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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. [ABSTRACT FROM AUTHOR]

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. Workflow employed for phytochemical assays, mass spectrometry-based metabolomics, protein-target identification, cell culture validations, and docking studies. Comparison of Bacopa monnieri and Centella asiatica non-redundant metabolite identification at MS level,as well as at MS/MS level [ABSTRACT FROM AUTHOR]

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 β-sheets appeared in A2780 cells after RuCN treatment. Treatment with RuCN/N-CDs caused a substantial increase in parallel β-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 β-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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) is a toxic metal for the human organism and for all ecosystems. Cd is naturally found at low levels; however, higher amounts of Cd in the environment result from human activities as it spreads into the air and water in the form of micropollutants as a consequence of industrial processes, pollution, waste incineration, and electronic waste recycling. The human body has a limited ability to respond to Cd exposure since the metal does not undergo metabolic degradation into less toxic species and is only poorly excreted. The extremely long biological half-life of Cd essentially makes it a cumulative toxin; chronic exposure causes harmful effects from the metal stored in the organs. The present paper considers exposure and potential health concerns due to environmental cadmium. Exposure to Cd compounds is primarily associated with an elevated risk of lung, kidney, prostate, and pancreatic cancer. Cd has also been linked to cancers of the breast, urinary system, and bladder. The multiple mechanisms of Cd-induced carcinogenesis include oxidative stress with the inhibition of antioxidant enzymes, the promotion of lipid peroxidation, and interference with DNA repair systems. Cd2+ can also replace essential metal ions, including redox-active ones. A total of 12 cancer types associated with specific genes coding for the Cd-metalloproteome were identified in this work. In addition, we summarize the proper treatments of Cd poisoning, based on the use of selected Cd detoxifying agents and chelators, and the potential for preventive approaches to counteract its chronic exposure. [ABSTRACT FROM AUTHOR]

Objective: Based on the tandem mass tag (TMT) technique, our study investigated the potential therapeutic targets of Liraglutide (LIRA) on streptozotocin (STZ) induced impaired glucose tolerance (IGT) in rats and discuss the biological mechanism of the drug against IGT. Methods: 10 rats were randomly selected from 31 male wistar rats of specific pathogen free (SPF) grade as control group and fed with conventional chow, offered the remaining rats a high fat and high sugar (HFSD) diet combined with an intraperitoneal injection of STZ to establish the IGT model, and excluded 2 non-model rats. Specifically, the model rats were randomly divided into Model group (n=10) and LIRA group (n=9). In addition, the LIRA group was subcutaneously injected with 0.06 mg/kg LIRA, during which the metabolic parameters including body weight and fasting blood glucose were recorded. After 8 weeks, samples were taken under anesthesia. Then, the cell morphology was observed using HE staining, and immunofluorescence was performed on the pancreatic tissues of the three groups of rats. Besides, the expression of differential proteins in pancreatic tissues of the three groups of rats was determined by the TMT proteomic labeling. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological function analysis were performed on the intersection of Model and LIRA differential proteins. Results: LIRA could not only significantly reduce blood glucose levels but also improve islet cell morphology and function in IGT rats. Among the differential proteins between the model group and the blank group, 44 were reversed after LIRA treatment, of which 14 were up-regulated, while 30 were downregulated, including PPIF, MPRIP, CYP51, TXNL1, BCL-2, etc. (FC>1.1or<0.909, P<0.05). According to the GO and KEGG analysis results, it was related to biological processes such as fatty acid metabolism and adipocyte generation, which involved multiple signaling pathways regulating the function of islet cells, such as MAPK, PI, Ras, FcgR, and unsaturated fatty acids, and pyruvate metabolism. Conclusion: To sum up, LIRA participated in anti-IGT therapy through regulation of multiple target proteins and biological functions. This study is of great reference for further exploring the mechanism of action of LIRA at the protein level of IGT. [ABSTRACT FROM AUTHOR]

A recently synthesized new eugenol derivative, ethyl 4-(2-methoxy-4-(oxiran-2-ylmethyl)phenoxy)butanoate, with a high insecticidal activity against Sf9 (Spodoptera frugiperda) insect cells, was encapsulated in the liposomal formulations of egg-phosphatidylcholine/cholesterol (Egg-PC:Ch) 70:30 and 100% dioleoylphosphatidylglycerol (DOPG), aiming at the future application as insecticides. Compound-loaded DOPG liposomes have sizes of 274 ± 12 nm, while Egg-PC:Ch liposomes exhibit smaller hydrodynamic diameters (69.5 ± 7 nm), high encapsulation efficiency (88.8 ± 2.7%), higher stability, and a more efficient compound release, thus, they were chosen for assays in Sf9 insect cells. The compound elicited a loss of cell viability up to 80% after 72 h of incubation. Relevantly, nanoencapsulation maintained the toxicity of the compound toward insect cells while lowering the toxicity toward human cells, thus showing the selectivity of the system. Structure-based inverted virtual screening was used to predict the most likely targets and molecular dynamics simulations and free energy calculations were used to demonstrate that this molecule can form a stable complex with insect odorant binding proteins and/or acetylcholinesterase. The results are promising for the future application of compound-loaded nanoliposome formulations as crop insecticides. [ABSTRACT FROM AUTHOR]

The unprecedented outbreak of the severe acute respiratory syndrome (SARS) Coronavirus-2, across the globe, triggered a worldwide uproar in the search for immediate treatment strategies. With no specific drug and not much data available, alternative approaches such as drug repurposing came to the limelight. To date, extensive research on the repositioning of drugs has led to the identification of numerous drugs against various important protein targets of the coronavirus strains, with hopes of the drugs working against the major variants of concerns (alpha, beta, gamma, delta, omicron) of the virus. Advancements in computational sciences have led to improved scope of repurposing via techniques such as structure-based approaches including molecular docking, molecular dynamic simulations and quantitative structure activity relationships, network-based approaches, and artificial intelligence-based approaches with other core machine and deep learning algorithms. This review highlights the various approaches to repurposing drugs from a computational biological perspective, with various mechanisms of action of the drugs against some of the major protein targets of SARS-CoV-2. Additionally, clinical trials data on potential COVID-19 repurposed drugs are also highlighted with stress on the major SARS-CoV-2 targets and the structural effect of variants on these targets. The interaction modelling of some important repurposed drugs has also been elucidated. Furthermore, the merits and demerits of drug repurposing are also discussed, with a focus on the scope and applications of the latest advancements in repurposing. [ABSTRACT FROM AUTHOR]

Colorectal cancer is one of the most prevalent cancer types. Although there have been breakthroughs in its treatments, a better understanding of the molecular mechanisms and genetic involvement in colorectal cancer will have a substantial role in producing novel and targeted treatments with better safety profiles. In this review, the main molecular pathways and driver genes that are responsible for initiating and propagating the cascade of signaling molecules reaching carcinoma and the aggressive metastatic stages of colorectal cancer were presented. Protein kinases involved in colorectal cancer, as much as other cancers, have seen much focus and committed efforts due to their crucial role in subsidizing, inhibiting, or changing the disease course. Moreover, notable improvements in colorectal cancer treatments with in silico studies and the enhanced selectivity on specific macromolecular targets were discussed. Besides, the selective multi-target agents have been made easier by employing in silico methods in molecular de novo synthesis or target identification and drug repurposing. [ABSTRACT FROM AUTHOR]

Herbicides are commonly deployed as the front-line treatment to control infestations of weeds in native ecosystems and among crop plants in agriculture. However, the prevalence of herbicide resistance in many species is a major global challenge. The specificity and effectiveness of herbicides acting on diverse weed species are tightly linked to targeted proteins. The conservation and variance at these sites among different weed species remain largely unexplored. Using novel genome data in a genome-guided approach, 12 common herbicide-target genes and their coded proteins were identified from seven species of Weeds of National Significance in Australia: Alternanthera philoxeroides (alligator weed), Lycium ferocissimum (African boxthorn), Senecio madagascariensis (fireweed), Lantana camara (lantana), Parthenium hysterophorus (parthenium), Cryptostegia grandiflora (rubber vine), and Eichhornia crassipes (water hyacinth). Gene and protein sequences targeted by the acetolactate synthase (ALS) inhibitors and glyphosate were recovered. Compared to structurally resolved homologous proteins as reference, high sequence conservation was observed at the herbicide-target sites in the ALS (target for ALS inhibitors), and in 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase (target for glyphosate). Although the sequences are largely conserved in the seven phylogenetically diverse species, mutations observed in the ALS proteins of fireweed and parthenium suggest resistance of these weeds to ALS-inhibiting and other herbicides. These protein sites remain as attractive targets for the development of novel inhibitors and herbicides. This notion is reinforced by the results from the phylogenetic analysis of the 12 proteins, which reveal a largely consistent vertical inheritance in their evolutionary histories. These results demonstrate the utility of high-throughput genome sequencing to rapidly identify and characterize gene targets by computational methods, bypassing the experimental characterization of individual genes. Data generated from this study provide a useful reference for future investigations in herbicide discovery and development. [ABSTRACT FROM AUTHOR]

Herbicides are commonly deployed as the front-line treatment to control infestations of weeds in native ecosystems and among crop plants in agriculture. However, the prevalence of herbicide resistance in many species is a major global challenge. The specificity and effectiveness of herbicides acting on diverse weed species are tightly linked to targeted proteins. The conservation and variance at these sites among different weed species remain largely unexplored. Using novel genome data in a genome-guided approach, 12 common herbicide-target genes and their coded proteins were identified from seven species of Weeds of National Significance in Australia: Alternanthera philoxeroides (alligator weed), Lycium ferocissimum (African boxthorn), Senecio madagascariensis (fireweed), Lantana camara (lantana), Parthenium hysterophorus (parthenium), Cryptostegia grandiflora (rubber vine), and Eichhornia crassipes (water hyacinth). Gene and protein sequences targeted by the acetolactate synthase (ALS) inhibitors and glyphosate were recovered. Compared to structurally resolved homologous proteins as reference, high sequence conservation was observed at the herbicide-target sites in the ALS (target for ALS inhibitors), and in 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase (target for glyphosate). Although the sequences are largely conserved in the seven phylogenetically diverse species, mutations observed in the ALS proteins of fireweed and parthenium suggest resistance of these weeds to ALS-inhibiting and other herbicides. These protein sites remain as attractive targets for the development of novel inhibitors and herbicides. This notion is reinforced by the results from the phylogenetic analysis of the 12 proteins, which reveal a largely consistent vertical inheritance in their evolutionary histories. These results demonstrate the utility of high-throughput genome sequencing to rapidly identify and characterize gene targets by computational methods, bypassing the experimental characterization of individual genes. Data generated from this study provide a useful reference for future investigations in herbicide discovery and development.

Recent years have seen the rise of allosteric modulation as an innovative approach for drug design and discovery, efforts which culminated in the development of several clinical candidates. Allosteric modulation of many drug targets, including mainly membrane-embedded receptors, have been vastly explored through small molecule screening campaigns, but much less attention has been paid to peptide-based allosteric modulators. However, peptides have a significant impact on the pharmaceutical industry due to the typically higher potency and selectivity for their targets, as compared with small molecule therapeutics. Therefore, peptides represent one of the most promising classes of molecules that can modulate key biological pathways. Here, we report on the allosteric modulation of proteins (ranging from G protein-coupled receptors to specific protein–protein interactions) by peptides for applications in drug discovery. Allosteric modulators represent an innovative class of drugs, potentially offering higher target/functional selectivity, fewer adverse on- and off-target effects, and lower toxicity in comparison to orthosteric ligands. In contrast to the more represented small-molecule allosteric modulators, peptide-based ones possess the key advantage of displaying an enhanced intrinsic selectivity profile due to a potentially larger contact surface area, as well as a structural and chiral complexity. Peptides are promising drug candidates for targeting 'undruggable' protein sites and protein–protein interactions in which large contact surfaces are needed. Despite intensive interest in allostery for drug development, the identification of relevant allosteric sites and the elucidation of the mechanism of action remain challenging. [ABSTRACT FROM AUTHOR]

Background: Virgin coconut oil (VCO) has antioxidant properties and is being increasingly used as nutraceuticals and cosmeceuticals. It also has a long history of ethnopharmacological use. Anticancer effect of VCO has been reported in several articles. The main bottleneck of exploring the anticancer efficacy of VCO is the difficulty in identification and validation of target proteins and their regulated pathways. Aim: The work plan was in-silico analysis using Comparative Toxicogenomics Database (CTD) and STRING. CTD curated and integrated data for more than 5700 gene-disease and 2000 chemical-disease relationship. Medium Chain Fatty Acids (MCFAs) from VCO like Lauric acid, Caprylic Acid, Capric Acid, and Myristic acid can target almost 17 cancer-associated proteins. Method: Using in silico and in vitro approach, an attempt was made to identify the target proteins and their pathways regulated by VCO. Result: We analyze curated and inferred VCO-gene expression data and illustrate the impact of VCO exposure on cancer-related gene network and molecular function. In enriched pathway analysis, it has been evident that all of them are the part of different cancer-associated pathways (Neoplasms, Digestive System Neoplasms, Urogenital Neoplasms, Liver Neoplasms). This response may mimic the biological response to VCO. In silico result was tested by in vitro study and VCO kill the Human hepatocellular carcinoma cell lines (hepG2). Conclusion: Based on the findings of this study and several published studies it is proposed that a VCO may have immense potential as a botanical product against cancer.

Bioscientists reading papers or patents strive to discern the key relationships reported within a document “D“ where a bioactivity “A” with a quantitative result “R” (e.g., an IC50) is reported for chemical structure “C” that modulates (e.g., inhibits) a protein target “P”. A useful shorthand for this connectivity thus becomes DARCP. The problem at the core of this article is that the community has spent millions effectively burying these relationships in PDFs over many decades but must now spend millions more trying to get them back out. The key imperative for this is to increase the flow into structured open databases. The positive impacts will include expanded data mining opportunities for drug discovery and chemical biology. Over the last decade commercial sources have manually extracted DARCP from ≈300,000 documents encompassing ≈7 million compounds interacting with ≈10,000 targets. Over a similar time, the Guide to Pharmacology, BindingDB and ChEMBL have carried out analogues DARCP extractions. Although their expert-curated numbers are lower (i.e., ≈2 million compounds against ≈3700 human proteins), these open sources have the great advantage of being merged within PubChem. Parallel efforts have focused on the extraction of document-to-compound (D-C-only) connectivity. In the absence of molecular mechanism of action (mmoa) annotation, this is of less value but can be automatically extracted. This has been significantly accomplished for patents, (e.g., by IBM, SureChEMBL and WIPO) for over 30 million compounds in PubChem. These have recently been joined by 1.4 million D-C submissions from three major chemistry publishers. In addition, both the European and US PubMed Central portals now add chemistry look-ups from abstracts and full-text papers. However, the fully automated extraction of DARCLP has not yet been achieved. This stands in contrast to the ability of biocurators to discern these relationships in minutes. Unfortunately, no journals have yet instigated a flow of author-specified DARCP directly into open databases. Progress may come from trends such as open science, open access (OA), findable, accessible, interoperable and reusable (FAIR), resource description framework (RDF) and WikiData. However, we will need to await the technical applicability in respect to DARCP capture to see if this opens up connectivity.

Biologically active proteins/regions without stable structure (i.e., intrinsically disordered proteins and regions (IDPs and IDRs)) are commonly found in all proteomes. They have a unique functional repertoire that complements the functionalities of ordered proteins and domains. IDPs/IDRs are multifunctional promiscuous binders capable of folding at interaction with specific binding partners on a template- or context-dependent manner, many of which undergo liquid-liquid phase separation, leading to the formation of membrane-less organelles and biomolecular condensates. Many of them are frequently related to the pathogenesis of various human diseases. All this defines IDPs/IDRs as attractive targets for the development of novel drugs. However, their lack of unique structures, multifunctionality, binding promiscuity, and involvement in unusual modes of action preclude direct use of traditional structure-based drug design approaches for targeting IDPs/IDRs, and make disorder-based drug discovery for these "protein clouds" challenging. Despite all these complexities there is continuing progress in the design of small molecules affecting IDPs/IDRs. This article describes the major structural features of IDPs/IDRs and the peculiarities of the disorder-based functionality. It also discusses the roles of IDPs/IDRs in various pathologies, and shows why the approaches elaborated for finding drugs targeting ordered proteins cannot be directly used for the intrinsic disorder-based drug design, and introduces some novel methodologies suitable for these purposes. Finally, it emphasizes that regardless of their multifunctionality, binding promiscuity, lack of unique structures, and highly dynamic nature, "protein clouds" are principally druggable. Significance Statement Intrinsically disordered proteins and regions are highly abundant in nature, have multiple important biological functions, are commonly involved in the pathogenesis of a multitude of human diseases, and are therefore considered as very attractive drug targets. Although dealing with these unstructured multifunctional protein/regions is a challenging task, multiple innovative approaches have been designed to target them by small molecules., (Copyright © 2024 American Society for Pharmacology and Experimental Therapeutics.)

Endometriosis is defined as endometrial tissues found outside the uterine cavity. ProEGCG is a prodrug of Epigallocatechin gallate (EGCG), a potent polyphenol found in green tea. It inhibits the development of endometriotic lesions of mouse model in vivo, with higher efficacy and more remarkable anti-oxidative ability than EGCG. Our study aims to identify the molecular binding targets and pharmacological actions of ProEGCG in treating endometriosis. Protein target interaction study is essential to fully characterize the mechanism of actions, related therapeutic effects, and side effects. We employed a combined approach, starting with an in silico reverse screening of protein targets and molecular docking, followed by in vitro cellular thermal shift assay (CESTA) to assess the stability of protein-small molecule complexes. Then microarray and immunostaining of endometriotic lesions in mice in vivo confirmed the molecular interaction of the selected targets after treatment. Our study identified enzymes nicotinamide nucleotide adenylyltransferase (NMNAT)1 and NMNAT3 as protein targets of ProEGCG in silico and in vitro and were overexpressed after ProEGCG treatment in vivo. These findings suggested that participation in nicotinate and nicotinamide metabolism potentially regulated the redox status of endometriosis via its antioxidative capacities through binding to the potential therapeutic targets of ProEGCG.

Endometriosis is defined as endometrial tissues found outside the uterine cavity. ProEGCG is a prodrug of Epigallocatechin gallate (EGCG), a potent polyphenol found in green tea. It inhibits the development of endometriotic lesions of mouse model in vivo , with higher efficacy and more remarkable anti-oxidative ability than EGCG. Our study aims to identify the molecular binding targets and pharmacological actions of ProEGCG in treating endometriosis. Protein target interaction study is essential to fully characterize the mechanism of actions, related therapeutic effects, and side effects. We employed a combined approach, starting with an in silico reverse screening of protein targets and molecular docking, followed by in vitro cellular thermal shift assay (CESTA) to assess the stability of protein-small molecule complexes. Then microarray and immunostaining of endometriotic lesions in mice in vivo confirmed the molecular interaction of the selected targets after treatment. Our study identified enzymes nicotinamide nucleotide adenylyltransferase (NMNAT)1 and NMNAT3 as protein targets of ProEGCG in silico and in vitro and were overexpressed after ProEGCG treatment in vivo. These findings suggested that participation in nicotinate and nicotinamide metabolism potentially regulated the redox status of endometriosis via its antioxidative capacities through binding to the potential therapeutic targets of ProEGCG. [ABSTRACT FROM AUTHOR]

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 (K D), 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. [Display omitted] • The latest advances in aptamer-based biosensors for detecting protein in body fluids are summarized. • The characteristics and construction strategies of aptasensors for fluid biopsy are systematically described. • A comprehensive view on the aptasensor techniques for proteindetection in body fluids would be provided. [ABSTRACT FROM AUTHOR]

Background Xingnaojing injections (XNJI) are widely used in Chinese medicine to mitigate brain injuries. An increasing number of studies have shown that XNJI may improve neurological function. However, XNJI’s active ingredients and molecular mechanisms when treating traumatic brain injury (TBI) are unknown. Methods XNJI’s chemical composition was acquisited from literature and the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. We used the “absorption, distribution, metabolism, and excretion” (ADME) parameter-based virtual algorithm to further identify the bioactive components. We then screened data and obtained target information regarding TBI and treatment compounds from public databases. Using a Venn diagram, we intersected the information to determine the hub targets. Cytoscape was used to construct and visualize the network. In accordance with the hub proteins, we then created a protein–protein interaction (PPI) network using STRING 11.0. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed according to the DAVID bioinformatics resource database (ver. 6.8). We validated the predicted compound’s efficacy using the experimental rat chronic constriction injury (CCI) model. The neuronal apoptosis was located using the TUNEL assay and the related pathways’ hub proteins were determined by PCR, Western blot, and immunohistochemical staining. Results We identified 173 targets and 35 potential compounds belonging to XNJI. STRING analysis was used to illustrate the protein–protein interactions and show that muscone played a fundamental role in XNJI’s efficacy. Enrichment analysis revealed critical signaling pathways in these components’ potential protein targets, including PI3K/AKT1, NF-kB, and p53. Moreover, the hub proteins CASP3, BCL2L1, and CASP8 were also involved in apoptosis and were associated with PI3K/AKT, NF-kB, and p53 signaling pathways. We showed that muscone and XNJI were similarly effective 168 h after CCI, demonstrating that the muscone in XNJI significantly attenuated neuronal apoptosis through the PI3K/Akt1/NF-kB/P53 pathway. Conclusion We verified the neuroprotective mechanism in muscone for the first time in TBI. Network pharmacology offers a new approach for identifying the potential active ingredients in XNJI.

Vitiligo is a chronic asymptomatic disorder affecting melanocytes from the basal layer of the epidermis which leads to a patchy loss of skin color. Even though it is one of the neglected disease conditions, people suffering from vitiligo are more prone to psychological disorders. As of now, various studies have been done in order to project auto-immune implications as the root cause. To understand the complexity of vitiligo, we propose the Vitiligo Information Resource (VIRdb) that integrates both the drug-target and systems approach to produce a comprehensive repository entirely devoted to vitiligo, along with curated information at both protein level and gene level along with potential therapeutics leads. These 25,041 natural compounds are curated from Natural Product Activity and Species Source Database. VIRdb is an attempt to accelerate the drug discovery process and laboratory trials for vitiligo through the computationally derived potential drugs. It is an exhaustive resource consisting of 129 differentially expressed genes, which are validated through gene ontology and pathway enrichment analysis. We also report 22 genes through enrichment analysis which are involved in the regulation of epithelial cell differentiation. At the protein level, 40 curated protein target molecules along with their natural hits that are derived through virtual screening. We also demonstrate the utility of the VIRdb by exploring the Protein–Protein Interaction Network and Gene–Gene Interaction Network of the target proteins and differentially expressed genes. For maintaining the quality and standard of the data in the VIRdb, the gold standard in bioinformatics toolkits like Cytoscape, Schrödinger’s GLIDE, along with the server installation of MATLAB, are used for generating results. VIRdb can be accessed through “http://www.vitiligoinfores.com/”.

At the turn of the 21st century, aptamers selected in vitro have secured their place in the mainstream study of nucleic acids and are commonly evolved via a process termed SELEX. While new sequences can be isolated from SELEX in as little as a 14-day time period, characterizing putative aptamer sequences poses a greater challenge and often goes unreported in the literature. Rigorous characterization and validation of individual sequences are required for reliable reporting of aptamer sequences with high affinity and specificity to their targets. Here, we present a protocol for the use of fluorescence anisotropy to characterize aptamers towards protein targets. This protocol also serves as an introduction for new aptamer researchers, in particular students, who wish to understand and perform aptamer binding experiments. [ABSTRACT FROM AUTHOR]

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Vitiligo is a chronic asymptomatic disorder affecting melanocytes from the basal layer of the epidermis which leads to a patchy loss of skin color. Even though it is one of the neglected disease conditions, people suffering from vitiligo are more prone to psychological disorders. As of now, various studies have been done in order to project auto-immune implications as the root cause. To understand the complexity of vitiligo, we propose the Vitiligo Information Resource (VIRdb) that integrates both the drug-target and systems approach to produce a comprehensive repository entirely devoted to vitiligo, along with curated information at both protein level and gene level along with potential therapeutics leads. These 25,041 natural compounds are curated from Natural Product Activity and Species Source Database. VIRdb is an attempt to accelerate the drug discovery process and laboratory trials for vitiligo through the computationally derived potential drugs. It is an exhaustive resource consisting of 129 differentially expressed genes, which are validated through gene ontology and pathway enrichment analysis. We also report 22 genes through enrichment analysis which are involved in the regulation of epithelial cell differentiation. At the protein level, 40 curated protein target molecules along with their natural hits that are derived through virtual screening. We also demonstrate the utility of the VIRdb by exploring the Protein–Protein Interaction Network and Gene–Gene Interaction Network of the target proteins and differentially expressed genes. For maintaining the quality and standard of the data in the VIRdb, the gold standard in bioinformatics toolkits like Cytoscape, Schrödinger’s GLIDE, along with the server installation of MATLAB, are used for generating results. VIRdb can be accessed through “http://www.vitiligoinfores.com/”. [ABSTRACT FROM AUTHOR]

Most crop plants are exposed to intermittent drought periods. To cope with these continuous changes, plants need strategies to prevent themselves from exhaustive adjustment maneuvers. Drought stress recovery has been shown to be an active process, possibly involved in a drought memory effect allowing plants to better cope with recurrent aridity. An integrated understanding of the molecular processes of enhanced drought tolerance is required to tailor key networks for improved crop protection. During summer, prolonged periods of drought are the major reason for economic yield losses of sugar beet (Beta vulgaris) in Europe. A drought stress and recovery time course experiment was carried out under controlled environmental conditions. In order to find regulatory key mechanisms enabling plants to rapidly react to periodic stress events, beets were either subjected to 11 days of progressive drought, or were drought stressed for 9 days followed by gradual rewatering for 14 days. Based on physiological measurements of leaf water relations and changes in different stress indicators, plants experienced a switch from moderate to severe water stress between day 9 and 11 of drought. The leaf proteome was analyzed, revealing induced protein pre-adjustment (prior to severe stress) and putative stress endurance processes. Three key protein targets, regulatory relevant during drought stress and with lingering levels of abundance upon rewatering were further exploited through their transcript performance. These three targets consist of a jasmonate induced, a salt-stress enhanced and a phosphatidylethanolamine-binding protein. The data demonstrate delayed protein responses to stress compared to their transcripts and indicate that the lingering mechanism is post-transcriptionally regulated. A set of lingering proteins is discussed with respect to a possible involvement in drought stress acclimation and memory effects.

Most crop plants are exposed to intermittent drought periods. To cope with these continuous changes, plants need strategies to prevent themselves from exhaustive adjustment maneuvers. Drought stress recovery has been shown to be an active process, possibly involved in a drought memory effect allowing plants to better cope with recurrent aridity. An integrated understanding of the molecular processes of enhanced drought tolerance is required to tailor key networks for improved crop protection. During summer, prolonged periods of drought are the major reason for economic yield losses of sugar beet (Beta vulgaris) in Europe. A drought stress and recovery time course experiment was carried out under controlled environmental conditions. In order to find regulatory key mechanisms enabling plants to rapidly react to periodic stress events, beets were either subjected to 11 days of progressive drought, or were drought stressed for 9 days followed by gradual rewatering for 14 days. Based on physiological measurements of leaf water relations and changes in different stress indicators, plants experienced a switch from moderate to severe water stress between day 9 and 11 of drought. The leaf proteome was analyzed, revealing induced protein pre-adjustment (prior to severe stress) and putative stress endurance processes. Three key protein targets, regulatory relevant during drought stress and with lingering levels of abundance upon rewatering were further exploited through their transcript performance. These three targets consist of a jasmonate induced, a salt-stress enhanced and a phosphatidylethanolamine-binding protein. The data demonstrate delayed protein responses to stress compared to their transcripts and indicate that the lingering mechanism is post-transcriptionally regulated. A set of lingering proteins is discussed with respect to a possible involvement in drought stress acclimation and memory effects. [ABSTRACT FROM AUTHOR]

Resveratrol (3, 4′, 5-trihydroxy-trans-stilbene) is a natural phytoalexin found in grapes and has long been thought to be the answer to the “French Paradox.” There is no shortage of preclinical and clinical studies investigating the broad therapeutic activity of resveratrol. However, in spite of many comprehensive reviews published on the bioactivity of resveratrol, there has yet to be a report focused on the variety and complexity of its structural binding properties, and its multi-targeted role. An improved understanding of disease mechanisms at the systems level has enabled targeted polypharmacology to mature into a rational drug discovery approach. Unlike traditional hit-to-lead campaigns that typically optimize activity and selectivity for a single target, polypharmacological drugs aim to selectively target multiple proteins, while avoiding critical off target interactions. This strategy bears promise of improved efficacy and reduced clinical attrition. This review seeks to investigate whether the bioactivity of resveratrol is due to a polypharmacological effect or promiscuity of the phenolic small molecule by examining the modes of binding with its diverse collection of protein targets. We focused on annotated targets, identified via the ChEMBL database, and matched these targets to a representative structure deposited in the Protein Data Bank (PDB), as crystal structures are most informative in understanding modes of binding at the atomic level. We discuss the structural aspects of resveratrol itself that permits binding to multiple proteins in various signaling pathways. Furthermore, we suggest that resveratrol’s bioactivity is a result of scaffold promiscuity rather than polypharmacology, and the variety of binding modes across targets display little similarity in the pattern of target interaction.

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., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Abstract The objective of drug repositioning is to apply existing drugs to different diseases or medical conditions than the original target, and thus alleviate to a certain extent the time and cost expended in drug development. Our system RESKO, RE positioning drugs using S ide Effects and K nowledge from O ntologies, identifies drugs with similar side-effects which are potential candidates for use elsewhere, the supposition is that similar side-effects may be caused by drugs targeting similar proteins and pathways. RESKO, integrates drug chemical data, protein interaction and ontological knowledge. The novel aspects of our system include a high level of biological knowledge through the use of pathway and biological ontology integration. This provides a explanation facility lacking in most of the existing methods and improves the repositioning process. We evaluate the shared side effects from the eight conventional Alzheimer drugs, from which sixty-seven candidate drugs based on a side-effect commonality were identified. The top 25 drugs on the list were further investigated in depth for their suitability to be repositioned, the literature revealed that many of the candidate drugs appear to have been trialed for Alzheimer’s disease. Thus verifying the accuracy of our system, we also compare our technique with several competing systems found in the literature. [ABSTRACT FROM AUTHOR]

Effective compounds isolated from Chinese herbs play an important role in the development of new candidate drugs, which can be widely used in the treatment of various diseases. Previous literature has revealed that Stellera chamaejasme L. possesses the activity of inhibiting liver cancer cells. Nevertheless, the interactions between active compounds isolated from this herb and targets related to liver cancer are still not very clear. In this study, we applied network pharmacology-based analysis to figure out these relationships. And eight compounds were predicted to have the most significant activity against liver cancer. At the same time, the binding modes between the top eight candidate compounds and the protein target Glutamine synthetase which is likely to be the most important target associated with liver cancer were identified. It is believed that the study can provide a reference for the discovery of new drug molecules. [ABSTRACT FROM AUTHOR]

Resveratrol (3, 4′, 5-trihydroxy-trans-stilbene) is a natural phytoalexin found in grapes and has long been thought to be the answer to the "French Paradox." There is no shortage of preclinical and clinical studies investigating the broad therapeutic activity of resveratrol. However, in spite of many comprehensive reviews published on the bioactivity of resveratrol, there has yet to be a report focused on the variety and complexity of its structural binding properties, and its multi-targeted role. An improved understanding of disease mechanisms at the systems level has enabled targeted polypharmacology to mature into a rational drug discovery approach. Unlike traditional hit-to-lead campaigns that typically optimize activity and selectivity for a single target, polypharmacological drugs aim to selectively target multiple proteins, while avoiding critical off target interactions. This strategy bears promise of improved efficacy and reduced clinical attrition. This review seeks to investigate whether the bioactivity of resveratrol is due to a polypharmacological effect or promiscuity of the phenolic small molecule by examining the modes of binding with its diverse collection of protein targets. We focused on annotated targets, identified via the ChEMBL database, and matched these targets to a representative structure deposited in the Protein Data Bank (PDB), as crystal structures are most informative in understanding modes of binding at the atomic level. We discuss the structural aspects of resveratrol itself that permits binding to multiple proteins in various signaling pathways. Furthermore, we suggest that resveratrol's bioactivity is a result of scaffold promiscuity rather than polypharmacology, and the variety of binding modes across targets display little similarity in the pattern of target interaction. [ABSTRACT FROM AUTHOR]

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. • Emphasized on potential targets and inhibitors of cell wall biosynthesis, nucleic acid metabolism and efflux pumps in Mtb • Described the individual pathways for the discovery of novel candidates that could potentially target the Mtb growth • Revealed the affinity and specificity of peptide inhibitors towards functional targets of Mtb • Elaborated the advantages & challenges in the novel anti-TB drug drug discovery processses [ABSTRACT FROM AUTHOR]

Estimation of interactions between drug-like compounds and drug targets is very important for drug discovery and toxicity assessment. Using data extracted from the 19th version of the ChEMBL database (https://www.ebi.ac.uk/chembl) as a training set and a Bayesian-like method realized in PASS software (http://www.way2drug.com/PASSOnline), we developed a computational tool for the prediction of interactions between protein targets and drug-like compounds. After training, PASS Targets became able to predict interactions of drug-like compounds with 2507 protein targets from different organisms based on analysis of structure–activity relationships for 589,107 different chemical compounds. The prediction accuracy, estimated as AUC ROC calculated by the leave-one-out cross-validation and 20-fold cross-validation procedures, was about 96%. Average AUC ROC value was about 90% for the external test set from approximately 700 known drugs interacting with 206 protein targets. [ABSTRACT FROM AUTHOR]