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GalaxyDock: Protein–Ligand Docking with Flexible Protein Side-chains

https://doi.org/10.1021/ci300342z
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function
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Side-chain flexibility in proteins upon ligand binding
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Modeling of Cdc25B Dual Specifity Protein Phosphatase Inhibitors: Docking of Ligands and Enzymatic Inhibition Mechanism
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From Modeling to Medicinal Chemistry: Automatic Generation of Two‐Dimensional Complex Diagrams
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An efficient molecular docking using conformational space annealing
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SODOCK: Swarm optimization for highly flexible protein–ligand docking
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AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility
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Molecular docking studies of selected tricyclic and quinone derivatives on trypanothione reductase of Leishmania infantum
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LigDockCSA: Protein–ligand docking using conformational space annealing
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Efficient inclusion of receptor flexibility in grid‐based protein–ligand docking*
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Bayesian statistical analysis of protein side‐chain rotamer preferences
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Pre‐existing soft modes of motion uniquely defined by native contact topology facilitate ligand binding to proteins
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Automated docking to multiple target structures: Incorporation of protein mobility and structural water heterogeneity in AutoDock
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Molecular docking of balanol to dynamics snapshots of protein kinase A
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Effective handling of induced‐fit motion in flexible docking
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Protein–ligand docking: Current status and future challenges
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Ensemble docking of multiple protein structures: Considering protein structural variations in molecular docking
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FLIPDock: Docking flexible ligands into flexible receptors
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Induced fit in liver X receptor beta: A molecular dynamics‐based investigation
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Docking and scoring with alternative side‐chain conformations
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Protein loop modeling by using fragment assembly and analytical loop closure
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Refinement of protein termini in template‐based modeling using conformational space annealing
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Assessment of ligand‐binding residue predictions in CASP9
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Refinement of unreliable local regions in template‐based protein models
inferredcites →https://doi.org/10.1006/jmbi.1996.0897openalex-snapshot
Development and validation of a genetic algorithm for flexible docking 1 1Edited by F. E. Cohen
inferredcites →https://doi.org/10.1006/jmbi.2001.4551openalex-snapshot
FlexE: efficient molecular docking considering protein structure variations
inferredcites →https://doi.org/10.1007/s10822-007-9114-2openalex-snapshot
Surflex-Dock 2.1: Robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search
inferredcites →https://doi.org/10.1007/s10822-007-9148-5openalex-snapshot
Protein–ligand docking with multiple flexible side chains
inferredcites →https://doi.org/10.1007/s10822-008-9188-5openalex-snapshot
A new method for ligand docking to flexible receptors by dual alanine scanning and refinement (SCARE)
inferredcites →https://doi.org/10.1016/1074-5521(95)90050-0openalex-snapshot
Molecular recognition of the inhibitor AG-1343 by HIV-1 protease: conformationally flexible docking by evolutionary programming
inferredcites →https://doi.org/10.1016/j.drudis.2006.05.012openalex-snapshot
Virtual ligand screening: strategies, perspectives and limitations
inferredcites →https://doi.org/10.1016/j.jmb.2004.01.003openalex-snapshot
Protein Flexibility in Ligand Docking and Virtual Screening to Protein Kinases
inferredcites →https://doi.org/10.1016/j.jmb.2008.11.010openalex-snapshot
RosettaLigand Docking with Full Ligand and Receptor Flexibility
inferredcites →https://doi.org/10.1016/j.sbi.2006.02.002openalex-snapshot
Flexible protein–protein docking
inferredcites →https://doi.org/10.1016/s1367-5931(02)00341-1openalex-snapshot
Protein flexibility and drug design: how to hit a moving target
inferredcites →https://doi.org/10.1021/ci6002637openalex-snapshot
Docking Ligands into Flexible and Solvated Macromolecules. 1. Development and Validation of FITTED 1.0
inferredcites →https://doi.org/10.1021/ja042260copenalex-snapshot
Representing Receptor Flexibility in Ligand Docking through Relevant Normal Modes
inferredcites →https://doi.org/10.1021/jm050540copenalex-snapshot
Novel Procedure for Modeling Ligand/Receptor Induced Fit Effects
inferredcites →https://doi.org/10.1021/jm051033yopenalex-snapshot
Discovery of Protein Phosphatase 2C Inhibitors by Virtual Screening
inferredcites →https://doi.org/10.1021/jm061277yopenalex-snapshot
Diverse, High-Quality Test Set for the Validation of Protein−Ligand Docking Performance
inferredcites →https://doi.org/10.1021/jm800217kopenalex-snapshot
Flexible Side Chain Models Improve Enrichment Rates in In Silico Screening
inferredcites →https://doi.org/10.1021/jm8009958openalex-snapshot
Four-Dimensional Docking: A Fast and Accurate Account of Discrete Receptor Flexibility in Ligand Docking
inferredcites →https://doi.org/10.1023/a:1011115820450openalex-snapshot
DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases
inferredcites →https://doi.org/10.1038/nrd1129openalex-snapshot
Implications of protein flexibility for drug discovery
inferredcites →https://doi.org/10.1039/b208248aopenalex-snapshot
HIV-1 protease: mechanism and drug discovery
inferredcites →https://doi.org/10.1074/jbc.271.42.26157openalex-snapshot
Crystal Structures of Catalytic Subunit of cAMP-dependent Protein Kinase in Complex with Isoquinolinesulfonyl Protein Kinase Inhibitors H7, H8, and H89
inferredcites →https://doi.org/10.1074/jbc.m304842200openalex-snapshot
The Three-dimensional Structure of the Liver X Receptor β Reveals a Flexible Ligand-binding Pocket That Can Accommodate Fundamentally Different Ligands
inferredcites →https://doi.org/10.1089/cmb.2007.0158openalex-snapshot
Minimizing and Learning Energy Functions for Side-Chain Prediction
inferredcites →https://doi.org/10.1093/bioinformatics/bts395openalex-snapshot
Side-chain rotamer changes upon ligand binding: common, crucial, correlate with entropy and rearrange hydrogen bonding
inferredcites →https://doi.org/10.1093/nar/gkr352openalex-snapshot
The FALC-Loop web server for protein loop modeling
inferredcites →https://doi.org/10.1110/ps.03250104openalex-snapshot
Improved side‐chain prediction accuracy using an ab initio potential energy function and a very large rotamer library
inferredcites →https://doi.org/10.1110/ps.041153605openalex-snapshot
Side‐chain flexibility in protein–ligand binding: The minimal rotation hypothesis
inferredcites →https://doi.org/10.1110/ps.062658307openalex-snapshot
IRECS: A new algorithm for the selection of most probable ensembles of side‐chain conformations in protein models
inferredcites →https://doi.org/10.1110/ps.8.3.603openalex-snapshot
Comparison of protein–protein interactions in serine protease‐inhibitor and antibody‐antigen complexes: Implications for the protein docking problem
inferredcites →https://doi.org/10.1186/1471-2105-11-374openalex-snapshot
Protein structure modelling and evaluation based on a 4-distance description of side-chain interactions

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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GalaxyDock2: Protein–ligand docking using beta‐complex and global optimization
inferred← citeshttps://doi.org/10.1002/jcc.26050openalex-snapshot
GalaxyDock3: Protein–ligand docking that considers the full ligand conformational flexibility
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Improvements, trends, and new ideas in molecular docking: 2012–2013 in review
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Multi‐state modeling of G‐protein coupled receptors at experimental accuracy
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Computational Multi-Target Drug Design
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Free-Docking and Template-Based Docking: Physics Versus Knowledge-Based Docking
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GalaxyDock BP2 score: a hybrid scoring function for accurate protein–ligand docking
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Prediction of CB[8] host–guest binding free energies in SAMPL6 using the double-decoupling method
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Receptor–ligand molecular docking
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Software for molecular docking: a review
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Molecular Docking—A Solved Problem?
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Docking strategies
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Virtual screening techniques in pharmaceutical research
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Resources for Docking-Based Virtual Screening
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Molecular docking—A solved problem?
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In silico identification of putative druggable pockets in PRL3, a significant oncology target
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DSDPFlex: Flexible-Receptor Docking with GPU Acceleration
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Evaluation of GalaxyDock Based on the Community Structure–Activity Resource 2013 and 2014 Benchmark Studies
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CSAR Benchmark Exercise 2013: Evaluation of Results from a Combined Computational Protein Design, Docking, and Scoring/Ranking Challenge
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Novel Consensus Docking Strategy to Improve Ligand Pose Prediction
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GalaxyDock-DL: Protein–Ligand Docking by Global Optimization and Neural Network Energy
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Physics-Inspired Accuracy Estimator for Model-Docked Ligand Complexes
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BP-Dock: A Flexible Docking Scheme for Exploring Protein–Ligand Interactions Based on Unbound Structures
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Influence of ligand’s directional configuration, chrysenes as model compounds, on the binding activity with aryl hydrocarbon receptor
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Symmetry-related residues as promising hotspots for the evolution of de novo oligomeric enzymes
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GalaxyRefine: protein structure refinement driven by side-chain repacking
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Pyridoxal 5’-phosphate supplementation modulates the heterologous expression and activity of a PLP dependent model protein in E.coli
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End-to-end protein–ligand complex structure generation with diffusion-based generative models
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Use of machine learning approaches for novel drug discovery
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FLEXIBLE TOPOLOGY: A NEW METHOD FOR DYNAMIC DRUG DESIGN
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DSDPFlex: An Improved Flexible-Receptor Docking Method with GPU Acceleration
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DSDPFlex: An Improved Flexible-Receptor Docking Method with GPU Acceleration
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Accurately accelerating drug design workflow
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Scoring Functions for Protein-Ligand Binding Affinity Prediction Using Structure-based Deep Learning: A Review
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Unveiling the Binding between the Armadillo-Repeat Domain of Plakophilin 1 and the Intrinsically Disordered Transcriptional Repressor RYBP
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Computational Approaches for the Discovery of Human Proteasome Inhibitors: An Overview
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A Review on Computational Software Tools for Drug Design and Discovery
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Docking strategies for predicting protein-ligand interactions and their application to structure-based drug design
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Additional file 1 of A multilayer dynamic perturbation analysis method for predicting ligand–protein interactions
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Additional file 1 of End-to-end protein–ligand complex structure generation with diffusion-based generative models
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Development of novel algorithms for data-driven prediction of interactions between proteins and small molecules
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