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Computational Method To Identify Druggable Binding Sites That Target Protein–Protein Interactions

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What this work says

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

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Automatic identification and representation of protein binding sites for molecular docking

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A method for localizing ligand binding pockets in protein structures

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On the nature of cavities on protein surfaces: Application to the identification of drug‐binding sites

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Detection of pockets on protein surfaces using small and large probe spheres to find putative ligand binding sites

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Automated prediction of ligand‐binding sites in proteins

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Improving accuracy and efficiency of blind protein‐ligand docking by focusing on predicted binding sites

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The Automatic Search for Ligand Binding Sites in Proteins of Known Three-dimensional Structure Using only Geometric Criteria

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Anatomy of hot spots in protein interfaces

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Structural response to mutation at a protein-protein interface 1 1Edited by R. Huber

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McVol - A program for calculating protein volumes and identifying cavities by a Monte Carlo algorithm

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Epik: a software program for pK a prediction and protonation state generation for drug-like molecules

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Towards the comprehensive, rapid, and accurate prediction of the favorable tautomeric states of drug-like molecules in aqueous solution

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Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments

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Beyond structural genomics: computational approaches for the identification of ligand binding sites in protein structures

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The road less traveled: modulating signal transduction enzymes by inhibiting their protein–protein interactions

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Context-Based Identification of Protein-Protein Interfaces and “Hot-Spot” Residues

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Critical review of the role of HTS in drug discovery

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Predicting druggable binding sites at the protein–protein interface

inferredcites →https://doi.org/10.1016/j.drudis.2010.05.015openalex-snapshot

Druggable pockets and binding site centric chemical space: a paradigm shift in drug discovery

inferredcites →https://doi.org/10.1016/j.jmgm.2005.08.002openalex-snapshot

Exploring protein–ligand recognition with Binding MOAD

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Molecular dynamics simulations of the conformational changes in signal transducers and activators of transcription, Stat1 and Stat3

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Alkylation of Cysteine 468 in Stat3 Defines a Novel Site for Therapeutic Development

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ZINC: A Free Tool to Discover Chemistry for Biology

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Binding Response: A Descriptor for Selecting Ligand Binding Site on Protein Surfaces

inferredcites →https://doi.org/10.1021/ci800324mopenalex-snapshot

Identifying and Characterizing Binding Sites and Assessing Druggability

inferredcites →https://doi.org/10.1021/ct300117jopenalex-snapshot

Druggability Assessment of Allosteric Proteins by Dynamics Simulations in the Presence of Probe Molecules

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A computational procedure for determining energetically favorable binding sites on biologically important macromolecules

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Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy

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Glide: A New Approach for Rapid, Accurate Docking and Scoring. 2. Enrichment Factors in Database Screening

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Studies Leading to Potent, Dual Inhibitors of Bcl-2 and Bcl-xL

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Quinazoline Sulfonamides as Dual Binders of the Proteins B-Cell Lymphoma 2 and B-Cell Lymphoma Extra Long with Potent Proapoptotic Cell-Based Activity

inferredcites →https://doi.org/10.1021/jm801385dopenalex-snapshot

Binding Site Detection and Druggability Index from First Principles

inferredcites →https://doi.org/10.1023/a:1008124202956openalex-snapshot

Fast prediction and visualization of protein binding pockets with PASS

inferredcites →https://doi.org/10.1038/nature06526openalex-snapshot

Reaching for high-hanging fruit in drug discovery at protein–protein interfaces

inferredcites →https://doi.org/10.1038/nchembio0306-112openalex-snapshot

Between a rock and a hard place?

inferredcites →https://doi.org/10.1063/1.3474951openalex-snapshot

Molecular dynamics simulation with weak coupling to heat and material baths

inferredcites →https://doi.org/10.1073/pnas.0308751101openalex-snapshot

Predicted 3D structure for the human β2 adrenergic receptor and its binding site for agonists and antagonists

inferredcites →https://doi.org/10.1073/pnas.202485799openalex-snapshot

A simple physical model for binding energy hot spots in protein–protein complexes

inferredcites →https://doi.org/10.1073/pnas.97.20.10712openalex-snapshot

Molecular mechanisms underlying differential odor responses of a mouse olfactory receptor

inferredcites →https://doi.org/10.1074/jbc.270.32.19008openalex-snapshot

A Binding Interface on the I Domain of Lymphocyte Function-associated Antigen-1 (LFA-1) Required for Specific Interaction with Intercellular Adhesion Molecule 1 (ICAM-1)

inferredcites →https://doi.org/10.1074/jbc.273.44.28937openalex-snapshot

Mapping the Intercellular Adhesion Molecule-1 and -2 Binding Site on the Inserted Domain of Leukocyte Function-associated Antigen-1

inferredcites →https://doi.org/10.1074/jbc.m306021200openalex-snapshot

Bcl-XL Mutations Suppress Cellular Sensitivity to Antimycin A

inferredcites →https://doi.org/10.1074/mcp.m400159-mcp200openalex-snapshot

Pocketome via Comprehensive Identification and Classification of Ligand Binding Envelopes

inferredcites →https://doi.org/10.1093/bioinformatics/bti315openalex-snapshot

Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites

inferredcites →https://doi.org/10.1093/bioinformatics/btl079openalex-snapshot

Predicting protein interaction sites: binding hot-spots in protein–protein and protein–ligand interfaces

inferredcites →https://doi.org/10.1093/nar/gkg512openalex-snapshot

CASTp: Computed Atlas of Surface Topography of proteins

inferredcites →https://doi.org/10.1093/nar/gki586openalex-snapshot

MEDock: a web server for efficient prediction of ligand binding sites based on a novel optimization algorithm

inferredcites →https://doi.org/10.1093/nar/gkj017openalex-snapshot

PINT: Protein-protein Interactions Thermodynamic Database

inferredcites →https://doi.org/10.1110/ps.062247506openalex-snapshot

Localization of binding sites in protein structures by optimization of a composite scoring function

inferredcites →https://doi.org/10.1111/j.1747-0285.2007.00483.xopenalex-snapshot

New Method for Fast and Accurate Binding‐site Identification and Analysis

inferredcites →https://doi.org/10.1126/science.275.5302.983openalex-snapshot

Structure of Bcl-x L -Bak Peptide Complex: Recognition Between Regulators of Apoptosis

inferredcites →https://doi.org/10.1126/science.7529940openalex-snapshot

A Hot Spot of Binding Energy in a Hormone-Receptor Interface

inferredcites →https://doi.org/10.1186/1471-2105-10-168openalex-snapshot

Fpocket: An open source platform for ligand pocket detection

inferredcites →https://doi.org/10.1186/1471-2105-7-316openalex-snapshot

CAVER: a new tool to explore routes from protein clefts, pockets and cavities

inferredcites →https://doi.org/10.1186/1472-6807-6-19openalex-snapshot

LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation.

inferredcites →https://doi.org/10.1371/journal.pone.0010109openalex-snapshot

Binding-Site Assessment by Virtual Fragment Screening

inferredcites →https://doi.org/10.1529/biophysj.107.117648openalex-snapshot

Ligand-Stabilized Conformational States of Human β2 Adrenergic Receptor: Insight into G-Protein-Coupled Receptor Activation

What points at this work

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

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Fractal Dimensions of Macromolecular Structures

inferred← citeshttps://doi.org/10.1007/978-1-4939-7756-7_6openalex-snapshot

Molecular Dynamics Simulation and Prediction of Druggable Binding Sites

inferred← citeshttps://doi.org/10.1007/978-94-024-1069-3_10openalex-snapshot

Function Prediction Using Patches, Pockets and Other Surface Properties

inferred← citeshttps://doi.org/10.1007/s10822-016-9975-3openalex-snapshot

Computer-aided drug design at Boehringer Ingelheim

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Protein-protein interaction inhibitors in cancer

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In silico design of low molecular weight protein–protein interaction inhibitors: Overall concept and recent advances

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inferred← citeshttps://doi.org/10.1021/acs.chemrev.5c00046openalex-snapshot

From Concepts to Inhibitors: A Blueprint for Targeting Protein–Protein Interactions

inferred← citeshttps://doi.org/10.1021/acs.jcim.2c01413openalex-snapshot

SiteRadar: Utilizing Graph Machine Learning for Precise Mapping of Protein–Ligand-Binding Sites

inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00103openalex-snapshot

AlphaSpace: Fragment-Centric Topographical Mapping To Target Protein–Protein Interaction Interfaces

inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.6b00302openalex-snapshot

Identification of Covalent Binding Sites Targeting Cysteines Based on Computational Approaches

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Temporally resolved and interpretable machine learning model of GPCR conformational transition

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Allosteric inhibition of RAN decreases miR-126 biogenesis in endothelial cells and controls acute myeloid leukemia growth

inferred← citeshttps://doi.org/10.1039/c4ib00136bopenalex-snapshot

An improved interolog mapping-based computational prediction of protein–protein interactions with increased network coverage

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Hot-spot analysis for drug discovery targeting protein-protein interactions

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Unraveling allostery within the angiotensin II type 1 receptor for Gα q and β-arrestin coupling

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Computer prediction of paratope on antithrombotic antibody 10B12 and epitope on platelet glycoprotein VI via molecular dynamics simulation

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