Quantitative Determination of Flexible Pharmacological Mechanisms Based On Topological Variation in Mice Anti-Ischemic Modular Networks

Identifying Qingkailing ingredients-dependent mesenchymal-epithelial transition factor-axiation "π" structuring module with angiogenesis and neurogenesis effects

OBJECTIVE

To explore the functional role of the drug-dependent mesenchymal-epithelial transition (Met)-axiation "π" structural module of neurogenesis after processing by three components of Qingkailing injection in neurogenesis and angiogenesis in cerebral ischemia.

METHODS

We used a Glutathione S-transferase (GST)-pull down assay, isothermal titration calorimetry assay, and other related methods to identify the relationships among Met, inositol polyphosphate phosphatase like 1 (Inppl1), and death associated protein kinase 3 (Dapk3) in this allosteric module. The biological effects of the modules of neurons generation composed of Met, Inppl1, and Dapk3 were measured through Western blot, apoptosis analysis, and double immunofluorescence labeling.

RESULTS

The GST-pull down assay revealed that proline-serine-threonine rich domain of Met binds to the Src homology domain of Inppl1 to form a protein-protein complex; Dapk3 with a C-terminal domain interacts weakly with the protein kinase C domain of Met in the intracellular region. Thus, we obtained a "π" structuring module considered a neural regeneration module. The biological effects of angiogenesis and neurogenesis modules composed of Met, Inppl1, and Dapk3 were also verified.

CONCLUSION

The study suggested that understanding the functional modules that contribute to pharmaceutics might provide novel signatures that can be used as endpoints to define disease processes under stroke or cerebral ischemia conditions.

Modular networks and genomic variation during progression from stable angina pectoris through ischemic cardiomyopathy to chronic heart failure

Background

Analyzing disease–disease relationships plays an important role for understanding etiology, disease classification, and drug repositioning. However, as cardiovascular diseases with causative links, the molecular relationship among stable angina pectoris (SAP), ischemic cardiomyopathy (ICM) and chronic heart failure (CHF) is not clear.

Methods

In this study, by integrating the multi-database data, we constructed paired disease progression modules (PDPMs) to identified relationship among SAP, ICM and CHF based on module reconstruction pairs (MRPs) of K-value calculation (a Euclidean distance optimization by integrating module topology parameters and their weights) methods. Finally, enrichment analysis, literature validation and structural variation (SV) were performed to verify the relationship between the three diseases in PDPMs.

Results

Total 16 PDPMs were found with K > 0.3777 among SAP, ICM and CHF, in which 6 pairs in SAP–ICM, 5 pairs for both ICM–CHF and SAP–CHF. SAP–ICM was the most closely related by having the smallest average K-value (K = 0.3899) while the maximum is SAP–CHF (K = 0.4006). According to the function of the validation gene, inflammatory response were through each stage of SAP–ICM–CHF, while SAP–ICM was uniquely involved in fibrosis, and genes were related in affecting the upstream of PI3K–Akt signaling pathway. 4 of the 11 genes (FLT1, KDR, ANGPT2 and PGF) in SAP–ICM–CHF related to angiogenesis in HIF-1 signaling pathway. Furthermore, we identified 62.96% SVs were protein deletion in SAP–ICM–CHF, and 53.85% SVs were defined as protein replication in SAP–ICM, while ICM–CHF genes were mainly affected by protein deletion.

Conclusion

The PDPMs analysis approach combined with genomic structural variation provides a new avenue for determining target associations contributing to disease progression and reveals that inflammation and angiogenesis may be important links among SAP, ICM and CHF progression.

Revealing the Modular Similarities and Differences Among Alzheimer's Disease, Vascular Dementia, and Parkinson's Disease in Genomic Networks

Alzheimer's disease (AD), vascular dementia (VD), and Parkinson's disease (PD) exert increasingly lethal or disabling effects on humans, but the associations among these diseases at the molecular level remain unclear. In our research, lists of genes related to these three diseases were acquired from public databases. We constructed gene-gene networks of the lists of disease-related genes using the STRING database and selected the plug-in MCODE as the most suitable method to divide the three disease-associated networks into modules through an entropy calculation. Notably, 1173 AD-related, 203 VD-related, and 722 PD-related genes as well as 72 overlapping genes were observed among the three diseases. By dividing the modules from the gene network, we divided the AD-related gene network into 27 modules, the VD-related gene network into 8 modules, and the PD-related gene network into 17 modules. After the enrichment analysis of each disease-related gene, 146 overlapping biological processes and 32 overlapping pathways were identified. Ultimately, through similarity analysis of the genes, biological processes, and pathways, we found that AD and VD were the most closely related at the biological process and pathway levels, with similarity coefficients of 0.2784 and 0.3626, respectively. After analyzing the overlapping gene network, we found that INS might play an important role in the network and that insulin and its signaling pathways may play a key role in these neurodegenerative diseases. Our research illustrates a new method for in-depth research on the three diseases, which may accelerate the progress of developing new therapeutics and may be applied to prevent neurodegenerative diseases.

Prediction of hepatocellular carcinoma risk in patients with chronic liver disease from dynamic modular networks

Background

Discovering potential predictive risks in the super precarcinomatous phase of hepatocellular carcinoma (HCC) without any clinical manifestations is impossible under normal paradigm but critical to control this complex disease.

Methods

In this study, we utilized a proposed sequential allosteric modules (AMs)-based approach and quantitatively calculated the topological structural variations of these AMs.

Results

We found the total of 13 oncogenic allosteric modules (OAMs) among chronic hepatitis B (CHB), cirrhosis and HCC network used SimiNEF. We obtained the 11 highly correlated gene pairs involving 15 genes (r > 0.8, P < 0.001) from the 12 OAMs (the out-of-bag (OOB) classification error rate < 0.5) partial consistent with those in independent clinical microarray data, then a three-gene set (cyp1a2-cyp2c19-il6) was optimized to distinguish HCC from non-tumor liver tissues using random forests with an average area under the curve (AUC) of 0.973. Furthermore, we found significant inhibitory effect on the tumor growth of Bel-7402, Hep 3B and Huh7 cell lines in zebrafish treated with the compounds affected those three genes.

Conclusions

These findings indicated that the sequential AMs-based approach could detect HCC risk in the patients with chronic liver disease and might be applied to any time-dependent risk of cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02791-9.

Genome Analysis Reveals a Synergistic Mechanism of Ursodeoxycholic Acid and Jasminoidin in Mice Brain Repair After Ischemia/Reperfusion: Crosstalk Among Muti-Pathways

Studies have shown that combination drug therapy which corresponding treatment involves multiple genes and targets is more effective against cerebral ischemia. To identify the synergistic mechanism of ursodeoxycholic acid and jasminoidin based on differential pathway network, which protect against brain ischemia-reperfusion injury. Totally 115 mice with focal cerebral ischemia-reperfusion injury were allocated into five groups: sham, vehicle, ursodeoxycholic acid (UA), jasminoidin (JA), and JA and UA combination group (JU). The differentially expressed genes identified by microarray which consisted of 11,644 complementary DNAs were loaded to the GeneGo MetaCore™ software to analyze the enriched pathways and processes among different groups. Of the top 10 pathways and process networks, 5, 6, and 3 overlapping pathways as well as 5, 3, and 4 overlapping process networks were observed between UA and JA, UA and JU, and JA and JU, respectively. Of these, three pathways and three process networks overlapped across the three groups. Interestingly, four representative pathways and six process networks were only noted in the JU group. Gene Ontology process analysis showed 2 processes were shared by all three treatment groups in the top 10 processes. The UA and JA combination resulted in synergistic effects through affecting multi-signal transduction pathways, different locations in the same pathway, and the new signaling pathway emerged in drug combination group, those together may enhance the treatment of cerebral ischemia-reperfusion injury through promoting neural cell apoptosis, decreasing calcium levels, inhibiting inflammation, and protecting neurons.

Met-Controlled Allosteric Module of Neural Generation as A New Therapeutic Target in Rodent Brain Ischemia

OBJECTIVE

To investigate a Met-controlled allosteric module (AM) of neural generation as a potential therapeutic target for brain ischemia.

METHODS

We selected Markov clustering algorithm (MCL) to mine functional modules in the related target networks. According to the topological similarity, one functional module was predicted in the modules of baicalin (BA), jasminoidin (JA), cholic acid (CA), compared with I/R model modules. This functional module included three genes: Inppl1, Met and Dapk3 (IMD). By gene ontology enrichment analysis, biological process related to this functional module was obtained. This functional module participated in generation of neurons. Western blotting was applied to present the compound-dependent regulation of IMD. Co-immunoprecipitation was used to reveal the relationship among the three members. We used IF to determine the number of newborn neurons between compound treatment group and ischemia/reperfusion group. The expressions of vascular endothelial growth factor (VEGF) and matrix metalloproteinase 9 (MMP-9) were supposed to show the changing circumstances for neural generation under cerebral ischemia.

RESULTS

Significant reduction in infarction volume and pathological changes were shown in the compound treatment groups compared with the I/R model group (P<0.05). Three nodes in one novel module of IMD were found to exert diverse compound-dependent ischemic-specific excitatory regulatory activities. An anti-ischemic excitatory allosteric module (AM_E) of generation of neurons (AM_E-GN) was validated successfully in vivo. Newborn neurons increased in BJC treatment group (P<0.05). The expression of VEGF and MMP-9 decreased in the compound treatment groups compared with the I/R model group (P<0.05).

CONCLUSIONS

AM_E demonstrates effectiveness of our pioneering approach to the discovery of therapeutic target. The novel approach for AM discovery in an effort to identify therapeutic targets holds the promise of accelerating elucidation of underlying pharmacological mechanisms in cerebral ischemia.

Mining the Synergistic Core Allosteric Modules Variation and Sequencing Pharmacological Module Drivers in a Preclinical Model of Ischemia

Identifying the variation of core modules and hubs seems to be critical for characterizing variable pharmacological mechanisms based on topological alteration of disease networks. We first identified a total of eight core modules by using an approach of multiple modular characteristic fusing (MMCF) from different targeted networks in ischemic mice. Interestingly, the value of module disturbance intensity (MDI) increased in drug combination group. Second, we redefined a weak allosteric module and a strong allosteric module. Then, we identified 15 pharmacological module drivers (PMDs) by leave‐one‐out screening with a cutoff of two folds, which were at least, in part, validated by expression and variation of topological contribution. Finally, we revealed the fusional and emergent variation of PMD in core modules contributing to multidimensional synergistic mechanism in ischemic mice and rats. Our findings provide a new set of drivers that might promote the pharmacological modular flexibility and offer a potential avenue for disease treatment.

Network-Wide Screen Identifies Variation of Novel Precise On-Module Targets Using Conformational Modudaoism

Modular targeting is promising in drug research at the network level, but it is challenging to quantificationally identify the precise on-modules. Based on a proposed Modudaoism (MD), we defined conserved MD (MDc) and varied MD (MDv) to quantitatively evaluate the conformational and energy variations of modules, and thereby identify the conserved and discrepant allosteric modules (AMs). Compared to the Z_summary , MDc/MDv got an optimized result of module preserved ratio and modular structure. In the mice anti-ischemic networks, 3, 5, and 1 conserved AMs as well as 4, 1, and 3 on-modules of baicalin (BA), jasminoidin (JA), and ursodeoxycholic acid (UA) were identified by MDc and MDv, 5 unique AMs and their characteristic actions were revealed. Besides, co-immunoprecipitation (Co-IP) experiments validated the representative modular structure. MDc/MDv method can quantitatively define the conformational variations of modules and screen the precise on-modules network-wide, which may provide a promising strategy for drug discovery.

Entropy-based divergent and convergent modular pattern reveals additive and synergistic anticerebral ischemia mechanisms

Module-based network analysis of diverse pharmacological mechanisms is critical to systematically understand combination therapies and disease outcomes. We first constructed drug-target ischemic networks in baicalin, jasminoidin, ursodeoxycholic acid, and their combinations baicalin and jasminoidin as well as jasminoidin and ursodeoxycholic acid groups and identified modules using the entropy-based clustering algorithm. The modules 11, 7, 4, 8 and 3 were identified as baicalin, jasminoidin, ursodeoxycholic acid, baicalin and jasminoidin and jasminoidin and ursodeoxycholic acid-emerged responsive modules, while 12, 8, 15, 17 and 9 were identified as disappeared responsive modules based on variation of topological similarity, respectively. No overlapping differential biological processes were enriched between baicalin and jasminoidin and jasminoidin and ursodeoxycholic acid pure emerged responsive modules, but two were enriched by their co-disappeared responsive modules including nucleotide-excision repair and epithelial structure maintenance. We found an additive effect of baicalin and jasminoidin in a divergent pattern and a synergistic effect of jasminoidin and ursodeoxycholic acid in a convergent pattern on "central hit strategy" of regulating inflammation against cerebral ischemia. The proposed module-based approach may provide us a holistic view to understand multiple pharmacological mechanisms associated with differential phenotypes from the standpoint of modular pharmacology.