<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tellis, Meenakshi</style></author><author><style face="normal" font="default" size="100%">Mathur, Monika</style></author><author><style face="normal" font="default" size="100%">Gurjar, Gayatri</style></author><author><style face="normal" font="default" size="100%">Kadoo, Narendra</style></author><author><style face="normal" font="default" size="100%">Gupta, Vidya</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification and functionality prediction of pathogenesis-related protein 1 from legume family</style></title><secondary-title><style face="normal" font="default" size="100%">Proteins-Structure Function and Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">NOV</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">85</style></volume><pages><style face="normal" font="default" size="100%">2066-2080</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The production and accumulation of pathogenesis-related (PR) proteins in plants is one of the important responses to biotic and abiotic stress. Large number of identified PR proteins has been categorized into 17 functional families based on their structure, phylogenetics, and biological activities. However, they are not widely studied in legume crops. Using 29 PR1 proteins from Arabidopsis thaliana, as query, here we have predicted 92 candidate PR1 proteins through the PSI-BLAST and HMMER programs. These candidate proteins were comprehensively analyzed with, multiple sequence alignment, domain architecture studies, signal peptide, and motif extraction followed by phylogenetic analysis. Further, response of two candidate PR1 proteins from chickpea against Fusarium oxysporum f.sp.ciceri attack was validated using qRT-PCR followed by their 3D structure prediction. To decipher mode of action for PR1s, docking of pathogen extracellular matrix components along with fungal elicitors was performed with two chickpea PR1 proteins. Based on these findings, we propose carbohydrate to be the unique pathogen-recognition feature for PR1 proteins and beta-glucanase activity via beta-glucan binding or modification.</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">2.289</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jagdale, Shounak</style></author><author><style face="normal" font="default" size="100%">Tellis, Meenakshi</style></author><author><style face="normal" font="default" size="100%">Barvkar, Vitthal T.</style></author><author><style face="normal" font="default" size="100%">Joshi, Rakesh S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Glucosinolate induces transcriptomic and metabolic reprogramming in Helicoverpa armigera</style></title><secondary-title><style face="normal" font="default" size="100%">3 Biotech</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Detoxification</style></keyword><keyword><style  face="normal" font="default" size="100%">Glucosinolate</style></keyword><keyword><style  face="normal" font="default" size="100%">Glutathione</style></keyword><keyword><style  face="normal" font="default" size="100%">mitochondria</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxidative stress</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">26</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Glucosinolates protect plants from herbivory. Lepidopteran insects have developed resistance to glucosinolates which is well studied. However, the molecular effects of glucosinolate intake on insects are unexplored. To elucidate this, we performed transcriptomics and metabolomics of sinigrin-fed Helicoverpa armigera. Transcriptomics exhibits significant dysregulation of 2375 transcripts, of which 1575 are upregulated and 800 downregulated. Gene Ontology analysis of differentially expressed genes reveals that key hydrolases, oxidoreductases, and transferases are majorly affected. The negative impact of sinigrin is significant and localized in the endomembrane system and mitochondria. It also disturbs various biological processes such as regulation of protein metabolism and cytoskeletal organization. Furthermore, H. armigera putative myrosinase-like enzymes may catalyze the breakdown of sinigrin to allyl isothiocyanate (AITC). AITC targets the electron transport chain causing oxidative stress. KEGG pathway enrichment shows significant upregulation of oxidative phosphorylation, glutathione metabolism and amino acid metabolism. Activation of these pathways induces glutathione synthesis for sinigrin detoxification. Differential gene expression indicates upregulation of glutathione S-transferase and succinate dehydrogenase suggesting mitochondrial impact. Transcriptomics data correlated with metabolomics show changes in serine, methionine, ornithine, and other metabolite levels. It corroborates well with the transcript alterations supporting the increased glutathione production. Thus, our data suggest that sinigrin generates oxidative stress in H. armigera and insects alter their metabolic wiring to overcome sinigrin-mediated deleterious effects.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">2.406
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bansode, Sneha</style></author><author><style face="normal" font="default" size="100%">Singh, Pawan Kumar</style></author><author><style face="normal" font="default" size="100%">Tellis, Meenakshi</style></author><author><style face="normal" font="default" size="100%">Chugh, Anita</style></author><author><style face="normal" font="default" size="100%">Deshmukh, Narendra</style></author><author><style face="normal" font="default" size="100%">Gupta, Mahesh</style></author><author><style face="normal" font="default" size="100%">Verma, Savita</style></author><author><style face="normal" font="default" size="100%">Giri, Ashok</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Mahesh</style></author><author><style face="normal" font="default" size="100%">Joshi, Rakesh</style></author><author><style face="normal" font="default" size="100%">Chaudhary, Dhruva</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comprehensive molecular and clinical investigation of approved Anti-HCV drugs repurposing against SARS-CoV-2 infection: a glaring gap between benchside and bedside medicine</style></title><secondary-title><style face="normal" font="default" size="100%">Vaccines</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">antiviral</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">daclatasvir</style></keyword><keyword><style  face="normal" font="default" size="100%">ledipasvir</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">sofosbuvir</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAR</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">515</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	The limited availability of effective treatment against SARS-CoV-2 infection is a major challenge in managing COVID-19. This scenario has augmented the need for repurposing anti-virals for COVID-19 mitigation. In this report, the anti-SARS-CoV-2 potential of anti-HCV drugs such as daclatasvir (DCV) or ledipasvir (LDP) in combination with sofosbuvir (SOF) was evaluated. The binding mode and higher affinity of these molecules with RNA-dependent-RNA-polymerase of SARS-CoV-2 were apparent by computational analysis. In vitro anti-SARS-CoV-2 activity depicted that SOF/DCV and SOF/LDP combination has IC50 of 1.8 and 2.0 mu M, respectively, comparable to remdesivir, an approved drug for COVID-19. Furthermore, the clinical trial was conducted in 183 mild COVID-19 patients for 14 days to check the efficacy and safety of SOF/DCV and SOF/LDP compared to standard of care (SOC) in a parallel-group, hybrid, individually randomized, controlled clinical study. The primary outcomes of the study suggested no significant difference in negativity after 3, 7 and 14 days in both treatments. None of the patients displayed any worsening in the disease severity, and no mortality was observed in the study. Although, the post hoc exploratory analysis indicated significant normalization of the pulse rate showed in SOF/DCV and SOF/LDP treatment vs. SOC. The current study highlights the limitations of bench side models in predicting the clinical efficacy of drugs that are planned for repurposing.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	4.961&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tellis, Meenakshi</style></author><author><style face="normal" font="default" size="100%">Mohite, Sharada</style></author><author><style face="normal" font="default" size="100%">Joshi, Rakesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Trehalase inhibition in Helicoverpa armigera activates machinery for alternate energy acquisition</style></title><secondary-title><style face="normal" font="default" size="100%">JOURNAL OF BIOSCIENCES</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Energy metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">glucose</style></keyword><keyword><style  face="normal" font="default" size="100%">Metabolomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptomics</style></keyword><keyword><style  face="normal" font="default" size="100%">trehalase</style></keyword><keyword><style  face="normal" font="default" size="100%">validamycin A</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUL </style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">74</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">3</style></issue><work-type><style face="normal" font="default" size="100%">Journal Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Indian&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;2.9&lt;/p&gt;
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