A novel severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) causing COVID-19 pandemic in humans, recently emerged and has exported in more than 200 countries as a result of rapid spread. In this study, we have made an attempt to investigate the SARS-CoV-2 genome reported from 13 different countries, identification of mutations in major coronavirus proteins of these different SARS-CoV-2 genomes and compared with SARS-CoV. These thirteen complete genome sequences of SARS-CoV-2 showed high identity (>99%) to each other, while they shared 82% identity with SARS-CoV. Here, we performed a very systematic mutational analysis of SARS-CoV-2 genomes from different geographical locations, which enabled us to identify numerous unique features of this viral genome. This includes several important country-specific unique mutations in the major proteins of SARS-CoV-2 namely, replicase polyprotein, spike glycoprotein, envelope protein and nucleocapsid protein. Indian strain showed mutation in spike glycoprotein at R408I and in replicase polyprotein at I671T, P2144S and A2798V,. While the spike protein of Spain & South Korea carried F797C and S221W mutation, respectively. Likewise, several important country specific mutations were analyzed. The effect of mutations of these major proteins were also investigated using various in silico approaches. Main protease (Mpro), the therapeutic target protein of SARS with maximum reported inhibitors, was thoroughly investigated and the effect of mutation on the binding affinity and structural dynamics of Mpro was studied. It was found that the R60C mutation in Mpro affects the protein dynamics, thereby, affecting the binding of inhibitor within its active site. The implications of mutation on structural characteristics were determined. The information provided in this manuscript holds great potential in further scientific research towards the design of potential vaccine candidates/small molecular inhibitor against COVID19.

Autophagy is a process essential for cellular energy consumption, survival, and defense mechanisms. The role of autophagy in several types of human cancers has been explicitly explained; however, the underlying molecular mechanism of autophagy in glioblastoma remains ambiguous. Autophagy is thought to be a “double-edged sword”, and its effect on tumorigenesis varies with cell type. On the other hand, autophagy may play a significant role in the resistance mechanisms against various therapies. Therefore, it is of the utmost importance to gain insight into the molecular mechanisms deriving the autophagy-mediated therapeutic resistance and designing improved treatment strategies for glioblastoma. In this review, we discuss autophagy mechanisms, specifically its pro-survival and growth-suppressing mechanisms in glioblastomas. In addition, we try to shed some light on the autophagy-mediated activation of the cellular mechanisms supporting radioresistance and chemoresistance in glioblastoma. This review also highlights autophagy’s involvement in glioma stem cell behavior, underlining its role as a potential molecular target for therapeutic interventions.

Cyclin-dependent kinase 2 (CDK2) is an essential protein kinase involved in the cell cycle regulation. The abnormal activity of CDK2 is associated with cancer progression and metastasis. Here, we have performed structure-based virtual screening of the PubChem database to identify potent CDK2 inhibitors. First, we retrieved all compounds from the PubChem database having at least 90% structural similarity with the known CDK2 inhibitors. The selected compounds were subjected to structure-based molecular docking studies to investigate their pattern of interaction and estimate their binding affinities with CDK2. Selected compounds were further filtered out based on their physicochemical and ADMET properties. Detailed interaction analysis revealed that selected compounds interact with the functionally important residues of the active site pocket of CDK2. All-atom molecular dynamics simulation was performed to evaluate conformational changes, stability and the interaction mechanism of CDK2 in-complex with the selected compound. We found that binding of 6-N,6-N-dimethyl-9-(2-phenylethyl)purine-2,6-diamine stabilizes the structure of CDK2 and causes minimal conformational change. Finally, we suggest that the compound (PubChem ID 101874157) would be a promising scaffold to be further exploited as a potential inhibitor of CDK2 for therapeutic management of cancer after required validation.

An adequate model for predicting bacteraemia has not yet been developed. This study aimed to evaluate the performance of an artificial neural network (ANN)-based prediction model in comparison with previous statistical models. The performance of multi-layer perceptron (MLP), a representative ANN model, was verified via comparison with a non-neural network model. A total of 1260 bacteraemia episodes were identified in 13,402 patients. In MLP with 128 hidden layer nodes, the area under the receiver operating characteristic curve (AUC) of the prediction performance was 0.729 (95% confidence interval [CI]; 0.712–0.728), while in MLP with 256 hidden layer nodes, it was 0.727 (95% CI; 0.713–0.727). In a conventional Bayesian statistical method, the AUC was 0.7. The aforementioned two MLP models exhibited the highest sensitivity (0.810). The ranking of clinical variables was used to describe the influential power of the prediction. Serum alkaline phosphatase was one of the most influential clinical variables, and one-out search was the best ranking method for measuring the influence of the clinical variables. Furthermore, adding variables beyond the 10 top-ranking ones did not significantly affect the prediction of bacteraemia. The ANN model is not inferior to conventional statistical approaches. Bacteraemia can be predicted using only the top 10 clinical variables determined by a ranking method, and the model can be used in clinical practice by applying real-time monitoring.

The COVID-19 outbreak continues to spread worldwide at a rapid rate. Currently, the absence of any effective antiviral treatment is the major concern for the global population. The reports of the occurrence of various point mutations within the important therapeutic target protein of SARS-CoV-2 has elevated the problem. The SARS-CoV-2 main protease (Mpro) is a major therapeutic target for new antiviral designs. In this study, the efficacy of PF-00835231 was investigated (a Mpro inhibitor under clinical trials) against the Mpro and their reported mutants. Various in silico approaches were used to investigate and compare the efficacy of PF-00835231 and five drugs previously documented to inhibit the Mpro. Our study shows that PF-00835231 is not only effective against the wild type but demonstrates a high affinity against the studied mutants as well.

SARS-CoV-2, previously named 2019 novel coronavirus (2019-nCoV), has been associated with the global pandemic of acute respiratory distress syndrome. First reported in December 2019 in the Wuhan province of China, this new RNA virus has several folds higher transmission among humans than its other family member (SARS-CoV and MERS-CoV). The SARS-CoV-2 spike receptor-binding domain (RBD) is the region mediating the binding of the virus to host cells via Angiotensin-converting enzyme 2 (ACE2), a critical step of viral. Here in this study, we have utilized in silico approach for the virtual screening of antiviral library extracted from the Asinex database against the Receptor binding domain (RBD) of the S1 subunit of the SARS-CoV-2 spike glycoprotein. Further, the molecules were ranked based on their binding affinity against RBD, and the top 15 molecules were selected. The affinity of these selected molecules to interrupt the ACE2-Spike interaction was also studied. It was found that the chosen molecules were demonstrating excellent binding affinity against spike protein, and these molecules were also very effectively interrupting the ACE2-RBD interaction.