Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Prediction of Protein Interactions by Structural Matching: Prediction of PPI Networks and the Effects of Mutations on PPIs that Combines Sequence and Structural Information
Date
2017
Author
Tunçbağ, Nurcan
Nussinov, Ruth
Gursoy, Attila
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
250
views
0
downloads
Cite This
Structural details of protein interactions are invaluable to the understanding of cellular processes. However, the identification of interactions at atomic resolution is a continuing challenge in the systems biology era. Although the number of structurally resolved complexes in the Protein Databank increases exponentially, the complexes only cover a small portion of the known structural interactome. In this chapter, we review the PRISM system that is a protein–protein interaction (PPI) prediction tool—its rationale, principles, and applications. We further discuss its extensions to discover the effect of single residue mutations, to model large protein assemblies, to improve its performance by exploiting conformational protein ensembles, and to reconstruct large PPI networks or pathway maps.
Subject Keywords
Structural matching
,
PPI prediction
,
Mutation mapping
,
PI network
,
Structural pathway modeling
URI
https://hdl.handle.net/11511/56483
Collections
Graduate School of Informatics, Book / Book chapter
Suggestions
OpenMETU
Core
DynaDom: structure-based prediction of T cell receptor inter-domain and T cell receptor-peptide-MHC (class I) association angles
Hoffmann, Thomas; Marıon, Antoıne; Antes, Iris (Springer Science and Business Media LLC, 2017-02-02)
Background: T cell receptor (TCR) molecules are involved in the adaptive immune response as they distinguish between self- and foreign-peptides, presented in major histocompatibility complex molecules (pMHC). Former studies showed that the association angles of the TCR variable domains (Va/V beta) can differ significantly and change upon binding to the pMHC complex. These changes can be described as a rotation of the domains around a general Center of Rotation, characterized by the interaction of two highly...
Predicting Protein-Protein Interactions from the Molecular to the Proteome Level
Keskin, Ozlem; Tunçbağ, Nurcan; Gursoy, Attila (2016-04-27)
Identification of protein protein interactions (PPIs) is at the center of molecular biology considering the unquestionable role of proteins in cells. Combinatorial interactions result in a repertoire of multiple functions; hence, knowledge of PPI and binding regions naturally serve to functional proteomics and drug discovery. Given experimental limitations to find all interactions in a proteome, computational prediction/modeling of protein interactions is a prerequisite to proceed on the way to complete int...
Prediction of enzyme classes in a hierarchical approach by using SPMap
Yaman, A.; Atalay, Mehmet Volkan; Atalay, Rengül (2010-04-01)
Enzymes are proteins that play important roles in biochemical reactions as catalysts. They are classified based on the reaction they catalyzed, in a hierarchical scheme by International Enzyme Commission (EC). This hierarchical scheme is expressed in four-level tree structure and a unique number is assigned to each enzyme class. There are six major classes at the top level according to the reaction they carried out and sub-classes at the lower levels are further specific reactions of these classes. The aim ...
Prediction of enzyme classes in a hierarchical approach by using spmap
Yaman, Ayşe Gül; Atalay, Mehmet Volkan; Department of Computer Engineering (2009)
Enzymes are proteins that play an important role in biochemical reactions as catalysts. They are classified based on the reaction they catalyzed, in a hierarchical scheme by International Enzyme Commission (EC). This hierarchical scheme is expressed as a four-level tree structure and a unique number is assigned to each enzyme class. There are six major classes at the top level according to the reaction they carried out and sub-classes at the lower levels are further specific reactions of these classes. The ...
Prediction of protein-protein interactions from sequence using evolutionary relations of proteins and species
Güney, Tacettin Doğacan; Can, Tolga; Department of Computer Engineering (2009)
Prediction of protein-protein interactions is an important part in understanding the biological processes in a living cell. There are completely sequenced organisms that do not yet have experimentally verified protein-protein interaction networks. For such organisms, we can not generally use a supervised method, where a portion of the protein-protein interaction network is used as training set. Furthermore, for newly-sequenced organisms, many other data sources, such as gene expression data and gene ontolog...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
N. Tunçbağ, R. Nussinov, and A. Gursoy,
Prediction of Protein Interactions by Structural Matching: Prediction of PPI Networks and the Effects of Mutations on PPIs that Combines Sequence and Structural Information
. 2017, p. 270.