Protein-protein interaction networks (PPI) and complex diseases

نویسندگان

  • Nahid Safari-Alighiarloo
  • Mohammad Taghizadeh
  • Mostafa Rezaei-Tavirani
  • Bahram Goliaei
  • Ali Asghar Peyvandi
چکیده

The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic (and physiologic) mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Combination Method of Centrality Measures and Biological Properties to Improve Detection of Protein Complexes in Weighted PPI Networks

Introduction: In protein-protein interaction networks (PPINs), a complex is a group of proteins that allows a biological process to take place. The correct identification of complexes can help better understanding of the function of cells used for therapeutic purposes, such as drug discoveries. One of the common methods for identifying complexes in the PPINs is clustering, but this study aimed ...

متن کامل

A Combination Method of Centrality Measures and Biological Properties to Improve Detection of Protein Complexes in Weighted PPI Networks

Introduction: In protein-protein interaction networks (PPINs), a complex is a group of proteins that allows a biological process to take place. The correct identification of complexes can help better understanding of the function of cells used for therapeutic purposes, such as drug discoveries. One of the common methods for identifying complexes in the PPINs is clustering, but this study aimed ...

متن کامل

Prediction of Protein Sub-Mitochondria Locations Using Protein Interaction Networks

Background: Prediction of the protein localization is among the most important issues in the bioinformatics that is used for the prediction of the proteins in the cells and organelles such as mitochondria. In this study, several machine learning algorithms are applied for the prediction of the intracellular protein locations. These algorithms use the features extracted from pro...

متن کامل

Study of PKA binding sites in cAMP-signaling pathway using structural protein-protein interaction networks

Backgroud: Protein-protein interaction, plays a key role in signal transduction in signaling pathways. Different approaches are used for prediction of these interactions including experimental and computational approaches. In conventional node-edge protein-protein interaction networks, we can only see which proteins interact but ‘structural networks’ show us how these proteins inter...

متن کامل

Investigating the effects of ibuprofen on the gene expression profile in Hippocampus of mice model of Alzheimer’s disease through bioinformatics analysis

Non-steroidal anti-inflammatory drugs (NSAIDs) identified effective in many diseases. One of which is neurodegenerative diseases including Alzheimer disease (AD). In this study gross alteration of gene expression in AD mice by ibuprofen treatment is investigated via Protein-protein interaction network (PPI) analysis. Expression profiling of microarray dataset GSE67306 was retrieved from GEO dat...

متن کامل

Identification and prioritization genes related to Hypercholesterolemia QTLs using gene ontology and protein interaction networks

Gene identification represents the first step to a better understanding of the physiological role of the underlying protein and disease pathways, which in turn serves as a starting point for developing therapeutic interventions. Familial hypercholesterolemia is a hereditary metabolic disorder characterized by high low-density lipoprotein cholesterol levels. Hypercholesterolemia is a quantitativ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2014