Protein interaction networks: centrality, modularity, dynamics, and applications

Meng, Xiangmao; Li, Wenkai; Peng, Xiaoqing; Li, Yaohang; Li, Min

doi:10.1007/s11704-020-8179-0

Cited by 30 publications

(16 citation statements)

References 195 publications

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“…Along with shared central amino acids, there are several different central amino acids in the interface of the both wild-type and mutated spike proteins and the ACE2 protein. This means that the exerted mutation, in part, has changed the functional roles of the interface amino acids (Meng et al 2021 ). It’s noteworthy that the ACE2 amino acids with higher centrality are more conversed.…”

Section: Discussionmentioning

confidence: 99%

Pierce into Structural Changes of Interactions Between Mutated Spike Glycoproteins and ACE2 to Evaluate Its Potential Biological and Therapeutic Consequences

Hashemi

Zarei

Mubarak

et al. 2021

Int J Pept Res Ther

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The structural consequences of ongoing mutations on the SARS-CoV-2 spike-protein remains to be fully elucidated. These mutations could change the binding affinity between the virus and its target cell. Moreover, obtaining new mutations would also change the therapeutic efficacy of the designed drug candidates. To evaluate these consequences, 3D structure of a mutant spike protein was predicted and checked for stability, cavity sites, and residue depth. The docking analyses were performed between the 3D model of the mutated spike protein and the ACE2 protein and an engineered therapeutic ACE2 against COVID-19. The obtained results revealed that the N501Y substitution has altered the interaction orientation, augmented the number of interface bonds, and increased the affinity against the ACE2. On the other hand, the P681H mutation contributed to the increased cavity size and relatively higher residue depth. The binding affinity between the engineered therapeutic ACE2 and the mutant spike was significantly higher with a distinguished binding orientation. It could be concluded that the mutant spike protein increased the affinity, preserved the location, changed the orientation, and altered the interface amino acids of its interaction with both the ACE2 and its therapeutic engineered version. The obtained results corroborate the more aggressive nature of mutated SARS-CoV-2 due to their higher binding affinity. Moreover, designed ACe2-baased therapeutics would be still highly effective against covid-19, which could be the result of conserved nature of cellular ACE2. Supplementary Information The online version contains supplementary material available at 10.1007/s10989-021-10346-1.

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Section: Discussionmentioning

confidence: 99%

Pierce into Structural Changes of Interactions Between Mutated Spike Glycoproteins and ACE2 to Evaluate Its Potential Biological and Therapeutic Consequences

Hashemi

Zarei

Mubarak

et al. 2021

Int J Pept Res Ther

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“…The utilization of dynamic networks has recently attracted the attention of the research community 16 . Nonetheless, constructing an accurate DPIN is still a challenge 17 . All available approaches use a cautious and relatively high threshold to determine the active time point of proteins.…”

Section: Introductionmentioning

confidence: 99%

“…16 Nonetheless, constructing an accurate DPIN is still a challenge. 17 All available approaches use a cautious and relatively high threshold to determine the active time point of proteins. As a result, dynamic information of genes with lower expression values than particular values is lost.…”

Section: Introductionmentioning

confidence: 99%

Construction of dynamic protein interaction network based on gene expression data and quartile one principle

2022

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Real protein interaction network (PIN) is dynamic. Researchers created dynamic PIN by combining static PIN with gene expression data to explain the dynamicity evolution of protein interactions. However, all available approaches failed to recognize low-or high-expression proteins as active proteins. Therefore, determining an adequate threshold is one of the system's biological challenges. In this study, a quartile one (q-one) method is proposed to determine the active time points for each protein according to its expression value's features and construct dynamic protein interaction networks (DPINs) in which a protein is added to the network if it is active in two successive time points. This leads to reduce the number of DPINs to half. The efficiency of the q-one approach and three-sigma (3-sigma) method in detecting protein complexes is evaluated using Markov cluster method, clique percolation method, and ClusterONE algorithms. In most cases, q-one outperforms the 3-sigma method in recall, precision and F-measure. This is in addition to its ability to reveal the dynamicity within the protein-protein interaction network and identify essential proteins.

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“…Vital nodes identification is an important issue in network science as it can be used in many fields and directions like link prediction [33], disease control [34,35], risk engineering [36,37], biology engineering [38][39][40] and decision making [41,42]. Therefore, it is essential to study on vital nodes identification.…”

Section: Introductionmentioning

confidence: 99%

A modified gravity model based on network efficiency for vital nodes identification in complex networks

Li¹,

Shang²,

Deng³

2021

Preprint

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Vital nodes identification is an essential problem in network science. Various methods have been proposedto solve this problem. In particular, based on the gravity model, a series of improved gravity models are proposed to find vital nodes better in complex networks. However, they still have the room to be improved.In this paper, a novel and improved gravity model, which is named network efficiency gravity centrality model (NEG), integrates gravity model and network efficiency is proposed. Compared to other methods based on different gravity models, the proposed method considers the effect of the nodes on structure robustness of the network better. To solidate the superiority of the proposed method, experiments on varieties of real-world networks are carried out.

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Protein interaction networks: centrality, modularity, dynamics, and applications

Cited by 30 publications

References 195 publications

Pierce into Structural Changes of Interactions Between Mutated Spike Glycoproteins and ACE2 to Evaluate Its Potential Biological and Therapeutic Consequences

Pierce into Structural Changes of Interactions Between Mutated Spike Glycoproteins and ACE2 to Evaluate Its Potential Biological and Therapeutic Consequences

Construction of dynamic protein interaction network based on gene expression data and quartile one principle

A modified gravity model based on network efficiency for vital nodes identification in complex networks

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