Decoding the underlying mechanisms of Di-Tan-Decoction in treating intracerebral hemorrhage based on network pharmacology.

BACKGROUND: Chinese medicine usually acts as "multi-ingredients, multi-targets and multi-pathways" on complex diseases, and these action modes reflect the coordination and integrity of the treatment process with traditional Chinese medicine (TCM). System pharmacology is developed based on the cross-disciplines of directional pharmacology, system biology, and mathematics, has the characteristics of integrity and synergy in the treatment process of TCM. Therefore, it is suitable for analyzing the key ingredients and mechanisms of TCM in treating complex diseases. Intracerebral Hemorrhage (ICH) is one of the leading causes of death in China, with the characteristics of high mortality and disability rate. Bring a significant burden on people and society. An increasing number of studies have shown that Chinese medicine prescriptions have good advantages in the treatment of ICH, and Ditan Decoction (DTT) is one of the commonly used prescriptions in the treatment of ICH. Modern pharmacological studies have shown that DTT may play a therapeutic role in treating ICH by inhibiting brain inflammation, abnormal oxidative stress reaction and reducing neurological damage, but the specific key ingredients and mechanism are still unclear. METHODS: To solve this problem, we established PPI network based on the latest pathogenic gene data of ICH, and CT network based on ingredient and target data of DTT. Subsequently, we established optimization space based on PPI network and CT network, and constructed a new model for node importance calculation, and proposed a calculation method for PES score, thus calculating the functional core ingredients group (FCIG). These core functional groups may represent DTT therapy for ICH. RESULTS: Based on the strategy, 44 ingredients were predicted as FCIG, results showed that 80.44% of the FCIG targets enriched pathways were coincided with the enriched pathways of pathogenic genes. Both the literature and molecular docking results confirm the therapeutic effect of FCIG on ICH via targeting MAPK signaling pathway and PI3K-Akt signaling pathway. CONCLUSIONS: The FCIG obtained by our network pharmacology method can represent the effect of DTT in treating ICH. These results confirmed that our strategy of active ingredient group optimization and the mechanism inference could provide methodological reference for optimization and secondary development of TCM.

Uncovering the potential mechanism of Xue Fu Zhu Yu Decoction in the treatment of intracerebral hemorrhage.

BACKGROUND: Chinese herbal medicine (CHM) is characterized by "multi- compounds, multi-targets and multi-pathway", which has advanced benefits for preventing and treating complex diseases, but there still exists unsolved issues, mainly include unclear material basis and underlying mechanism of prescription. Integrated pharmacology is a hot cross research area based on system biology, mathematics and poly-pharmacology. It can systematically and comprehensively investigate the therapeutic reaction of compounds or drugs on pathogenic genes network, and is especially suitable for the study of complex CHM systems. Intracerebral Hemorrhage (ICH) is one of the main causes of death among Chinese residents, which is characterized with high mortality and high disability rate. In recent years, the treatment of ICH by CHM has been deeply researched. Xue Fu Zhu Yu Decoction (XFZYD), one of the commonly used prescriptions in treating ICH at clinic level, has not been clear about its mechanism. METHODS: Here, we established a strategy, which based on compounds-targets, pathogenetic genes, network analysis and node importance calculation. Using this strategy, the core compounds group (CCG) of XFZYD was predicted and validated by in vitro experiments. The molecular mechanism of XFZYD in treating ICH was deduced based on CCG and their targets. RESULTS: The results show that the CCG with 43 compounds predicted by this model is highly consistent with the corresponding Compound-Target (C-T) network in terms of gene coverage, enriched pathway coverage and accumulated contribution of key nodes at 89.49%, 88.72% and 90.11%, respectively, which confirmed the reliability and accuracy of the effective compound group optimization and mechanism speculation strategy proposed by us. CONCLUSIONS: Our strategy of optimizing the effective compound groups and inferring the mechanism provides a strategic reference for explaining the optimization and inferring the molecular mechanism of prescriptions in treating complex diseases of CHM.

Phenotypic Screening of Molecular Docking Enriched Chemical Libraries from Targets Identified in Ischemic Stroke Genome Data by Network-Based Method.

Cerebral ischemia (IS) is one of the main cardiovascular diseases threatening life and disability. Like most cardiovascular events, the disease progression of is affects a variety of signaling pathways and changes multiple overexpressed genes in the body. The use of new therapeutic agents to interfere with the disease progression of cardiovascular diseases (such as is) can be achieved by selectively regulating small molecules of the target set of different signal pathways, also known as selective multipharmacology. Phenotypic screening can be an effective method to solve this problem, but the lack of targeted methods for ischemic stroke limits its impact. Here, we aim to identify IS-specific targets by RNA sequencing data with a network-based approach. Molecular docking approach was applied to screen over 210,000 molecules from SPECS compound library. Screening of this enriched library resulted in 605 candidates that led to several potent active hits. The novelty analysis suggested that the structure scaffolds of the compounds were dissimilar to existing IKKB inhibitors, and further biological test result confirmed two identified compounds represented novel IKKB inhibitors. Further, docking exploration with IKKB (PDB id: 4KIK) showed that the three selective compounds were stable inside the binding pocket of IKKB which shared a homology of compound-protein interactions in comparison with the bioactive inhibitor of CHEMBL1762621. Our screening method is expected to produce selective multidrug lead compounds for the development of treatments for complex diseases, such as ischemic stroke.