Predicting Protein–Protein Interactions from the Molecular to the Proteome Level

Abstract

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.

PRISM-EM: template interface-based modelling of multi-protein complexes guided by cryo-electron microscopy density maps

“…computational time. Binary interactions are predicted by using interface motifs that recur at protein interfaces (Tsai et al, 1996(Tsai et al, , 1997Keskin et al, 2008Keskin et al, , 2016. PRISM is based on these principles and considers recurring motifs in protein interfaces (Tuncbag et al, 2011;Baspinar et al, 2014;Ogmen et al, 2005;Aytuna et al, 2005).…”

Simulated Isotope Exchange Patterns Enable Protein Structure Determination

“…[1] Protein docking has emerged to understand the abundance of PPIs at the molecular level in which the conformations of pairwise protein assemblies are predicted from the high resolution structures of their constituents. [2] Obtaining native structures from the high background of non-native state remains a significant challenge that can be met to some extent by utilizing available biophysical or biochemical information to drive the docking simulation. [3][4][5] Hydrogen deuterium exchange mass spectrometry (HDX-MS) can provide rapid and unique insight into protein-protein interfaces and has enormous potential for data-driven docking.…”

Synthesis of Gold Nanoparticles to Capture Lifelike Proteins: Application on the Multichannel Sensor Array Design

“…Proteins usually fold into one or more specific spatial conformations driven by the noncovalent interactions such as hydrogen bonding, ionic interactions, Van der Waals, and hydrophobic packing [1][2][3]. Due to the heterogeneous surfaces and numerous spatial configurations, proteins can interact with each other in unpredictable ways [4] and provide opportunities to prepare nanoparticles in the templates of proteins.…”