Network pharmacology and experimental insights into STAT3 inhibition by novel isoxazole derivatives of piperic acid in triple negative breast cancer.

STAT3 is a crucial member within a family of seven essential transcription factors. Elevated STAT3 levels have been identified in various cancer types, notably in breast cancer (BC). Consequently, inhibiting STAT3 is recognized as a promising and effective strategy for therapeutic intervention against breast cancer. We herein synthesize a library of isoxazole (PAIs) from piperic acid [2E, 4E)-5-(2H-1,3-Benzodioxol-5-yl) penta-2,4-dienoic acid] on treatment with propargyl bromide followed by oxime under prescribed reaction conditions. Piperic acid was obtained by hydrolysis of piperine extracted from Piper nigrum. First, we checked the binding potential of isoxazole derivatives with breast cancer target proteins by network pharmacology, molecular docking, molecular dynamic (MD) simulation and cytotoxicity analysis as potential anti-breast cancer (BC) agents. The multi-source databases were used to identify possible targets for isoxazole derivatives. A network of protein-protein interactions (PPIs) was generated by obtaining 877 target genes that overlapped gene symbols associated with isoxazole derivatives and BC. Molecular docking and MD modelling demonstrated a strong affinity between isoxazole derivatives and essential target genes. Further, the cell viability studies of isoxazole derivatives on the human breast carcinoma cell lines showed toxicity in all breast cancer cell lines. In summary, our study indicated that the isoxazole derivative showed the significant anticancer activity. The results highlight the prospective utility of isoxazole derivatives as new drug candidates for anticancer chemotherapy, suggesting route for the continued exploration and development of drugs suitable for clinical applications.

A validated restriction enzyme ddPCR cg05575921 (AHRR) assay to accurately assess smoking exposure.

BACKGROUND & METHODS: In this study, a novel restriction enzyme (RE) digestion-based droplet digital polymerase chain reaction (ddPCR) assay was designed for cg005575921 within the AHRR gene body and compared with matching results obtained by bisulfite conversion (BIS) ddPCR and Illumina DNA methylation array. RESULTS: The RE ddPCR cg05575921 assay appeared concordant with BIS ddPCR (r2 = 0.94, P < 0.0001) and, when compared with the Illumina array, had significantly better smoking status classification performance for current versus never smoked (AUC 0.96 versus 0.93, P < 0.04) and current versus ex-smoker (AUC 0.88 versus 0.83, P < 0.04) comparisons. CONCLUSIONS: The RE ddPCR cg05575921 assay accurately predicts smoking status and could be a useful component of 'precision-medicine' chronic disease risk screening tools.

Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity.

The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. The widespread threat of metal(loid) toxicity can jeopardize global food security due to contaminated food supplies and pose environmental risks, contributing to soil and water pollution and thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms to combat metal(loid) stress. Amid the array of innovative approaches, omics, notably transcriptomics, proteomics, and metabolomics, have emerged as transformative tools, shedding light on the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, and analytical pipelines support these omics approaches by harnessing diverse information and facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores: (1) the multifaceted strategies that plants use to adapt to metal(loid) toxicity in their environment; (2) the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species; (3) the integration of omics data with artificial intelligence and high-throughput phenotyping; (4) the latest bioinformatics databases, tools and pipelines for single and/or multi-omics data integration; (5) the latest insights into stress adaptations and tolerance mechanisms for future outlooks; and (6) the capacity of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.

Synthesis, biological profile and computational insights of new derivatives of benzo [B][1,4] diazepines as prospective anticancer agents for inhibiting the CDK-2 protein.

In the current work, a new series of benzo[b][1, 4] diazepines (A-1 to C-4) was synthesized and screened against three different human cancer cell lines, HepG2 (hepatocellular carcinoma), HeLa (cervical cancer) and MCF-7 (breast cancer), by employing MTT (MTT 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) assay. The outcomes of in vitro screening revealed that all the compounds exhibited momentous anticancer activity, most notably against the MCF-7 cell line by B1-4 compounds. Further, network pharmacology, UALCAN analysis, molecular docking, molecular dynamics (MD) simulations and density functional theory calculations were conducted to explore expression analysis, pharmacokinetics, toxicity profiles and binding interactions of the B1-4 compounds. By UALCAN, we explored the expression analysis of CDK-2 in 19 cancers. Through UALCAN, Pan-cancer analysis revealed that the expression of CDK-2 in 19 cancers was statistically significant. Among the 19 cancers, the CDK-2 expression was significantly upregulated in breast cancer (BRCA), cervical cancer (CESC) and lung carcinoma (LUSC) than normal tissues. Enzyme-docking examination revealed that B1-4 compounds exhibited significant binding affinity against the CDK-2 (PDB ID: 5IEV) drug target protein. Furthermore, MD simulations supported the docking results, which confirmed that the ligand + protein complex was in a stable conformation throughout the simulation time of 100 nanoseconds. Therefore, the present study demonstrates the potential of these benzo [b][1,4] diazepines as promising drug candidates against cancer.Communicated by Ramaswamy H. Sarma.

A new series of benzodiazepine molecules were designed and synthesized as CDK-2 inhibitors.In vitro anticancer potential against HepG2, HeLa and MCF-7 cancer cells were assessed.Network pharmacology; expression analysis; in silico docking; molecular dynamics simulation; molecular mechanics­generalized Born and surface area; and absorption, distribution, metabolism, excretion and toxicity studies were carried out.This study overall revealed the anticancer activity of benzodiazepines by integrating network pharmacology, molecular modeling and in vitro experiments.

Exploration of comprehensive marine natural products database against dengue viral non-structural protein 1 using high-throughput computational studies.

Dengue virus (DENV) non-structural protein 1 (NS1) is a versatile quasi-protein essential for the multiplication of the virus. This study applied high-throughput virtual screening (HTVS) and molecular dynamics (MD) simulation to detect the potential marine natural compounds against the NS1 of DENV. The structure of the NS1 protein was retrieved from Protein Data Bank with (PDB ID: 4O6B). Missing residues were added using modeler software. Molecular operating environment (MOE) programme was used to prepare the protein before docking. Virtual screening was performed on PyRx software to identify natural compounds retrieved from Comprehensive Marine Natural Products Database (CMNPD) against the NS1 protein, and best-docked compounds were examined by molecular docking and molecular dynamic (MD) simulation. Out of 31,561 marine compounds, the top 10 compounds showed docking scores lesser than -8.0 kcal/mol. One of the best hit compounds, CMNPD6802, was further analyzed using MD simulation study at 100 nanoseconds and Molecular Mechanics with Generalized Born and Surface Area Solvation (MM/GBSA). Based on its total binding energy, determined using the MM/GBSA approach, CMNPD6802 was ranked first. Its pharmacokinetic properties concerning the target protein NS1 were also evaluated. The results of the MD simulation showed that CMNPD6802 remained in close contact with the protein throughout the activation period, mapped using principal component analysis. These findings suggest that CMNPD6802 could serve as an NS1 inhibitor and may be a potential candidate for treating DENV infections.Communicated by Ramaswamy H. Sarma.

Deciphering the chemical constituents and antimicrobial activity of Prangos pabularia Lindl. using LC-MS/MS in combination with experimental evaluation and computational studies.

This study meticulously explores the antimicrobial potential of Prangos pabularia Lindl.'s aerial parts through a comprehensive blend of in vitro and in silico analysis. Extracts with varying polarities underwent LC-MS/MS identification of active components, followed by in vitro and in silico assessments of antimicrobial efficacy against Escherichia coli, Bacillus cereus, Candida albicans, Candida glabrata, and Candida paropsilosis. The methanolic extract exhibited significant antimicrobial activity with a MIC value of 48 µg/mL against all tested strains. Molecular docking revealed the compound 9-(3-methylbut-2-enoxy)-furo-(3,2-g)-chromen-7-one's highest binding affinity against the penicillin-binding protein (PBP) bacterial drug target molecule. Other compounds also displayed substantial interactions with key antimicrobial drug target proteins. Further, Molecular dynamics simulations affirmed the stability of protein and ligand conformations. Collectively, these results underscore Prangos pabularia Lindl.'s aerial parts as a promising botanical resource in combating diverse microbial infections. This comprehensive approach not only validates it's in vitro antimicrobial properties but also provides molecular insights into interaction mechanisms, advancing our comprehension of the plant's therapeutic potential.

Mapping phenotypic performance and novel SNPs for cold tolerance in tomato (Solanum lycopersicum) genotypes through GWAS and population genetics.

The cold stress susceptibility of tomato (Solanum lycopersicum) curtails its cultivation, with significant impact in temperate regions and on cropping seasons. To unravel genomic regions responsible for cold stress resilience, a diverse set of fifty genotypes encompassing cultivated, wild species, and landraces were genotyped using genotyping-by-sequencing. Over two years and six trials employing both early and late sowing, these lines were evaluated. Illumina-based next-generation sequencing produced up to 3 million reads per sample from individually sequenced library pools. The Tassel pipeline yielded 10,802 variants, subsequently filtered to 3,854 SNPs for genome-wide association analysis (GWAS). Employing clustering methods (population structure) via TASSEL, SNPhylo, and Kinship matrix, the fifty genotypes clustered into four distinct gene pools. The GWAS for cold tolerance in tomato integrated key traits including yield. Using six independent phenotypic datasets representing various environments, the study identified 4,517 significant marker-trait associations for cold tolerance traits. Notably, pivotal variations (> 10%) in cold stress tolerance, particularly proline content, were linked to marker-trait associations. Additionally, 5,727 significant marker-trait associations for yield and yield-related traits were unveiled, shedding light on fruit yield and directly associated attributes. The investigation pinpointed 685 candidate genes across all examined traits, including 60 genes associated with biological processes within these genomic regions. Remarkably, 7 out of the 60 genes were directly linked to abiotic stress tolerance, functioning as stress-responsive genes either directly or indirectly. The identified genes, particularly those associated with stress response, could hold the key to enhancing cold tolerance and overall crop productivity in tomato cultivation.

Genome-wide SNP discovery and genotyping delineates potential QTLs underlying major yield-attributing traits in buckwheat.

Buckwheat (Fagopyrum spp.) is an important nutritional and nutraceutical-rich pseudo-cereal crop. Despite its obvious potential as a functional food, buckwheat has not been fully harnessed due to its low yield, self-incompatibility, increased seed cracking, limited seed set, lodging, and frost susceptibility. The inadequate availability of genomics resources in buckwheat is one of the major reasons for this. In the present study, genome-wide association mapping (GWAS) was conducted to identify loci associated with various morphological and yield-related traits in buckwheat. High throughput genotyping by sequencing led to the identification of 34,978 single nucleotide polymorphisms that were distributed across eight chromosomes. Population structure analysis grouped the genotypes into three sub-populations. The genotypes were also characterized for various qualitative and quantitative traits at two diverse locations, the analysis of which revealed a significant difference in the mean values. The association analysis revealed a total of 71 significant marker-trait associations across eight chromosomes. The candidate genes were identified near 100 Kb of quantitative trait loci (QTLs), providing insights into several metabolic and biosynthetic pathways. The integration of phenology and GWAS in the present study is useful to uncover the consistent genomic regions, related markers associated with various yield-related traits, and potential candidate genes having implications for being utilized in molecular breeding for the improvement of economically important traits in buckwheat. Moreover, the identified QTLs will assist in tracking the desirable alleles of target genes within the buckwheat breeding populations/germplasm.

Anti-lung Cancer Activity of Synthesized Substituted 1,4-Benzothiazines: An Insight from Molecular Docking and Experimental Studies.

BACKGROUND: Thiazine, a 6-membered distinctive heterocyclic motif with sulfur and nitrogen atoms, is one of the heterocyclic compounds that functions as a core scaffold in a number of medicinally significant molecules. Small thiazine-based compounds may operate simultaneously on numerous therapeutic targets and by employing a variety of methods to halt the development, proliferation, and vasculature of cancer cells. We have, herein, reported a series of substituted 1,4 benzothiazines as potential anticancer agents for the treatment of lung cancer. METHODS: In order to synthesize 2,3-disubstituted-1,4 benzothiazines in good yield, a facile green approach for the oxidative cycloaddition of 2-amino benzenethiol and 1,3-dicarbonyls employing a catalytic amount of ceric ammonium nitrate has been devised. All the molecules have been characterized by spectral analysis and tested for anticancer activity against the A-549 lung cancer cell line using various functional assays. Further in silico screening of compound 3c against six crucial inflammatory molecular targets, such as Il1-α (PDB ID: 5UC6), Il1- ß (PDB ID: 6Y8I), Il6 (PDB ID: 1P9M), vimentin (PDB ID: 3TRT), COX-2 (PDB ID: 5KIR), Il8 (PDB ID: 5D14), and TNF-α (PDB ID: 2AZ5), was done using AutoDock tool. RESULTS: Among the synthesized compounds, propyl 3-methyl-3,4-dihydro-2H-benzo[b][1,4]thiazine-2- carboxylate (3c) was found to be most active based on cell viability assays using A-549 lung cancer cell line and was found to effectively downregulate various pro-inflammatory genes, like Il1-α, Il1-ß, Il6, vimentin, COX-2, Il8, and TNF-α in vitro. The ability of the molecule to effectively suppress the proliferation and migration of lung cancer cells in vitro has been further demonstrated by the colony formation unit assay and wound healing assay. Molecular docking analysis showed the maximal binding affinity (- 7.54 kcal/mol) to be exhibited by compound 3c against IL8. CONCLUSION: A green unconventional route for the synthesis of 2,3-disubstituted-1,4 benzothiazines has been developed. All the molecules were screened for their activity against lung cancer and the data suggested that the presence of an additional unbranched alkyl group attached to the thiazine ring increased their activity. Also, in vitro and in silico modeling confirmed the anti-cancer efficiency of compound 3c, encouraging the exploration of such small molecules against cancer.

Comparative transcriptome analysis of E. coli & Staphylococcus aureus infected goat mammary epithelial cells reveals genes associated with infection.

Mastitis, an inflammatory disease of the mammary gland, imposes a significant financial burden on the dairy sector. However, the specific molecular mechanisms underlying their interactions with goat mammary epithelial cells (GMECs) remain poorly understood. This study aimed to investigate the transcriptomic response of GMECs during infection with E. coli and S. aureus, providing insights into the host-pathogen interactions. Differential expression of gene (DEGs) analysis was done to find genes and pathways dysregulated in the wake of infection. E. coli infection triggered a robust upregulation of immune response genes, including pro-inflammatory chemokines and cytokines as well as genes involved in tissue repair and remodeling. Conversely, S. aureus infection showed a more complex pattern, involving the activation of immune-related gene as well as those involved in autophagy, apoptosis and tissue remodeling. Furthermore, several key pathways, such as Toll-like receptor signaling and cytokine-cytokine receptor interaction, were differentially modulated in response to each pathogen. Understanding the specific responses of GMECs to these pathogens will provide a foundation for understanding the complex dynamics of infection and host response, offering potential avenues for the development of novel strategies to prevent and treat bacterial infections in both animals and humans.

Network pharmacology and experimental validation for deciphering the action mechanism of Fritillaria cirrhosa D. Don constituents in suppressing breast carcinoma.

Fritillaria cirrhosa D. Don is a well-known medicinal plant of Kashmir Himalaya. Traditionally, it has been used to treat several diseases, including cancer. However, the molecular mechanism behind anticancer activity remains unclear. Therefore, in the present study, we have performed high performance-liquid chromatography-mass spectrometry (HR-LC/MS), network pharmacology, molecular docking and molecular dynamic (MD) simulation methods were used to explore the underlying molecular mechanism of F. cirrhosa for the treatment of breast cancer (BC). The targets of F. cirrhosa for treating BC were predicted using databases like SwissTargetPrediction, Gene Cards and OMIM. Protein-protein interaction analysis and network construction were performed using the Search Tool for the Retrieval of Interacting Genes/Proteins programme, and analysis of Gene Ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes pathway enrichment was done using the Cytoscape programme. In addition, molecular docking was used to investigate intermolecular interactions between the compounds and the proteins using the Autodock tool. MD simulations studies were also used to explore the stability of the representative AKT1 gene peiminine and Imperialine-3-ß-glucoside. In addition, experimental treatment of F. cirrhosa was also verified. HR-LC/MS detected the presence of several secondary metabolites. Afterward, molecular docking was used to verify the effective activity of the active ingredients against the prospective targets. Additionally, Peiminine and Imperialine-3-ß-glucoside showed the highest binding energy score against AKT-1 (-12.99 kcal/mol and -12.08 kcal/mol). AKT1 with Peiminine and Imperialine-3-ß-glucoside was further explored for MD simulations. During the MD simulation study at 100 nanoseconds, a stable complex formation of AKT1 + Peiminine and Imperialine-3-ß-glucoside was observed. The binding free energy calculations using MM/GBSA showed significant binding of the ligand with protein (ΔG: -79.83 ± 3.0 kcal/mol) between AKT1 + Peiminine was observed. The principal component analysis exhibited a stable converged structure by achieving global motion. Lastly, F. cirrhosa extracts also exhibited momentous anticancer activity through in vitro studies. Therefore, present study revealed the molecular mechanism of F. cirrhosa constituents for the effective treatment of BC by deactivating various multiple gene targets, multiple pathways particularly the PI3K-Akt signaling pathway. These findings emphasized the momentous anti-BC activity of F. cirrhosa constituents.Communicated by Ramaswamy H. Sarma.

Fritillaria cirrhosa D. Don is well-known, the medicinal plant in the Kashmir Himalaya. Traditionally, it has been used to treat various diseases, including cancer.Many secondary metabolites were identified in F. cirrhosa using high performance-liquid chromatography-mass spectrometry technique, and these bioactive components and potential breast cancer (BC) therapy targets were validated using network pharmacology, molecular docking and MD simulation studies.The bioactive components such as Peimine, Imperialine 3-glucoside and other vital phytocompounds of F. cirrhosa have been demonstrated to interact with AKT1 efficiently, indicating their relevance in inhibiting AKT1 and other protein targets in BC.This study overall showed the anticancer activity of F. cirrhosa extracts by integrating network pharmacology, docking analysis and in vitro experiments.

Gaps in current methods to detect polymorphic CpGs from Illumina Infinium human methylation microarrays and exploring their potential impact in multi-EWAS analyses.

DNA methylation (DNAm) epigenome-wide association studies (EWAS) have been performed on diverse ethnicities to discover novel biomarkers associated with various diseases, such as cancers, autoimmune diseases, and neurological disorders. However, genetic polymorphisms can influence DNAm levels resulting in methylation quantitative trait loci (meQTL). These can be either direct effects, by altering the sequence of the methylation (CpG) site itself, or, in the case of array-based measures, indirectly altering the detection probe-binding site interaction. Given that genetic variant frequencies associated with meQTL can differ between population groups, these have the potential to confound EWAS observations, particularly in multi-ethnic populations. In this study, we analysed publicly available DNA methylation profiles (450K array), consisting of 1342 individuals from 6 distinct ancestral groups. We investigate two distinct tools (GapHunter and MethylToSNP) specifically designed to identify CpG sites that may be influenced by genetic variation. Results from this aggregated trans-ancestral epigenome-wide dataset suggest that both tools fail to consistently identify not only rarer (MAF < 0.05) genetic variant effects but also more than half of sites predicted to be associated with variants with much higher allele frequencies (MAF >0.2). In addition, there is a relatively low concordance in the detection of polymorphic CpGs between GapHunter and MethylToSNP. Screening of CpG site associations from EWAS using either of these tools is unlikely to be a robust or comprehensive means of identifying all genetic variant confounding effects.

Integrons in the development of antimicrobial resistance: critical review and perspectives.

Antibiotic resistance development and pathogen cross-dissemination are both considered essential risks to human health on a worldwide scale. Antimicrobial resistance genes (AMRs) are acquired, expressed, disseminated, and traded mainly through integrons, the key players capable of transferring genes from bacterial chromosomes to plasmids and their integration by integrase to the target pathogenic host. Moreover, integrons play a central role in disseminating and assembling genes connected with antibiotic resistance in pathogenic and commensal bacterial species. They exhibit a large and concealed diversity in the natural environment, raising concerns about their potential for comprehensive application in bacterial adaptation. They should be viewed as a dangerous pool of resistance determinants from the "One Health approach." Among the three documented classes of integrons reported viz., class-1, 2, and 3, class 1 has been found frequently associated with AMRs in humans and is a critical genetic element to serve as a target for therapeutics to AMRs through gene silencing or combinatorial therapies. The direct method of screening gene cassettes linked to pathogenesis and resistance harbored by integrons is a novel way to assess human health. In the last decade, they have witnessed surveying the integron-associated gene cassettes associated with increased drug tolerance and rising pathogenicity of human pathogenic microbes. Consequently, we aimed to unravel the structure and functions of integrons and their integration mechanism by understanding horizontal gene transfer from one trophic group to another. Many updates for the gene cassettes harbored by integrons related to resistance and pathogenicity are extensively explored. Additionally, an updated account of the assessment of AMRs and prevailing antibiotic resistance by integrons in humans is grossly detailed-lastly, the estimation of AMR dissemination by employing integrons as potential biomarkers are also highlighted. The current review on integrons will pave the way to clinical understanding for devising a roadmap solution to AMR and pathogenicity. Graphical AbstractThe graphical abstract displays how integron-aided AMRs to humans: Transposons capture integron gene cassettes to yield high mobility integrons that target res sites of plasmids. These plasmids, in turn, promote the mobility of acquired integrons into diverse bacterial species. The acquisitions of resistant genes are transferred to humans through horizontal gene transfer.

Exploring the tumor immune microenvironment in ovarian cancer: a way-out to the therapeutic roadmap.

INTRODUCTION: Despite cancer treatment strides, mortality due to ovarian cancer remains high globally. While immunotherapy has proven effective in treating cancers with low cure rates, it has limitations. Growing evidence suggests that both tumoral and non-tumoral components of the tumor immune microenvironment (TIME) play a significant role in cancer growth. Therefore, developing novel and focused therapy for ovarian cancer is critical. Studies indicate that TIME is involved in developing ovarian cancer, particularly genome-, transcriptome-, and proteome-wide studies. As a result, TIME may present a prospective therapeutic target for ovarian cancer patients. AREAS COVERED: We examined several TIME-targeting medicines and the connection between TIME and ovarian cancer. The key protagonists and events in the TIME and therapeutic strategies that explicitly target these events in ovarian cancer are discussed. EXPERT OPINION: We highlighted various targeted therapies against TIME in ovarian cancer, including anti-angiogenesis therapies and immune checkpoint inhibitors. While these therapies are in their infancy, they have shown promise in controlling ovarian cancer progression. The use of 'omics' technology is helping in better understanding of TIME in ovarian cancer and potentially identifying new therapeutic targets. TIME-targeted strategies could account for an additional treatment strategy when treating ovarian cancer.

Network pharmacology combined with molecular docking and in vitro verification reveals the therapeutic potential of Delphinium roylei munz constituents on breast carcinoma.

Delphinium roylei Munz is an indigenous medicinal plant to India where its activity against cancer has not been previously investigated, and its specific interactions of bioactive compounds with vulnerable breast cancer drug targets remain largely unknown. Therefore, in the current study, we aimed to evaluate the anti-breast cancer activity of different extracts of D. roylei against breast cancer and deciphering the molecular mechanism by Network Pharmacology combined with Molecular Docking and in vitro verification. The experimental plant was extracted with various organic solvents according to their polarity index. Phytocompounds were identified by High resolution-liquid chromatography-mass spectrometry (HR-LC/MS) technique, and SwissADME programme evaluated their physicochemical properties. Next, target(s) associated with the obtained bioactives or breast cancer-related targets were retrieved by public databases, and the Venn diagram selected the overlapping targets. The networks between overlapping targets and bioactive were visualized, constructed, and analyzed by STRING programme and Cytoscape software. Finally, we implemented a molecular docking test (MDT) using AutoDock Vina to explore key target(s) and compound(s). HR-LC/MS detected hundreds of phytocompounds, and few were accepted by Lipinski's rules after virtual screening and therefore classified as drug-like compounds (DLCs). A total of 464 potential target genes were attained for the nine quantitative phytocompounds and using Gene Cards, OMIM and DisGeNET platforms, 12063 disease targets linked to breast cancer were retrieved. With Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment, a total of 20 signalling pathways were manifested, and a hub signalling pathway (PI3K-Akt signalling pathway), a key target (Akt1), and a key compound (8-Hydroxycoumarin) were selected among the 20 signalling pathways via molecular docking studies. The molecular docking investigation revealed that among the nine phytoconstituents, 8-hydroxycoumarin showed the best binding energy (-9.2 kcal/mol) with the Akt1 breast cancer target. 8-hydroxycoumarin followed all the ADME property prediction using SwissADME, and 100 nanoseconds (ns) MD simulations of 8-hydroxycoumarin complexes with Akt1 were found to be stable. Furthermore, D. roylei extracts also showed significant antioxidant and anticancer activity through in vitro studies. Our findings indicated for the first time that D. roylei extracts could be used in the treatment of BC.

Conservation genetics of endangered Trillium govanianum Wall. ex D. Don - A pharmaceutically prized medicinal plant from the Himalaya and implications for species recovery.

Understanding the genetic diversity and population structure of pharmaceutically important endangered plant species is crucial for their conservation and sustainable use. Despite the continuous population decline in Trillium govanianum Wall. ex D. Don, a highly prized medicinal plant endemic to the Himalaya, information regarding its conservation genetics has been lacking. Here, we employed a conservation genetics approach to investigate how drastically declining populations in natural habitats impact population genetic diversity and structure of this endangered species across the Kashmir Himalaya. We used Start codon targeted (SCoT) and Simple sequence repeat (SSR) markers to assess the intra- and inter-population genetic variation in seven sites across the study region. Based on these markers, we found a very low genetic diversity in T. govanianum populations. Very low levels of observed heterozygosity (Ho = 0.000) and that expected (He = 0.064) in the populations indicate high heterozygote deficiency and high levels of inbreeding depression (FIS = 1.000). A high genetic differentiation was observed among the populations for both SCoT (Gst = 0.719) and SSR (Fst = 0.707) markers. Both the markers showed low gene flow, SCoT (Nm = 0.195) and SSR (Nm = 0.119), depicting high among-population variation than within-population variation. Analysis of molecular variance also indicated a higher genetic variation between the populations than within populations. We also observed a significant positive correlation between genetic divergence and geographical distance, indicating that genetic differentiation in T. govanianum follows a pattern of isolation by distance. Bayesian structure and cluster analysis grouped the populations according to their geographical proximity. Further, redundancy analysis (RDA) revealed the presence of one polymorphic locus for each marker with high discriminatory power. Overall, our findings reveal a very low genetic diversity, high levels of inbreeding, and high genetic differentiation among the populations; likely resulting from habitat fragmentation, population isolation, bottleneck effect, low gene flow, and predominantly asexual reproduction currently operative in the species. Finally, based on the insights gained, we discuss the potential implications of our findings in guiding species recovery and habitat rehabilitation of T. govanianum in the Himalaya with conservation lessons for elsewhere in the world.

Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat.

BACKGROUND: Buckwheat (Fagopyrum spp.), belonging to the Polygonaceae family, is an ancient pseudo-cereal with high nutritional and nutraceutical properties. Buckwheat proteins are gluten-free and show balanced amino acid and micronutrient profiles, with higher content of health-promoting bioactive flavonoids that make it a golden crop of the future. Plant metabolome is increasingly gaining importance as a crucial component to understand the connection between plant physiology and environment and as a potential link between the genome and phenome. However, the genetic architecture governing the metabolome and thus, the phenome is not well understood. Here, we aim to obtain a deeper insight into the genetic architecture of seed metabolome in buckwheat by integrating high throughput metabolomics and genotyping-by-sequencing applying an array of bioinformatics tools for data analysis. RESULTS: High throughput metabolomic analysis identified 24 metabolites in seed endosperm of 130 diverse buckwheat genotypes. The genotyping-by-sequencing (GBS) of these genotypes revealed 3,728,028 SNPs. The Genome Association and Prediction Integrated Tool (GAPIT) assisted in the identification of 27 SNPs/QTLs linked to 18 metabolites. Candidate genes were identified near 100 Kb of QTLs, providing insights into several metabolic and biosynthetic pathways. CONCLUSIONS: We established the metabolome inventory of 130 germplasm lines of buckwheat, identified QTLs through marker trait association and positions of potential candidate genes. This will pave the way for future dissection of complex economic traits in buckwheat.

Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science.

In the ever-evolving field of drug discovery, the integration of Artificial Intelligence (AI) and Machine Learning (ML) with cheminformatics has proven to be a powerful combination. Cheminformatics, which combines the principles of computer science and chemistry, is used to extract chemical information and search compound databases, while the application of AI and ML allows for the identification of potential hit compounds, optimization of synthesis routes, and prediction of drug efficacy and toxicity. This collaborative approach has led to the discovery, preclinical evaluations and approval of over 70 drugs in recent years. To aid researchers in the pursuit of new drugs, this article presents a comprehensive list of databases, datasets, predictive and generative models, scoring functions and web platforms that have been launched between 2021 and 2022. These resources provide a wealth of information and tools for computer-assisted drug development, and are a valuable asset for those working in the field of cheminformatics. Overall, the integration of AI, ML and cheminformatics has greatly advanced the drug discovery process and continues to hold great potential for the future. As new resources and technologies become available, we can expect to see even more groundbreaking discoveries and advancements in these fields.Communicated by Ramaswamy H. Sarma.

Putting CRISPR-Cas system in action: a golden window for efficient and precise genome editing for crop improvement.

The daunting task of feeding an ever-growing population is an immense challenge for the contemporary scientific community, especially in view of the rapidly changing climate throughout the world. Amidst these threatening crises, we witness rapid development in genome editing (GE) technologies, revolutionizing the field of applied genomics and molecular breeding. Various GE tools have been developed during the last two decades, but the CRISPR/Cas system has most recently made a significant impact on crop improvement. The major breakthroughs of this versatile toolbox are genomic modifications like single base-substitutions, multiplex GE, gene regulation, screening mutagenesis, and enhancing the breeding of wild crop plants. Previously, this toolbox was used to modify genes related to significant traits such as biotic/abiotic resistance/tolerance, post-harvest traits, nutritional regulation, and to address self-incompatibility analysis-related challenges. In the present review, we have demonstrated the functional dynamics of CRISPR-based GE and its applicability in targeting genes to accomplish novel editing of crops. The compiled knowledge will provide a solid foundation for highlighting the primary source for applying CRISPR/Cas as a toolbox for enhancing crops, to achieve food and nutritional security.