Predicting the Structure of Protein–Protein Complexes Using the SwarmDock Web Server

2014 ◽  
pp. 181-197 ◽  
Author(s):  
Mieczyslaw Torchala ◽  
Paul A. Bates
Keyword(s):  
Protein Complexes ◽  
Web Server

scholarly journals PPI-MASS: An Interactive Web Server to Identify Protein-Protein Interactions From Mass Spectrometry-Based Proteomics Data

2021 ◽  
Vol 8 ◽  
Author(s):  
Mariela González-Avendaño ◽  
Simón Zúñiga-Almonacid ◽  
Ian Silva ◽  
Boris Lavanderos ◽  
Felipe Robinson ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Web Server ◽  
Target Protein ◽  
Protein Protein Interactions ◽  
Proteomics Data ◽  
Functional Protein ◽  
Web Platform ◽  
The Web

Mass spectrometry-based proteomics methods are widely used to identify and quantify protein complexes involved in diverse biological processes. Specifically, tandem mass spectrometry methods represent an accurate and sensitive strategy for identifying protein-protein interactions. However, most of these approaches provide only lists of peptide fragments associated with a target protein, without performing further analyses to discriminate physical or functional protein-protein interactions. Here, we present the PPI-MASS web server, which provides an interactive analytics platform to identify protein-protein interactions with pharmacological potential by filtering a large protein set according to different biological features. Starting from a list of proteins detected by MS-based methods, PPI-MASS integrates an automatized pipeline to obtain information of each protein from freely accessible databases. The collected data include protein sequence, functional and structural properties, associated pathologies and drugs, as well as location and expression in human tissues. Based on this information, users can manipulate different filters in the web platform to identify candidate proteins to establish physical contacts with a target protein. Thus, our server offers a simple but powerful tool to detect novel protein-protein interactions, avoiding tedious and time-consuming data postprocessing. To test the web server, we employed the interactome of the TRPM4 and TMPRSS11a proteins as a use case. From these data, protein-protein interactions were identified, which have been validated through biochemical and bioinformatic studies. Accordingly, our web platform provides a comprehensive and complementary tool for identifying protein-protein complexes assisting the future design of associated therapies.

scholarly journals Protinfo PPC: A web server for atomic level prediction of protein complexes

2009 ◽  
Vol 37 (suppl_2) ◽  
pp. W519-W525 ◽  
Author(s):  
Weerayuth Kittichotirat ◽  
Michal Guerquin ◽  
Roger E. Bumgarner ◽  
Ram Samudrala
Keyword(s):  
Protein Complexes ◽  
Web Server ◽  
Atomic Level

scholarly journals PICI: A web server with a multi-parametric algorithm for identifying interaction sites within protein complexes

2016 ◽  
Vol 12 (2) ◽  
pp. 78-81 ◽  
Author(s):  
Arindam Atanu Das ◽  
◽  
Ramadas Krishna ◽  
Keyword(s):  
Protein Complexes ◽  
Web Server ◽  
Interaction Sites ◽  
Parametric Algorithm

scholarly journals VoroMQA web server for assessing three-dimensional structures of proteins and protein complexes

2019 ◽  
Vol 47 (W1) ◽  
pp. W437-W442 ◽  
Author(s):  
Kliment Olechnovič ◽  
Česlovas Venclovas
Keyword(s):  
Computational Models ◽  
Protein Complexes ◽  
Solvent Accessibility ◽  
Voronoi Tessellation ◽  
Protein Structures ◽  
Web Server ◽  
Energy Estimates ◽  
Protein Chain ◽  
Input Structure ◽  
The Web

Abstract The VoroMQA (Voronoi tessellation-based Model Quality Assessment) web server is dedicated to the estimation of protein structure quality, a common step in selecting realistic and most accurate computational models and in validating experimental structures. As an input, the VoroMQA web server accepts one or more protein structures in PDB format. Input structures may be either monomeric proteins or multimeric protein complexes. For every input structure, the server provides both global and local (per-residue) scores. Visualization of the local scores along the protein chain is enhanced by providing secondary structure assignment and information on solvent accessibility. A unique feature of the VoroMQA server is the ability to directly assess protein-protein interaction interfaces. If this type of assessment is requested, the web server provides interface quality scores, interface energy estimates, and local scores for residues involved in inter-chain interfaces. VoroMQA, the underlying method of the web server, was extensively tested in recent community-wide CASP and CAPRI experiments. During these experiments VoroMQA showed outstanding performance both in model selection and in estimation of accuracy of local structural regions. The VoroMQA web server is available at http://bioinformatics.ibt.lt/wtsam/voromqa.

scholarly journals PCFamily: a web server for searching homologous protein complexes

2010 ◽  
Vol 38 (suppl_2) ◽  
pp. W516-W522 ◽  
Author(s):  
Yu-Shu Lo ◽  
Chun-Yu Lin ◽  
Jinn-Moon Yang
Keyword(s):  
Protein Complexes ◽  
Web Server ◽  
Homologous Protein

scholarly journals PRODIGY: a web server for predicting the binding affinity of protein–protein complexes

2016 ◽  
pp. btw514 ◽  
Author(s):  
Li C. Xue ◽  
João Pglm Rodrigues ◽  
Panagiotis L. Kastritis ◽  
Alexandre Mjj Bonvin ◽  
Anna Vangone
Keyword(s):  
Binding Affinity ◽  
Protein Complexes ◽  
Web Server

scholarly journals DeepComplex: A Web Server of Predicting Protein Complex Structures by Deep Learning Inter-chain Contact Prediction and Distance-Based Modelling

2021 ◽  
Vol 8 ◽  
Author(s):  
Farhan Quadir ◽  
Raj S. Roy ◽  
Elham Soltanikazemi ◽  
Jianlin Cheng
Keyword(s):  
Deep Learning ◽  
Protein Function ◽  
Tertiary Structure ◽  
Quaternary Structure ◽  
Protein Complexes ◽  
Function Analysis ◽  
Web Server ◽  
Learning Technology ◽  
Multiple Sequence ◽  
Contact Prediction

Proteins interact to form complexes. Predicting the quaternary structure of protein complexes is useful for protein function analysis, protein engineering, and drug design. However, few user-friendly tools leveraging the latest deep learning technology for inter-chain contact prediction and the distance-based modelling to predict protein quaternary structures are available. To address this gap, we develop DeepComplex, a web server for predicting structures of dimeric protein complexes. It uses deep learning to predict inter-chain contacts in a homodimer or heterodimer. The predicted contacts are then used to construct a quaternary structure of the dimer by the distance-based modelling, which can be interactively viewed and analysed. The web server is freely accessible and requires no registration. It can be easily used by providing a job name and an email address along with the tertiary structure for one chain of a homodimer or two chains of a heterodimer. The output webpage provides the multiple sequence alignment, predicted inter-chain residue-residue contact map, and predicted quaternary structure of the dimer. DeepComplex web server is freely available at http://tulip.rnet.missouri.edu/deepcomplex/web_index.html

Electron Microscopy and image analysis of nucleo-protein complexes

1994 ◽  
Vol 52 ◽  
pp. 88-89
Author(s):  
E. H. Egelman ◽  
X. Yu
Keyword(s):  
Electron Microscopy ◽  
Image Analysis ◽  
Normal Cell ◽  
Genetic Recombination ◽  
Protein Complexes ◽  
Chromosomal Rearrangements ◽  
Reca Protein ◽  
E Coli ◽  
Helical Polymer ◽  
Specific Protease

The RecA protein of E. coli has been shown to mediate genetic recombination, regulate its own synthesis, control the expression of other genes, act as a specific protease, form a helical polymer and have an ATPase activity, among other observed properties. The unusual filament formed by the RecA protein on DNA has not previously been shown to exist outside of bacteria. Within this filament, the 36 Å pitch of B-form DNA is extended to about 95 Å, the pitch of the RecA helix. We have now establishedthat similar nucleo-protein complexes are formed by bacteriophage and yeast proteins, and availableevidence suggests that this structure is universal across all of biology, including humans. Thus, understanding the function of the RecA protein will reveal basic mechanisms, in existence inall organisms, that are at the foundation of general genetic recombination and repair.Recombination at this moment is assuming an importance far greater than just pure biology. The association between chromosomal rearrangements and neoplasms has become stronger and stronger, and these rearrangements are most likely products of the recombinatory apparatus of the normal cell. Further, damage to DNA appears to be a major cause of cancer.

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