scholarly journals Re-ranking of Computational Protein–Peptide Docking Solutions With Amino Acid Profiles of Rigid-Body Docking Results

2020 ◽  
Author(s):  
Masahito Ohue
Keyword(s):  
Amino Acid ◽  
Rigid Body ◽  
Protein Interactions ◽  
Complex Structure ◽  
Protein Docking ◽  
Ranking Method ◽  
Body Protein ◽  
Regulatory Pathways ◽  
Peptide Docking ◽  
Peptide Interactions

AbstractProtein–peptide interactions, in which one partner is a globular protein and the other is a flexible linear peptide, are important for understanding cellular processes and regulatory pathways, and are therefore targets for drug discovery. In this study, I combined rigid-body protein-protein docking software (MEGADOCK) and global flexible protein–peptide docking software (CABS-dock) to establish a re-ranking method with amino acid contact profiles using rigid-body sampling decoys. I demonstrate that the correct complex structure cannot be predicted (< 10 Å peptide RMSD) using the current version of CABS-dock alone. However, my newly proposed re-ranking method based on the amino acid contact profile using rigid-body search results (designated the decoy profile) demonstrated the possibility of improvement of predictions. Adoption of my proposed method along with continuous efforts for effective computational modeling of protein–peptide interactions can provide useful information to understand complex biological processes in molecular detail and modulate protein-protein interactions in disease treatment.

scholarly journals Performance and Its Limits in Rigid Body Protein-Protein Docking

Structure ◽  
2020 ◽  
Vol 28 (9) ◽  
pp. 1071-1081.e3 ◽  
Author(s):  
Israel T. Desta ◽  
Kathryn A. Porter ◽  
Bing Xia ◽  
Dima Kozakov ◽  
Sandor Vajda
Keyword(s):  
Rigid Body ◽  
Protein Docking ◽  
Body Protein

scholarly journals AutoDock CrankPep: combining folding and docking to predict protein–peptide complexes

2019 ◽  
Vol 35 (24) ◽  
pp. 5121-5127 ◽  
Author(s):  
Yuqi Zhang ◽  
Michel F Sanner
Keyword(s):  
Amino Acids ◽  
Protein Interactions ◽  
Disordered Proteins ◽  
Supplementary Information ◽  
Protein Protein Interactions ◽  
Peptide Docking ◽  
Novel Approach ◽  
Peptide Interactions ◽  
Therapeutic Molecules ◽  
Peptide Complexes

Abstract Motivation Protein–peptide interactions mediate a wide variety of cellular and biological functions. Methods for predicting these interactions have garnered a lot of interest over the past few years, as witnessed by the rapidly growing number of peptide-based therapeutic molecules currently in clinical trials. The size and flexibility of peptides has shown to be challenging for existing automated docking software programs. Results Here we present AutoDock CrankPep or ADCP in short, a novel approach to dock flexible peptides into rigid receptors. ADCP folds a peptide in the potential field created by the protein to predict the protein–peptide complex. We show that it outperforms leading peptide docking methods on two protein–peptide datasets commonly used for benchmarking docking methods: LEADS-PEP and peptiDB, comprised of peptides with up to 15 amino acids in length. Beyond these datasets, ADCP reliably docked a set of protein–peptide complexes containing peptides ranging in lengths from 16 to 20 amino acids. The robust performance of ADCP on these longer peptides enables accurate modeling of peptide-mediated protein–protein interactions and interactions with disordered proteins. Availability and implementation ADCP is distributed under the LGPL 2.0 open source license and is available at http://adcp.scripps.edu. The source code is available at https://github.com/ccsb-scripps/ADCP. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals pyDockWEB: a web server for rigid-body protein–protein docking using electrostatics and desolvation scoring

2013 ◽  
Vol 29 (13) ◽  
pp. 1698-1699 ◽  
Author(s):  
Brian Jiménez-García ◽  
Carles Pons ◽  
Juan Fernández-Recio
Keyword(s):  
Rigid Body ◽  
Web Server ◽  
Protein Docking ◽  
Body Protein

scholarly journals YAPP-CD: Yet another protein-peptide complex database

2021 ◽  
Author(s):  
Joon-Sang Park
Keyword(s):  
Structural Biology ◽  
Protein Interactions ◽  
Pharmaceutical Products ◽  
Protein Protein Interactions ◽  
Peptide Complex ◽  
Prediction Quality ◽  
Peptide Docking ◽  
Peptide Interactions ◽  
Peptide Complexes ◽  
Increasing Demand

Protein-peptide interactions are of great interest to the research community not only because they serve as mediators in many protein-protein interactions but also because of the increasing demand for peptide-based pharmaceutical products. Protein-peptide docking is a major tool for studying protein-peptide interactions, and several docking methods are currently available. Among various protein-peptide docking algorithms, template-based approaches, which utilize known protein-peptide complexes or templates to predict a new one, have been shown to yield more reliable results than template-free methods in recent comparative research. To obtain reliable results with a template-based docking method, the template database must be comprehensive enough; that is, there must be similar templates of protein-peptide complexes to the protein and peptide being investigated. Thus, the template database must be updated to leverage recent advances in structural biology. However, the template database distributed with GalaxyPepDock, one of the most widely used peptide docking programs, is outdated, limiting the prediction quality of the method. Here, we present an up-to-date protein-peptide complex database called YAPP-CD, which can be directly plugged into the GalaxyPepDock binary package to improve GalaxyPepDock's prediction quality by drawing on recent discoveries in structural biology. Experimental results show that YAPP-CD significantly improves GalaxyPepDock's prediction quality, e.g., the average Ligand/Interface RMSD of a benchmark set is reduced from 7.60 A/3.62 A to 3.47 A/1.71 A.

scholarly journals RDOCK: Refinement of rigid-body protein docking predictions

2003 ◽  
Vol 53 (3) ◽  
pp. 693-707 ◽  
Author(s):  
Li Li ◽  
Rong Chen ◽  
Zhiping Weng
Keyword(s):  
Rigid Body ◽  
Protein Docking ◽  
Body Protein

pyDockEneRes: per-residue decomposition of protein–protein docking energy

2019 ◽  
Vol 36 (7) ◽  
pp. 2284-2285 ◽  
Author(s):  
Miguel Romero-Durana ◽  
Brian Jiménez-García ◽  
Juan Fernández-Recio
Keyword(s):  
Binding Affinity ◽  
Protein Interactions ◽  
Structural Model ◽  
Protein Complexes ◽  
Complex Structure ◽  
Protein Docking ◽  
Supplementary Information ◽  
Scoring Functions ◽  
Residue Decomposition ◽  
Docking Energy

Abstract Motivation Protein–protein interactions are key to understand biological processes at the molecular level. As a complement to experimental characterization of protein interactions, computational docking methods have become useful tools for the structural and energetics modeling of protein–protein complexes. A key aspect of such algorithms is the use of scoring functions to evaluate the generated docking poses and try to identify the best models. When the scoring functions are based on energetic considerations, they can help not only to provide a reliable structural model for the complex, but also to describe energetic aspects of the interaction. This is the case of the scoring function used in pyDock, a combination of electrostatics, desolvation and van der Waals energy terms. Its correlation with experimental binding affinity values of protein–protein complexes was explored in the past, but the per-residue decomposition of the docking energy was never systematically analyzed. Results Here, we present pyDockEneRes (pyDock Energy per-Residue), a web server that provides pyDock docking energy partitioned at the residue level, giving a much more detailed description of the docking energy landscape. Additionally, pyDockEneRes computes the contribution to the docking energy of the side-chain atoms. This fast approach can be applied to characterize a complex structure in order to identify energetically relevant residues (hot-spots) and estimate binding affinity changes upon mutation to alanine. Availability and implementation The server does not require registration by the user and is freely accessible for academics at https://life.bsc.es/pid/pydockeneres. Supplementary information Supplementary data are available at Bioinformatics online.

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