Phytocompounds from Phyllanthus acidus (L.) Skeels in the management of Monkeypox Virus infections.

Monkeypox is a communicable disease similar to smallpox, primarily occurring in African countries. However, recently it has spread to countries outside Africa and may arise as the next threat after COVID-pandemic. The causative organism, i.e. Monkeypox Virus (MPV) spreads from one individual to another primarily through inhalation of respiratory droplets or through contact with skin lesions of infected individuals. No known drugs are available specifically for MPV. Due to its similarity with smallpox, treatment of monkeypox is being attempted through the administration of the smallpox vaccine. Therefore, we evaluated the efficacy of the plant Phyllanthus acidus against MPV since it is traditionally used in the treatment of chickenpox and smallpox. Through functional annotation, PASS prediction and Network pharmacology analysis, the effectiveness of these chosen P. acidus-derived phytocompounds against MPV was confirmed. Target prediction of the phytocompounds identified in GC-MS analysis of the plant extract showed them to be associated with 76 human proteins. The compounds also show good binding affinity with selected viral proteins: DNA polymerase (DNApol), Putative Virulence Factor (vPVF) and Cytokine Binding Protein. Prediction of Activity Spectra for Substances (PASS) and functional annotation of the target proteins further support their antiviral nature through interaction with these proteins. The compounds were found to modulate pathways related to symptoms of viral infection and this may help in maintaining homeostasis. Our study demonstrates antiviral activity as well as the therapeutic potential of the plant against MPV infection.Communicated by Ramaswamy H. Sarma.

Neem and Turmeric in the management of Covid Associated Mucormycosis (CAM) derived through network pharmacology.

Mucormycosis or 'Black Fungus' has been known to target immunocompromised individuals even before the emergence of COVID-19. Nevertheless, the present circumstances provide the best opening for Covid Associated Mucormycosis (CAM), as the global pandemic is engulfing a large part of human population making them immunocompromised. This drastic increase in Mucormycosis infections has to be addressed as early as possible. There is a growing tendency of relying upon herbal drugs that have minimal side effects and does not compromise our immune system. Recently, the concept of network pharmacology has grabbed the attention of modern science, especially advanced medical sciences. This is a new discipline that can use computational power to systematically catalogue the molecular interactions between botanical formulations and the human body. In this study, Neem and Turmeric was considered as the target plants and an attempt was made to reveal various aspects through which phytocompounds derived from them may effectively manage CAM menace. We have taken a step-by-step approach for identifying the target proteins and ligands associated with Mucormycosis treatment. Functional network analysis and Molecular docking approaches were applied to validate our findings. Quercetin derived from both Neem and Turmeric was found to be one of the main phytocompounds working against Mucormycosis. Along with that, Caffeic acid, Curcumin, Kaempferol, Tetrahydrocurcumin and Myricetin also play a pivotal role in fighting against Black-Fungus. A thorough analysis of our result suggested a triple-front attack on the fungal pathogens and the approaches are necrosis inhibition, iron chelation and immuno-boosting.Communicated by Ramaswamy H. Sarma.

Biotechnology for propagation and secondary metabolite production in Bacopa monnieri.

Bacopa monnieri (L.) Wettst. or water hyssop commonly known as "Brahmi" is a small, creeping, succulent herb from the Plantaginaceae family. It is popularly employed in Ayurvedic medicine as a nerve tonic to improve memory and cognition. Of late, this plant has been reported extensively for its pharmacologically active phyto-constituents. The main phytochemicals are brahmine, alkaloids, herpestine, and saponins. The saponins include bacoside A, bacoside B, and betulic acid. Investigation into the pharmacological effect of this plant has thrived lately, encouraging its neuroprotective and memory supporting capacity among others. Besides, it possesses many other therapeutic activities like antimicrobial, antioxidant, anti-inflammatory, gastroprotective properties, etc. Because of its multipurpose therapeutic potential, it is overexploited owing to the prioritization of natural remedies over conventional ones, which compels us to conserve them. B. monnieri is confronting the danger of extinction from its natural habitat as it is a major cultivated medico-botanical and seed propagation is restricted due to less seed availability and viability. The ever-increasing demand for the plant can be dealt with mass propagation through plant tissue culture strategy. Micropropagation utilizing axillary meristems as well as de novo organogenesis have been widely investigated in this plant which has also been explored for its conservation and production of different types of secondary metabolites. Diverse in vitro methods such as organogenesis, cell suspension, and callus cultures have been accounted for with the aim of production and/or enhancement of bacosides. Direct shoot-organogenesis was initiated in excised leaf and internodal explants without any exogenous plant growth regulator(s) (PGRs), and the induction rate was improved when exogenous cytokinins and other supplements were used. Moreover, biotechnological toolkits like Agrobacterium-mediated transformation and the use of mutagens have been reported. Besides, the molecular marker-based studies demonstrated the clonal fidelity among the natural and in vitro generated plantlets also elucidating the inherent diversity among the natural populations. Agrobacterium-mediated transformation system was mostly employed to optimize bacoside biosynthesis and heterologous expression of other genes. The present review aims at depicting the recent research outcomes of in vitro studies performed on B. monnieri which include root and shoot organogenesis, callus induction, somatic embryogenesis, production of secondary metabolites by in vitro propagation, acclimatization of the in vitro raised plantlets, genetic transformation, and molecular marker-based studies of clonal fidelity. KEY POINTS: • Critical and up to date records on in vitro propagation of Bacopa monnieri • In vitro propagation and elicitation of secondary metabolites from B. monnieri • Molecular markers and transgenic studies in B. monnieri.

Assessing the genetic diversity of rice originating from Bangladesh, Assam and West Bengal.

BACKGROUND: Genetic diversity among rice cultivars from Bangladesh and North East India was assessed using a custom 384-SNP microarray assay. A total of 511 cultivars were obtained from several sources, choosing landraces likely to be from the aus subpopulation and modern improved cultivars from Bangladesh. Cultivars from the OryzaSNP set and Rice Diversity Panel 1 (RDP1) were also included for reference. RESULTS: The population analysis program STRUCTURE was used to infer putative population groups in the panel, revealing four groups: indica (76 cultivars), japonica (55) and two distinct groups within the aus subpopulation (aus-1 = 99, aus-2 = 151). Principal Component Analysis was used to confirm the four population groups identified by STRUCTURE. The analysis revealed cultivars that belonged to neither aus-1 nor aus-2 but which are clearly aus based on the combined probabilities of their membership of the two aus groups which have been termed aus-admix (96). Information obtained from the panel of 511 cultivars was used to assign rice groups to 74 additional landraces obtained from Assam and West Bengal. While both the aus-1 and aus-2 groups were represented approximately equally in India, aus-2 (which includes cultivar N 22) was more common in Bangladesh, but was not found at all in West Bengal. CONCLUSIONS: Examining the distribution of landrace names within theaus-1 and aus-2 groups suggests that aus-1 is associated with the term "boro", a word used to describe a winter growing season in Bangladesh and Assam. The information described here has been used to select a population of 300 cultivars for Genome Wide Association studies of the aus rice subpopulation.

Mifepristone and misoprostol compared with misoprostol alone for induction of labor in intrauterine fetal death: A randomized trial.

AIM: To assess whether mifepristone and misoprostol are more beneficial than misoprostol alone for the induction of labor in women with intrauterine fetal death. METHODS: A randomized double blind placebo-controlled parallel group superiority trial was conducted. One hundred and ten women who had experienced fetal death at or later than 20 weeks of gestation were randomized by computer-generated random number sequence to receive 200 mg of mifepristone or matched placebo tablets orally. Misoprostol was administered vaginally to women of both groups after 36-48 h. The main outcomes studied were the fetal-placental delivery rate within 24 hours of commencement of the first dose of misoprostol without additional intervention and the induction-delivery interval. RESULTS: Successful delivery occurred significantly more frequently in women who received mifepristone prior to misoprostol than in women who received only misoprostol (92.5% [49/53] compared with 71.2% [37/52] respectively; P = 0.001). The mean induction-delivery interval was also significantly shorter when using mifepristone plus misoprostol than using misoprostol alone (9.8 h, standard deviation, 4.4 compared with 16.3 h standard deviation, 5.7, respectively; P < 0.001). CONCLUSION: Use of a combination of mifepristone and misoprostol significantly improved the rate of successful delivery and shortened the induction-delivery interval in women who had experienced fetal death compared with the use of misoprostol alone.

A grammar inference approach for predicting kinase specific phosphorylation sites.

Kinase mediated phosphorylation site detection is the key mechanism of post translational mechanism that plays an important role in regulating various cellular processes and phenotypes. Many diseases, like cancer are related with the signaling defects which are associated with protein phosphorylation. Characterizing the protein kinases and their substrates enhances our ability to understand the mechanism of protein phosphorylation and extends our knowledge of signaling network; thereby helping us to treat such diseases. Experimental methods for predicting phosphorylation sites are labour intensive and expensive. Also, manifold increase of protein sequences in the databanks over the years necessitates the improvement of high speed and accurate computational methods for predicting phosphorylation sites in protein sequences. Till date, a number of computational methods have been proposed by various researchers in predicting phosphorylation sites, but there remains much scope of improvement. In this communication, we present a simple and novel method based on Grammatical Inference (GI) approach to automate the prediction of kinase specific phosphorylation sites. In this regard, we have used a popular GI algorithm Alergia to infer Deterministic Stochastic Finite State Automata (DSFA) which equally represents the regular grammar corresponding to the phosphorylation sites. Extensive experiments on several datasets generated by us reveal that, our inferred grammar successfully predicts phosphorylation sites in a kinase specific manner. It performs significantly better when compared with the other existing phosphorylation site prediction methods. We have also compared our inferred DSFA with two other GI inference algorithms. The DSFA generated by our method performs superior which indicates that our method is robust and has a potential for predicting the phosphorylation sites in a kinase specific manner.

An ensemble method approach to investigate kinase-specific phosphorylation sites.

Protein phosphorylation is one of the most significant and well-studied post-translational modifications, and it plays an important role in various cellular processes. It has made a considerable impact in understanding the protein functions which are involved in revealing signal transductions and various diseases. The identification of kinase-specific phosphorylation sites has an important role in elucidating the mechanism of phosphorylation; however, experimental techniques for identifying phosphorylation sites are labor intensive and expensive. An exponentially increasing number of protein sequences generated by various laboratories across the globe require computer-aided procedures for reliably and quickly identifying the phosphorylation sites, opening a new horizon for in silico analysis. In this regard, we have introduced a novel ensemble method where we have selected three classifiers (least square support vector machine, multilayer perceptron, and k-Nearest Neighbor) and three different feature encoding parameters (dipeptide composition, physicochemical properties of amino acids, and protein-protein similarity score). Each of these classifiers is trained on each of the three different parameter systems. The final results of the ensemble method are obtained by fusing the results of all the classifiers by a weighted voting algorithm. Extensive experiments reveal that our proposed method can successfully predict phosphorylation sites in a kinase-specific manner and performs significantly better when compared with other existing phosphorylation site prediction methods.

A composite method based on formal grammar and DNA structural features in detecting human polymerase II promoter region.

An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG) can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques.

Evidence for Wolbachia symbiosis in microfilariae of Wuchereria bancrofti from West Bengal, India.

Wolbachia are symbiotic endobacteria that infect the majority of filarial nematodes, including Wuchereria bancrofti, Brugia malayi and Onchocerca volvulus. Recent studies have suggested that Wolbachia are necessary for the reproduction and survival of filarial nematodes and have highlighted the use of antibiotic therapy such as tetracycline/doxycycline as a novel method of treatment for infections caused by these organisms. Before such therapy is conceived and implemented on a large scale, it is necessary to assess the prevalence of the endosymbiont in W. bancrofti from different geographical locations. We present data from molecular and electron microscopic studies to provide evidence for Wolbachia symbiosis in W. bancrofti microfilariae collected from two districts (Bankura and Birbhum) of West Bengal, India.