A Practical Step-by-Step Guide for Quantifying Retroactivity in Gene Networks

György, András

doi:10.1007/978-1-0716-1032-9_14

Cited by 4 publications

(4 citation statements)

References 61 publications

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“…In this work,

for each node n of a network was calculated using the Brandes algorithm [ 77 ]. The betweenness centrality of a node n reflects the amount of control that this node exerts over the interaction between communities of neighboring nodes in the network [ 78 ] and can be computed as follows:

where s and t are the source and target nodes in the network different from n ,

denotes the number of shortest paths from all s to all t , and

is the number of shortest paths from s to t that must pass through node n . Here, unweighted betweenness centralities were calculated for each node in the literature-informed protein–protein network.…”

Section: Methodsmentioning

confidence: 99%

Proteomic Network Analysis of Bronchoalveolar Lavage Fluid in Ex-Smokers to Discover Implicated Protein Targets and Novel Drug Treatments for Chronic Obstructive Pulmonary Disease

Mammen

Morris

et al. 2022

Pharmaceuticals

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Bronchoalveolar lavage of the epithelial lining fluid (BALF) can sample the profound changes in the airway lumen milieu prevalent in chronic obstructive pulmonary disease (COPD). We compared the BALF proteome of ex-smokers with moderate COPD who are not in exacerbation status to non-smoking healthy control subjects and applied proteome-scale translational bioinformatics approaches to identify potential therapeutic protein targets and drugs that modulate these proteins for the treatment of COPD. Proteomic profiles of BALF were obtained from (1) never-smoker control subjects with normal lung function (n = 10) or (2) individuals with stable moderate (GOLD stage 2, FEV1 50–80% predicted, FEV1/FVC < 0.70) COPD who were ex-smokers for at least 1 year (n = 10). After identifying potential crucial hub proteins, drug–proteome interaction signatures were ranked by the computational analysis of novel drug opportunities (CANDO) platform for multiscale therapeutic discovery to identify potentially repurposable drugs. Subsequently, a literature-based knowledge graph was utilized to rank combinations of drugs that most likely ameliorate inflammatory processes. Proteomic network analysis demonstrated that 233 of the >1800 proteins identified in the BALF were significantly differentially expressed in COPD versus control. Functional annotation of the differentially expressed proteins was used to detail canonical pathways containing the differential expressed proteins. Topological network analysis demonstrated that four putative proteins act as central node proteins in COPD. The drugs with the most similar interaction signatures to approved COPD drugs were extracted with the CANDO platform. The drugs identified using CANDO were subsequently analyzed using a knowledge-based technique to determine an optimal two-drug combination that had the most appropriate effect on the central node proteins. Network analysis of the BALF proteome identified critical targets that have critical roles in modulating COPD pathogenesis, for which we identified several drugs that could be repurposed to treat COPD using a multiscale shotgun drug discovery approach.

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“…In this work,

where s and t are the source and target nodes in the network different from n ,

denotes the number of shortest paths from all s to all t , and

Section: Methodsmentioning

confidence: 99%

Proteomic Network Analysis of Bronchoalveolar Lavage Fluid in Ex-Smokers to Discover Implicated Protein Targets and Novel Drug Treatments for Chronic Obstructive Pulmonary Disease

Mammen

Morris

et al. 2022

Pharmaceuticals

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show abstract

“…In this work, C b ( n ) for each node n of a network was calculated using the Brandes algorithm. 47 The betweenness centrality of a node n reflects the amount of control that this node exerts over the interaction between communities of neighboring nodes in the network 48 and can be computed as follows: Where s and t are the source and target nodes in the network different from n , σ s,t denotes the number of shortest paths from all s to all t , and σ s,t is the number of shortest paths from s to t that must pass through node n . Here, unweighted betweenness centralities were calculated for each node in the literature-informed protein-protein network.…”

Section: Methodsmentioning

confidence: 99%

“…In this work, 𝐶 𝑏 (𝑛) for each node n of a network was calculated using the Brandes algorithm. 47 The betweenness centrality of a node n reflects the amount of control that this node exerts over the interaction between communities of neighboring nodes in the network 48 and can be computed as follows:…”

Section: Network Topological Analysismentioning

confidence: 99%

Proteomic network analysis of bronchoalveolar lavage fluid in ex-smokers to discover implicated protein targets and novel drug treatments for chronic obstructive pulmonary disease

Mammen

Morris

et al. 2022

Preprint

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Rationale: Bronchoalveolar lavage of the epithelial lining fluid can sample the profound changes in the airway lumen milieu prevalent in Chronic Obstructive Pulmonary Disease (COPD). Characterizing the proteins in bronchoalveolar lavage fluid in COPD with advanced proteomic methods will identify disease-related changes, provide insight into pathogenetic mechanisms and potential therapeutics that will aid in the discovery of more effective therapeutics for COPD. Objectives: We compared epithelial lining fluid proteome of ex-smokers with moderate COPD who are not in exacerbation status COPD, to non-smoking healthy control subjects using advanced proteomics methods and applied proteome-scale translational bioinformatics approaches to identify potential therapeutic protein targets and drugs that modulate these proteins towards the treatment of COPD. Methods: Proteomic profiles of bronchalveolar lavage fluid were obtained from 1) never-smoker control subjects with normal lung function (n=10) or 2) individuals with stable moderate (GOLD stage 2, FEV1 50% – 80% predicted) COPD who were ex-smokers for at least one year (n=10). NIH Database for Annotation, Visualization and Integrated Discovery (DAVID) and Ingenuity Pathway Analysis (IPA) were the two bioinformatics tools employed for network analysis on the differentially expressed proteins to identify potential crucial hub proteins. The drug-proteome interaction signature comparison and ranking approach implemented in the Computational Analysis of Novel Drug Opportunities (CANDO) platform for multiscale therapeutic discovery was utilized to identify potential repurposable drugs for the treatment of COPD based on the BALF proteome. Subsequently, a literature-based knowledge graph was utilized to rank combinations of drugs that would most likely ameloriate inflammatory processes by inhibition or activation of their functions. Results: Proteomic network analysis demonstrated that 233 of the >1800 proteins identified in the BALF were differentially expressed in COPD versus control, including proteins associated with inflammation, structural elements, and energy metabolism. Functional annotation of the differentially expressed proteins by their implicated biological processes, cellular localization, and transcription factor interactions was accomplished via DAVID. Canonical pathways containing the differential expressed proteins were detailed via the Ingenuity Pathway Analysis application. Topological network analysis demonstrated that four proteins act as central node proteins in the inflammatory pathways in COPD. The CANDO multiscale drug discovery platform was used to analyze the behavioral similarity between the interaction signatures of all FDA-approved drugs and the identified BALF proteins. The drugs with the signatures most similar interaction signatures to approved COPD drugs were extracted with the CANDO platform. The analysis revealed 189 drugs that putatively target the proteins implicated in COPD. The putative COPD drugs that were identified using CANDO were subsequently analyzed using a knowledge based technique to identify an optimal two drug combination that had the most appropriate effect on the central node proteins. Conclusion: Analysis of the BALF proteome revealed novel differentially expressed proteins in the epithelial lining fluid that elucidate COPD pathogenesis. Network analyses identified critical targets that have critical roles in modulating COPD pathogenesis, for which we identified several drugs that could be repurposed to treat COPD using a multiscale shotgun drug discovery approach.

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“…Orthogonal systems and resource allocation. Cellular functions are interconnected, and exogenous constructs can be affected by retroactivity, where changes in a downstream process impact the functionality of upstream modules, leading to difficult-to-predict effects [36,37]. For this reason, attention has been dedicated to the development of orthogonal components that enable the insulation of exogenous processes from the native gene expression machinery [38,39].…”

Section: Introductionmentioning

confidence: 99%