An Insight on the Prospect of Quinazoline and Quinazolinone Derivatives as Anti-tubercular Agents.

Multiple potential drugs have been developed based on the heterocyclic molecules for the treatment of different symptoms. Among the existing heterocyclic molecules, quinazoline and quinazolinone derivatives have been found to exhibit extensive pharmacological and biological characteristics. One significant property of these molecules is their potency as anti-tubercular agents. Thus, both quinazoline and quinazolinone derivatives are modified using different functional groups as substituents for investigating their anti-tubercular activities. We present a summary of the reported anti-tubercular drugs, designed using quinazoline and quinazolinone derivatives, in this review.

Selection of Ideal Reference Genes for Gene Expression Analysis in COVID-19 and Mucormycosis.

Selection of reference genes during real-time quantitative PCR (qRT-PCR) is critical to determine accurate and reliable mRNA expression. Nonetheless, not a single study has investigated the expression stability of candidate reference genes to determine their suitability as internal controls in SARS-CoV-2 infection or COVID-19-associated mucormycosis (CAM). Using qRT-PCR, we determined expression stability of the nine most commonly used housekeeping genes, namely, TATA-box binding protein (TBP), cyclophilin (CypA), ß-2-microglobulin (B2M), 18S rRNA (18S), peroxisome proliferator-activated receptor gamma (PPARG) coactivator 1 alpha (PGC-1α), glucuronidase beta (GUSB), hypoxanthine phosphoribosyltransferase 1 (HPRT-1), ß-ACTIN, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in patients with COVID-19 of various severities (asymptomatic, mild, moderate, and severe) and those with CAM. We used statistical algorithms (delta-CT [threshold cycle], NormFinder, BestKeeper, GeNorm, and RefFinder) to select the most appropriate reference gene and observed that clinical severity profoundly influences expression stability of reference genes. CypA demonstrated the most consistent expression irrespective of disease severity and emerged as the most suitable reference gene in COVID-19 and CAM. Incidentally, GAPDH, the most commonly used reference gene, showed the maximum variations in expression and emerged as the least suitable. Next, we determined expression of nuclear factor erythroid 2-related factor 2 (NRF2), interleukin-6 (IL-6), and IL-15 using CypA and GAPDH as internal controls and show that CypA-normalized expression matches well with the RNA sequencing-based expression of these genes. Further, IL-6 expression correlated well with the plasma levels of IL-6 and C-reactive protein, a marker of inflammation. In conclusion, GAPDH emerged as the least suitable and CypA as the most suitable reference gene in COVID-19 and CAM. The results highlight the expression variability of housekeeping genes due to disease severity and provide a strong rationale for identification of appropriate reference genes in other chronic conditions as well. IMPORTANCE Gene expression studies are critical to develop new diagnostics, therapeutics, and prognostic modalities. However, accurate determination of expression requires data normalization with a reference gene, whose expression does not vary across different disease stages. Misidentification of a reference gene can produce inaccurate results. Unfortunately, despite the global impact of COVID-19 and an urgent unmet need for better treatment, not a single study has investigated the expression stability of housekeeping genes across the disease spectrum to determine their suitability as internal controls. Our study identifies CypA and then TBP as the two most suitable reference genes for COVID-19 and CAM. Further, GAPDH, the most commonly used reference gene in COVID-19 studies, turned out to be the least suitable. This work fills an important gap in the field and promises to facilitate determination of an accurate expression of genes to catalyze development of novel molecular diagnostics and therapeutics for improved patient care.

Artificial Intelligence (AI) in Drugs and Pharmaceuticals.

The advancement of computing and technology has invaded all the dimensions of science. Artificial intelligence (AI) is one core branch of Computer Science, which has percolated to all the arenas of science and technology, from core engineering to medicines. Thus, AI has found its way for application in the field of medicinal chemistry and heath care. The conventional methods of drug design have been replaced by computer-aided designs of drugs in recent times. AI is being used extensively to improve the design techniques and required time of the drugs. Additionally, the target proteins can be conveniently identified using AI, which enhances the success rate of the designed drug. The AI technology is used in each step of the drug designing procedure, which decreases the health hazards related to preclinical trials and also reduces the cost substantially. The AI is an effective tool for data mining based on the huge pharmacological data and machine learning process. Hence, AI has been used in de novo drug design, activity scoring, virtual screening and in silico evaluation in the properties (absorption, distribution, metabolism, excretion and toxicity) of a drug molecule. Various pharmaceutical companies have teamed up with AI companies for faster progress in the field of drug development, along with the healthcare system. The review covers various aspects of AI (Machine learning, Deep learning, Artificial neural networks) in drug design. It also provides a brief overview of the recent progress by the pharmaceutical companies in drug discovery by associating with different AI companies.

Synthesis, characterization and utility of a series of novel copper(II) complexes as excellent surface disinfectants against nosocomial infections.

Nosocomial infections are among the major public health concerns, especially during the ongoing Covid19 pandemic. There is a great demand for novel chemical agents that are capable of killing specific pathogens or augmenting the efficiency of existing disinfectants. Herein, we report the synthesis and comprehensive characterization (through FT-IR, HR-MS, SEM, TGA-DSC, CV, UV and SCXRD analyses) of six novel copper(II) complexes, [CuL(4X-An)] (5a-5d), [CuL(An)] (5e), and [CuL(benzhydrylamine)] (5f), and their evaluation as anti-microbial agents against WHO priority pathogens, confirming their possible use in hospital settings. The compounds were synthesized with a Schiff base (H2L) obtained by the condensation reaction of 3-acetyl-6-methyl-2H-pyran-2,4(3H)-dione (DHA) and benzohydrazide and further addition of different p-substituted aniline (An) molecules. Single crystal structure analyses revealed that the aniline derivatives are isostructural to the copper atom in a square planar coordination, while the benzhydrylamine complex forms a dimer (5f), with a square pyramidal coordination geometry for the metal. Time-kill kinetics and reduced microbial recovery studies revealed excellent bactericidal action against Staphylococcus aureus and Enterococcus faecalis. Particularly, the novel compound 5f significantly reduced microbial recovery compared to ethanol-based sanitisers. In fact, addition of 5f to 70% ethanol remarkably synergized the killing with >6-log reduction in microbial burden. Overall, our novel compounds would increase the disinfection efficacy in hospitals and industries, thereby improving the efficiency and minimizing the risk of infections.

Gamma-glutamyl transpeptidase from two plant growth promoting rhizosphere fluorescent pseudomonads.

Glutathione is the most abundant non-protein thiol compound present in many cells. Because this molecule is involved in many physiological processes, each cell maintains a critical level of glutathione. Gamma-glutamyl transpeptidase (GGT, E.C.2.3.2.2) is the key enzyme involved in the glutathione cycle. In the present study, GGT was isolated from two plant growth promoting rhizosphere isolates, Pseudomonas protegens strain Pf-5 and Pseudomonas fluorescens strain PfT-1. GGT in these strains is located in the periplasm and possessed good hydrolytic activity at pH 8.0. Strains Pf-5 and PfT-1 showed maximum enzyme activity when grown at 30­35 °C. The ggt gene from both the strains was cloned in pGEM-T cloning vector and sequenced. Subsequently, GGT expressed in Escherichia coli BL21(DE3) using the pET-28a(+) expression vector was purified and characterized. The enzymes are active in a wide range of pH and some divalent cations significantly enhanced the hydrolytic activity. These enzymes showed higher thermal stability as compared to those of other mesophilic strains, as they retained ~50 % of activity at 50 °C even after 12 h of incubation. The enzymes could also tolerate up to 3.0 M NaCl.