Prediction of protein-protein interactions from evolutionary information.
نویسندگان
چکیده
The more we know about the molecular biology of the cell, the more we see genes and proteins as part of networks or pathways instead of as isolated entities and understand their function as avariable of the cellular context.To fulfill this newparadigm, genomic sequences offer a catalog of building blocks, and protein interactions provide the first information for the challenging task of understanding the functions of these genes and proteins within their situation in networks and pathways. To further refine the information on the context and timing in which these observed biological functions take place, additional insight from genetic regulatory mechanisms and genetic specificity (cell-type specificity, individual differences, etc.) will become increasingly important. The study of protein interactions can be divided into two complementary aspects, the determination of the residues or regions implicated in the interactions and the deciphering of the identity of the interaction partners (which proteins interact with which ones). These two problems have been typically addressed by biophysical and biochemical techniques, such as binding studies (chromatographic isolation of complexes, coimmunoprecipitation, protection, cross-linking studies, etc.) and indirect genetic methods (gene suppression studies, systematic mutagenesis, and interspecies exchanges). The development of genomic and postgenomic technologies has changed the panorama considerably, with the possibility of obtaining systematically massive amounts of data about protein interactions. Progress has been done in the automation of experimental approaches such as yeast-two-hybrid based methods and mass spectrometry determination of components of macromolecular complexes. At the same time, a number of new bioinformatics techniques have been developed
منابع مشابه
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 کاملDiscovering Domains Mediating Protein Interactions
Background: Protein-protein interactions do not provide any direct information regarding the domains within the proteins that mediate the interactions. The majority of proteins are multi domain proteins and the interaction between them is often defined by the pairs of their domains. Most of the former studies focus only on interacting domain pairs. However they do not consider the in...
متن کاملProtein Secondary Structure Prediction: a Literature Review with Focus on Machine Learning Approaches
DNA sequence, containing all genetic traits is not a functional entity. Instead, it transfers to protein sequences by transcription and translation processes. This protein sequence takes on a 3D structure later, which is a functional unit and can manage biological interactions using the information encoded in DNA. Every life process one can figure is undertaken by proteins with specific functio...
متن کاملStudy 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 کاملThe inference of protein-protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships
MOTIVATION The prediction of protein-protein interactions is currently an important issue in bioinformatics. The mirror tree method uses evolutionary information to predict protein-protein interactions. However, it has been recognized that predictions by the mirror tree method lead to many false positives. The incentive of our study was to solve this problem by improving the method of extractin...
متن کاملEvolutionary Analysis of Mammalian ACE2 and the Key Residues Involved in Binding to the Spike Protein Revealed Potential SARS-CoV-2 Hosts
Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spilled over to humans via wild mammals, entering the host cell using angiotensin-converting enzyme 2 (ACE2) as receptor through Spike (S) protein binding. While SARS-CoV-2 became fully adapted to humans and globally spread, some mammal species were infected back. The present study evaluated the potential risk of mammals...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Methods of biochemical analysis
دوره 44 شماره
صفحات -
تاریخ انتشار 2003