Leveraging binding pose metadynamics to optimise target fishing predictions for three diverse ligands and their true targets.

Computational target fishing plays an important role in target identification, particularly in drug discovery campaigns utilizing phenotypic screening. Numerous approaches exist to predict potential targets for a given ligand, but true targets may be inconsistently ranked. More advanced simulation methods may provide benefit in such cases by reranking these initial predictions. We evaluated the ability of binding pose metadynamics to improve the predicted rankings for three diverse ligands and their six true targets. Initial predictions using pharmacophore mapping showed no true targets ranked in the top 50 and two targets each ranked within the 50-100, 100-150, and 250-300 ranges respectively. Following binding pose metadynamics, ranking of true targets improved for four out of the six targets and included the highest ranked predictions overall, while rankings deteriorated for two targets. The revised rankings predicted two true targets ranked within the top 50, and one target each within the 50-100, 100-150, 150-200, and 200-250 ranges respectively. The findings of this study demonstrate that binding pose metadynamics may be of benefit in refining initial predictions from structure-based target fishing algorithms, thereby improving the efficiency of the target identification process in drug discovery efforts.

Equisetum arvense standardized dried extract hinders age-related osteosarcopenia.

Age-associated osteosarcopenia is an unresolved syndrome characterized by the concomitant loss of bone (osteopenia) and skeletal muscle (sarcopenia) tissues increasing falls, immobility, morbidity, and mortality. Unbalanced resorption of bone in the remodeling process and excessive protein breakdown, especially fast type II myosin heavy chain (MyHC-II) isoform and myofiber metabolic shift, are the leading causes of bone and muscle deterioration in the elderly, respectively. Equisetum arvense (EQ) is a plant traditionally recommended for many pathological conditions due to its anti-inflammatory properties. Thus, considering that a chronic low-grade inflammatory state predisposes to both osteoporosis and sarcopenia, we tested a standardized hydroalcoholic extract of EQ in in vitro models of muscle atrophy [C2C12 myotubes treated with proinflammatory cytokines (TNFα/IFNγ), excess glucocorticoids (dexamethasone), or the osteokine, receptor activator of nuclear factor kappa-B ligand (RANKL)] and osteoclastogenesis (RAW 264.7 cells treated with RANKL). We found that EQ counteracted myotube atrophy, blunting the activity of several pathways depending on the applied stimulus, and reduced osteoclast formation and activity. By in silico target fishing, IKKB-dependent nuclear factor kappa-B (NF-κB) inhibition emerges as a potential common mechanism underlying EQ's anti-atrophic effects. Consumption of EQ (500 mg/kg/day) by pre-geriatric C57BL/6 mice for 3 months translated into: i) maintenance of muscle mass and performance; ii) restrained myofiber oxidative shift; iii) slowed down age-related modifications in osteoporotic bone, significantly preserving trabecular connectivity density; iv) reduced muscle- and spleen-related inflammation. EQ can preserve muscle functionality and bone remodeling during aging, potentially valuable as a natural treatment for osteosarcopenia.

Prediction of compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy.

For understanding a chemical compound's mechanism of action and its side effects, as well as for drug discovery, it is crucial to predict its possible protein targets. This study examines 15 developed target-centric models (TCM) employing different molecular descriptions and machine learning algorithms. They were contrasted with 17 third-party models implemented as web tools (WTCM). In both sets of models, consensus strategies were implemented as potential improvement over individual predictions. The findings indicate that TCM reach f1-score values greater than 0.8. Comparing both approaches, the best TCM achieves values of 0.75, 0.61, 0.25 and 0.38 for true positive/negative rates (TPR, TNR) and false negative/positive rates (FNR, FPR); outperforming the best WTCM. Moreover, the consensus strategy proves to have the most relevant results in the top 20 % of target profiles. TCM consensus reach TPR and FNR values of 0.98 and 0; while on WTCM reach values of 0.75 and 0.24. The implemented computational tool with the TCM and their consensus strategy at: https://bioquimio.udla.edu.ec/tidentification01/ . Scientific Contribution: We compare and discuss the performances of 17 public compound-target interaction prediction models and 15 new constructions. We also explore a compound-target interaction prioritization strategy using a consensus approach, and we analyzed the challenging involved in interactions modeling.

Target fishing reveals PfPYK-1 and PfRab6 as potential targets of an antiplasmodial 4-anilino-2-trichloromethylquinazoline hit compound.

We present investigations about the mechanism of action of a previously reported 4-anilino-2-trichloromethylquinazoline antiplasmodial hit-compound (Hit A), which did not share a common mechanism of action with established commercial antimalarials and presented a stage-specific effect on the erythrocytic cycle of P. falciparum at 8 < t < 16 h. The target of Hit A was searched by immobilising the molecule on a solid support via a linker and performing affinity chromatography on a plasmodial lysate. Several anchoring positions of the linker (6,7 and 3') and PEG-type linkers were assessed, to obtain a linked-hit molecule displaying in vitro antiplasmodial activity similar to that of unmodified Hit A. This allowed us to identify the PfPYK-1 kinase and the PfRab6 GTP-ase as potential targets of Hit A.

Systems Pharmacology Strategy for the Investigation of Action Mechanisms of Qin Herb Libanotis Buchtormensis (Fisch.) DC. in Bone Diseases.

INTRODUCTION: Qin medicines are medicinal plants growing in habitat around the peak of Qinling Mountain. Their unique curative effects on bone metabolic diseases and pain diseases have been favoured by the local people in clinical trials for thousands of years. Libanotis buchtormensis (Fisch.) DC. (LBD), is one of the popular Qin herbs, which has been widely used for the treatment of various diseases, such as osteoporosis, rheumatic, and cardiovascular diseases. However, due to the multiple compounds in LBD, the underlying molecular mechanisms of LBD remain unclear. OBJECTIVE: This study aimed to systemically investigate the underlying mechanisms of LBD against bone diseases. METHODS: In this study, a systems pharmacology platform included the potential active compound screening, target fishing, and network pharmacological analysis was employed to decipher the action mechanisms of LBD. RESULTS: As a result, 12 potential active compounds and 108 targets were obtained. Furthermore, compound-target network and target-pathway network analysis showed that multi-components interacted with multi-targets and multi-pathways, i.e., MARK signalling pathway, mTORC1 signalling pathway, etc., involved in the regulation of the immune system and circulatory system. These results suggested the mechanisms of the therapeutic effects of LBD on various diseases through most compounds targeted by multiple targets. CONCLUSION: In conclusion, we successfully predicted the LBD bioactive compounds and potential targets, implying that LBD could be applied as a novel therapeutic herb in osteoporosis, rheumatic, and cardiovascular diseases. This work provides insight into the therapeutic mechanisms of LBD for treating various diseases.

Zuogui pill disrupt the malignant cycle in breast cancer bone metastasis through the Piezo1-Notch-1-GPX4 pathway and active molecules fishing.

BACKGROUND: Breast cancer bone metastasis is closely associated with the bone microenvironment. Zuogui Pill (ZGP), a clinically approved formulation in China, effectively regulates the bone microenvironment for the prevention and treatment of osteoporosis. PURPOSE: Few reports have utilized the ZGP for bone metastasis models. This study investigated the intervention and bone-protective properties of ZGP against breast cancer bone metastasis, explored the potential mechanism, and screened for its active compositions by molecules fishing. METHODS: To investigate the intervention efficacy of ZGP and its protein-level mechanism of action, the mouse bone metastasis model and in vitro cell co-culture model were constructed. Affinity ultrafiltration, molecular docking, cellular thermal shift assay and physical scale detection were used to investigate the affinity components of the RANKL protein in ZGP. RESULTS: The administration of ZGP combined with zoledronic acid inhibited the development of tumors and secondary lung metastasis in mice. This translated to a prolonged survival period and enhanced quality of life. ZGP could disrupt the malignant cycle by modulating the Piezo1-Notch-1-GPX4 signaling pathway in the "bone-cancer" communication in the cell co-culture model. Furthermore, 25 chemical components of ZGP were identified, with 10 active compounds exhibiting significant affinity for the RANKL protein. CONCLUSION: The findings of this work highlighted ZGP's potential for intervening in the progression of breast cancer bone metastasis. Thus, this investigation served as an experimental foundation for expanding the application scope of ZGP and for advancing drug development efforts in bone metastasis treatment.

An in silico insight on the mechanistic aspects of gelsenicine toxicity: A reverse screening study pointing to the possible involvement of acetylcholine binding receptor.

Gelsedine-type alkaloids are highly toxic plant secondary metabolites produced by shrubs belonging to the Gelsemium genus. Gelsenicine is one of the most concerning gelsedine-type alkaloids with a lethal dose lower than 1 mg/Kg in mice. Several reported episodes of poisoning in livestock and fatality cases in humans due to the usage of Gelsemium plants extracts were reported. Also, gelsedine-type alkaloids were found in honey constituting a potential food safety issue. However, their toxicological understanding is scarce and the molecular mechanism underpinning their toxicity needs further investigations. In this context, an in silico approach based on reverse screening, docking and molecular dynamics successfully identified a possible gelsenicine biological target shedding light on its toxicodynamics. In line with the available crystallographic data, it emerged gelsenicine could target the acetylcholine binding protein possibly acting as a partial agonist against α7 nicotinic acetylcholine receptor (AChR). Overall, these results agreed with evidence previously reported and prioritized AChR for further dedicated analysis.

In silico Strategy: A Promising Implement in the Development of Multitarget Drugs against Neurodegenerative Diseases.

Multi-target drug development (MTDD) is the demand of the recent era, especially in the case of multi-factorial conditions such as cancer, depression, neurodegenerative diseases (NDs), etc. The MTDD approaches have many advantages; avoidance of drug-drug interactions, predictable pharmacokinetic profile, and less drug resistance. The wet lab practice in MTDD is very challenging for the researchers, and the chances of late-stage failure are obvious. Identification of an appropriate target (Target fishing) is another challenging task in the development of multi-target drugs. The in silico tools will be one of the promising tools in the MTDD for the NDs. Therefore the outlook of the review comprises a short description of NDs, target associated with different NDs, in silico studies so far done for MTDD for various NDs. The main thrust of this review is to explore the present and future aspects of in silico tools used in MTDD for different NDs in combating the challenge of drug development and the application of various in silico tools to solve the problem of target fishing.

Unraveling the Potential Anti-Severe Acute Respiratory Syndrome Coronavirus 2 Mechanisms of Ginger by Computational Target Fishing.

Ginger (Zingiber officinale) is one of the most commonly consumed botanical foods. Owing to its anti-inflammatory and antiviral properties, ginger has been widely used as a homemade remedy during the corona virus disease 2019 (COVID-19) pandemic; however, the mechanisms of its therapeutic activities against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain obscure. In this study, we used a drug-likeness approach to screen the active compounds of ginger. Next, we identified candidate targets of active compounds responsible for the anti-SARS-CoV-2 effects of ginger using chemical similarity searching and SARS-CoV-2-human protein-protein interaction (PPI) data. Finally, we analyzed PPIs, Gene Ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment of the candidate proteins using different bioinformatics tools. A network comprising ginger compounds, human proteins, and SARS-CoV-2 proteins was built through Cytoscape 3.3. The results indicate that the anti-SARS-CoV-2 activity of ginger involves 20 active compounds, 18 potential human targets, and 12 SARS-CoV-2 proteins. These form a pharmacological network in which sigma nonopioid intracellular receptor 1 (SIGMAR1) and histone deacetylase 2 may be druggable hub proteins. In addition, molecular docking showed that 8-gingerdione and dihydrocapsaicin may preferentially interact with SIGMAR1, which was confirmed by further molecular dynamics simulation (150 ns) experiments. In conclusion, ginger targets multiple human proteins and affects multiple SARS-CoV-2 proteins to exert anti-COVID-19 effects. Although further experimental verification is needed, this study provides a quick visual overview of the anti-SARS-CoV-2 action of ginger.

Target fishing and molecular modeling of nitroheteroaylchalcones with potent antituberculosis activity / Target fishing e modelagem molecular de nitroheteroarilchalconas com potente atividade antituberculose

Computer-aided drug planning strategies have contributed to the research and development of new anti-tuberculosis (TB) drugs to avoid resistance and reduce treatment time and the number of drugs used in therapy. The aim of work was to carry out a docking study to identify the possible mechanism of action of the hits LabMol73, 84, 86 and 93 previously tested in the Microplate Assay Blue Alamar (MABA), Low Oxygen Recovery Assay (LORA) assays in sensitive strains from M.tb. H37Rv and resistant to the standard drugs rifampicin and isoniazid, due to the promising inhibitory result against these strains, suggesting a different mechanism of action from existing drugs. The reverse virtual screening was performed on the Pharmmapper platform, which identifies targets by pharmacophoric model. The most promising targets have been validated. The DM was performed in the OpenEye Maestro program for analysis of poses and energy score. Sixteen targets M.tb. H37Rv were identified and only nine demonstrated viability for computational testing. The most promising results were observed in the mycolic acid cyclopropane synthase (PDB:1L1E) and pantothenate synthetase (PDB:1N2B) targets. Since, in the target 1L1E score results obtained were between -6.998 to -7.767 kcal/mol. In the 1N2B target the results were between -6.421 to -7.293 kcal/mol, presenting themselves as the most promising targets due to their similar score scores between the two targets suggesting that the mechanism of action may be the inhibition of one of these targets. These targets proved to be promising for elucidating the mechanism of action of the analyzed nitro heteroaryl chalcones, as they corroborate the assay against resistant strains, demonstrating that standard drugs have activity against other targets and also because mycolic acid and pantothenate are directly linked to virulence and resistance of M.tb. H37Rv.

Computer-aided drug planning strategies have contributed to the research and development of new anti-tuberculosis (TB) drugs to avoid resistance and reduce treatment time and the number of drugs used in therapy. The aim of work was to carry out a docking study to identify the possible mechanism of action of the hits LabMol73, 84, 86 and 93 previously tested in the Microplate Assay Blue Alamar (MABA), Low Oxygen Recovery Assay (LORA) assays in sensitive strains from M.tb. H37Rv and resistant to the standard drugs rifampicin and isoniazid, due to the promising inhibitory result against these strains, suggesting a different mechanism of action from existing drugs. The reverse virtual screening was performed on the Pharmmapper platform, which identifies targets by pharmacophoric model. The most promising targets have been validated. The DM was performed in the OpenEye Maestro program for analysis of poses and energy score. Sixteen targets M.tb. H37Rv were identified and only nine demonstrated viability for computational testing. The most promising results were observed in the mycolic acid cyclopropane synthase (PDB:1L1E) and pantothenate synthetase (PDB:1N2B) targets. Since, in the target 1L1E score results obtained were between -6.998 to -7.767 kcal/mol. In the 1N2B target the results were between -6.421 to -7.293 kcal/mol, presenting themselves as the most promising targets due to their similar score scores between the two targets suggesting that the mechanism of action may be the inhibition of one of these targets. These targets proved to be promising for elucidating the mechanism of action of the analyzed nitro heteroaryl chalcones, as they corroborate the assay against resistant strains, demonstrating that standard drugs have activity against other targets and also because mycolic acid and pantothenate are directly linked to virulence and resistance of M.tb. H37Rv.

On the human health benefits of microalgal phytohormones: An explorative in silico analysis.

Phytohormones represent a group of secondary metabolites with different chemical structures, in which belong auxins, cytokinins, gibberellins, or brassinosteroids. In higher plants, they cover active roles in growth or defense function, while their potential benefits for human health protection were noted for some phytohormones and little explored for many others. In this study, we developed a target fishing strategy on fifty-three selected naturally occurring phytohormones covering different families towards proteins involved in key cellular functions related to human metabolism and health protection/disease. This in silico analysis strategy aims to screen the potential human health-driven bioactivity of more than fifty phytohormones through the analysis of their interactions with specific targets. From this analysis, twenty-eight human targets were recovered. Some targets e.g., the proteins mitochondrial glutamate dehydrogenase (GLUD1) or nerve growth factor (NGF) bound many phytohormones, highlighting their involvement in amino acid metabolism and/or in the maintenance or survival of neurons. Conversely, some phytohormones specifically interacted with some proteins, e.g., SPRY domain-containing SOCS box protein 2 (SPSB2) or Inosine-5'-monophosphate dehydrogenase 1 (IMPDH1), both involved in human immune response. They were then investigated with a molecular docking analysis approach. Our bioprospecting study indicated that many phytohormones may endow human health benefits, with potential functional role in multiple cellular processes including immune response and cell cycle progression.

Comprehensive assessment of nine target prediction web services: which should we choose for target fishing?

Identification of potential targets for known bioactive compounds and novel synthetic analogs is of considerable significance. In silico target fishing (TF) has become an alternative strategy because of the expensive and laborious wet-lab experiments, explosive growth of bioactivity data and rapid development of high-throughput technologies. However, these TF methods are based on different algorithms, molecular representations and training datasets, which may lead to different results when predicting the same query molecules. This can be confusing for practitioners in practical applications. Therefore, this study systematically evaluated nine popular ligand-based TF methods based on target and ligand-target pair statistical strategies, which will help practitioners make choices among multiple TF methods. The evaluation results showed that SwissTargetPrediction was the best method to produce the most reliable predictions while enriching more targets. High-recall similarity ensemble approach (SEA) was able to find real targets for more compounds compared with other TF methods. Therefore, SwissTargetPrediction and SEA can be considered as primary selection methods in future studies. In addition, the results showed that k = 5 was the optimal number of experimental candidate targets. Finally, a novel ensemble TF method based on consensus voting is proposed to improve the prediction performance. The precision of the ensemble TF method outperforms the individual TF method, indicating that the ensemble TF method can more effectively identify real targets within a given top-k threshold. The results of this study can be used as a reference to guide practitioners in selecting the most effective methods in computational drug discovery.

Artificial intelligence-driven identification of morin analogues acting as CaV1.2 channel blockers: Synthesis and biological evaluation.

Morin is a vasorelaxant flavonoid, whose activity is ascribable to CaV1.2 channel blockade that, however, is weak as compared to that of clinically used therapeutic agents. A conventional strategy to circumvent this drawback is to synthesize new derivatives differently decorated and, in this context, morin-derivatives able to interact with CaV1.2 channels were found by employing the potential of PLATO in target fishing and reverse screening. Three different derivatives (5a-c) were selected as promising tools, synthesized, and investigated in in vitro functional studies using rat aorta rings and rat tail artery myocytes. 5a-c were found more effective vasorelaxant agents than the naturally occurring parent compound and antagonized both electro- and pharmaco-mechanical coupling in an endothelium-independent manner. 5a, the series' most potent, reduced also Ca2+ mobilization from intracellular store sites. Furthermore, 5a≈5c > 5b inhibited Ba2+ current through CaV1.2 channels. However, compound 5a caused also a concentration-dependent inhibition of KCa1.1 channel currents.

[Progress of target determination and mechanism of bioactive components of traditional Chinese medicine].

The pharmacodynamic substances of traditional Chinese medicine(TCM) are the basis for the research of TCM and the development of innovative drugs. However, the lack of clarity of targets and molecular mechanisms is the bottleneck problem that restricts the research of pharmacodynamic substances of TCM. Bioactive components are the material basis of the efficacy of TCM, which exert activity by regulating the corresponding targets. Therefore, it is very important to identify the targets of the bioactive components to elucidate the pharmacological mechanism of TCM. Proteins are the most important drug targets, and study of the interaction between the proteins and bioactive components of TCM plays a key role in the development of pharmacological mechanism of TCM. In recent years, the main techniques for detecting the interaction between the bioactive components and proteins include surface plasmon resonance, fluorescence resonance energy transfer, bio-layer interference, molecular docking, proteome chip, target fishing, target mutant, and protein crystallization techniques, etc. This review summarized the biological target detection techniques and their applications in locating the targets of the bioactive components in TCM in the last decade, and this paper will provide useful strategies to elucidate the pharmacological mechanisms of TCM.

Seafood Paramyosins as Sources of Anti-Angiotensin-Converting-Enzyme and Anti-Dipeptidyl-Peptidase Peptides after Gastrointestinal Digestion: A Cheminformatic Investigation.

Paramyosins, muscle proteins occurring exclusively in invertebrates, are abundant in seafoods. The potential of seafood paramyosins (SP) as sources of anti-angiotensin-converting-enzyme (ACE) and anti-dipeptidyl-peptidase (DPP-IV) peptides is underexplored. This in silico study investigated the release of anti-ACE and anti-DPP-IV peptides from SP after gastrointestinal (GI) digestion. We focused on SP of the common octopus, Humboldt squid, Japanese abalone, Japanese scallop, Mediterranean mussel, Pacific oyster, sea cucumber, and Whiteleg shrimp. SP protein sequences were digested on BIOPEP-UWM, followed by identification of known anti-ACE and anti-DPP-IV peptides liberated. Upon screening for high-GI-absorption, non-allergenicity, and non-toxicity, shortlisted peptides were analyzed via molecular docking and dynamic to elucidate mechanisms of interactions with ACE and DPP-IV. Potential novel anti-ACE and anti-DPP-IV peptides were predicted by SwissTargetPrediction. Physicochemical and pharmacokinetics of peptides were predicted with SwissADME. GI digestion liberated 2853 fragments from SP. This comprised 26 known anti-ACE and 53 anti-DPP-IV peptides exhibiting high-GI-absorption, non-allergenicity, and non-toxicity. SwissTargetPrediction predicted three putative anti-ACE (GIL, DL, AK) and one putative anti-DPP-IV (IAL) peptides. Molecular docking found most of the anti-ACE peptides may be non-competitive inhibitors, whereas all anti-DPP-IV peptides likely competitive inhibitors. Twenty-five nanoseconds molecular dynamics simulation suggests the stability of these screened peptides, including the three predicted anti-ACE and one predicted anti-DPP-IV peptides. Seven dipeptides resembling approved oral-bioavailable peptide drugs in physicochemical and pharmacokinetic properties were revealed: AY, CF, EF, TF, TY, VF, and VY. In conclusion, our study presented in silico evidence for SP being a promising source of bioavailable and safe anti-ACE and anti-DPP-IV peptides following GI digestions.

PLATO: A Predictive Drug Discovery Web Platform for Efficient Target Fishing and Bioactivity Profiling of Small Molecules.

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse ligand-based screening, based on a collection of 632,119 compounds known to be experimentally active on 6004 protein targets. An efficient backend implementation allows to speed-up the process that returns results for query in less than 20 s. The graphical user interface is intuitive to give practitioners easy input and transparent output, which is available as a standard report in portable document format. PLATO has been validated on thousands of external data, with performances better than those of other parallel approaches. PLATO is available free of charge (http://plato.uniba.it/ accessed on 13 April 2022).

A target fishing study to spot possible biological targets of fusaric acid: Inhibition of protein kinase-A and insights on the underpinning mechanisms.

Fusaric acid is a secondary metabolite produced by various Fusarium fungi, present with relatively high incidence in Fusarium-contaminated foods. It was already described as phytotoxic and cytotoxic. However, the understanding of its molecular mechanisms is still fragmentary and further data are needed to ensure an informed assessment of the risk related to its presence in food. This work applied an integrated in silico/in vitro approach to reveal novel potential biological activities of fusaric acid and to investigate the underpinning mechanisms. An in silico reverse screening was used to identify novel biological targets for fusaric acid. Computational results indicated as target protein kinase-A, which was confirmed with biochemical cell-free assays providing evidence of its actual inhibitory potential. Cell-based experiments on intestinal cells (HCEC-1CT cells) identified the mitochondrial network and cell membranes as potentially affected organelles, possibly resulting from PKA inhibition. The integration of 3D molecular modeling supported the plausibility of fusaric acid-dependent inhibition. From the hazard identification perspective, considering the Low Observed Adverse Effect Level described here (0.1 mM) and the possible level of contamination in food, fusaric acid might raise concern from a food safety standpoint and the gastrointestinal tract was described as a meaningful system to investigate with priority.

Marantodes pumilum: Systematic computational approach to identify their therapeutic potential and effectiveness.

ETHNOPHARMACOLOGICAL RELEVANCE: Marantodes pumilum (MP) herbs, locally known as Kacip Fatimah, are widely used traditionally to improve women's health. The herb is frequently used for gynecological issues such as menstrual problems, facilitating and quickening delivery, post-partum medication, treats flatulence and dysentery, and. MP extracts are thought to aid in the firming and toning of abdominal muscles, tighten breasts and vaginal muscles, and anti-dysmenorrhea. It also was used for the treatment of gonorrhea and hemorrhoids. As MP product has been produced commercially recently, more in-depth studies should be conducted. The presence of numerous active compounds in MP might provide a synergistic effect and potentially offer other health benefits than those already identified and known. AIM OF THE STUDY: This study aimed to use a computational target fishing approach to predict the possible therapeutic effect of Marantodes pumilum and evaluated their effectivity. MATERIALS AND METHODS: This study involves a computational approach to identify the potential targets by using target fishing. Several databases were used: PubChem database to obtain the chemical structure of interested compounds; Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) server and the SWISSADME web tool to identify and select the compounds having drug-likeness properties; PharmMapper was used to identify top ten target protein of the selected compounds and Online Mendelian Inheritance in Man (OMIM) was used to predict human genetic problems; the gene id of top-10 proteins was obtained from UniProtKB to be analyzed by using GeneMANIA server to check the genes' function and their co-expression; Gene Pathway established by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) of the selected targets were analyzed by using EnrichR server and confirmed by using DAVID (The Database for Annotation, Visualization and Integrated Discovery) version 6.8 and STRING database. All the interaction data was analyzed by Cytoscape version 3.7.2 software. The protein structure of most putative proteins was obtained from the RCSB protein data bank. Thedocking analysis was conducted using PyRx biological software v0.8 and illustrated by BIOVIA Discovery Studio Visualizer version 20.1.0. As a preliminary evaluation, a cell viability assay using Sulforhodamine B was conducted to evaluate the potential of the predicted therapeutic effect. RESULTS: It was found that four studied compounds are highly correlated with three proteins: EFGR, CDK2, and ESR1. These proteins are highly associated with cancer pathways, especially breast cancer and prostate cancer. Qualitatively, cell proliferation assay conducted shown that the extract has IC50 of 88.69 µg/ml against MCF-7 and 66.51 µg/ml against MDA-MB-231. CONCLUSIONS: Natural herbs are one of the most common forms of complementary and alternative medicine, and they play an important role in disease treatment. The results of this study show that in addition to being used traditionally to maintain women's health, the use of Marantodes pumilum indirectly has the potential to protect against the development of cancer cells, especially breast cancer. Therefore, further research is necessary to confirm the potential of this plant to be used in the development of anti-cancer drugs, especially for breast cancer.

Recent Advances in In Silico Target Fishing.

In silico target fishing, whose aim is to identify possible protein targets for a query molecule, is an emerging approach used in drug discovery due its wide variety of applications. This strategy allows the clarification of mechanism of action and biological activities of compounds whose target is still unknown. Moreover, target fishing can be employed for the identification of off targets of drug candidates, thus recognizing and preventing their possible adverse effects. For these reasons, target fishing has increasingly become a key approach for polypharmacology, drug repurposing, and the identification of new drug targets. While experimental target fishing can be lengthy and difficult to implement, due to the plethora of interactions that may occur for a single small-molecule with different protein targets, an in silico approach can be quicker, less expensive, more efficient for specific protein structures, and thus easier to employ. Moreover, the possibility to use it in combination with docking and virtual screening studies, as well as the increasing number of web-based tools that have been recently developed, make target fishing a more appealing method for drug discovery. It is especially worth underlining the increasing implementation of machine learning in this field, both as a main target fishing approach and as a further development of already applied strategies. This review reports on the main in silico target fishing strategies, belonging to both ligand-based and receptor-based approaches, developed and applied in the last years, with a particular attention to the different web tools freely accessible by the scientific community for performing target fishing studies.

New evidence for tamoxifen as an antischistosomal agent: in vitro, in vivo and target fishing studies.

Background: Praziquantel is the only drug available to treat schistosomiasis, and there is an urgent demand for new anthelmintic agents. Methodology & results: We conducted in-depth in vitro and in vivo studies and report a target fishing investigation. In vitro, tamoxifen was active against adult and immature worms at low concentrations (<5 µM). Tamoxifen at a single dose (400 mg/kg) or once daily for five consecutive days (100 mg/kg/day) in mice harboring either adult (patent infection) or juvenile (prepatent infection) significantly reduced worm burden (30-70%) and egg production (70-90%). Target fishing studies revealed propionyl-CoA carboxylase as a potential target for tamoxifen in Schistosoma mansoni and glucose uptake by S. mansoni was also significantly reduced. Conclusion: Our results provide news evidence of antiparasitic effect of tamoxifen and reveal propionyl-CoA carboxylase as a potential target.