specific internal control. A total of 180 randomly selected samples portioning into two subsets based on crude and high-quality RNA extraction were used to compare this assay with a nationwide available commercial kit (Sansure Biotech Inc., (Hunan, China)), so that we could analyze the variation and validity of this in-house developed method. Our customized-designed primers can specifically detect the viral RNA likewise Sansure. We separately optimized SYBR Green RT-PCR reaction of N, E, S, and RdRp genes based on singleplex melting curve analysis at the initial stage. After several rounds of optimization on multiplex assays of different primer combinations, the optimized method finally targeted N and E genes of the SARS-CoV-2 virus, together with the ß-actin gene of the host as an internal control. Comparing with the Sansure commercial kit, our proposed assay provided up to 97% specificity and 93% sensitivity. The cost of each sample processing ranged between ~2 and ~6 USD depending on the purification level of extracted RNA template. Overall, this one-step and one-tube method can revolutionize the COVID-19 diagnosis in low-income countries.

Short-Term Load Forecasting Model Considering the Impact of COVID-19 Lockdown in Bangladesh

The impact of COVID-19 lockdown on short-term load forecasting in Bangladesh has been investigated in this paper. Machine learning models have been proved to be the most efficient regarding such prediction. Models like Artificial Neural Network (ANN), Long Short-Term Memory (LSTM) and Random Forest (RF) have been used in this study to build robust models taking the COVID-19 lockdown situation into account. Data sets for the models were formulated by taking daily generation reports, weather indicators and holidays. This study aims to compare different machine learning models to find out the best model for load forecasting keeping into account the impact of COVID-19 lockdown. The results of these methods have been compared based on accuracy metrics. It has been observed that LSTM shows the least error among the compared models. © 2021 IEEE.

Dominant clade-featured SARS-CoV-2 co-occurring mutations reveal plausible epistasis: An in silico based hypothetical model.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into eight fundamental clades with four of these clades (G, GH, GR, and GV) globally prevalent in 2020. To explain plausible epistatic effects of the signature co-occurring mutations of these circulating clades on viral replication and transmission fitness, we proposed a hypothetical model using in silico approach. Molecular docking and dynamics analyses showed the higher infectiousness of a spike mutant through more favorable binding of G614 with the elastase-2. RdRp mutation p.P323L significantly increased genome-wide mutations (p < 0.0001), allowing for more flexible RdRp (mutated)-NSP8 interaction that may accelerate replication. Superior RNA stability and structural variation at NSP3:C241T might impact protein, RNA interactions, or both. Another silent 5'-UTR:C241T mutation might affect translational efficiency and viral packaging. These four G-clade-featured co-occurring mutations might increase viral replication. Sentinel GH-clade ORF3a:p.Q57H variants constricted the ion-channel through intertransmembrane-domain interaction of cysteine(C81)-histidine(H57). The GR-clade N:p.RG203-204KR would stabilize RNA interaction by a more flexible and hypo-phosphorylated SR-rich region. GV-clade viruses seemingly gained the evolutionary advantage of the confounding factors; nevertheless, N:p.A220V might modulate RNA binding with no phenotypic effect. Our hypothetical model needs further retrospective and prospective studies to understand detailed molecular events and their relationship to the fitness of SARS-CoV-2.

Impact of the COVID-19 pandemic on the environment and socioeconomic viability: a sustainable production chain alternative

Purpose: The purpose of this study is to address the global COVID-19 pandemic related to its sustainability, such as environmental, economic and social concerns. The short study also examined how various innovative approaches can help promote sustainable production. Design/methodology/approach: The methodology examines hypothetical scenarios of the current pandemic and tries to describe the quality of evidence to facilitate careful, critical engagement by readers. Secondary data is used to identify sustainability challenges, such as environmental, social and economic viability challenges. The information in this report was gathered from numerous media outlets, research agencies, policy papers, newspapers and other sources to gain a better knowledge of the issue. Findings: As a result, most industry executives and policymakers are looking for appropriate strategies and policies to improve their practices and meet consumer demand. The outcomes explore that the COVID-19 pandemic is a central factor in changes in people’s behavior, reflecting sustainability such as environmental, social and economic responsibility. The COVID-19 outbreak, surprisingly, had a bigger effect on sustainable consumption, accompanied by environmental sustainability, and, to a lesser extent, social and economic viability. Research limitations/implications: Limited secondary evidence and data could not scrutinize the study’s actual problem statements. Hence, it is recommended that the gap in research be fulfilled by conducting a primary survey among various groups of economists, environmentalists and industrialists using the cluster sampling technique by validating the questionnaire of the total sustainable production system. Proposing frameworks for improving the resilience of production and a systematic possible upgraded manufacturing system by using the Industry 4.0 technology during operational processes could advance market demand. Practical implications: The COVID-19 scenario has compelled manufacturing firms to put their production systems on hold for an extended period while they seek long-term solutions to assure simple delivery and cooperation from both business and consumer standpoints. Various aspects of supply and demand are discussed in the referendum, as well as production and consumption challenges during the COVID-19 era. There is a need to restore the production system and find the right source of raw materials. This work focuses on commodity inventory management systems due to mass production, but due to pandemics, it is not in demand and vice versa. The researcher made comprehensible remarks on the use of digitization in the pandemic, which improves social distancing and social well-being and promotes the production system as well. Besides, manufacturing plants should switch to digital manufacturing to reduce the number of workplaces and hence the risk of an outbreak. Therefore, a better supply chain network is needed to supply more manufacturing units. Social implications: There is a bright side of coronavirus that the public health crisis raised worldwide has brought many opportunities for governments and society to make eternal reforms in the public health sector door. During restricted movements for fulfilling market demand, the Industry 4.0 technologies for automation, mechanization and digitalization can help significantly advance a company. This technological advancement and computer digitization for the perspective people may improve the environment, economic and social sustainability also increase social media adoption, which can be crucial for agri-businesses to evaluate customers’ behavior and consumption trends. Originality/value: The paper also instructed to identify critical success factors, barriers and drivers for dealing with the pandemic situation and to develop a strategic policy framework to improve production and process flexibility through the remarkable introduction of digital manufacturing. Before it is too late to stop the spread, producers and consumers must grasp the limits to which suppliers might drive nature. © 2021, Emerald Publishing Limited.

Fresh Insight through a Keynesian Theory Approach to Investigate the Economic Impact of the COVID-19 Pandemic in Pakistan

Beyond the immediate impositions of dealing with COVID-19, this disease represents a severe and significant challenge confronting Pakistan’s economy. The study’s objective was to evaluate the coronavirus epidemic’s effect on Pakistan’s economy and measures devised to mitigate the damage done by this disease. The study research design used the elementary concept of Keynesian theory comprising of the mapping of systematic behavior of the COVID-19 pandemic. Issues were formally underpinned, described, and visualized through the Keynesian theory concept. The eruption of COVID-19 has jolted the national and international economy. Pakistan is included, causing millions of people to stay at home, lose their jobs, and suspend or end business operations. Unemployment in Pakistan has reached nearly 25 million people, driving many towards conditions of hunger and poverty as the major economic damage in several sectors is anticipated at around PKR 1.3 trillion. The hardest-affected sectors comprise industries such as tourism and travel, financial markets, entertainment, manufacturing, etc., having a devastating effect on gross domestic product (GDP). It is mainly daily-wage earners and people running small businesses that have been seriously exploited and subjected to a curfew-like situation. However, the Keynesian theory suggests that supportive macroeconomic policies must restore trust, demand recovery, and provide interest-free loans to overcome Pakistan’s currently upcoming crisis.

The COVID-19 Pandemic: Are There Any Impacts on Sustainability?

This paper sets out to explain and describe the potential ways to control COVID-19′s impact on the environment and what controllable strategies and anticipations emerge from rethinking sustainable production. The rapid and devastating spread of this disease has made millions of people throughout the world cover themselves, wear gloves, and use hand sanitizers and other medical applications. However, it means that a huge amount of clinical waste is being dumped into landfills or the oceans, and such activity may simply worsen the infection’s transmission and the sustainability of the environment, the socio-economy, and sustainable productions. This disease has greatly changed the way people live and has caused considerable occupational job losses and misfortunes, sending sustainable businesses and other organizations to the wall. Virtually every country is trying to stop the infection transmission by testing patients and isolating people, but the environmental effects of the pandemic and sustainable business have not previously been analyzed. The study suggests that the current options for sustainable production must be measured and also further researched.

Evolutionary dynamics of SARS-CoV-2 nucleocapsid protein and its consequences.

The emerged novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a global health crisis that warrants an accurate and detailed characterization of the rapidly evolving viral genome for understanding its epidemiology, pathogenesis, and containment. Here, we explored 61,485 sequences of the nucleocapsid (N) protein, a potent diagnostic and prophylactic target, for identifying the mutations to review their roles in real-time polymerase chain reaction based diagnosis and observe consequent impacts. Compared to the Wuhan reference strain, a total of 1034 unique nucleotide mutations were identified in the mutant strains (49.15%, n = 30,221) globally. Of these mutations, 367 occupy primer binding sites including the 3'-end mismatch to the primer-pair of 11 well-characterized primer sets. Noteworthily, CDC (USA) recommended the N2 primer set contained a lower mismatch than the other primer sets. Moreover, 684 amino acid (aa) substitutions were located across 317 (75.66% of total aa) unique positions including 82, 21, and 83 of those in the RNA binding N-terminal domain (NTD), SR-rich region, and C-terminal dimerization domain, respectively. Moreover, 11 in-frame deletions, mostly (n = 10) within the highly flexible linker region, were revealed, and the rest was within the NTD region. Furthermore, we predicted the possible consequence of high-frequency mutations (≥20) and deletions on the tertiary structure of the N protein. Remarkably, we observed that a high frequency (67.94% of mutated sequences) co-occuring mutations (R203K and G204R) destabilized and decreased overall structural flexibility. The N protein of SARS-CoV-2 comprises an average of 1.2 mutations per strain compared to 4.4 and 0.4 in Middle East respiratory syndrome-related coronavirus and SARS-CoV, respectively. Despite being proposed as the alternative target to spike protein for vaccine and therapeutics, the ongoing evolution of the N protein may challenge these endeavors, thus needing further immunoinformatics analyses. Therefore, continuous monitoring is required for tracing the ongoing evolution of the SARS-CoV-2 N protein in prophylactic and diagnostic interventions.

Understanding the possible origin and genotyping of the first Bangladeshi SARS-CoV-2 strain.

The novel coronavirus, SARS-CoV-2, has caused the most unfathomable pandemic in the history of humankind. Bangladesh is also a victim of this critical situation. To investigate the genomic features of the pathogen from Bangladesh, the first complete genome of the virus has very recently been published. Therefore, long-awaited questions regarding the possible origin and typing of the strain(s) can now be answered. Here, we endeavor to mainly discuss the published reports or online-accessed data (results) regarding those issues and present a comprehensive picture of the typing of the virus alongside the probable origin of the subclade containing the Bangladeshi strain. Our observation suggested that this strain might have originated from the United Kingdom or the other European countries epidemiologically linked to the United Kingdom. According to different genotyping classification schemes, this strain belongs to the A2a clade under the G major clade, is of B and/or L type, and is a SARS-CoV-2a substrain. In the future, randomized genomic data will certainly increase in Bangladesh, however because of globalization and immigrant movement, we urgently need a mass regional sequencing approach targeting the partial or complete genome that can link the epidemiological data and may help in further clinical intervention.

An Alternative Laboratory Assessment Approach for Multimedia Modules in a Transnational Education (TNE) Programme during COVID-19

Experimentation is a key component of any engineering education, and it can be either hardware or simulation (software) based experiments or mixed. While the teaching and learning are provided in an alternative manner (mostly online) for ensuring the continuity of education and the student learning experiences due to the COVID-19 pandemic, both hardware and software based laboratory assessments must also be conducted in an alternative manner. In this paper, we share and discuss a systematic approach as an alternative laboratory assessment (ALA) for Multimedia Engineering modules in the Transnational Education (TNE) programme between Queen Mary University of London (QMUL) and Beijing University of Post and Telecommunications (BUPT). We have conducted this study to verify how the ALA using the systematic approach for two multimedia modules have achieved the intended learning outcomes. Based on the quantitative analysis, we have suggested how we can improve the laboratory assessment in the alternative approach.

Prevalence and stability of SARS-CoV-2 RNA on Bangladeshi banknotes.

Originating in December 2019 in China, SARS-CoV-2 has emerged as the deadliest pandemic in humankind's history. Along with direct contact and droplet contaminations, the possibility of infections through contaminated surfaces and fomites is investigating. This study aims to assess SARS-CoV-2 viral RNA's prevalence by real-time one-step reverse transcriptase PCR on banknotes circulating in Bangladesh. We also evaluated the persistence of the virus on banknotes spiked with SARS-CoV-2 positive diluted human nasopharyngeal samples. Among the 425 banknote samples collected from different entities, 7.29% (n = 31) were tested positive for targeted genes. Twenty-four positive representative samples were assessed for n gene fragments by conventional PCR and sequenced. All the samples that carry viral RNA belonged to the GR clade, the predominantly circulating clade in Bangladesh. In the stability test, the n gene was detected for up to 72 h on banknotes spiked with nasopharyngeal samples, and CT values increase significantly with time (p < 0.05). orf1b gene was observed to be less stable, especially on old banknotes, and usually went beyond detectable limit within 8 to 10 h. The stability of virus RNA well fitted by the Weibull model and concave curve for new banknotes and convex curve for old banknotes revealed. Handling banknotes is unavoidable; hence, these findings imply that proper hygiene practice is needed to limit SARS-CoV-2 transmission through banknotes.

Electrical peak load clustering analysis using K-means algorithm and silhouette coefficient

Nowadays, data analysis widely used in many fields especially in engineering. Clustering is one of data analysis methods to organize the amount of data into groups with similarity characteristics. One powerful analysis method to learn information by grouping data is clustering algorithms. The clustering advantages for electrical power utilities is to learn load behavior and provide information for power plant operation and also generation cost. In this paper, a simulation concept is proposed for analysis of peak load data by K-means clustering algorithm based on historical dataset. The results show electrical peak loads clustering by K-means algorithm are optimum classified into three clusters. This cluster evaluated by silhouette scores which high, intermediate, and low load level interpretation. One cluster has centroid during January, June, and July are relatively lower than another cluster caused by Indonesia national holiday. This concept also evaluates the load level affected by Covid-19 pandemic condition. © 2020 IEEE.

Epitope-based chimeric peptide vaccine design against S, M and E proteins of SARS-CoV-2, the etiologic agent of COVID-19 pandemic: an in silico approach.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19), a public health emergency of international concerns declared by the World Health Organization (WHO). An immuno-informatics approach along with comparative genomics was applied to design a multi-epitope-based peptide vaccine against SARS-CoV-2 combining the antigenic epitopes of the S, M, and E proteins. The tertiary structure was predicted, refined and validated using advanced bioinformatics tools. The candidate vaccine showed an average of ≥90.0% world population coverage for different ethnic groups. Molecular docking and dynamics simulation of the chimeric vaccine with the immune receptors (TLR3 and TLR4) predicted efficient binding. Immune simulation predicted significant primary immune response with increased IgM and secondary immune response with high levels of both IgG1 and IgG2. It also increased the proliferation of T-helper cells and cytotoxic T-cells along with the increased IFN-γ and IL-2 cytokines. The codon optimization and mRNA secondary structure prediction revealed that the chimera is suitable for high-level expression and cloning. Overall, the constructed recombinant chimeric vaccine candidate demonstrated significant potential and can be considered for clinical validation to fight against this global threat, COVID-19.

Genome-wide analysis of SARS-CoV-2 virus strains circulating worldwide implicates heterogeneity.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a novel evolutionary divergent RNA virus, is responsible for the present devastating COVID-19 pandemic. To explore the genomic signatures, we comprehensively analyzed 2,492 complete and/or near-complete genome sequences of SARS-CoV-2 strains reported from across the globe to the GISAID database up to 30 March 2020. Genome-wide annotations revealed 1,516 nucleotide-level variations at different positions throughout the entire genome of SARS-CoV-2. Moreover, nucleotide (nt) deletion analysis found twelve deletion sites throughout the genome other than previously reported deletions at coding sequence of the ORF8 (open reading frame), spike, and ORF7a proteins, specifically in polyprotein ORF1ab (n = 9), ORF10 (n = 1), and 3´-UTR (n = 2). Evidence from the systematic gene-level mutational and protein profile analyses revealed a large number of amino acid (aa) substitutions (n = 744), demonstrating the viral proteins heterogeneous. Notably, residues of receptor-binding domain (RBD) showing crucial interactions with angiotensin-converting enzyme 2 (ACE2) and cross-reacting neutralizing antibody were found to be conserved among the analyzed virus strains, except for replacement of lysine with arginine at 378th position of the cryptic epitope of a Shanghai isolate, hCoV-19/Shanghai/SH0007/2020 (EPI_ISL_416320). Furthermore, our results of the preliminary epidemiological data on SARS-CoV-2 infections revealed that frequency of aa mutations were relatively higher in the SARS-CoV-2 genome sequences of Europe (43.07%) followed by Asia (38.09%), and North America (29.64%) while case fatality rates remained higher in the European temperate countries, such as Italy, Spain, Netherlands, France, England and Belgium. Thus, the present method of genome annotation employed at this early pandemic stage could be a promising tool for monitoring and tracking the continuously evolving pandemic situation, the associated genetic variants, and their implications for the development of effective control and prophylaxis strategies.

Comparative molecular investigation of the potential inhibitors against SARS-CoV-2 main protease: a molecular docking study.

Recent outbreak of novel coronavirus and its rapid pandemic escalation in all over the world has drawn the attention to urgent need for effective drug development. However, due to prolonged vaccine and drug development procedure against a newly emerged devastating SARS-CoV-2 virus pathogen, repurposing of existing potential pertinent drug molecules would be preferable strategy to reduce mortality immediately and further development of new drugs to combat overall global Covid-19 crisis in all over the world. Herein, we have filtered 23 prospective drug candidates through literature review. Assessing evidences from molecular docking studies, it was clearly seen that, Epirubicin, Vapreotida, and Saquinavir exhibited better binding affinity against SARS-CoV-2 Main Protease than other drug molecules among the 23 potential inhibitors. However, 50 ns molecular dynamics simulation indicated the less mobile nature of the docked complex maintaining structural integrity. Our overall prediction findings indicate that Epirubicin, Vapreotida, and Saquinavir may inhibit COVID-19 by synergistic interactions in the active cavity and those results can pave the way in drug discovery although it has to be further validated by in-vitro and in-vivo investigations.Communicated by Ramaswamy H. Sarma.