ABSTRACT
Coronavirus disease 2019 (COVID-19) has developed as a pandemic, and it created an outrageous effect on the current healthcare and economic system throughout the globe. To date, there is no appropriate therapeutics or vaccines against the disease. The entire human race is eagerly waiting for the development of new therapeutics or vaccines against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Efforts are being taken to develop vaccines at a rapid rate for fighting against the ongoing pandemic situation. Amongst the various vaccines under consideration, some are either in the preclinical stage or in the clinical stages of development (phase-I, -II, and -III). Even, phase-III trials are being conducted for some repurposed vaccines like Bacillus Calmette–Guérin, polio vaccine, and measlesmumps-rubella. We have highlighted the ongoing clinical trial landscape of the COVID-19 as well as repurposed vaccines. An insight into the current status of the available antigenic epitopes for SARS-CoV-2 and different types of vaccine platforms of COVID-19 vaccines has been discussed. These vaccines are highlighted throughout the world by different news agencies. Moreover, ongoing clinical trials for repurposed vaccines for COVID-19 and critical factors associated with the development of COVID-19 vaccines have also been described.
ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus (CoV), has recently emerged as a significant pathogen for humans and the cause for the recent outbreak of the 2019 novel coronavirus disease (COVID-19) throughout the globe. For developing any preventive measure, an understanding of the zoonotic pattern for this virus is a necessity. We should have a clear knowledge of its reservoir host, its distribution pattern and spreading routes. Information about zoonotic reservoirs and its transmission among them can help to understand the COVID-19 outbreaks. In this article, we discuss about the bats as the zoonotic reservoir of several CoV strains, co-existence of bats and CoV/viruses, the sequence similarity of SARS-CoV-2 with bat SARS-like CoV, the probable source of the origin of SARS-CoV-2 strain and COVID-19 outbreak, intermediate host of CoVs and SARS-CoV-2, human to human transmission and the possibility to maintain the zoonotic barriers. Our knowledge about the zoonotic reservoir of SARS-CoV-2 and its transmission ability may help develop the preventive measures and control for the future outbreak of CoV.
ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus (CoV), has recently emerged as a significant pathogen for humans and the cause for the recent outbreak of the 2019 novel coronavirus disease (COVID-19) throughout the globe. For developing any preventive measure, an understanding of the zoonotic pattern for this virus is a necessity. We should have a clear knowledge of its reservoir host, its distribution pattern and spreading routes. Information about zoonotic reservoirs and its transmission among them can help to understand the COVID-19 outbreaks. In this article, we discuss about the bats as the zoonotic reservoir of several CoV strains, co-existence of bats and CoV/viruses, the sequence similarity of SARS-CoV-2 with bat SARS-like CoV, the probable source of the origin of SARS-CoV-2 strain and COVID-19 outbreak, intermediate host of CoVs and SARS-CoV-2, human to human transmission and the possibility to maintain the zoonotic barriers. Our knowledge about the zoonotic reservoir of SARS-CoV-2 and its transmission ability may help develop the preventive measures and control for the future outbreak of CoV.
ABSTRACT
Ebola virus disease (EVD) is associated with haemorrhagic fever in humans and nonhuman primates, with a high rate of fatality (up to 90%). Some outbreaks in human history have proven the lethality of EVD. The recent epidemic of 2014 and 2015 in West Africa was the deadliest of all time (11 284 deaths). To understand the transmission dynamics, we have reviewed the epidemiology of EVD to date. The absence of any licensed vaccines or approved drugs against Ebola virus (EBOV) further highlights the severity and crisis level of EVD. Some organizations (public and private) are making considerable efforts to develop novel therapeutic approaches or vaccines to contain the outbreak of EBOV shortly. Here, we summarized the various potential drugs and vaccines (undergoing multiple phases of clinical trials) that have arisen as an alternative against EBOV, and we highlighted the numerous issues and limitations hindering this process. Alternatively, an increasing focus on strengthening the medical and civic health structure could provide speedy benefits in containing the spread of EVD, as well as offer a resilient foundation for the deployment of novel drugs and vaccines to the affected countries, once such drugs and vaccines become available.
ABSTRACT
Objective: Druggability of a target protein depends on the interacting micro-environment between the target protein and drugs. Therefore, a precise knowledge of the interacting micro-environment between the target protein and drugs is requisite for drug discovery process. To understand such micro-environment, we performed in silico interaction analysis between a human target protein, Dipeptidyl Peptidase-IV [DPP-4], and three anti-diabetic drugs [saxagliptin, linagliptin and vildagliptin]
Materials and Methods: During the theoretical and bioinformatics analysis of micro-environmental properties, we performed drug-likeness study, protein active site predictions, docking analysis and residual interactions with the protein-drug interface. Micro-environmental landscape properties were evaluated through various parameters such as binding energy, intermolecular energy, electrostatic energy, van der Waals'+H-bond+desolvo energy [EVHD] and ligand efficiency [LE] using different in silico methods. For this study, we have used several servers and software, such as Molsoft prediction server, CASTp server, AutoDock software and LIGPLOT server
Results: Through micro-environmental study, highest log P value was observed for linagliptin [1.07]. Lowest binding energy was also observed for linagliptin with DPP-4 in the binding plot. We also identified the number of H-bonds and residues involved in the hydrophobic interactions between the DPP-4 and the anti-diabetic drugs. During interaction, two H-bonds and nine residues, two H-bonds and eleven residues as well as four H-bonds and nine residues were found between the saxagliptin, linagliptin as well as vildagliptin cases and DPP-4, respectively
Conclusion: Our in silico data obtained for drug-target interactions and micro-environmental signature demonstrates linagliptin as the most stable interacting drug among the tested anti-diabetic medicines
Subject(s)
Humans , Molecular Targeted Therapy , Protein Binding , Drug Discovery , Dipeptidyl Peptidase 4/drug effects , Dipeptidyl-Peptidase IV Inhibitors , Models, MolecularABSTRACT
Research related to induce pluripotent stem [iPS] cell generation has increased rapidly in recent years. Six transcription factors, namely OCT4, SOX2, C-MYC, KLF4, NANOG, and LIN28 have been widely used for iPS cell generation. As there is a lack of data on intra- and inter-networking among these six different transcription factors, the objective of this study is to analyze the intra- and inter-networks between them using bioinformatics. In this computational biology study, we used AminoNet, MATLAB to examine networking between the six different transcription factors. The directed network was constructed using MATLAB programming and the distance between nodes was estimated using a phylogram. The protein-protein interactions between the nuclear reprogramming factors was performed using the software STRING. The relationship between C-MYC and NANOG was depicted using a phylogenetic tree and the sequence analysis showed OCT4, C-MYC, NANOG, and SOX2 together share a common evolutionary origin. This study has shown an innovative rapid method for the analysis of intra and inter-networking among nuclear reprogramming factors. Data presented may aid researchers to understand the complex regulatory networks involving iPS cell generation