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We predicted the protein therapeutic targets specific to a Ru-based potential drug and its combination with pristine and N-doped carbon dot drug delivery systems, denoted as RuCN/CDs and RuCN/N-CDs. Synchrotron-based FTIR microspectroscopy (µFTIR) in addition to bioinformatics data on drug structures and protein sequences were applied to assess changes in the protein secondary structure of A2780 cancer cells. µFTIR revealed the moieties of the target proteins' secondary structure changes only after the treatment with RuCN and RuCN/N-CDs. A higher content of α-helices and a lower content of ß-sheets appeared in A2780 cells after RuCN treatment. Treatment with RuCN/N-CDs caused a substantial increase in parallel ß-sheet numbers, random coil content, and tyrosine residue numbers. The results obtained suggest that the mitochondrion-related proteins NDUFA1 and NDUFB5 are affected by RuCN either via overexpression or stabilisation of helical structures. RuCN/N-CDs either induce overexpression of the ß-sheet-rich protein NDUFS1 and affect its random coil structure or interact and stabilise its structure via hydrogen bonding between -NH2 groups from N-CDs with protein C=O groups and -OH groups of serine, threonine, and tyrosine residues. The N-CD nanocarrier tunes this drug's action by directing it toward a specific protein target, changing this drug's coordination ability and inducing changes in the protein's secondary structures and function.

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Background: Cannabis sativa with a rich history of traditional medicinal use, has garnered significant attention in contemporary research for its potential therapeutic applications in various human diseases, including pain, inflammation, cancer, and osteoarthritis. However, the specific molecular targets and mechanisms underlying the synergistic effects of its diverse phytochemical constituents remain elusive. Understanding these mechanisms is crucial for developing targeted, effective cannabis-based therapies. Methods: To investigate the molecular targets and pathways involved in the synergistic effects of cannabis compounds, we utilized DRIFT, a deep learning model that leverages attention-based neural networks to predict compound-target interactions. We considered both whole plant extracts and specific plant-based formulations. Predicted targets were then mapped to the Reactome pathway database to identify the biological processes affected. To facilitate the prediction of molecular targets and associated pathways for any user-specified cannabis formulation, we developed CANDI (Cannabis-derived compound Analysis and Network Discovery Interface), a web-based server. This platform offers a user-friendly interface for researchers and drug developers to explore the therapeutic potential of cannabis compounds. Results: Our analysis using DRIFT and CANDI successfully identified numerous molecular targets of cannabis compounds, many of which are involved in pathways relevant to pain, inflammation, cancer, and other diseases. The CANDI server enables researchers to predict the molecular targets and affected pathways for any specific cannabis formulation, providing valuable insights for developing targeted therapies. Conclusions: By combining computational approaches with knowledge of traditional cannabis use, we have developed the CANDI server, a tool that allows us to harness the therapeutic potential of cannabis compounds for the effective treatment of various disorders. By bridging traditional pharmaceutical development with cannabis-based medicine, we propose a novel approach for botanical-based treatment modalities.

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Background: Natural products exhibit structural complexity, diversity, and historical therapeutic significance, boasting attractive functions and biological activities that have significantly influenced drug discovery endeavors. The identification of target proteins of active natural compounds is crucial for advancing novel drug innovation. Currently, methods for identifying targets of natural products can be categorized into labeling and label-free approaches based on whether the natural bioactive constituents are modified into active probes. In addition, there is a new avenue for rapidly exploring the targets of natural products based on their innate functions. Aim: This review aimed to summarize recent advancements in both labeling and label-free approaches to the identification of targets for natural products, as well as the novel target identification method based on the natural functions of natural products. Methods: We systematically collected relevant articles published in recent years from PubMed, Web of Science, and ScienceDirect, focusing on methods employed for identifying protein targets of bioactive natural products. Furthermore, we systematically summarized the principles, procedures, and successful cases, as well as the advantages and limitations of each method. Results: Labeling methods allow for the direct labeling of target proteins and the exclusion of indirectly targeted proteins. However, these methods are not suitable for studying post-modified compounds with abolished activity, chemically challenging synthesis, or trace amounts of natural active compounds. Label-free methods can be employed to identify targets of any natural active compounds, including trace amounts and multicomponent mixtures, but their reliability is not as high as labeling methods. The structural complementarity between natural products and their innate receptors significantly increase the opportunities for finding more promising structural analogues of the natural products, and natural products may interact with several structural analogues of receptors in humans. Conclusion: Each approach presents benefits and drawbacks. In practice, a combination of methods is employed to identify targets of natural products. And natural products' innate functions-based approach is a rapid and selective strategy for target identification. This review provides valuable references for future research in this field, offering insights into techniques and methodologies.

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Fluid biopsy technology, characterized by its minimally invasive nature, speed, and continuity, has become a rapidly advancing and widely applied real-time diagnostic technique. Among various biomarkers, proteins represent the most abundant class of disease indicators. The sensitive and accurate detection of protein markers in bodily fluids is significantly influenced by the control exerted by recognition ligands. Aptamers, which are structurally dynamic functional oligonucleotides, exhibit high affinity, specific recognition of targets, and notable characteristics of high editability and modularity. These features make aptamer universal "recognition-capture" components, contribute to a significant leap in their applications within the biosensor domain. In this context, we provide a comprehensive review of the extensive application of aptamer-based biosensors in fluid biopsy. We systematically compile the characteristics and construction strategies of aptamer-based biosensors tailored for fluid biopsy, including aptamer sequences, affinity (KD), fluid background, sensing technologies, sensor construction strategies, incubation time, detection performance, and influencing factors. Furthermore, a comparative analysis of their advantages and disadvantages was conducted. In conclusion, we delineate and deliberate on prospective research trajectories and challenges that lie ahead in the realm of aptamer-based biosensors for fluid biopsy.

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Calixarenes are displaying great potential for the development of new drug delivery systems, diagnostic imaging, biosensing devices and inhibitors of biological processes. In particular, calixarene derivatives are able to interact with many different enzymes and function as inhibitors. By screening of the potential drug target database (PDTD) with a reverse docking procedure, we identify and discuss a selection of 100 proteins that interact strongly with calix[4]arene. We also discover that leucine (23.5 %), isoleucine (11.3 %), phenylalanines (11.3 %) and valine (9.5 %) are the most frequent binding residues followed by hydrophobic cysteines and methionines and aromatic histidines, tyrosines and tryptophanes. Top binders are peroxisome proliferator-activated receptors that already are targeted by commercial drugs, demonstrating the practical interest in calix[4]arene. Nuclear receptors, potassium channel, several carrier proteins, a variety of cancer-related proteins and viral proteins are prominent in the list. It is concluded that calix[4]arene, which is characterized by facile access, well-defined conformational characteristics, and ease of functionalization at both the lower and higher rims, could be a potential lead compound for the development of enzyme inhibitors and theranostic platforms.

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Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb., two nootropics, are recognized in Indian Ayurvedic texts. Studies have attempted to understand their action as memory enhancers and neuroprotectants, but many molecular aspects remain unknown. We propose that Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb. share common neuroprotective mechanisms. Mass spectrometry-based untargeted metabolomics and network pharmacology approach were used to identify potential protein targets for the metabolites from each extract. Phytochemical analyses and cell culture validation studies were also used to assess apoptosis and ROS activity using aqueous extracts prepared from both herbal powders. Further, docking studies were also performed using the LibDock protocol. Untargeted metabolomics and network pharmacology approach unveiled 2751 shared metabolites and 3439 and 2928 non-redundant metabolites from Bacopa monnieri and Centella asiatica extracts, respectively, suggesting a potential common neuroprotective mechanism among these extracts. Protein-target prediction highlighted 92.4% similarity among the proteins interacting with metabolites for these extracts. Among them, kinases mapped to MAPK, mTOR, and PI3K-AKT signaling pathways represented a predominant population. Our results highlight a significant similarity in the metabolome of Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb., and their potential protein targets may be attributed to their common neuroprotective functions.

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MicroRNAs (miRNAs) are short, endogenously encoded small RNAs, 18-26 nucleotides in length, which can posttranscriptionally regulate gene expression through translation inhibition or endonucleolytic cleavage. The muskmelon is one of the most widely cultivated fruits in the Cucurbitaceae family. Despite its significance, only 120 miRNAs from different families have been reported in muskmelon. In this study, we aimed to expand this knowledge base by predicting 40 new miRNAs in muskmelon using a spectrum of genomic-based tools. Precursor and mature sequences were obtained from microRNA registry database as reference and analyzed via the basic local alignment search tool (Blastn) for ESTs identification. After removing the non-coding sequences, the remaining candidate sequences were analyzed using MFOLD to generate secondary structures for the newly predicted miRNAs. Additionally, the predicted muskmelon miRNAs were validated using a set of five randomly chosen primers and RT-PCR. Through gene ontology (GO) analysis, we identified 89 targets associated with newly predicted muskmelon miRNAs. Transcription factor-coding genes play a crucial role in plant growth and development. Additionally, the miR4249 has been found to have the same targets in muskmelon that have been linked to cell signaling and transcription factors. The identified targets are integral for diverse biological processes including plant growth, development, metabolism, aging, disease resistance, and resistance to environmental stresses, such as salt, cold, and oxidative stress. As a result, the outcomes of this study demonstrate that this mechanism not only contributes to the production of a higher quality crop but also enhances overall production.

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Idiopathic pulmonary fibrosis (IPF) is a devastating interstitial lung disease characterized by the relentless deposition of extracellular matrix (ECM), causing lung distortions and dysfunction. Animal models of human IPF can provide great insight into the mechanistic pathways underlying disease progression and a means for evaluating novel therapeutic approaches. In this study, we describe the effect of bleomycin concentration on disease progression in the classical rat bleomycin model. In a dose-response study (1.5, 2, 2.5 U/kg i.t), we characterized lung fibrosis at day 14 after bleomycin challenge using endpoints including clinical signs, inflammatory cell infiltration, collagen content, and bronchoalveolar lavage fluid-soluble profibrotic mediators. Furthermore, we investigated fibrotic disease progression after 2 U/kg i.t. bleomycin administration at days 3, 7, and 14 by quantifying the expression of clinically relevant signaling molecules and pathways, epithelial mesenchymal transition (EMT) biomarkers, ECM components, and histopathology of the lung. A single bleomycin challenge resulted in a progressive fibrotic response in rat lung tissue over 14 days based on lung collagen content, histopathological changes, and modified Ashcroft score. The early fibrogenesis phase (days 3 to 7) is associated with an increase in profibrotic mediators including TGFß1, IL6, TNFα, IL1ß, CINC1, WISP1, VEGF, and TIMP1. In the mid and late fibrotic stages, the TGFß/Smad and PDGF/AKT signaling pathways are involved, and clinically relevant proteins targeting galectin-3, LPA1, transglutaminase-2, and lysyl oxidase 2 are upregulated on days 7 and 14. Between days 7 and 14, the expressions of vimentin and α-SMA proteins increase, which is a sign of EMT activation. We confirmed ECM formation by increased expressions of procollagen-1Aα, procollagen-3Aα, fibronectin, and CTGF in the lung on days 7 and 14. Our data provide insights on a complex network of several soluble mediators, clinically relevant signaling pathways, and target proteins that contribute to drive the progressive fibrotic phenotype from the early to late phase (active) in the rat bleomycin model. The framework of endpoints of our study highlights the translational value for pharmacological interventions and mechanistic studies using this model.

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MicroRNAs (miRNAs) are typically non-coding RNAs of 18-26 nucleotides (nts) that are produced endogenously and regulated post-transcriptionally through degradation or translational repression. Since miRNAs are evolutionarily conserved, their preservation is essential for important regulatory functions in plant development, growth, and responses to environmental stress. Sorghum bicolor (sbi) is a valuable food and fodder crop which is grown worldwide. A range of sbi miRNAs were identified so far as being connected to plant development and stress responses. Herein, we employed a variety of bioinformatics tools for miRNA profiling in sbi and a PCR-based platform for the validation of these miRNAs. In total, 74 new conserved sbi miRNAs from 52 miRNA families have been predicted. Using the psRNA Target method, 10613 different protein targets of these predicted miRNAs have been attained. These targets include 54 GO-terms which have substantial targets in the biological, molecular, and cellular processes. We particularly found that the sbi-miR1861c and sbi-miR5050 are involved to regulate sulphur compound biosynthetic process, while the significant spliceosomal complex is regulated by sbi-miR815b and sbi-miR7768b. Also, we report that the pre-ribosome, electron transport chain, cell communication, cellular respiration, protein localization, and photosynthesis are controlled by sbi-miR2907b, sbi-miR530, sbi-miR7749, sbi-miR1858a, sbi-mi7729a, and sbi-miR417, respectively. The identification and validation of these novel sbi miRNAs shall contribute a lot in improving the crop yield and ensure sustainable agriculture.

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While a congestive heart failure patient will ultimately need an assist device or even a replacement heart as the disease progresses, not every patient is qualified for such advanced therapy. Such patients awaiting better circulatory support benefit from positive inotropes in the meantime as palliative care. These agents are often prescribed in patients with acute decompensated heart failure, with reduced left ventricular ejection fraction and symptoms of organ dysfunction. Although positive inotropes, for example, digoxin, dobutamine, milrinone, levosimendan, etc., are successfully marketed and in use, a lot of their adverse effects, like arrhythmias, hypotension, and even sudden cardiac death, are rather encouraging further research on the development of novel positive inotropes. This review has investigated the molecular mechanisms of some of these adverse effects in terms of the proteins they target, followed by research on newer targets. Studies from 2013-2023 that have reported new small molecules with positive inotropic effects have been revisited in order to determine the progress made so far in drug discovery.

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Inflammation plays a crucial role in the onset or progression of a variety of acute and chronic diseases. Non-steroidal anti-inflammatory drugs (NSAIDs) are the only available FDA-approved therapy. The therapeutic outcome of NSAIDs is still finite due to off-target effects and extreme side effects on other vital organs. Bioactive syringin has been manifested to hold anti-osteoporosis, cardiac hypertrophy, alter autophagy, anti-cancer, neuro-preventive effects, etc. However, its multi-protein targeting potential in inflammation mostly remains unexplored. In the present work, we have checked the multi-protein targeting potential of bioactive glycoside syringin in inflammatory diseases. Based on the binding score of protein-ligand complexes, glycoside syringin scored greater than -7 kcal/mol against 12 inflammatory proteins. Our molecular dynamic simulation study (200 ns) confirmed that bioactive syringin remained inside the binding cavity of inflammatory proteins (JAK1, TYK2, and COX1) in a stable conformation. Further, our co-expression analysis suggests that these genes play an essential role in multiple pathways and are regulated by multiple miRNAs. Our study demonstrates that bioactive glycoside syringin might be a multi-protein targeting potential against inflammatory diseases and could be further investigated utilizing different preclinical approaches.Communicated by Ramaswamy H. Sarma.

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BACKGROUND: Diabetes mellitus (DM) is a metabolic disorder known to impair many physiological functions via reactive oxygen species (ROS). Aldose reductase, sorbitol dehydrogenase, dipeptidyl peptidase IV, α-amylase and α-glucosidase are pharmacotherapeutic protein targetsin type-2 diabetes mellitus (T2DM). Inhibitors of these enzymes constitute a new class of drugs used in the management and treatment of T2DM. Some reports have claimed that medicinal plant extracts that serves as food (and as an antioxidant source) can reduce these alterations by eliminating ROS caused by DM. Ethnobotanical survey claims Jatropha gossypifolia commonly called "fig-nut" and "Lapa- lapa" in the Yoruba land of South-western Nigeria, to be used for the treatment and management of diabetes, in addition to its nutritive value. OBJECTIVE: The nutritional composition and in-silico antidiabetic potential of the bioactive constituents of J. gossypifolia leaf extracts were investigated. METHODS: Proximate, minerals and gas chromatography-mass spectroscopy (GC-MS) analysis were carried out using standard procedures. Phytocompounds present in J. gossypifolia methanol (JGM) and ethyl acetate (JGE) leaf extracts were tested as potential antagonists of selected protein targets via in-silico techniques. Drug-likeness, pharmacokinetic properties and toxicity of the promising docked ligands were also predicted. RESULTS: Proximate, minerals and gas chromatography­mass spectroscopy (GC-MS) analysis were carried out using standard procedures. Phytocompounds present in J. gossypifolia methanol (JGM) and ethyl acetate (JGE) leaf extracts were tested for their potential antagonistic effects on selected protein targets via in-silico techniques. Drug-likeness, pharmacokinetic properties and toxicity of the promising docked ligands were also predicted. Results: The proximate and mineral analysis revealed CONCLUSION: Benzene-1,2,4,5-tetramethyl from JGE extracts exhibited the most promising antidia- betic potential in-silico, suggesting its candidature as diabetes-target-protein inhibitor which may be developed for the treatment of type-2 diabetes mellitus.

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Extracting "high ranking" or "prime protein targets" (PPTs) as potent MRSA drug candidates from a given set of ligands is a key challenge in efficient molecular docking. This study combines protein-versus-ligand matching molecular docking (MD) data extracted from 10 independent molecular docking (MD) evaluations - ADFR, DOCK, Gemdock, Ledock, Plants, Psovina, Quickvina2, smina, vina, and vinaxb to identify top MRSA drug candidates. Twenty-nine active protein targets (APT) from the enhanced DUD-E repository ( http://DUD-E.decoys.org ) are matched against 1040 ligands using "forward modeling" machine learning for initial "data mining and modeling" (DDM) to extract PPTs and the corresponding high affinity ligands (HALs). K-means clustering (KMC) is then performed on 400 ligands matched against 29 PTs, with each cluster accommodating HALs, and the corresponding PPTs. Performance of KMC is then validated against randomly chosen head, tail, and middle active ligands (ALs). KMC outcomes have been validated against two other clustering methods, namely, Gaussian mixture model (GMM) and density based spatial clustering of applications with noise (DBSCAN). While GMM shows similar results as with KMC, DBSCAN has failed to yield more than one cluster and handle the noise (outliers), thus affirming the choice of KMC or GMM. Databases obtained from ADFR to mine PPTs are then ranked according to the number of the corresponding HAL-PPT combinations (HPC) inside the derived clusters, an approach called "reverse modeling" (RM). From the set of 29 PTs studied, RM predicts high fidelity of 5 PPTs (17%) that bind with 76 out of 400, i.e., 19% ligands leading to a prediction of next-generation MRSA drug candidates: PPT2 (average HPC is 41.1%) is the top choice, followed by PPT14 (average HPC 25.46%), and then PPT15 (average HPC 23.12%). This algorithm can be generically implemented irrespective of pathogenic forms and is particularly effective for sparse data.

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PURPOSE: The resistance of parasite to readily affordable antimalarial drugs, the high cost of currently potent drugs, and the resistance of vector mosquitoes to insecticides threaten the possibility of malaria eradication in malaria endemic areas. Due to the fact that quinine and artemisinin were isolated from plants sources, researchers have been encouraged to search for new antimalarials from medicinal plants. This is especially the case in Africa where a large percentage of the population depends on medicinal plant to treat malaria and other ailments. METHOD: In this study, we evaluated previously characterized Plasmodium-cidal compounds obtained from the African flora to identify their likely biochemical targets, for an insight into their possible antimalarial chemotherapy. Molecular docking study was first conducted, after which remarkable compounds were submitted for molecular dynamic (MD) simulations studies. RESULTS: From a total of 38 Plasmodium-cidal compounds docked with confirmed Plasmodium falciparum protein drug targets [plasmepsin II (PMII), histo-aspartic protein (HAP) and falcipain-2 (FP)], two pentacyclic triterpene, cucurbitacin B and 3 beta-O-acetyl oleanolic acid showed high binding affinity relative to artesunate. This implies their capacity to inhibit the three selected P. falciparum target proteins, and consequently, antimalarial potential. From the MD simulations studies and binding free energy outcomes, results confirmed that the two compounds are stable in complex with the selected antimalarial targets; they also showed excellent binding affinities during the 100 ns simulation. CONCLUSION: These results showed that cucurbitacin B and 3 beta-O-acetyl oleanolic acid are potent antimalarials and should be considered for further studies.

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Rheumatoid arthritis (RA) is a debilitating autoimmune disorder with an inflammatory condition targeting the joints that affects millions of patients worldwide. Several unmet needs still need to be addressed despite recent improvements in the management of RA. Although current RA therapies can diminish inflammation and alleviate symptoms, many patients remain unresponsive or experience flare-ups of their ailment. The present study aims to address these unmet needs through in silico research, with a focus on the identification of novel, potentially active molecules. Therefore, a molecular docking analysis has been conducted using AutoDockTools 1.5.7 on Janus kinase (JAK) inhibitors that are either approved for RA or in advanced phases of research. The binding affinities of these small molecules against JAK1, JAK2, and JAK3, which are target proteins implicated in the pathophysiology of RA, have been assessed. Subsequent to identifying the ligands with the highest affinity for these target proteins, a ligand-based virtual screening was performed utilizing SwissSimilarity, starting with the chemical structures of the previously identified small molecules. ZINC252492504 had the highest binding affinity (-9.0 kcal/mol) for JAK1, followed by ZINC72147089 (-8.6 kcal/mol) for JAK2, and ZINC72135158 (-8.6 kcal/mol) for JAK3. Using SwissADME, an in silico pharmacokinetic evaluation showed that oral administration of the three small molecules may be feasible. Based on the preliminary results of the present study, additional extensive research is required for the most promising candidates to be conducted so their efficacy and safety profiles can be thoroughly characterized, and they can become medium- and long-term pharmacotherapeutic solutions for the treatment of RA.

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Advancement in the area of anti-tubercular drug development has been full-fledged, yet, a very less number of drug molecules have reached phase II clinical trials, and therefore "End-TB" is still a global challenge. Inhibitors to specific metabolic pathways of Mycobacterium tuberculosis (Mtb) gain importance in strategizing anti-tuberculosis drug discovery. The lead compounds that target DNA replication, protein synthesis, cell wall biosynthesis, bacterial virulence and energy metabolism are emerging as potential chemotherapeutic options against Mtb growth and survival within the host. In recent times, the in silico approaches have become most promising tools in the identification of suitable inhibitors for specific protein targets of Mtb. An update in the fundamental understanding of these inhibitors and the mechanism of interaction may bring hope to future perspectives in novel drug development and delivery approaches. This review provides a collective impression of the small molecules with potential antimycobacterial activities and their target pathways in Mtb such as cell wall biosynthesis, DNA replication, transcription and translation, efflux pumps, antivirulence pathways and general metabolism. The mechanism of interaction of specific inhibitor with their respective protein targets has been discussed. The comprehensive knowledge of such an impactful area of research would essentially reflect in the discovery of novel drug molecules and effective delivery approaches. This narrative review encompasses the knowledge of emerging targets and promising chemical inhibitors that could potentially translate in to the anti-TB-drug discovery.

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The mycotoxin citrinin, which can contaminate food, is a major global concern. Citrinin is regarded as an inevitable pollutant in foods and feed since fungi are widely present in the environment. To identify contentious toxicity and lessen its severity by understanding the targets of citrinin in the human body and the impacted biosynthetic pathways, we analyzed the production of citrinin from Aspergillus flavus and Penicillium notatum and used a thorough bioinformatics analysis to characterize the toxicity and predict genes and protein targets for it. The predicted median fatal dosage (LD50) for citrinin was 105 mg/kg weight, and it belonged to toxicity class 3 (toxic if swallowed). Citrinin was found to be well absorbed by human intestinal epithelium and was a Pgp nonsubstrate (permeability glycoprotein), which means that once it is absorbed, it cannot be pumped out, hence leading to bioconcentration or biomagnification in the human body. The main targets of toxicity were casp3, TNF, IL10, IL1B, BAG3, CCNB1, CCNE1, and CDC25A, and the biological pathways implicated were signal transduction involved in DNA damage checkpoints, cellular and chemical responses to oxidative stress, DNA damage response signal transduction by P53, stress-activated protein kinase signaling cascade, netrin-UNC5B signaling, PTEN gene regulation, and immune response. Citrinin was linked to neutrophilia, squamous cell carcinoma, Fanconi anemia, leukemia, hepatoblastoma, and fatty liver diseases. The transcription factors E2F1, HSF1, SIRT1, RELA, NFKB, JUN, and MYC were found to be responsible. When data mining was performed on citrinin targets, the top five functional descriptions were a cell's response to an organic cyclic compound, the netrin-UNC5B signaling pathway, lipids and atherosclerosis, thyroid cancer, and controlling the transcription of the PTEN gene.

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The mitochondrial permeability transition pore (mtPTP) plays a vital role in altering the structure and function of mitochondria. Cyclophilin D (CypD) is a mitochondrial protein that regulates mtPTP function and a known drug target for therapeutic studies involving mitochondria. While the effect of aromatase inhibition on the mtPTP has been studied previously, the effect of anastrozole on the mtPTP has not been completely elucidated. The role of anastrozole in modulating the mtPTP was evaluated by docking, molecular dynamics and network-guided studies using human CypD data. The peripheral blood mononuclear cells (PBMCs) of patients with mitochondrial disorders and healthy controls were treated with anastrozole and evaluated for mitochondrial permeability transition pore (mtPTP) function and apoptosis using a flow cytometer. Spectrophotometry was employed for estimating total ATP levels. The anastrozole-CypD complex is more stable than cyclosporin A (CsA)-CypD. Anastrozole performed better than cyclosporine in inhibiting mtPTP. Additional effects included inducing mitochondrial membrane depolarization and a reduction in mitochondrial swelling and superoxide generation, intrinsic caspase-3 activity and cellular apoptosis, along with an increase in ATP levels. Anastrozole may serve as a potential therapeutic agent for mitochondrial disorders and ameliorate the clinical phenotype by regulating the activity of mtPTP. However, further studies are required to substantiate our preliminary findings.Communicated by Ramaswamy H. Sarma.

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Multitarget bioactive molecules (MBMs) are of increasing importance in drug discovery as they could produce high efficacy and a low chance of resistance. Several advanced approaches of quantitative proteomics were developed to accurately identify the protein targets of MBMs, but little study has been carried out in a sequential manner to identify primary protein targets (PPTs) of MBMs. This set of proteins will first interact with MBMs in the temporal order and play an important role in the mode of action of MBMs, especially when MBMs are at low concentrations. Herein, we describe a valuable observation that the result of the enrichment process is highly dependent on concentrations of the probe and the proteome. Interestingly, high concentrations of probe and low concentrations of incubated proteome will readily miss the hyper-reactive protein targets and thereby increase the probability of rendering PPTs with false-negative results, while low concentrations of probe and high concentrations of incubated proteome more than likely will capture the PPTs. Based on this enlightening observation, we developed a proof-of-concept approach to identify the PPTs of iodoacetamide, a thiol-reactive MBM. This study will deepen our understanding of the enrichment process and improve the accuracy of pull-down-guided target identification.

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Epigenetic mechanisms leading to transcriptional regulation, including DNA methylation, are frequently dysregulated in diverse cancers. Interfering with aberrant DNA methylation performed by DNA cytosine methyltransferases (DNMTs) is a clinically validated approach. In particular, the selective inhibition of the de novo DNMT3A and DNMT3B enzymes, whose expression is limited to early embryogenesis, adult stem cells, and in cancers, is particularly attractive; such selectivity is likely to attenuate the dose limiting toxicity shown by current, non-selective DNMT inhibitors. We use molecular dynamics (MD) based computational analysis to study known small molecule binders of DNMT3A, then propose reversible, tight binding, and selective inhibitors that exploit the Asn1192/Arg688 difference between the maintenance DNMT1 and DNMT3A near the active site. A similar strategy exploiting the presence of a unique active site cysteine Cys666 is used to propose DNMT3A-selective irreversible inhibitors. We report our results of relative binding energies of the known and proposed compounds estimated using MM/GBSA and umbrella sampling (US) techniques, and our evaluation of other end-point binding free energy calculation methods for these receptors. These calculations offer insight into the potential for small molecules to selectively target the active site of DNMT3A.

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