Therapeutic Management with Repurposing Approaches: A Mystery During COVID-19 Outbreak.

The ubiquitous pandemic that emerged due to COVID-19 affected the whole planet. People all over the globe became vulnerable to the unpredictable emergence of coronavirus. The sudden emergence of respiratory disease in coronavirus infected several patients. This affected human life drastically, from mild symptoms to severe illness, leading to mortality. COVID-19 is an exceptionally communicable disease caused by SARS-CoV-2. According to a genomic study, the viral spike RBD interactions with the host ACE2 protein from several coronavirus strains and the interaction between RBD and ACE2 highlighted the potential change in affinity from the virus causing the COVID-19 outbreak to a progenitor type of SARS-CoV-2. SARS-CoV-2, which could be the principal reservoir, is phylogenetically related to the SARS-like bat virus. Other research works reported that intermediary hosts for the transmission of viruses to humans could include cats, bats, snakes, pigs, ferrets, orangutans, and monkeys. Even with the arrival of vaccines and individuals getting vaccinated and treated with FDA-approved repurposed drugs like Remdesivir, the first and foremost steps aimed towards the possible control and minimization of community transmission of the virus include social distancing, self-realization, and self-health care. In this review paper, we discussed and summarized various approaches and methodologies adopted and proposed by researchers all over the globe to help with the management of this zoonotic outbreak by following repurposed approaches.

Safety, Pharmacokinetics, Serum Neutralizing Titers, and Immunogenicity of Adintrevimab, a Monoclonal Antibody Targeting SARS-CoV-2: A Randomized, Double-Blind, Placebo-Controlled, Phase 1 Dose-escalation Study in Healthy Adults.

INTRODUCTION: Adintrevimab is a fully human immunoglobulin G1 extended half-life monoclonal antibody that was developed to have broad neutralization against SARS-CoV, SARS-CoV-2, and other SARS-like CoVs with pandemic potential. Here we report the safety, pharmacokinetics (PK), serum viral neutralizing antibody (sVNA) titers, and immunogenicity results of the first three cohorts evaluated in the first-in-human study of adintrevimab in healthy adults. METHODS: This is a phase 1, randomized, placebo-controlled, single ascending-dose study of adintrevimab administered intramuscularly (IM) or intravenously (IV) to healthy adults aged ≥ 18-55 years with no current or prior SARS-CoV-2 infection. Participants were randomized 8:2 to adintrevimab or placebo in each of three dose cohorts: adintrevimab 300 mg IM (cohort 1), 500 mg IV (cohort 2), and 600 mg IM (cohort 3). Follow-up was 12 months. Blood samples were taken predose and at multiple time points postdose up to month 12 to assess sVNA, PK, and antidrug antibodies (ADAs). RESULTS: Thirty participants received a single dose of adintrevimab (n = 24; 8 per cohort) or placebo (n = 6). All except one adintrevimab participant in cohort 1 completed the study. No participants in any treatment arm experienced a study drug-related adverse event. Across adintrevimab-treated participants, 11 (45.8%) experienced at least one TEAE. All but one TEAE were mild in severity, and all were either viral infection or respiratory symptoms. There were no serious adverse events, discontinuations due to adverse events, or deaths. Adintrevimab exhibited a linear and dose-proportional PK profile and extended serum half-life (mean 96, 89, and 100 days in cohorts 1, 2, and 3, respectively). Participants receiving adintrevimab demonstrated dose-dependent increased sVNA titers and breadth across multiple variants. CONCLUSION: Adintrevimab at doses of 300 mg IM, 500 mg IV, and 600 mg IM was well tolerated in healthy adults. Adintrevimab demonstrated dose-proportional exposure, rapid development of neutralizing antibody titers, and an extended half-life.

Effect of Double Mutation (L452R and E484Q) on the Binding Affinity of Monoclonal Antibodies (mAbs) against the RBD-A Target for Vaccine Development.

The COVID-19 pandemic, caused by SARS-CoV-2, emerges as a global health problem, as the viral genome is evolving rapidly to form several variants. Advancement and progress in the development of effective vaccines and neutralizing monoclonal antibodies are promising to combat viral infections. In the current scenario, several lineages containing "co-mutations" in the receptor-binding domain (RBD) region of the spike (S) protein are imposing new challenges. Co-occurrence of some co-mutations includes delta (L452R/T478K), kappa (L452R/E484Q), and a common mutation in both beta and gamma variants (E484K/N501Y). The effect of co-mutants (L452R/E484Q) on human angiotensin-converting enzyme 2 (hACE2) binding has already been elucidated. Here, for the first time, we investigated the role of these RBD co-mutations (L452R/E484Q) on the binding affinity of mAbs by adopting molecular dynamics (MD) simulation and free-energy binding estimation. The results obtained from our study suggest that the structural and dynamic changes introduced by these co-mutations reduce the binding affinity of the viral S protein to monoclonal antibodies (mAbs). The structural changes imposed by L452R create a charged patch near the interfacial surface that alters the affinity towards mAbs. In E484Q mutation, polar negatively charged E484 helps in the formation of electrostatic interaction, while the neutrally charged Q residue affects the interaction by forming repulsive forces. MD simulations along with molecular mechanics-generalized Born surface area (MMGBSA) studies revealed that the REGN 10933, BD-368-2, and S2M11 complexes have reduced binding affinity towards the double-mutant RBD. This indicates that their mutant (MT) structures have a stronger ability to escape from most antibodies than the wild type (WT). However, EY6A Ab showed higher affinity towards the double MT-RBD complex as compared to the WT. However, no significant effect of the per-residue contribution of double-mutated residues was observed, as this mAb does not interact with the region harboring L452 and E484 residues.

E-Learning Environment Based Intelligent Profiling System for Enhancing User Adaptation

Online learning systems have expanded significantly over the last couple of years. Massive Open Online Courses (MOOCs) have become a major trend on the internet. During the COVID-19 pandemic, the count of learner enrolment has increased in various MOOC platforms like Coursera, Udemy, Swayam, Udacity, FutureLearn, NPTEL, Khan Academy, EdX, SWAYAM, etc. These platforms offer multiple courses, and it is difficult for online learners to choose a suitable course as per their requirements. In order to improve this e-learning education environment and to reduce the drop-out ratio, online learners will need a system in which all the platform's offered courses are compared and recommended, according to the needs of the learner. So, there is a need to create a learner's profile to analyze so many platforms in order to fulfill the educational needs of the learners. To develop a profile of a learner or user, three input parameters are considered: personal details, educational details, and knowledge level. Along with these parameters, learners can also create their user profiles by uploading their CVs or LinkedIn. In this paper, the major innovation is to implement a user interface-based intelligent profiling system for enhancing user adaptation in which feedback will be received from a user and courses will be recommended according to user/learners' preferences.

IoT Fog-Enabled Multi-Node Centralized Ecosystem for Real Time Screening and Monitoring of Health Information

In today's technological and stressful world, when everyone is busy in their daily routines and places blind faith in pharmaceutical advancements to protect their health, the sudden, horrifying effects of the COVID-19 pandemic have resulted in serious emotional and psychological impacts in the general population. In spite of advanced vaccination campaigns, fear and hesitation have become a part of human life since there are a number of people who do not want to take these immunity boosting vaccinations. Such people may become carriers of infectious viruses, leading to a more rapid rate of spread;therefore, this class of spreaders needs to be screened at the earliest opportunity. In this context, there is a need for advanced health monitoring systems which can assist the pharmaceutical industry to monitor and record the health status of people. To address this need and reduce the uncertainty of the situation, this study has designed and tested an Internet of Things (IoT) and Fog computing-based multi-node architecture was for real-time initial screening and recording of such subjects. The proposed system was able to record current body temperature and location coordinates along with the facial images. Further, the proposed system was able to transmit data to a cloud database using internet-connected services. An implementation and reviews-based working environment analysis was conducted to determine the efficacy of the proposed system. It was observed from the statistical analysis that the proposed IoT Fog-enabled ecosystem could be utilized efficiently.

Genomic and structural mechanistic insight to reveal the differential infectivity of omicron and other variants of concern.

BACKGROUND: The genome of SARS-CoV-2, is mutating rapidly and continuously challenging the management and preventive measures adopted and recommended by healthcare agencies. The spike protein is the main antigenic site that binds to the host receptor hACE-2 and is recognised by antibodies. Hence, the mutations in this site were analysed to assess their role in differential infectivity of lineages having these mutations, rendering the characterisation of these lineages as variants of concern (VOC) and variants of interest (VOI). METHODS: In this work, we examined the genome sequence of SARS-CoV-2 VOCs and their phylogenetic relationships with the other PANGOLIN lineages. The mutational landscape of WHO characterized variants was determined and mutational diversity was compared amongst the different severity groups. We then computationally studied the structural impact of the mutations in receptor binding domain of the VOCs. The binding affinity was quantitatively determined by molecular dynamics simulations and free energy calculations. RESULTS: The mutational frequency, as well as phylogenetic distance, was maximum in the case of omicron followed by the delta variant. The maximum binding affinity was for delta variant followed by the Omicron variant. The increased binding affinity of delta strain followed by omicron as compared to other variants and wild type advocates high transmissibility and quick spread of these two variants and high severity of delta variant. CONCLUSION: This study delivers a foundation for discovering the improved binding knacks and structural features of SARS-CoV-2 variants to plan novel therapeutics and vaccine candidates against the virus.

Intelligent Load-Balancing Framework for Fog-Enabled Communication in Healthcare

The present technological era significantly makes use of Internet-of-Things (IoT) devices for offering and implementing healthcare services. Post COVID-19, the future of the healthcare system is highly reliant upon the inculcation of Artificial-Intelligence (AI) mechanisms in its day-to-day procedures, and this is realized in its implementation using sensor-enabled smart and intelligent IoT devices for providing extensive care to patients relative to the symmetric concept. The offerings of such AI-enabled services include handling the huge amount of data processed and sensed by smart medical sensors without compromising the performance parameters, such as the response time, latency, availability, cost and processing time. This has resulted in a need to balance the load of the smart operational devices to avoid any failure of responsiveness. Thus, in this paper, a fog-based framework is proposed that can balance the load among fog nodes for handling the challenging communication and processing requirements of intelligent real-time applications.

Structural and functional insights into the spike protein mutations of emerging SARS-CoV-2 variants.

Since the emergence of the first case of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2), the viral genome has constantly undergone rapid mutations for better adaptation in the host system. These newer mutations have given rise to several lineages/ variants of the virus that have resulted in high transmission and virulence rates compared to the previously circulating variants. Owing to this, the overall caseload and related mortality have tremendously increased globally to > 233 million infections and > 4.7 million deaths as of Sept. 28th, 2021. SARS-CoV-2, Spike (S) protein binds to host cells by recognizing human angiotensin-converting enzyme 2 (hACE2) receptor. The viral S protein contains S1 and S2 domains that constitute the binding and fusion machinery, respectively. Structural analysis of viral S protein reveals that the virus undergoes conformational flexibility and dynamicity to interact with the hACE2 receptor. The SARS-CoV-2 variants and mutations might be associated with affecting the conformational plasticity of S protein, potentially linked to its altered affinity, infectivity, and immunogenicity. This review focuses on the current circulating variants of SARS-CoV-2 and the structure-function analysis of key S protein mutations linked with increased affinity, higher infectivity, enhanced transmission rates, and immune escape against this infection.

Blockchain Enabled Transparent and Anti-Counterfeiting Supply of COVID-19 Vaccine Vials.

The COVID-19 pandemic has profoundly affected almost all facets of peoples' lives, various economic areas and regions of the world. In such a situation implementation of a vaccination can be viewed as essential but its success will be dependent on availability and transparency in the distribution process that will be shared among the stakeholders. Various distributed ledgers (DLTs) such as blockchain provide an open, public, immutable system that has numerous applications due the mentioned abilities. In this paper the authors have proposed a solution based on blockchain to increase the security and transparency in the tracing of COVID-19 vaccination vials. Smart contracts have been developed to monitor the supply, distribution of vaccination vials. The proposed solution will help to generate a tamper-proof and secure environment for the distribution of COVID-19 vaccination vials. Proof of delivery is used as a consensus mechanism for the proposed solution. A feedback feature is also implemented in order to track the vials lot in case of any side effect cause to the patient. The authors have implemented and tested the proposed solution using Ethereum test network, RinkeyBy, MetaMask, one clicks DApp. The proposed solution shows promising results in terms of throughput and scalability.