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Exploring the Potential of Protein-Based Pharmacophore Models in Ligand Pose Prediction and Ranking

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What this work says

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

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Critical evaluation of search algorithms for automated molecular docking and database screening

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Flexible docking using tabu search and an empirical estimate of binding affinity

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Application of structure‐based focusing to the estrogen receptor

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Evaluation of the performance of four molecular docking programs on a diverse set of protein‐ligand complexes

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Can we trust docking results? Evaluation of seven commonly used programs on PDBbind database

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Automatic identification and representation of protein binding sites for molecular docking

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Comparing protein–ligand docking programs is difficult

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The computer program LUDI: A new method for the de novo design of enzyme inhibitors

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GALAHAD: 1. Pharmacophore identification by hypermolecular alignment of ligands in 3D

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PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results

inferredcites →https://doi.org/10.1016/0022-2836(82)90153-xopenalex-snapshot

A geometric approach to macromolecule-ligand interactions

inferredcites →https://doi.org/10.1016/j.ddtec.2010.09.002openalex-snapshot

Grid-derived structure-based 3D pharmacophores and their performance compared to docking

inferredcites →https://doi.org/10.1021/bk-1995-0606.ch024openalex-snapshot

Distance Comparisons: A New Strategy for Examining Three-Dimensional Structure—Activity Relationships

inferredcites →https://doi.org/10.1021/ci049885eopenalex-snapshot

LigandScout: 3-D Pharmacophores Derived from Protein-Bound Ligands and Their Use as Virtual Screening Filters

inferredcites →https://doi.org/10.1021/ci050141qopenalex-snapshot

A Comparative Study on the Application of Hierarchical−Agglomerative Clustering Approaches to Organize Outputs of Reiterated Docking Runs

inferredcites →https://doi.org/10.1021/ci200620hopenalex-snapshot

Protein Pharmacophore Selection Using Hydration-Site Analysis

inferredcites →https://doi.org/10.1021/ci7003626openalex-snapshot

Maximum Common Binding Modes (MCBM): Consensus Docking Scoring Using Multiple Ligand Information and Interaction Fingerprints

inferredcites →https://doi.org/10.1021/ci800064zopenalex-snapshot

Hot-Spots-Guided Receptor-Based Pharmacophores (HS-Pharm): A Knowledge-Based Approach to Identify Ligand-Anchoring Atoms in Protein Cavities and Prioritize Structure-Based Pharmacophores

inferredcites →https://doi.org/10.1021/ci800105popenalex-snapshot

Targets Looking for Drugs: A Multistep Computational Protocol for the Development of Structure-Based Pharmacophores and Their Applications for Hit Discovery

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Comparative Assessment of Scoring Functions on a Diverse Test Set

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Identification of Common Functional Configurations Among Molecules

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Automated Pharmacophore Identification for Large Chemical Data Sets

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

inferredcites →https://doi.org/10.1021/jm030580lopenalex-snapshot

The PDBbind Database: Collection of Binding Affinities for Protein−Ligand Complexes with Known Three-Dimensional Structures

inferredcites →https://doi.org/10.1021/jm048957qopenalex-snapshot

The PDBbind Database: Methodologies and Updates

inferredcites →https://doi.org/10.1023/a:1007996124545openalex-snapshot

Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes

inferredcites →https://doi.org/10.1023/a:1016357811882openalex-snapshot

Further development and validation of empirical scoring functions for structure-based binding affinity prediction

inferredcites →https://doi.org/10.1107/s0567739476001873openalex-snapshot

A solution for the best rotation to relate two sets of vectors

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Algorithm 457: finding all cliques of an undirected graph

What points at this work

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

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ClassyPose: A Machine‐Learning Classification Model for Ligand Pose Selection Applied to Virtual Screening in Drug Discovery

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A pose prediction approach based on ligand 3D shape similarity

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Structure-based pharmacophore modeling approaches using probe-based methods

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Multi-level structure-based pharmacophore modelling of caspase-3-non-peptide complexes: Extracting essential pharmacophore features and its application to virtual screening

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Mapping of Protein Binding Sites using clustering algorithms - Development of a pharmacophore based drug discovery tool

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AutoPH4: An Automated Method for Generating Pharmacophore Models from Protein Binding Pockets

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Apo2ph4 : A Versatile Workflow for the Generation of Receptor-based Pharmacophore Models for Virtual Screening

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Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein–Protein Interactions

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All in One: Cavity Detection, Druggability Estimate, Cavity-Based Pharmacophore Perception, and Virtual Screening

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Conservation and Relevance of Pharmacophore Point Types

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Pharmacophore-Based Similarity Scoring for DOCK

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FitDock: protein–ligand docking by template fitting

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Improving the accuracy of pose prediction by incorporating symmetry-related molecules

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