Article detail · 2016
Predicting Protein Protein Interactions from the Molecular to the Proteome Level
- Year
- 2016
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue Chemical Reviews
- Catalog match (ISSN) Chemical Reviews
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
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 interactions at the proteome level. This review aims to provide a background on PPIs and their types. Computational methods for PPI predictions can use a variety of biological data including sequence-, evolution-, expression-, and structure-based data. Physical and statistical modeling are commonly used to integrate these data and infer PPI predictions. We review and list the state-of-the-art methods, servers, databases, and tools for protein-protein interaction prediction.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
386 citations
OpenAlex cited_by_count (cache / database)
23 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
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- Methods for Discovering and Targeting Druggable Protein-Protein Interfaces and Their Application to Repurposing 2018
- A Proximity Mapping Journey Into the Biology of the Mammalian Centrosome/Cilium Complex 2020
- Analysis of single amino acid variations in singlet hot spots of protein–protein interfaces 2018
- Developments in integrative modeling with dynamical interfaces 2018
- PRISM-EM: template interface-based modelling of multi-protein complexes guided by cryo-electron microscopy density maps 2016