The post-genomic era has witnessed an unprecedented accumulation of biological data driven by high-throughput technologies such as next-generation sequencing, transcriptomics, microarrays, genotyping-by-sequencing, and proteomics. Although these advances have enabled comprehensive exploration of complex biological systems, the resulting data volume, dimensionality, and heterogeneity pose substantial computational and analytical challenges. This review provides a structured overview of data mining and computational approaches commonly used for biological big data analysis, with a focus on their applications across genomics, transcriptomics, proteomics, and systems biology. Specifically, we summarize widely adopted analytical workflows and bioinformatics tools for NGS, transcriptome, GBS, QTL, and microarray data analysis, and illustrate their utility through representative applications in disease diagnosis, drug discovery, developmental biology, agriculture, and precision medicine. In addition to outlining methodological capabilities, the review discusses key limitations encountered in practice, including validation of experimentation data, data integration across platforms, scalability, and challenges in biological interpretation. By consolidating current methodologies, tools, and application domains, this review aims to provide a practical reference for researchers navigating biological big data analysis while highlighting areas where further methodological development is needed.

The widespread presence of economically dominant pathogens has significantly hindered agricultural growth and productivity by affecting the quality and yield of crops. The recent deregistration of essential bactericides and nematicides have underscored the urgency for the development of novel agrochemical candidates. In response, N-7 alkylated xanthine derivatives were synthesized using various alkylbromides and characterized with the help of various spectroscopic techniques. The synthesized derivatives were explored for antioxidant, antibacterial, antifungal and antinemic properties. A comprehensive evaluation of antioxidant potential of synthesized compounds utilizing various models revealed that compound 7-decyl-1H-purine-2,6-(3H,7H)-dione (2j) exhibited strong antioxidant potential due to enhancement of electron-donating characterin reference to ascorbic acid. Furthermore, evaluation of antimicrobial activity against Dickeya sp., Xanthomonas campestris and Fusarium oxysporum, and antinemicactivity against Meloidogyne incognita, demonstrated that compound (2j), among other tested compounds, displayed noteworthy inhibitory activity against these pathogens as compared to reference drugs i.e. ciprofloxacin, gentamycin (antimicrobial activity) and carbofuran (antinemic activity). Also, in silico investigations were performed aiming for acetylcholine esterase enzyme inhibition activities to recognize novel interactions of the tested compounds with target binding sites of Meloidogyne incognita. The promising in vitro results warrant further validation under in vivo and field conditions. This research offers valuable insights that these compounds can serve as key precursors for future development of agrochemical agents for managing biotic stresses and improving crop productivity.

Azoles are widely used in agriculture to combat fungal pathogens and protect crops. However, their increased use in recent years has raised concerns due to their endocrine-disrupting properties and other toxic effects, posing risks to human, animal, and environmental health. This study sought to characterize the interaction between selected azoles and the androgen receptor (AR) and to assess their impact on the receptor's normal activity. Molecular docking was performed with azoles and dihydrotestosterone (DHT) as reference ligand, followed by molecular mechanics/generalized born surface area (MM/GBSA) analysis of the docked complexes to evaluate their binding affinity with AR. ADMET analysis was conducted for all compounds along with density functional theory calculations, molecular dynamics simulations (MDS), and post-MDS MM/GBSA binding energy calculations for the top six azoles, including DHT, to assess their toxicity, chemical reactivity, structural and conformational stability, mobility, interaction patterns, and binding affinity. Additionally, experimental studies of the top six azoles, based on their affinity for AR, revealed that they inhibited the dimerization of DHT-bound ARs in the cytoplasm and suppressed DHT-induced AR expression. These findings underscore the importance of developing targeted strategies to mitigate the reproductive toxicity of azoles and promote environmental health.

Disruption of estrogen receptor alpha (ERα) by endocrine-active pesticides may contribute to lipid metabolic dysregulation. We aimed to clarify the docking dynamics of methiocarb with ERα and evaluate its potential to induce lipid accumulation through ERα activation using non-animal testing systems. Molecular docking predicted favorable binding between methiocarb and ERα, primarily through interactions involving the amino group. This prediction was validated using ERα reporter gene assays. Methiocarb-induced lipid accumulation was assessed in 3T3-L1 adipocytes, with or without co-treatment using the ERα antagonist methyl-piperidino-pyrazole (MPP). Methiocarb significantly activated ERα transcriptional activity and promoted ERα-dependent lipid accumulation. Co-treatment with MPP attenuated this effect, whereas antagonists for the glucocorticoid receptor (RU-486) and ERβ (PHTPP) had no effect. Methiocarb increased the expression of adipogenic and lipogenic transcription factors, including PPARγ, C/EBPα, FAS, and SREBP1, as well as the adipocyte-specific marker FABP4, in an ERα-dependent manner. Methiocarb binding to ERα promotes lipid accumulation and upregulates adipogenic/lipogenic transcriptional networks. This approach highlights the utility of ERα-mediated screening to identify potential metabolic disruptors among structurally related pesticides.

This study explored the interactions between benzophenones (BPs) and androgen receptors (AR) using computational and experimental approaches. BPs are potential endocrine disruptors that are commonly found in cosmetics, such as sunscreen. Molecular docking and molecular mechanics with generalized Born and surface area continuum solvation calculations revealed that dihydroxylation form of BP-1, BP-2 had higher binding affinities to AR compared with BP-1, BP-3. Key interactions with residues, such as Gln711 and Asn705, were identified. Density functional theory analysis revealed that BP-2 has a balanced energy gap, which contributes to its stability and reactivity. Cell-based assays validated these computational results, showing that BP-2 had stronger AR antagonistic effect than BP-1 and BP-3. Furthermore, BP-2 enhances the AR-mediated luciferase signal at specific concentration through inducing dimerization of cytosolic AR, whereas BP-1 and BP-3 had no AR agonistic effects. These changes in AR-mediated transcriptional activation activity were observed in flutamide and hydroxyflutamide as well. As expected, changes in AR-mediated endocrine disrupting potential due to configurational modification of BP-1 to BP-2 by dihydroxylation resulted in whole AR protein expression. These findings suggest that BP-2 is a strong AR modulator and a potential endocrine disruptor, offering insights into how similar compounds may interact with AR.

Veterinary systems biology is an innovative approach that integrates biological data at the molecular and cellular levels, allowing for a more extensive understanding of the interactions and functions of complex biological systems in livestock and veterinary science. It has tremendous potential to integrate multi-omics data with the support of vetinformatics resources for bridging the phenotype-genotype gap via computational modeling. To understand the dynamic behaviors of complex systems, computational models are frequently used. It facilitates a comprehensive understanding of how a host system defends itself against a pathogen attack or operates when the pathogen compromises the host's immune system. In this context, various approaches, such as systems immunology, network pharmacology, vaccinology and immunoinformatics, can be employed to effectively investigate vaccines and drugs. By utilizing this approach, we can ensure the health of livestock. This is beneficial not only for animal welfare but also for human health and environmental well-being. Therefore, the current review offers a detailed summary of systems biology advancements utilized in veterinary sciences, demonstrating the potential of the holistic approach in disease epidemiology, animal welfare and productivity.

Bisphenol A (BPA) and its various forms used as BPA alternatives in industries are recognized toxic compounds and antiandrogenic endocrine disruptors. These chemicals are widespread in the environment and frequently detected in biological samples. Concerns exist about their impact on hormones, disrupting natural biological processes in humans, together with their negative impacts on the environment and biotic life. This study aims to characterize the interaction between BPA analogs and the androgen receptor (AR) and the effect on the receptor's normal activity. To achieve this goal, molecular docking was conducted with BPA and its analogs and dihydrotestosterone (DHT) as a reference ligand. Four BPA analogs exhibited higher affinity (-10.2 to -8.7 kcal/ mol) for AR compared to BPA (-8.6 kcal/mol), displaying distinct interaction patterns. Interestingly, DHT (-11.0 kcal/mol) shared a binding pattern with BPA. ADMET analysis of the top 10 compounds, followed by molecular dynamics simulations, revealed toxicity and dynamic behavior. Experimental studies demonstrated that only BPA disrupts DHT-induced AR dimerization, thereby affecting AR's function due to its binding nature. This similarity to DHT was observed during computational analysis. These findings emphasize the importance of targeted strategies to mitigate BPA toxicity, offering crucial insights for interventions in human health and environmental well-being.

Bisphenol A (BPA), an endocrine-disrupting substance commonly found in plastics and receipts, is associated with adverse effects, including endocrine disorders, reduced fertility, and metabolic issues. To gain insights into its effects on biological systems, we observed the adverse effects of BPA in male Institute of Cancer Research (ICR) mice exposed to BPA at the lowest observed adverse effect level for 6 weeks, in comparison with the control groups. We constructed a comprehensive transcriptome profile using 20 different tissues to analyze the changes in the whole-body systems. This involved employing differential gene expression, tissue-specific gene, and gene co-expression network analyses. The study revealed that BPA exposure led to significant differences in the transcriptome in the thymus, suggesting activation of T-cell differentiation and maturation in response to BPA treatment. Furthermore, various tissues exhibited immune response activation, potentially due to the migration of immune cells from the thymus. BPA exposure also caused immune-related functional changes in the colon, liver, and kidney, as well as abnormal signaling responses in the sperm. The transcriptome analysis serves as a valuable resource for understanding the functional impact of BPA, providing profound insights into the effects of BPA exposure and emphasizing the need for further research on potential associated health risks.

The use of Bisphenol A (BPA) and its analogs in industries, as well as the products made from them, is becoming a significant concern for human health. Scientific studies have revealed that BPA functions as an endocrine disruptor. While some analogs of BPA (bisphenols) have been used for a longer time, it was later discovered that they are toxic, similar to BPA. Their widespread use ensures their presence in the environment, and thus, everyone is exposed to them. Scientific research has shown that BPA interacts with estrogen-related receptor gamma (ERRγ), affecting its normal function. ERRγ is involved in biological processes including energy metabolism and mitochondrial function. Therefore, continuous exposure to bisphenols increases the risk of various diseases. In our previous study, we observed that some analogs of BPA had a higher binding affinity to ERRγ compared to BPA itself and analyzed the amino acid residues involved in this interaction. We hypothesized that by antagonizing the interaction between bisphenols and ERRγ, we could neutralize their toxic effects. Taking into account the health benefits of millets and their toxin removal properties, virtual screening of millet-derived compounds was conducted along with prediction of their ADMET profiles. Top five candidates were prioritized for Density Functional Theory (DFT) calculations and further analyses. Long-term molecular dynamics simulation (1 µs) were utilized to evaluate their binding, stability, and antagonizing abilities. Furthermore, reevaluation of their binding energy was conducted using the MM-PBSA method. This study reports millet-derived compounds, namely, Tricin 7-rutinoside, Tricin 7-glucoside, Glucotricin, Kaempferol, and Setarin. These compounds are predicted to be potent competitive inhibitors that can antagonize the interactions between bisphenols and ERRγ. These compounds could potentially assist in the development of future therapeutics. They may also be considered for use as food supplements, although further investigations, including wet-lab experiments and clinical studies, are needed.

Black mold disease provoked by Aspergillus niger is one of the major postharvest diseases in Allium cepa. In the present study, efforts have been made to model the polygalacturonase protein of Aspergillus niger that is involved in disease progression as a promising molecular target for the identification of novel fungicides through computational approach. We used I-TASSER to determine the 3D structure of the target protein and docked it with naturally occurring phytoalexins which included nimbolide, nimbolin, Azadiradione, Quercetin and Azadirone. The result of present study revealed that nimbolide has the greatest affinity towards polygalacturonase as compared to other phytoalexins which binds the protein at amino acid residues Gln205, Gln261, Tyr262 with four hydrogen bonds and − 8.0 kcal/mol binding energy. Further, molecular dynamics simulation of protein and docked nimbolide-polyglacturonase complex was carried out to validate the stability of the system at the atomic level. Based on the study, this may lead to inhibition of pathogenic protein. Thus, it is of interest to consider the molecule for further validation at lab and field conditions for ensuring food and nutritional security.

Bisphenol A (BPA) is a very important chemical from the commercial perspective. Many useful products are made from it, so its production is increasing day by day. It is widely known that Bisphenol A (BPA) and its analogs are present in the environment and that they enter our body through various routes on a daily basis as we use things made of this chemical in our daily lives. BPA has already been reported to be an endocrine disruptor. Studies have shown that BPA binds strongly to the human estrogen-related receptor gamma (ERRγ) and is an important target of it. This study seeks to understand how it interacts with ERRγ. Molecular docking of BPA and its analogs with ERRγ was performed, and estradiol was taken as a reference. Then, physico-chemical and toxicological analysis of BPA compounds was performed. Subsequently, the dynamic behavior of ERRγ and ERRγ-BPA compound complexes was studied by molecular dynamics simulations over 500 ns, and using this simulated data, their binding energies were again calculated using the MM-PBSA method. We observed that the binding affinity of BPA and its analogs was much higher than that of estradiol, and apart from being toxic, they can be easily absorbed in our body as their physicochemical properties are similar to those of oral medicines. Therefore, this study facilitates the understanding of the structure–activity relationship of ERRγ and BPA compounds and provides information about the key amino acid residues of ERRγ that interact with BPA compounds, which can be helpful to design competitive inhibitors so that we can interrupt the interaction of BPA with ERRγ. In addition, it provides information on BPA and its analogs and will also be helpful in developing new therapeutics.

Biological big data are a massive amount of data generated from multi-omics experiments, such as genomics, transcriptomics, proteomics, metabolomics, phenomics, glycomics, epigenomics, and other omics. These data are used to study biological processes and to gain insights into how living systems work. It can also be used to develop new treatments for diseases and understand the causes of certain conditions. The storage and analysis of these data present several challenges owing to their sheer size and complexity. Storing these data efficiently requires a large amount of storage space and processing power. Furthermore, there are certain limitations in terms of the kind of insights that can be gained from multi-omics data because of their complexity. Despite these challenges, biological big data offers great potential for advancing our understanding of biology and developing new treatments for diseases. Big-data research is a rapidly growing field, with numerous applications. As the amount of data continues to increase, it is important to understand its storage, utility, limitations, and challenges. In this review article, various sources of big-data research and their storage capacities, limitations, and challenges are discussed. Factors affecting the data quality and accuracy have been reported. It will be helpful for researchers to understand the available big data in biology for their further utilization and integration into novel discovery.

The porcine epidemic diarrhea virus (PEDV) represents a major health issue for piglets worldwide and does significant damage to the pork industry. Thus, new therapeutic approaches are urgently needed to manage PEDV infections. Due to the current lack of a reliable remedy, this present study aims to identify novel compounds that inhibit the 3CL protease of the virus involved in replication and pathogenesis. To identify potent antiviral compounds against the 3CL protease, a virtual screening of natural compounds (n = 97,999) was conducted. The top 10 compounds were selected based on the lowest binding energy and the protein-ligand interaction analyzed. Further, the top five compounds that demonstrated a strong binding affinity were subjected to drug-likeness analysis using the ADMET prediction, which was followed by molecular dynamics simulations (500 ns), free energy landscape, and binding free energy calculations using the MM-PBSA method. Based on these parameters, four putative lead (ZINC38167083, ZINC09517223, ZINC04339983, and ZINC09517238) compounds were identified that represent potentially effective inhibitors of the 3CL protease. Therefore, these can be utilized for the development of novel antiviral drugs against PEDV. However, this requires further validation through in vitro and in vivo studies.

Mastitis poses a major threat to dairy farms globally; it results in reduced milk production, increased treatment costs, untimely compromised genetic potential, animal deaths, and economic losses. Streptococcus agalactiae is a highly virulent bacteria that cause mastitis. The administration of antibiotics for the treatment of this infection is not advised due to concerns about the emergence of antibiotic resistance and potential adverse effects on human health. Thus, there is a critical need to identify new therapeutic approaches to combat mastitis. One promising target for the development of antibacterial therapies is the transmembrane histidine kinase of bacteria, which plays a key role in signal transduction pathways, secretion systems, virulence, and antibiotic resistance. In this study, we aimed to identify novel natural compounds that can inhibit transmembrane histidine kinase. To achieve this goal, we conducted a virtual screening of 224,205 natural compounds, selecting the top ten based on their lowest binding energy and favorable protein–ligand interactions. Furthermore, molecular docking of eight selected antibiotics and five histidine kinase inhibitors with transmembrane histidine kinase was performed to evaluate the binding energy with respect to top-screened natural compounds. We also analyzed the ADMET properties of these compounds to assess their drug-likeness. The top two compounds (ZINC000085569031 and ZINC000257435291) and top-screened antibiotics (Tetracycline) that demonstrated a strong binding affinity were subjected to molecular dynamics simulations (100 ns), free energy landscape, and binding free energy calculations using the MM-PBSA method. Our results suggest that the selected natural compounds have the potential to serve as effective inhibitors of transmembrane histidine kinase and can be utilized for the development of novel antibacterial veterinary medicine for mastitis after further validation through clinical studies.

EDITORIAL article Front. Vet. Sci., 30 October 2023Sec. Livestock Genomics Volume 10 - 2023 | https://doi.org/10.3389/fvets.2023.1292733