Last few decades, viruses are a real menace to human safety. Therefore, the rapid identification of viruses should be one of the best ways to prevent an outbreak and important implications for medical healthcare. The recent outbreak of coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus which belongs to the single-stranded, positive-strand RNA viruses. The pandemic dimension spread of COVID-19 poses a severe threat to the health and lives of seven billion people worldwide. There is a growing urgency worldwide to establish a point-of-care device for the rapid detection of COVID-19 to prevent subsequent secondary spread. Therefore, the need for sensitive, selective, and rapid diagnostic devices plays a vital role in selecting appropriate treatments and to prevent the epidemics. During the last decade, electrochemical biosensors have emerged as reliable analytical devices and represent a new promising tool for the detection of different pathogenic viruses. This review summarizes the state of the art of different virus detection with currently available electrochemical detection methods. Moreover, this review discusses different fabrication techniques, detection principles, and applications of various virus biosensors. Future research also looks at the use of electrochemical biosensors regarding a potential detection kit for the rapid identification of the COVID-19.
Most recently, an outbreak of severe pneumonia caused by the infection of SARS-CoV-2, a novel coronavirus first identified in Wuhan, China, imposes serious threats to public health. Upon infecting host cells, coronaviruses assemble a multi-subunit RNA-synthesis complex of viral non-structural proteins (nsp) responsible for the replication and transcription of the viral genome. Therefore, the role and inhibition of nsp12 are indispensable. A cryo-EM structure of RdRp from SARs-CoV-2 was used to identify novel drugs from Northern South African medicinal compounds database (NANPDB) by using computational virtual screening and molecular docking approaches. Considering Remdesivir as the control, 42 compounds were shortlisted to have docking score better than Remdesivir. The top 5 hits were validated by using molecular dynamics simulation approach and free energy calculations possess strong inhibitory properties than the Remdesivir. Thus, this study paved a way for designing novel drugs by decoding the architecture of an important enzyme and its inhibition with compounds from natural resources. This disclosing of necessary knowledge regarding the screening and the identification of top hits could help to design effective therapeutic candidates against the coronaviruses and design robust preventive measurements.
Intratumoral
glucose depletion-induced cancer starvation represents
an important strategy for anticancer therapy, but it is often limited
by systemic toxicity, nonspecificity, and adaptive development of
parallel energy supplies. Herein, we introduce a concept of cascaded
catalytic nanomedicine by combining targeted tumor starvation and
deoxygenation-activated chemotherapy for an efficient cancer treatment
with reduced systemic toxicity. Briefly, nanoclustered cascaded enzymes
were synthesized by covalently cross-linking glucose oxidase (GOx)
and catalase (CAT) via a pH-responsive polymer. The
release of the enzymes can be first triggered by the mildly acidic
tumor microenvironment and then be self-accelerated by the subsequent
generation of gluconic acid. Once released, GOx can rapidly deplete
glucose and molecular oxygen in tumor cells while the toxic side product, i.e., H2O2, can be readily decomposed
by CAT for site-specific and low-toxicity tumor starvation. Furthermore,
the enzymatic cascades also created a local hypoxia with the oxygen
consumption and reductase-activated prodrugs for an additional chemotherapy.
The current report represents a promising combinatorial approach using
cascaded catalytic nanomedicine to reach concurrent selectivity and
efficiency of cancer therapeutics.
Combined drug repurposing and virtual screening strategies with molecular dynamics simulation identified potent inhibitors for SARS-CoV-2 main protease (3CLpro), Journal of Biomolecular Structure and Dynamics,
Helicobacter Pylori is a known causal agent of gastric malignancies and peptic ulcers. The extremophile nature of this bacterium is protecting it from designing a potent drug against it. Therefore, the use of computational approaches to design antigenic, stable and safe vaccine against this pathogen could help to control the infections associated with it. Therefore, in this study, we used multiple immunoinformatics approaches along with other computational approaches to design a multi-epitopes subunit vaccine against H. Pylori. A total of 7 CTL and 12 HTL antigenic epitopes based on c-terminal cleavage and MHC binding scores were predicted from the four selected proteins (CagA, OipA, GroEL and cagA). The predicted epitopes were joined by AYY and GPGPG linkers. Β-defensins adjuvant was added to the N-terminus of the vaccine. For validation, immunogenicity, allergenicity and physiochemical analysis were conducted. The designed vaccine is likely antigenic in nature and produced robust and substantial interactions with Toll-like receptors (TLR-2, 4, 5, and 9). The vaccine developed was also subjected to an in silico cloning and immune response prediction model, which verified its efficiency of expression and the immune system provoking response. These analyses indicate that the suggested vaccine may produce particular immune responses against H. pylori, but laboratory validation is needed to verify the safety and immunogenicity status of the suggested vaccine design.
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