2012
DOI: 10.1002/iub.1040
|View full text |Cite
|
Sign up to set email alerts
|

From protein interaction networks to novel therapeutic strategies

Abstract: SummaryCellular mechanisms that sustain health or contribute to disease emerge mostly from the complex interplay among various molecular entities. To understand the underlying relationships between genotype, environment and phenotype, one has to consider the intricate and nonsequential interaction patterns formed between the different sets of cellular players. Biological networks capture a variety of molecular interactions and thus provide an excellent opportunity to consider physiological characteristics of i… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
25
0
1

Year Published

2013
2013
2023
2023

Publication Types

Select...
8
2

Relationship

1
9

Authors

Journals

citations
Cited by 38 publications
(27 citation statements)
references
References 85 publications
(86 reference statements)
0
25
0
1
Order By: Relevance
“…The reasons for choosing AD for this study are two-fold [3]: first, the lack of food and drug administration (FDA) approved drugs to treat AD today, in spite of decades of research on the disease's molecular mechanisms; second, the wealth of biomedical research articles published for AD studies can make validations of our approach less challenging. Biological networks capture a variety of molecular interactions and in particular, protein–protein interaction networks facilitate the understanding of pathogenic mechanisms that trigger the onset and progression of diseases [4]. Protein interaction networks present gene products that physically interact with each other to accomplish particular cellular functions, such as metabolism, cell cycle control, and signal transduction [5].…”
Section: Introductionmentioning
confidence: 99%
“…The reasons for choosing AD for this study are two-fold [3]: first, the lack of food and drug administration (FDA) approved drugs to treat AD today, in spite of decades of research on the disease's molecular mechanisms; second, the wealth of biomedical research articles published for AD studies can make validations of our approach less challenging. Biological networks capture a variety of molecular interactions and in particular, protein–protein interaction networks facilitate the understanding of pathogenic mechanisms that trigger the onset and progression of diseases [4]. Protein interaction networks present gene products that physically interact with each other to accomplish particular cellular functions, such as metabolism, cell cycle control, and signal transduction [5].…”
Section: Introductionmentioning
confidence: 99%
“…As above, the addition of protein structural information gives a better understanding of the mechanism by which a protein carries out its function, allowing a more complete understanding how bioactive molecules disrupt that function and, for example, of the differential effects of drugs on different patients (110). In particular, there has been much interest in the disruption of physical interactions as a treatment mechanism (76, 79). The disruption of PPIs with certain classes of molecules has been shown to be therapeutic and several drugs targeting important interactions have been successfully developed (see (149) for some examples).…”
Section: Analyzing Interactomesmentioning
confidence: 99%
“…Hence, a critical aspect to improve cancer treatment is not only to inhibit the primary oncogenic pathways that induce abnormal cell proliferation but, simultaneously, to prevent functional redundancies and pathway cross-talk that facilitate survival of cancer cell populations rendering tumors resistant to therapy. Current network pharmacology principles aim for a synergistic multitarget intervention strategy to improve clinical efficacies, while tackling critical aspects such as drug resistance (19,20). In line with this idea, we have derived a network-based computational method to quantify the cross-talk between signaling pathways involved in breast cancer and we assessed how combinatorial perturbations impact the signaling cross-talk.…”
Section: Introductionmentioning
confidence: 99%