Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a member of the Coronaviridae family, causing major destructions to human life directly and indirectly to the economic crisis around the world. Although there is significant reporting on the whole genome sequences and updated data for the different receptors are widely analyzed and screened to find a proper medication. Only a few bioassay experiments were completed against SARS-CoV-2 spike protein. We collected the compounds dataset from the PubChem Bioassay database having 1786 compounds and split it into the ratio of 80–20% for model training and testing purposes, respectively. Initially, we have created 11 models and validated them using a fivefold validation strategy. The hybrid consensus model shows a predictive accuracy of 95.5% for training and 94% for the test dataset. The model was applied to screen a virtual chemical library of Natural products of 2598 compounds. Our consensus model has successfully identified 75 compounds with an accuracy range of 70–100% as active compounds against SARS-CoV-2 RBD protein. The output of ML data (75 compounds) was taken for the molecular docking and dynamics simulation studies. In the complete analysis, the Epirubicin and Daunorubicin have shown the docking score of −9.937 and −9.812, respectively, and performed well in the molecular dynamics simulation studies. Also, Pirarubicin, an analogue of anthracycline, has widely been used due to its lower cardiotoxicity. It shows the docking score of −9.658, which also performed well during the complete analysis. Hence, after the following comprehensive pipeline-based study, these drugs can be further tested in vivo for further human utilization. Communicated by Ramaswamy H. Sarma

Background: Epidermal growth factor receptor (EGFR/HER-1) and its role in tumor development and progression through the mechanism of tumor angiogenesis is prevalent in non-small lung cancer, head and neck cancer, cholangiocarcinoma & glioblastoma. Previous treatments targeting the oncogenic activity of EGFR's kinase domain have been hindered by acquired mutational resistance and side effects from existing drugs like erlotinib, highlighting the need for new EGFR inhibitors through structure- based drug designing. Objective: The research aims to develop novel quinazoline derivatives through structure-based virtual screening, molecular docking, and molecular dynamics simulation to potentially interact with EGFR's kinase domain and impede tumor angiogenic phenomenon. Methods: Quinazoline derivatives were retrieved and filtered from the PubChem database using structure- based virtual screening and the Lipinski rule of five drug-likeness studies. Molecular docking-based virtual screening methods and molecular dynamics simulation were then carried out to identify top leads. Results: A total of 1000 quinazoline derivatives were retrieved, with 671 compounds possessing druglike properties after applying Lipinski filters. Further filtration using ADME and toxicity filters yielded 28 compounds with good pharmacokinetic profiles. Docking-based virtual screening identified seven compounds with better binding scores than the control drug, dacomitinib. After cross-checking binding scores, three top compounds QU524, QU571, and QU297 were selected for molecular dynamics simulation study of 100 ns interval using Desmond module of Schrodinger maestro to understand their conformational stability. Conclusion: The research results showed that the selected quinazoline leads exhibited better binding affinity and conformational stability than the control drug, erlotinib. These compounds also had good pharmacokinetic and pharmacodynamic profiles and did not violate Lipinski’s rule of five limits. The findings suggest that these leads have the potential to target EGFR's kinase domain and inhibit the EGFR-associated phenomenon of tumor angiogenesis.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is one of the rapid spreading coronaviruses that belongs to the Coronaviridae family. The rapidly evolving nature of SARS-CoV-2 results in a variety of variants with a capability of evasion to existing therapeutics and vaccines. So, there is an imperative need to discover potent drugs that can able to disrupt the function of multiple drug targets to tackle the SARS-CoV-2 menace. Here in this study, we took the different targets of SARS-CoV-2 prepared in the Schrodinger maestro. The library of the DrugBank database is screened against the selected crucial targets. Our molecular docking, Molecular Mechanics/Generalized Born Surface Area (MMGBSA), and molecular dynamics simulation studies led to identifying dinaciclib and theodrenaline as potential drugs against multiple drug targets: main protease, NSP15-endoribonuclease and papain-like-protease, of SARS-CoV-2. Dinaciclib with papain-like protease and NSP15-endoribonuclease show the docking score of −7.015 and −8.737, respectively, while the theodrenaline with NSP15-endoribonuclease and main protease produced the docking score of −8.507 and −7.289, respectively. Furthermore, the binding free energy calculations with MM/GBSA and molecular dynamics simulation studies of the complexes confirm the reliability of the drugs. The selected drugs are capable of binding to multiple targets simultaneously, thus withstanding their activity of target disruption in different variants of SARS-CoV-2. Although, the repurposed drugs are showing potent activity, but may need further in-vitro and in-vivo validations. Communicated by Ramaswamy H. Sarma

Codon usage bias (CUB) is an omnipresent phenomenon, which occurs in nearly all organisms. Previous studies of codon bias in Plasmodium species were based on a limited dataset. This study uses whole genome datasets for comparative genome analysis of six Plasmodium species using CUB and other related methods for the first time. Codon usage bias, compositional variation in translated amino acid frequency, effective number of codons and optimal codons are analyzed for P.falciparum, P.vivax, P.knowlesi, P.berghei, P.chabaudii and P.yoelli. A plot of effective number of codons versus GC3 shows their differential codon usage pattern arises due to a combination of mutational and translational selection pressure. The increased relative usage of adenine and thymine ending optimal codons in highly expressed genes of P.falciparum is the result of higher composition biased pressure, and usage of guanine and cytosine bases at third codon position can be explained by translational selection pressure acting on them. While higher usage of adenine and thymine bases at third codon position in optimal codons of P.vivax highlights the role of translational selection pressure apart from composition biased mutation pressure in shaping their codon usage pattern. The frequency of those amino acids that are encoded by AT ending codons are significantly high in P.falciparum due to action of high composition biased mutational pressure compared with other Plasmodium species. The CUB variation in the three rodent parasites, P.berghei, P.chabaudii and P.yoelli is strikingly similar to that of P.falciparum. The simian and human malarial parasite, P.knowlesi shows a variation in codon usage bias similar to P.vivax but on closer study there are differences confirmed by the method of Principal Component Analysis (PCA). CDS - Coding sequences, GC1 - GC composition at first site of codon, GC2 - GC composition at second site of codon, GC3 - GC composition at third site of codon, Ala - Alanine, Arg - Arginine, Asn - Asparagine, Asp - Aspartic acid, Cys - Cysteine, Gln - Glutamine Glu - Glutamic acid Gly - Glycine His - Histidine Ile - Isoleucine Leu - Leucine Lys - Lysine Met - Methionine Phe - Phenylalanine Pro - Proline Ser - Serine Thr - Threonine Trp - Tryptophan Tyr - Tyrosine Val - Valine.

The incidence of diabetes, obesity, and metabolic diseases has reached an epidemic status worldwide. Insulin resistance is a common link in the development of these conditions, and hyperinsulinemia is a central hallmark of peripheral insulin resistance. However, how hyperinsulinemia leads to systemic insulin resistance is less clear. We now provide evidence that hyperinsulinemia promotes the release of soluble pro-inflammatory mediators from macrophages that lead to systemic insulin resistance. Our observations suggest that hyperinsulinemia induces Sirtuin1 (SIRT1) repression and stimulates NF-κB p65 nuclear translocation and transactivation of NF-κB to promote the extracellular release of pro-inflammatory mediators. We further showed that low-dose naltrexone (LDN) abrogates hyperinsulinemia-mediated SIRT1 repression and prevents NF-κB p65 nuclear translocation. This, in turn, attenuates the hyperinsulinemia-induced release of pro-inflammatory cytokines and reinstates insulin sensitivity both in in vitro and in-vivo diet-induced hyperinsulinemic mouse model. Notably, our data indicate that Sirt1 knockdown or inhibition blunts the anti-inflammatory properties of LDN in vitro. Using numerous complementary in silico and in vitro experimental approaches, we demonstrated that LDN can bind to SIRT1 and increase its deacetylase activity. Together, these data support a critical role of SIRT1 in inflammation and insulin resistance in hyperinsulinemia. LDN improves hyperinsulinemia-induced insulin resistance by reorienting macrophages towards anti-inflammation. Thus, LDN treatment may provide a novel therapeutic approach against hyperinsulinemia-associated insulin resistance.