Cargando…

Docking of peptides to GPCRs using a combination of CABS-dock with FlexPepDock refinement

The structural description of peptide ligands bound to G protein-coupled receptors (GPCRs) is important for the discovery of new drugs and deeper understanding of the molecular mechanisms of life. Here we describe a three-stage protocol for the molecular docking of peptides to GPCRs using a set of d...

Descripción completa

Detalles Bibliográficos
Autores principales:	Badaczewska-Dawid, Aleksandra E, Kmiecik, Sebastian, Koliński, Michał
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Oxford University Press 2020
Materias:	Problem Solving Protocol
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138832/ https://www.ncbi.nlm.nih.gov/pubmed/32520310 http://dx.doi.org/10.1093/bib/bbaa109

Ejemplares similares

Protein–peptide docking using CABS-dock and contact information
por: Blaszczyk, Maciej, et al.
Publicado: (2018)

Rosetta FlexPepDock ab-initio: Simultaneous Folding, Docking and Refinement of Peptides onto Their Receptors
por: Raveh, Barak, et al.
Publicado: (2011)

CABS-dock standalone: a toolbox for flexible protein–peptide docking
por: Kurcinski, Mateusz, et al.
Publicado: (2019)

InterPepScore: a deep learning score for improving the FlexPepDock refinement protocol
por: Johansson-Åkhe, Isak, et al.
Publicado: (2022)

High-resolution global peptide-protein docking using fragments-based PIPER-FlexPepDock
por: Alam, Nawsad, et al.
Publicado: (2017)

Rosetta FlexPepDock web server—high resolution modeling of peptide–protein interactions
por: London, Nir, et al.
Publicado: (2011)

Rosetta FlexPepDock to predict peptide-MHC binding: An approach for non-canonical amino acids
por: Bloodworth, Nathaniel, et al.
Publicado: (2022)

CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site
por: Kurcinski, Mateusz, et al.
Publicado: (2015)

FlexPepDock lessons from CAPRI peptide–protein rounds and suggested new criteria for assessment of model quality and utility
por: Marcu, Orly, et al.
Publicado: (2017)

A protocol for CABS-dock protein–peptide docking driven by side-chain contact information
por: Kurcinski, Mateusz, et al.
Publicado: (2017)

Improving protein–ligand docking and screening accuracies by incorporating a scoring function correction term
por: Zheng, Liangzhen, et al.
Publicado: (2022)

Integrative modeling of diverse protein-peptide systems using CABS-dock
por: Puławski, Wojciech, et al.
Publicado: (2023)

CABS-flex predictions of protein flexibility compared with NMR ensembles
por: Jamroz, Michal, et al.
Publicado: (2014)

CABS-flex: server for fast simulation of protein structure fluctuations
por: Jamroz, Michal, et al.
Publicado: (2013)

PaFlexPepDock: Parallel Ab-Initio Docking of Peptides onto Their Receptors with Full Flexibility Based on Rosetta
por: Li, Haiou, et al.
Publicado: (2014)

Correction: PaFlexPepDock: Parallel Ab-Initio Docking of Peptides onto Their Receptors with Full Flexibility Based on Rosetta
Publicado: (2014)

Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking
por: Zalewski, Mateusz, et al.
Publicado: (2021)

Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data
por: Sidorczuk, Katarzyna, et al.
Publicado: (2022)

CABS-flex standalone: a simulation environment for fast modeling of protein flexibility
por: Kurcinski, Mateusz, et al.
Publicado: (2019)

APPTEST is a novel protocol for the automatic prediction of peptide tertiary structures
por: Timmons, Patrick Brendan, et al.
Publicado: (2021)

Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly
por: Beslic, Denis, et al.
Publicado: (2022)

DeepImmuno: deep learning-empowered prediction and generation of immunogenic peptides for T-cell immunity
por: Li, Guangyuan, et al.
Publicado: (2021)

iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities
por: Xu, Jing, et al.
Publicado: (2023)

CABS-flex 2.0: a web server for fast simulations of flexibility of protein structures
por: Kuriata, Aleksander, et al.
Publicado: (2018)

ENNAVIA is a novel method which employs neural networks for antiviral and anti-coronavirus activity prediction for therapeutic peptides
por: Timmons, Patrick Brendan, et al.
Publicado: (2021)

HLAB: learning the BiLSTM features from the ProtBert-encoded proteins for the class I HLA-peptide binding prediction
por: Zhang, Yaqi, et al.
Publicado: (2022)

Quantum annealing-based clustering of single cell RNA-seq data
por: Kubacki, Michal, et al.
Publicado: (2023)

Insights from analyses of low complexity regions with canonical methods for protein sequence comparison
por: Jarnot, Patryk, et al.
Publicado: (2022)

TP53_PROF: a machine learning model to predict impact of missense mutations in TP53
por: Ben-Cohen, Gil, et al.
Publicado: (2022)

HiConfidence: a novel approach uncovering the biological signal in Hi-C data affected by technical biases
por: Kobets, Victoria A, et al.
Publicado: (2023)

GalaxyPepDock: a protein–peptide docking tool based on interaction similarity and energy optimization
por: Lee, Hasup, et al.
Publicado: (2015)

pyGOMoDo: GPCRs modeling and docking with python
por: Ribeiro, Rui P, et al.
Publicado: (2023)

Protein functional annotation of simultaneously improved stability, accuracy and false discovery rate achieved by a sequence-based deep learning
por: Hong, Jiajun, et al.
Publicado: (2019)

Clinical trials, progression-speed differentiating features and swiftness rule of the innovative targets of first-in-class drugs
por: Li, Ying Hong, et al.
Publicado: (2019)

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies
por: Tang, Jing, et al.
Publicado: (2019)

CAFU: a Galaxy framework for exploring unmapped RNA-Seq data
por: Chen, Siyuan, et al.
Publicado: (2019)

Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research
por: Feng, Zhiwei, et al.
Publicado: (2020)

MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm
por: Bai, Qifeng, et al.
Publicado: (2020)

New insights on human essential genes based on integrated analysis and the construction of the HEGIAP web-based platform
por: Chen, Hebing, et al.
Publicado: (2019)

A comprehensive method protocol for annotation and integrated functional understanding of lncRNAs
por: Kunz, Meik, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_bphu8ka8btt2uiku25v8d9or4l