Identification and characterization of rhizospheric microbial diversity by 16S ribosomal RNA gene sequencing

Computation-Guided Rational Design of Cysteine-Less Protein Variants in Engineered hCGL

The engineered human cystathionine-γ-lyase (hCGL) resulting in enhanced activity toward both cysteine and cystine unveils a potential robust antitumor activity. However, the presence of cysteine residues has the potential to induce oligomerization or incorrect disulfide bonding, which may decrease the bioavailability of biopharmaceuticals. Through a meticulous design process targeting the cysteine residues within engineered hCGL, a set of potential beneficial mutants were obtained by virtual screening employing Rosetta and ABACUS. Experimental measurements have revealed that most of the mutants showed increased activity toward both substrates l-Cys and CSSC. Furthermore, mutants C109V and C229D demonstrated Tm value increases of 8.2 and 1.8 °C, respectively. After an 80 min incubation at 60 °C, mutant C229D still maintained high residual activity. Unexpectedly, mutant C109V, displaying activity approximately 2-fold higher than the activity of wild type (WT) for both substrates, showed disappointing instability in plasma, which suggests that computational design still requires further consideration. Analysis of their structure and molecular dynamics (MD) simulation revealed the impact of hydrophobic interaction, hydrogen bonds, and near-attack conformation (NAC) stability on activity and stability. This study acquired information about mutants that exhibit enhanced activity or thermal resistance and serve as valuable guidance for subsequent specific cysteine modifications.

Investigating the anti-cancer compounds from Calliandra harrisii for precision medicine in pancreatic cancer via in-silico drug design and GC-MS analysis

Pancreatic cancer is a fatal illness caused by mutations in multiple genes. Pancreatic cancer damages the organ that helps in digestion, resulting in symptoms including fatigue, bloating, and nausea. The use of medicinal plants has been crucial in the treatment of numerous disorders. The medicinal plant Calliandra Harrisi has been widely exploited for its possibilities in biology and medicine. The current study aimed to assess the biopotential of biologically active substances against pancreatic cancer. The GC-MS data of these phytochemicals from Calliandra Harrisi were further subjected to computational approaches with pancreatic cancer genes to evaluate their potential as therapeutic candidates. Molecular docking analysis revealed that N-[Carboxymethyl] maleamic acid is the leading molecule responsible for protein denaturation inhibition, having the highest binding affinity of 6.8 kJ/mol among all other compounds with KRAS inflammatory proteins. Furthermore, ADMET analysis and Lipinski's rule validation were also performed revealing its higher absorption in the gastrointestinal tract. The results of the hepatotoxicity test demonstrated that phytochemicals are non-toxic, safe to use, and do not cause necrosis, fibrosis, or vacuolar degeneration even at excessive levels. Calliandra Harrisi has phytoconstituents that have a variety of pharmacological uses in consideration.

Prediction of interactomic hub genes in PBMC cells in type 2 diabetes mellitus, dyslipidemia, and periodontitis

BACKGROUND AND OBJECTIVE

In recent years, the complex interplay between systemic health and oral well-being has emerged as a focal point for researchers and healthcare practitioners. Among the several important connections, the convergence of Type 2 Diabetes Mellitus (T2DM), dyslipidemia, chronic periodontitis, and peripheral blood mononuclear cells (PBMCs) is a remarkable example. These components collectively contribute to a network of interactions that extends beyond their domains, underscoring the intricate nature of human health. In the current study, bioinformatics analysis was utilized to predict the interactomic hub genes involved in type 2 diabetes mellitus (T2DM), dyslipidemia, and periodontitis and their relationships to peripheral blood mononuclear cells (PBMC) by machine learning algorithms.

MATERIALS AND METHODS

Gene Expression Omnibus datasets were utilized to identify the genes linked to type 2 diabetes mellitus(T2DM), dyslipidemia, and Periodontitis (GSE156993).Gene Ontology (G.O.) Enrichr, Genemania, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used for analysis for identification and functionalities of hub genes. The expression of hub D.E.G.s was confirmed, and an orange machine learning tool was used to predict the hub genes.

RESULT

The decision tree, AdaBoost, and Random Forest had an A.U.C. of 0.982, 1.000, and 0.991 in the R.O.C. curve. The AdaBoost model showed an accuracy of (1.000). The findings imply that the AdaBoost model showed a good predictive value and may support the clinical evaluation and assist in accurately detecting periodontitis associated with T2DM and dyslipidemia. Moreover, the genes with p-value < 0.05 and A.U.C.>0.90, which showed excellent predictive value, were thus considered hub genes.

CONCLUSION

The hub genes and the D.E.G.s identified in the present study contribute immensely to the fundamentals of the molecular mechanisms occurring in the PBMC associated with the progression of periodontitis in the presence of T2DM and dyslipidemia. They may be considered potential biomarkers and offer novel therapeutic strategies for chronic inflammatory diseases.

AI-driven covalent drug design strategies targeting main protease (mpro) against SARS-CoV-2: structural insights and molecular mechanisms

The emergence of new SARS-CoV-2 variants has raised concerns about the effectiveness of COVID-19 vaccines. To address this challenge, small-molecule antivirals have been proposed as a crucial therapeutic option. Among potential targets for anti-COVID-19 therapy, the main protease (Mpro) of SARS-CoV-2 is important due to its essential role in the virus's life cycle and high conservation. The substrate-binding region of the core proteases of various coronaviruses, including SARS-CoV-2, SARS-CoV, and Middle East respiratory syndrome coronavirus (MERS-CoV), could be used for the generation of new protease inhibitors. Various drug discovery methods have employed a diverse range of strategies, targeting both monomeric and dimeric forms, including drug repurposing, integrating virtual screening with high-throughput screening (HTS), and structure-based drug design, each demonstrating varying levels of efficiency. Covalent inhibitors, such as Nirmatrelvir and MG-101, showcase robust and high-affinity binding to Mpro, exhibiting stable interactions confirmed by molecular docking studies. Development of effective antiviral drugs is imperative to address potential pandemic situations. This review explores recent advances in the search for Mpro inhibitors and the application of artificial intelligence (AI) in drug design. AI leverages vast datasets and advanced algorithms to streamline the design and identification of promising Mpro inhibitors. AI-driven drug discovery methods, including molecular docking, predictive modeling, and structure-based drug repurposing, are at the forefront of identifying potential candidates for effective antiviral therapy. In a time when COVID-19 potentially threat global health, the quest for potent antiviral solutions targeting Mpro could be critical for inhibiting the virus.Communicated by Ramaswamy H. Sarma.

Whole proteome analysis of MDR Klebsiella pneumoniae to identify mRNA and multiple epitope based vaccine targets against emerging nosocomial and lungs associated infections

Klebsiella pneumonia is a Gram negative facultative anaerobic bacterium involved in various community-acquired pneumonia, nosocomial and lungs associated infections. Frequent usage of several antibiotics and acquired resistance mechanisms has made this bacterium multi-drug resistance (MDR), complicating the treatment of patients. To avoid the spread of this bacterium, there is an urgent need to develop a vaccine based on immuno-informatics approaches that is more efficient than conventional method of vaccine prediction or development. Initially, the complete proteomic sequence of K. pneumonia was picked over for specific and prospective vaccine targets. From the annotation of the whole proteome, eight immunogenic proteins were selected, and these shortlisted proteins were interpreted for CTL, B-cells, and HTL epitopes prediction, to construct mRNA and multi-epitope vaccines. The Antigenicity, allergenicity and toxicity analysis validate the vaccine's design, and its molecular docking was done with immuno-receptor the TLR-3. The docking interaction showed a stronger binding affinity with a minimum energy of -1153.2 kcal/mol and established 23 hydrogen bonds, 3 salt bridges, 1 disulfide bond, and 340 non-binding contacts. Further validation was done using In-silico cloning which shows the highest CAI score of 0.98 with higher GC contents of 72.25% which represents a vaccine construct with a high value of expression in E. coli. Immune Simulation shows that the antibodies (IgM, IgG1, and IgG2) production exceeded 650,000 in 2 to 3 days but the response was completely neutralized in the 5th day. In conclusion, the study provides the effective, safe and stable vaccine construct against Klebsiella pneumonia, which further needs in vitro and in vivo validations.Communicated by Ramaswamy H. Sarma.

Study on the characterization of endosulfan-degrading bacterial strains isolated from contaminated rhizospheric soil

In the present study, we have isolated endosulfan tolerant bacterial strains from the rhizosphere of plants growing in a pesticide-contaminated area. The tolerance capacities of these strains were tested up to 50,000 µg ml^-1 of endosulfan. It was found that out of nineteen, four strains (EAG-EC-12, EAG-EC-13, EAG-EC-14, and EAG-EC-15) were capable of surviving up to 50,000 µg ml^-1 endosulfan concentration in the media; thus, these four strains were selected for the characterization. Among four, two strains were identified as Serratia liquefaciens, while the other two strains were Bacillus sp. and Brevibacterium halotolerans. The result shows that growth of strain Serratia liquefaciens 1 and Serratia liquefaciens 2 in treated medium was statistically similar to that of control (cfu 6.8 × 10⁷) after 24 h, while strains Bacillus sp. and Brevibacterium halotolerans have shown growth significantly less than the control. The degradation potential of these strains was analyzed against 100 to 250 µg ml^-1 of endosulfan in a Minimal Broth Medium (MBM), and it was recorded that only 9, 2, 7, and 19% of endosulfan (100 µg ml^-1) remain after a 72 h incubation period of Bacillus sp., Serratia liquefaciens 1, Serratia liquefaciens 2, and Brevibacterium halotolerans, respectively. This endosulfan removal potential of studied strains was decreased with an increase in concentration of endosulfan.

Significance of Plant Growth Promoting Rhizobacteria in Grain Legumes: Growth Promotion and Crop Production

Grain legumes are an important component of sustainable agri-food systems. They establish symbiotic association with rhizobia and arbuscular mycorrhizal fungi, thus reducing the use of chemical fertilizers. Several other free-living microbial communities (PGPR—plant growth promoting rhizobacteria) residing in the soil-root interface are also known to influence biogeochemical cycles and improve legume productivity. The growth and function of these microorganisms are affected by root exudate molecules secreted in the rhizosphere region. PGPRs produce the chemicals which stimulate growth and functions of leguminous crops at different growth stages. They promote plant growth by nitrogen fixation, solubilization as well as mineralization of phosphorus, and production of phytohormone(s). The co-inoculation of PGPRs along with rhizobia has shown to enhance nodulation and symbiotic interaction. The recent molecular tools are helpful to understand and predict the establishment and function of PGPRs and plant response. In this review, we provide an overview of various growth promoting mechanisms of PGPR inoculations in the production of leguminous crops.