An in silico discovery of potential 3CL protease inhibitors of SARS-CoV-2 based upon inactivation of the cysteine 145-Histidine 41 catalytic dyad.

Coronavirus disease 19 (COVID19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, several countries are at risk of the pandemic caused by this virus. In the absence of any vaccine or virus-specific antiviral treatments, the need is to fast track search for potential drug candidates to combat the virus. Though there are known drugs that are being repurposed to fight against the SARS-CoV-2, there is a requirement for the virus-specific drugs at the earliest. One of the main drug targets of SARS-CoV-2 is an essential non-structural protein, 3CL protease, critical for the life cycle of the virus. We have used molecular docking studies to screen a chemically diverse set of small molecules to identify potential drug candidates to target this protein. Of the 22,630 molecules from varied small molecule libraries, based on the binding affinities and physicochemical properties, we finalized 30 molecules to be potential drug candidates. Eight of these molecules bind in a manner allowing for the scope of a nearly orthogonal backside nucleophilic attack on their suitably placed electrophilic carbonyl groups by the thiol group of cysteine residue 145, while remaining inside a 4 Ǻ distance range. It is interesting since carbonyl groups are known to be attacked in a similar fashion by external nucleophiles and can be relevant when considering these molecules as potential mechanism-based irreversible inhibitors of the 3CLPro. Further, ADMET analysis and Molecular dynamics simulations and available bioactive assays led to the identification of three molecules with high potential to be explored as drug candidates/lead molecules to target 3CLPro of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Dengue outbreak and severity prediction: current methods and the future scope.

Dengue virus (DENV) is the causative agent of dengue fever and severe dengue. Every year, millions of people are infected with this virus. There is no vaccine available for this disease. Dengue virus is present in four serologically varying strains, DENV 1, 2, 3, and 4, and each of these serotypes is further classified into various genotypes based on the geographic distribution and genetic variance. Mosquitoes play the role of vectors for this disease. Tropical countries and some temperate parts of the world witness outbreaks of dengue mainly during the monsoon (rainy) seasons. Several algorithms have been developed to predict the occurrence and prognosis of dengue disease. These algorithms are mainly based on epidemiological data, climate factors, and online search patterns in the infected area. Most of these algorithms are based on either machine learning or deep learning techniques. We summarize the different software tools available for predicting the outbreaks of dengue based on the aforementioned factors, briefly outline the methodology used in these algorithms, and provide a comprehensive list of programs available for the same in this article.

Nanotechnology in combating biofilm: A smart and promising therapeutic strategy.

Since the birth of civilization, people have recognized that infectious microbes cause serious and often fatal diseases in humans. One of the most dangerous characteristics of microorganisms is their propensity to form biofilms. It is linked to the development of long-lasting infections and more severe illness. An obstacle to eliminating such intricate structures is their resistance to the drugs now utilized in clinical practice (biofilms). Finding new compounds with anti-biofilm effect is, thus, essential. Infections caused by bacterial biofilms are something that nanotechnology has lately shown promise in treating. More and more studies are being conducted to determine whether nanoparticles (NPs) are useful in the fight against bacterial infections. While there have been a small number of clinical trials, there have been several in vitro outcomes examining the effects of antimicrobial NPs. Nanotechnology provides secure delivery platforms for targeted treatments to combat the wide range of microbial infections caused by biofilms. The increase in pharmaceuticals' bioactive potential is one of the many ways in which nanotechnology has been applied to drug delivery. The current research details the utilization of several nanoparticles in the targeted medication delivery strategy for managing microbial biofilms, including metal and metal oxide nanoparticles, liposomes, micro-, and nanoemulsions, solid lipid nanoparticles, and polymeric nanoparticles. Our understanding of how these nanosystems aid in the fight against biofilms has been expanded through their use.

The RNA Secondary Structure Analysis Reveals Potential for Emergence of Pathogenic Flaviviruses.

The Flavivirus genus is divided into four groups: Mosquito-borne flaviviruses, Tick-borne flaviviruses, no-known vector flaviviruses, and Insect specific flaviviruses. Millions of people are affected worldwide every year due to the flaviviral infections. The 5' UTR of the RNA genome plays a critical role in the biology of flaviviruses. To explore any correlation between the topology of the 5' UTR and pathogenesis, a global scale study of the RNA secondary structure of different groups of flaviviruses has been conducted. We found that most of the pathogenic flaviviruses, irrespective of their mode of transmission, tend to form a Y shaped topology in the Stem loop A of the 5' UTR. Some of the current non-pathogenic flaviviruses were also observed to form Y shaped structure. Based on this study, it has been proposed that the flaviviruses having the Y shaped topology in their 5' UTR regions may have the potential to become pathogenic.

The RNA secondary structural variation in the cyclization elements of the dengue genome and the possible implications in pathogenicity.

Dengue virus (DENV), the causative agent of dengue fever and severe dengue, exists as four antigenically different serotypes. These serotypes are further classified into genotypes and have varying degrees of pathogenicity. The 5' and 3' ends of the genomic RNA play a critical role in the viral life cycle. A global scale study of the RNA structural variation among the sero- and genotypes was carried out to correlate RNA structure with pathogenicity. We found that the GC rich stem and rigid loop structure of the 5' end of the genomic RNA of DENV 2 differs significantly from the others. The observed variation in base composition and base pairing may confer structural and functional advantage in highly virulent strains. This variation in the structure may influence the ease of cyclization and recruitment of viral RNA polymerase, NS5 RdRp, thereby affecting the pathogenicity of these strains.

Finding small molecules with pan-serotype activity to target Dengue non-structural protein 1.

Dengue virus (DENV) is a mosquito-borne flavivirus which causes Dengue fever and severe Dengue. It exists as four antigenically different serotypes that are further classified into genotypes with varying degrees of pathogenicity. The non-structural protein 1 (NS1) of DENV has an important role in viral replication and its pathogenesis. NS1 is also considered as an important diagnostic marker for Dengue pathogenesis. To the best of our knowledge, there are no attempts to explore small molecule drugs to target the NS1 of all the serotypes. Here, we have taken the DENV 2 NS1 crystal structure as a reference to model the NS1 structure of the other three serotypes. Once the active site of the NS1 is identified, virtual screening of plant flavonoids is carried out against the NS1 of all the four serotypes. The top 200 molecules in the library with high binding affinities are further analysed to find the common ones having comparable affinities to all the four serotypes. The predicted common flavonoids are subjected to ADMET profiling to further select the most potential molecules that can be used to target NS1 of all the four serotypes.