Exploring the anti-proliferative activity of Pelargonium sidoides DC with in silico target identification and network pharmacology

Network pharmacology combined with molecular docking and experimental verification to elucidate the effect of flavan-3-ols and aromatic resin on anxiety

This study investigated the potential anxiolytic properties of flavan-3-ols and aromatic resins through a combined computational and experimental approach. Network pharmacology techniques were utilized to identify potential anxiolytic targets and compounds by analyzing protein-protein interactions and KEGG pathway data. Molecular docking and simulation studies were conducted to evaluate the binding interactions and stability of the identified targets. Behavioral tests, including the elevated plus maze test, open field test, light-dark test, actophotometer, and holeboard test, were used to assess anxiolytic activity. The compound-target network analysis revealed complex interactions involving 306 nodes and 526 edges, with significant interactions observed and an average node degree of 1.94. KEGG pathway analysis highlighted pathways such as neuroactive ligand-receptor interactions, dopaminergic synapses, and serotonergic synapses as being involved in anxiety modulation. Docking studies on EGCG (Epigallocatechin gallate) showed binding energies of -9.5 kcal/mol for MAOA, -9.2 kcal/mol for SLC6A4, and -7.4 kcal/mol for COMT. Molecular dynamic simulations indicated minimal fluctuations, suggesting the formation of stable complexes between small molecules and proteins. Behavioral tests demonstrated a significant reduction in anxiety-like behavior, as evidenced by an increased number of entries into and time spent in the open arm of the elevated plus maze test, light-dark test, open field center activity, hole board head dips, and actophotometer beam interruptions (p < 0.05 or p < 0.01). This research provides a comprehensive understanding of the multi-component, multi-target, and multi-pathway intervention mechanisms of flavan-3-ols and aromatic resins in anxiety treatment. Integrated network and behavioral analyses collectively support the anxiolytic potential of these compounds and offer valuable insights for future research in this area.

Isolation of oligostilbenes from Iris lactea Pall. var. chinensis (Fisch.) Koidz and their anti-inflammatory activities

Iris lactea Pall. var. chinensis (Fisch.) Koidz (Iris lactea) is an herbaceous perennial widely distributed in China, India, and South Korea. Iris lactea has been extensively used in traditional Chinese medicine. The present study isolated a new oligostilbene (compound 1), together with three known oligostilbenes (compounds 2, 3 and 4) from the seeds of Iris lactea. The structures of these compounds were elucidated by HRESIMS, NMR, and chemical analyses. The network-based pharmacologic analysis platform was used to predict the target proteins related to inflammation of isolated compounds. Furthermore, the isolated compounds were tested for their anti-inflammatory effects in LPS-stimulated RAW 264.7 cells. In this network, 138 candidate targets of compounds related to its therapeutic effect on inflammation were identified. In addition, compounds 1, 2, 3 and 4 significantly decreased NO content and the IL-6 levels as well as the expression of COX-2 in LPS-stimulated RAW 264.7 cells.

Network pharmacology-based analysis for unraveling potential cancer-related molecular targets of Egyptian propolis phytoconstituents accompanied with molecular docking and in vitro studies

Cancer is one of the predominant causes of death worldwide. The new trend nowadays is to exploit natural products with the hope of developing new anticancer agents with fewer side effects. Propolis is one of these natural products which showed effectiveness in cancer treatment. The aim of this study is to understand the multi-level mechanism of action of propolis constituents in cancer treatment using an integrated approach of network pharmacology-based analysis, molecular docking and in vitro cytotoxicity testing. An inhouse database of chemical constituents from Egyptian propolis was compiled and assessed for its ADME properties using the QikProp module in the Schrodinger software. STITCH, UniProt, STRING, KEGG and DAVID databases were used for construction of constituent-target gene, gene-pathway, and constituent-target gene-pathway networks with the aid of Cytoscape 3.8.2. The network pharmacology-based analysis showed that the hit propolis constituents related to cancer targets were genistein, luteolin, benzoic acid, quercetin and vanillic acid, whereas the main cancer-associated targets were CYP1A1, CYP19A1, ESR1, NOS3, CASP3 and AKT1. Twenty-four cancer-related pathways were recognized where the most enriched ones were pathways in cancer and estrogen signaling pathway. The most enriched biological processes involved in the mechanism of action of propolis constituents in cancer treatment were negative regulation of the apoptotic process and the metabolic process and negative regulation of cellular glucuronidation. Molecular docking analysis of the top hit compounds against the most enriched target proteins in the constructed networks was carried out using the Maestro interface of the Schrodinger software. Among hit compounds, quercetin and genistein exhibited the most stabilized interaction. Finally, confirmation of the potential anticancer activity of propolis was assured by in vitro cytotoxicity testing of propolis extract on human prostate cancer (DU-145), breast adenocarcinoma (MCF-7) and colorectal adenocarcinoma (Caco-2) cell lines. This study presents deeper insights about propolis molecular mechanisms of action in cancer for the first time using an integrated approach of network pharmacology, molecular docking and in vitro testing.

TCM network pharmacology: A new trend towards combining computational, experimental and clinical approaches

Traditional Chinese medicine (TCM) is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases. The holistic view of TCM coincides with the new generation of medical research paradigm characterized by network and system. TCM gave birth to a new method featuring holistic and systematic "network target", a core theory and method of network pharmacology. TCM is also an important research object of network pharmacology. TCM network pharmacology, which aims to understand the network-based biological basis of complex diseases, TCM syndromes and herb treatments, plays a critical role in the origin and development process of network pharmacology. This review introduces new progresses of TCM network pharmacology in recent years, including predicting herb targets, understanding biological foundation of diseases and syndromes, network regulation mechanisms of herbal formulae, and identifying disease and syndrome biomarkers based on biological network. These studies show a trend of combining computational, experimental and clinical approaches, which is a promising direction of TCM network pharmacology research in the future. Considering that TCM network pharmacology is still a young research field, it is necessary to further standardize the research process and evaluation indicators to promote its healthy development.

A network pharmacology-based approach to explore potential targets of Caesalpinia pulcherima: an updated prototype in drug discovery

Caesalpinia pulcherima (CP) is a traditional herb used for the treatment of asthma, bronchitis, cancer, anti-bacterial, anti-fungal and as abortifacient. In the present study, bioactive components and potential targets in the treatment of breast cancer validated through in silico, in vitro and in vivo approach. The results for the analysis were as among 29 components, only four components were found active for further study which proved the use of CP as a multi-target herb for betterment of clinical uses. The results found by PPI states that our network has significant interactions which include the ESR-1, ESR-2, ESRRA, MET, VEGF, FGF, PI3K, PDK-1, MAPK, PLK-1, NEK-2, and GRK. Compound-target network involves 4 active compound and 150 target genes which elucidate the mechanisms of drug action in breast cancer treatment. Furthermore, on the basis of the above results the important proteins were fetched for the docking study which helps in predicting the possible interaction between components and targets. The results of the western blotting showed that CP regulates ER and EGFR expression in MCF-7 cell. In addition to this animal experimentation showed that CP significantly improved immunohistological status in MNU induced carcinoma rats. Network pharmacology approach not only helps us to confirm the study of the chosen target but also gave an idea of compound-target network as well as pathways associated to the CP for treating the complex metabolic condition as breast cancer and they importance for experimental verification.

Network Pharmacology Study of Heat-Clearing and Detoxifying Traditional Chinese Medicine for Alzheimer's Disease

This study aims to explore the possible homologous mechanism of 7 frequently-used herbs for heat-clearing and detoxification in traditional Chinese medicine (HDTCM) for treating Alzheimer's disease (AD), one of the most common types of dementia, based on network pharmacology. Herbs that satisfied the criteria of containing chlorogenic acid, relating to AD and aligning with HDTCM, were simultaneously collected to determine whether they have anti-AD effect based on a survey of the literature. Herb-ingredient-target-disease networks were constructed by collecting information from the TCMSP and GeneCards public databases. The common targets of the herbs and AD were identified for conducting a Gene Ontology (GO) analyses and a Reactome pathway enrichment analysis. The results showed that PTGS1, IL-6, CASP3, and VEGFA were the predicted key gene targets. The IL-4 and IL-13 signaling pathway, the ESR-mediated signaling pathway, and the extranuclear estrogen signaling pathway were the significant pathways associated with the 7 herbs. This study revealed that the analogous anti-AD mechanism of the 7 herbs of HDTCM may be associated with anti-inflammation, which is a common effect of the chlorogenic acid and quercetin components.

Identifying cancer-related molecular targets of Nandina domestica Thunb. by network pharmacology-based analysis in combination with chemical profiling and molecular docking studies

ETHNOPHARMACOLOGICAL RELEVANCE

The fruits of Nandina domestica Thunb. have served as folk medicines in Chinese and Japanese tradition for treatment of several tumors including pharynx tumor and tooth abscess for many years, yet its exact mechanism of action is not yet known.

AIM OF THE STUDY

The study targets the identification of the main constituents of the fruits extracts and investigation of their mode of action in cancer therapy via pharmacology-based analysis and molecular docking.

MATERIALS AND METHODS

The different extracts of N. domestica Thunb. were analyzed via UPLC-MS/MS for identification of their active constituents. STITCH, DAVID, KEGG and STRING database were utilized for construction of compound-target and compound-target-pathway networks using Cytoscape 3.2.1. Molecular docking analysis of the top hit compounds was performed against the identified top hit molecular targets in the constructed networks. In vitro-testing of Nandina domestica Thunb. against colorectal cancer cell lines was carried out and correlated to the chemical profile of the extract to identify important biomarkers. The ADME properties of the active compounds were also evaluated.

RESULTS

22 compounds were identified by UPLC-MS/MS analysis and were forwarded to network pharmacology-based analysis. Results showed the enrichment of 5 compounds and 4 molecular targets in the network namely; AKT1, CASP3, MAPK1 and TP53. The pathway analysis of the identified targets revealed that 15 cancer-related pathways were enriched including colorectal cancer, endometrial cancer and small-cell lung cancer. In-vitro testing of the extracts against colo-rectal cancer cell lines revealed the fractions enriched in the identified hit compounds were indeed the most active as revealed from the HCA-heat-map. ADME results showed that all compounds were drug-like candidates showing acceptable values according to Lipinski's rule.

CONCLUSIONS

Network pharmacology analysis revealed that the compounds isoquercitrin, quercitrin, berberine, chlorogenic acid and caffeic acid showed strong synergistic interactions with the cancer-related targets and pathways. It could be concluded that N. domestica Thunb. constituents affect both apoptosis and Akt-signaling pathways during the stages of early and intermediate adenoma through interaction with the targets CASP3 and MAPK1 (ErC2) while during the stages of late adenoma and carcinoma, the compounds acts through the p53 and ErbB signaling pathways.

A Network Pharmacology Study on the Active Ingredients and Potential Targets of Tripterygium wilfordii Hook for Treatment of Rheumatoid Arthritis

Traditional Chinese medicine has specific effect on some chronic diseases in clinic, especially in rheumatic diseases. Tripterygium wilfordii Hook (TWH) is a traditional Chinese medicine commonly used in the treatment of rheumatoid arthritis (RA); the unique therapeutic effect has been confirmed by a large number of research papers. TWH has many compounds that lead to its active compounds. However, the potential targets and pharmacological and molecular mechanism of its action treatment of rheumatic diseases are not entirely clear. Therefore, the network pharmacology approach is needed to further study and explore its treatment mechanism. We have successfully set up 10 networks, including four major networks and other networks. Four major networks include rheumatoid arthritis disease network, compound-compound target network of TWH, TWH compound target-rheumatoid arthritis disease network, and TWH-rheumatoid arthritis disease-mechanism network. Other networks consist of RA disease and TWH related targets clusters, biological processes, and pathways network. Our study successfully predicted, explained, and confirmed the TWH of RA disease molecular synergy and found the potential of RA related targets, cluster, biological process, and pathways. This study not only provides prompts to the researcher who explores pharmacological and biological molecular mechanism of TWH applying to RA disease, but also proves a feasible method for discovering potential activated compounds from Chinese herbs.

Lupenone is a good anti-inflammatory compound based on the network pharmacology

The dried rhizome of Musa basjoo Sieb. et Zucc. is Rhizoma Musae. It has been used to treat diabetes in Miao medicine in China. Lupenone was isolated from Rhizoma Musae and has good anti-diabetic activity. Its mechanism of action is unclear. Diabetes is a chronic low-level systemic inflammatory disease, and lupenone has anti-inflammatory activity, but the underlying mechanism is not fully elucidated. In this study, we aimed to construct the drug-target biologic network and predict the anti-inflammatory mechanism of lupenone. The network-based pharmacologic analysis platform was used to identify the target proteins related to inflammation. Furthermore, the effects of lupenone on acute, subacute and diabetic pancreatic inflammation were evaluated. The "component-target-disease" network was constructed using Cytoscape. Lupenone could regulate transcription factor p65, NF-kappa-B inhibitor alpha, transcription factor AP-1, NF-kappa-B essential modulator, nuclear factor NF-kappa-B p105 subunit, epidermal growth factor receptor, hypoxia-inducible factor 1-alpha and other proteins related to the PI3K-Akt, Toll-like receptor and NF-kappa B signaling pathways. In addition, lupenone significantly decreased acute and subacute inflammation in mice as well as the IL-1β and IFN-γ levels in the pancreas of diabetic rats. The above results provide strong support for studying the molecular mechanism of lupenone in the treatment of diabetes from the perspective of anti-inflammation.

Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.