PepBind: A Comprehensive Database and Computational Tool for Analysis of Protein–Peptide Interactions

Das, Arindam; Sharma, Om P.; Kumar, Mithilesh; Krishna, Rajamani; Mathur, Premendu P.

doi:10.1016/j.gpb.2013.03.002

Cited by 62 publications

(47 citation statements)

References 47 publications

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“…Several servers analyze interfaces in either the asymmetric units and/or the deposited biological assemblies of PDB entries [6][7][8][9][10][11] , and some are intended to predict which interfaces may be biologically relevant by measuring conservation scores and physical features and using machine learning predictors [12][13][14] . Interactions with peptides, nucleic acids, and ligands have also been analyzed and presented in several webservers and databases 9,[15][16][17][18][19][20][21] .…”

Section: Introductionmentioning

confidence: 99%

ProtCID: A data resource for structural information on protein interactions

Dunbrack

2019

Preprint

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Structural information on the interactions of proteins with other molecules is plentiful, and for some proteins and protein families, there may be 100s of available structures. It can be very difficult for a scientist who is not trained in structural bioinformatics to access this information comprehensively. Previously, we developed the Protein Common Interface Database (ProtCID), which provided clusters of the interfaces of full-length protein chains as a means of identifying biological assemblies. Because proteins consist of domains that act as modular functional units, we have extended the analysis in ProtCID to the individual domain level. This has greatly increased the number of large protein-protein clusters in ProtCID, enabling the generation of hypotheses on the structures of biological assemblies of many systems. The analysis of domain families allows us to extend ProtCID to the interactions of domains with peptides, nucleic acids, and ligands. ProtCID provides complete annotations and coordinate sets for every cluster.

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Section: Introductionmentioning

confidence: 99%

ProtCID: A data resource for structural information on protein interactions

Dunbrack

2019

Preprint

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“…Peptides mediate up to 40% of known protein-protein interactions in higher eukaryotes. Peptide binding plays a key role in cellular signaling, protein trafficking, immune response and oncology (Petsalaki and Russell, 2008;Das et al, 2013). In addition, peptides have served as promising drug candidates with high specificity and relatively low toxicity (Ahrens et al, 2012;Fosgerau and Hoffmann, 2015;Kahler et al, 2018;Lee et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…X-ray crystallography and nuclear magnetic resonance (NMR) have been utilized to determine high-resolution structures of peptide-protein complexes. These structures are often deposited into the Protein Data Bank (PDB) and also collected in specific databases focused on peptide-protein complex structures, including the PeptiDB (London et al, 2010), PepX (Vanhee et al, 2010) and PepBind (Das et al, 2013). Particularly, PeptiDB is a set of 103 non-redundant protein-peptide structures extracted from the PDB.…”

Section: Introductionmentioning

confidence: 99%

“…The PepBind contains a comprehensive dataset of 3100 available peptide-protein structures from the PDB, irrespective of the structure determination methods and similarity in their protein backbone. More than 40% of the structures in PepBind are involved in cell regulatory pathways, nearly 20% in the immune system and ~30% with protease or other hydrolase activities (Das et al, 2013). These databases have greatly facilitated structure-based modeling and drug design of peptide-protein interactions.…”

Section: Introductionmentioning

confidence: 99%

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Improved Modeling of Peptide-Protein Binding through Global Docking and Accelerated Molecular Dynamics Simulations

Wang

Alekseenko

Kozakov

et al. 2019

Preprint

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Peptides mediate up to 40% of known protein-protein interactions in higher eukaryotes and play a key role in cellular signaling, protein trafficking, immunology and oncology. However, it is challenging to predict peptide-protein binding with conventional computational modeling approaches, due to slow dynamics and high peptide flexibility. Here, we present a prototype of the approach which combines global peptide docking using ClusPro PeptiDock and all-atom enhanced simulations using Gaussian accelerated molecular dynamics (GaMD). For three distinct model peptides, the lowest backbone root-mean-square deviations (RMSDs) of their bound conformations relative to X-ray structures obtained from PeptiDock were 3.3 Å -4.8 Å, being medium quality predictions according to the Critical Assessment of PRediction of Interactions (CAPRI) criteria. GaMD simulations refined the peptide-protein complex structures with significantly reduced peptide backbone RMSDs of 0.6 Å -2.7 Å, yielding two high quality (subangstrom) and one medium quality models. Furthermore, the GaMD simulations identified important low-energy conformational states and revealed the mechanism of peptide binding to the target proteins. Therefore, PeptiDock+GaMD is a promising approach for exploring peptideprotein interactions.

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“…Here we report a web server PICI (Protein Inter-Chain Interactions) version 3.2, which calculates and recognizes various kinds of interactions in structural coordinate files of proteins. PICI initially developed as an integrated tool in PepBind database server [14] to aid analysis of protein-peptide interaction interface. The improved web server includes several programs and scripts to execute its function more efficiently across large protein-protein interfaces.…”

Section: Introductionmentioning

confidence: 99%

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

Das

Krishna

2016

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Identifying interactions between proteins in a complex is essential to analyze their role in various cellular activities and structural stability. Therefore, effective algorithms and computer programs are required for the better understanding of various interactions exist at the protein-protein interface. The protein inter-chain interaction (PICI) server was developed to identify these interaction sites and various interactions that contribute to the specificity and strength of the protein complex by using Protein Interaction Identification Algorithm (PIIA). The multi-parametric approach of this algorithm involves the interface area between the subunits, the atomic coordinate distance, the linearity of bonds, the orientation of aromatic side-chains, and physicochemical properties of the residues. Particular advantages of PICI include its ability to identify various strong and weak interactions, including those which have not been considered before by any other server. Representation of interface data in text tables, 3D interaction visualizer, colored sequence viewer, and a dynamic colored graphical matrix display makes it distinct from similar web servers. Users can analyze interactions within multi-chain proteins by their PDBids or by uploading a structure atomic coordinate file and can download the result in plain text or XML format.Availability:PICI is freely accessible at http://pici.bicpu.edu.in/

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PepBind: A Comprehensive Database and Computational Tool for Analysis of Protein–Peptide Interactions

Cited by 62 publications

References 47 publications

ProtCID: A data resource for structural information on protein interactions

ProtCID: A data resource for structural information on protein interactions

Improved Modeling of Peptide-Protein Binding through Global Docking and Accelerated Molecular Dynamics Simulations

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

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