The pharmacological activity of Acacia nilotica's phytochemical constituents was confirmed with evidence-based studies, but the determination of exact targets that they bind and the mechanism of action were not done; consequently, we aim to identify the exact targets that are responsible for the pharmacological activity via the computational methods. Furthermore, we aim to predict the pharmacokinetics (ADME) properties and the safety profile in order to identify the best drug candidates. To achieve those goals, various computational methods were used including the ligand-based virtual screening and molecular docking. Moreover, pkCSM and SwissADME web servers were used for the prediction of pharmacokinetics and safety. The total number of the investigated compounds and targets was 25 and 61, respectively. According to the results, the pharmacological activity was attributed to the interaction with essential targets. Ellagic acid, Kaempferol, and Quercetin were the best A. nilotica's phytochemical constituents that contribute to the therapeutic activities, were non-toxic as well as non-carcinogen. The administration of Ellagic acid, Kaempferol, and Quercetin as combined drug via the novel drug delivery systems will be a valuable therapeutic choice for the treatment of recent diseases attacking the public health including cancer, multidrug-resistant bacterial infections, diabetes mellitus, and chronic inflammatory systemic disease.

The design, synthesis, and development of novel non-steroidal anti-inflammatory drugs (NSAIDs) with better activity and lower side effects are respectable area of research. Novel Diclofenac Schiff's bases (M1, M2, M4, M7, and M8) were designed and synthesized, and their respective chemical structures were deduced using various spectral tools (IR, 1H NMR, 13C NMR, and MS). The compounds were synthesized via Schiff's condensation reaction and their anti-inflammatory activity was investigated applying the Carrageenan-induced paw edema model against Diclofenac as positive control. Percentage inhibition of edema indicated that all compounds were exhibiting a comparable anti-inflammatory activity as Diclofenac. Moreover, the anti-inflammatory activity was supported via virtual screening using molecular docking study. Interestingly compound M2 showed the highest in vivo activity (61.32% inhibition) when compared to standard Diclofenac (51.36% inhibition) as well as the best binding energy score (-10.765) and the virtual screening docking score (-12.142).

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Pseudomonas stutzeri is a valuable bacteria for understanding of the taxonomical and the phylogenetic relationships. The study of genetic relationships between organisms or genes is carried out by molecular phylogeny. We aim to study the relationships according to16S rRNA gene sequences between our samples and the closest strains from other countries over the world. To our knowledge, the phylogenetic studies between strains from Sudan with strains from other countries were not done before. A total of 140 currency notes in different denominations were collected randomly from several locations including hospitals, food sellers and transporters. From the collected notes, a total of 135 bacterial colonies were isolated and from them 14 isolates were identified as a pseudomonas stutzeri. In the study, streaking plate method was used for the isolation of pure bacterial culture, Chelex 100 method was used for DNA extraction, conventional PCR was used for amplification of the targeted gene, agarose gel electrophoresis and various bioinformatics tools were used for nucleotide sequence analysis. The PCR products were sent for Macrogen Company-Netherlands for purification and nucleotide sequencing. After sequencing 3 samples were noisy, hence they were excluded. According to phylogenetic analysis, we found that the samples were closely related to strains from southeast Asia (Indonesia), east Asia (China), south-central Asia (Bangladesh), south Asia (India), north Africa (Tunisia) and south Europe (Italy and Greece). Despite the samples were from the same source (currency notes), we found that there is broad sequence variation between them.

Due to the current COVID-19 pandemic, the rapid discovery of a safe and effective vaccine is an essential issue, consequently, this study aims to predict potential COVID-19 peptide-based vaccine utilizing the Nucleocapsid phosphoprotein (N) and Spike Glycoprotein (S) via the Immunoinformatics approach. To achieve this goal, several Immune Epitope Database (IEDB) tools, molecular docking, and safety prediction servers were used. According to the results, The Spike peptide peptides SQCVNLTTRTQLPPAYTNSFTRGVY is predicted to have the highest binding affinity to the B-Cells. The Spike peptide FTISVTTEI has the highest binding affinity to the MHC I HLA-B1503 allele. The Nucleocapsid peptides KTFPPTEPK and RWYFYYLGTGPEAGL have the highest binding affinity to the MHC I HLA-A0202 allele and the three MHC II alleles HLA-DPA1*01:03/DPB1*02:01, HLA-DQA1*01:02/DQB1-*06:02, HLA-DRB1, respectively. Furthermore, those peptides were predicted as non-toxic and non-allergen. Therefore, the combination of those peptides is predicted to stimulate better immunological responses with respectable safety.

BackgroundHuman Metapneumovirus is a major cause of acute respiratory infections especially in children besides it’s responsible for substantial hospitalizations associated with significant morbidity and treatment cost. Hence vaccination is required. Consequently, we aim to predict effective, safe, and universal epitope-based peptides vaccine against the HMPV using its Fusion Protein via the Immunoinformatics approach since there are no licensed vaccines or antiviral treatments yet.To achieve this goal, various Immunoinformatics databases and web servers, including, the Immune Epitope Database used the Allergen FP v.1.0, and ToxinPred web servers as well as Phyre2 web portal for the modeling of peptide 3D structure and molecular docking study on Cresset Flare software.Result According to the results, the peptide GSTVYYPN was the best predicted B-cells epitopes. Moreover, the peptide VIYMVQLPI with population coverage 48.27% in class(C) I, 35.12% in (C)II, and the peptides LIGVYGSSV with 44.03% in C II, YTNVFTLEV with 61.92% in class I were the best-predicted T-cells epitopes that will interact effectively with the MHC I and MHC II molecules respectively.Conclusions We recommend the use of them, the highest coverage, and the best -combined allele’s bindings of immunogenic multiple peptide vaccines. Also, experimental studies recommend validating the results.

This study aimed to investigate the anticancer activity of Haplophyllum tuberculatum(Forsk.) aerial parts ethanol extract and fractions and reveal the potential anticancer targets, binding modes, pharmacokinetics, and toxicity properties of its phytoconstituents. MTT assay was used to investigate the anticancer activity. TargetNet, ChemProt version 2.0, and CLC-Pred web servers were used for virtual screening, and Cresset Flare software was used for molecular docking with the 26 predicted targets. Moreover, pkCSM, swiss ADME, and eMolTox web servers were used to predict pharmacokinetics and safety. Ethanolic extracts of H. tuberculatum on HepG2 and HeLa cell lines showed promising activities with IC50 values 54.12 and 48.1 µg/mL, respectively. Further, ethyl acetate fraction showed the highest cytotoxicity on HepG2 and HeLa cell lines with IC50 values 41.7 and 52.31 µg/mL. Of 70 compounds screened virtually, polygamain, justicidin A, justicidin B, haplotubine, kusunokinin, and flindersine were predicted as safe anticancer drugs candidates. They showed the highest binding scores with targets involved in cell growth, proliferation, survival, migration, tumor suppression, induction of apoptosis, metastasis, and drug resistance. Our findings revealed the potency of H. tuberculatum as a source of anticancer candidates that further studies should support.