Control Analysis of Protein-Protein Interaction Network Reveals Potential Regulatory Targets for MYCN

From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive Disorder

Major Depressive Disorder (MDD) is a significant neurological condition associated with aberrations in brain functional networks. Traditional studies have predominantly analyzed these from a network topology perspective. However, given the brain's dynamic and complex nature, exploring its mechanisms from a network control standpoint provides a fresh and insightful framework. This research investigates the integration of network controllability and machine learning to pinpoint essential biomarkers for MDD using functional magnetic resonance imaging (fMRI) data. By employing network controllability methods, we identify crucial brain regions that are instrumental in facilitating transitions between brain states. These regions demonstrate the brain's ability to navigate various functional states, emphasizing the utility of network controllability metrics as potential biomarkers. Furthermore, these metrics elucidate the complex dynamics of MDD and support the development of precision medicine strategies that incorporate machine learning to improve the precision of diagnostics and the efficacy of treatments. This study underscores the value of merging machine learning with network neuroscience to craft personalized interventions that align with the unique pathological profiles of individuals, ultimately enhancing the management and treatment of MDD.

Measuring criticality in control of complex biological networks

Recent controllability analyses have demonstrated that driver nodes tend to be associated to genes related to important biological functions as well as human diseases. While researchers have focused on identifying critical nodes, intermittent nodes have received much less attention. Here, we propose a new efficient algorithm based on the Hamming distance for computing the importance of intermittent nodes using a Minimum Dominating Set (MDS)-based control model. We refer to this metric as criticality. The application of the proposed algorithm to compute criticality under the MDS control framework allows us to unveil the biological importance and roles of the intermittent nodes in different network systems, from cellular level such as signaling pathways and cell-cell interactions such as cytokine networks, to the complete nervous system of the nematode worm C. elegans. Taken together, the developed computational tools may open new avenues for investigating the role of intermittent nodes in many biological systems of interest in the context of network control.

Total network controllability analysis discovers explainable drugs for Covid-19 treatment

BACKGROUND

The active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural controllability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against viral infections. Accordingly, we extended structural controllability to total structural controllability and introduced the concept of control hubs. Perturbing any control hub may render the cell uncontrollable by exogenous stimuli like viral infections, so control hubs are ideal drug targets.

RESULTS

We developed an efficient algorithm to identify all control hubs, applying it to a largest homogeneous network of human protein interactions, including interactions between human and SARS-CoV-2 proteins. Our method recognized 65 druggable control hubs with enriched antiviral functions. Utilizing these hubs, we categorized potential drugs into four groups: antiviral and anti-inflammatory agents, drugs acting on the central nervous system, dietary supplements, and compounds enhancing immunity. An exemplification of our approach's effectiveness, Fostamatinib, a drug initially developed for chronic immune thrombocytopenia, is now in clinical trials for treating Covid-19. Preclinical trial data demonstrated that Fostamatinib could reduce mortality rates, ICU stay length, and disease severity in Covid-19 patients.

CONCLUSIONS

Our findings confirm the efficacy of our novel strategy that leverages control hubs as drug targets. This approach provides insights into the molecular mechanisms of potential therapeutics for Covid-19, making it a valuable tool for interpretable drug discovery. Our new approach is general and applicable to repurposing drugs for other diseases.

The BRD4 Inhibitor dBET57 Exerts Anticancer Effects by Targeting Superenhancer-Related Genes in Neuroblastoma

Neuroblastoma (NB) is the most common solid tumor of the neural crest cell origin in children and has a poor prognosis in high-risk patients. The oncogene MYCN was found to be amplified at extremely high levels in approximately 20% of neuroblastoma cases. In recent years, research on the targeted hydrolysis of BRD4 to indirectly inhibit the transcription of the MYCN created by proteolysis targeting chimaera (PROTAC) technology has become very popular. dBET57 (S0137, Selleck, TX, USA) is a novel and potent heterobifunctional small molecule degrader based on PROTAC technology. The purpose of this study was to investigate the therapeutic effect of dBET57 in NB and its potential mechanism. In this study, we found that dBET57 can target BRD4 ubiquitination and disrupt the proliferation ability of NB cells. At the same time, dBET57 can also induce apoptosis, cell cycle arrest, and decrease migration. Furthermore, dBET57 also has a strong antiproliferation function in xenograft tumor models in vivo. In terms of mechanism, dBET57 targets the BET protein family and the MYCN protein family by associating with CRBN and destroys the SE landscape of NB cells. Combined with RNA-seq and ChIP-seq public database analysis, we identified the superenhancer-related genes TBX3 and ZMYND8 in NB as potential downstream targets of dBET57 and experimentally verified that they play an important role in the occurrence and development of NB. In conclusion, these results suggest that dBET57 may be an effective new therapeutic drug for the treatment of NB.