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Assessment of Pharmaceutical Protein–Ligand Pose and Affinity Predictions in CASP16

https://doi.org/10.1002/prot.70061
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What this work says

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

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The 1.8 A crystal structure of human cathepsin G in complex with Suc‐Val‐Pro‐PheP‐(OPh)2: a Janus‐faced proteinase with two opposite specificities.
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AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
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Assessment of protein assembly prediction in CASP13
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High‐accuracy protein structure prediction in CASP14
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Applying and improving AlphaFold at CASP14
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New prediction categories in CASP15
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Assessment of protein–ligand complexes in CASP15
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Assessment of three‐dimensional RNA structure prediction in CASP15
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A large‐scale experiment to assess protein structure prediction methods
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The CASP 16 Experimental Protein–Ligand Datasets
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The SAMPL2 blind prediction challenge: introduction and overview
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D3R grand challenge 2015: Evaluation of protein–ligand pose and affinity predictions
inferredcites →https://doi.org/10.1007/s10822-017-0049-yopenalex-snapshot
Performance of HADDOCK and a simple contact-based protein–ligand binding affinity predictor in the D3R Grand Challenge 2
inferredcites →https://doi.org/10.1007/s10822-017-0088-4openalex-snapshot
D3R Grand Challenge 2: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies
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D3R Grand Challenge 3: blind prediction of protein–ligand poses and affinity rankings
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D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies
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SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction
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An overview of the SAMPL8 host–guest binding challenge
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Structure–Activity relationship of benzo[b]thiophene-2-sulfonamide derivatives as novel human chymase inhibitors
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Structure-based design, synthesis, and binding mode analysis of novel and potent chymase inhibitors
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CSAlign and CSAlign-Dock: Structure alignment of ligands considering full flexibility and application to protein–ligand docking
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Evaluating GPCR modeling and docking strategies in the era of deep learning-based protein structure prediction
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AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings
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Comparative Assessment of Pose Prediction Accuracy in RNA–Ligand Docking
inferredcites →https://doi.org/10.1021/acs.jcim.4c02296openalex-snapshot
The Need for Continuing Blinded Pose- and Activity Prediction Benchmarks
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CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma
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Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations
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Structural, Electronic, and Electrostatic Determinants for Inhibitor Binding to Subsites S1 and S2 in SARS-CoV-2 Main Protease
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CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes
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Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field
inferredcites →https://doi.org/10.1038/s41467-025-67403-2openalex-snapshot
Enantioselective protein affinity selection mass spectrometry (E-ASMS)
inferredcites →https://doi.org/10.1038/s41586-021-03819-2openalex-snapshot
Highly accurate protein structure prediction with AlphaFold
inferredcites →https://doi.org/10.1038/s41587-023-01773-0openalex-snapshot
Fast and accurate protein structure search with Foldseek
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State-specific protein–ligand complex structure prediction with a multiscale deep generative model
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PDB-wide collection of binding data: current status of the PDBbind database
inferredcites →https://doi.org/10.1093/bioinformatics/btz422openalex-snapshot
AlphaFold at CASP13
inferredcites →https://doi.org/10.1093/bioinformatics/btz459openalex-snapshot
AutoDock CrankPep : combining folding and docking to predict protein–peptide complexes
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A NEW MEASURE OF RANK CORRELATION
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SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information
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ChEMBL: towards direct deposition of bioassay data
inferredcites →https://doi.org/10.1093/nar/gky427openalex-snapshot
SWISS-MODEL: homology modelling of protein structures and complexes
inferredcites →https://doi.org/10.1101/2024.11.19.624167openalex-snapshot
Boltz-1 Democratizing Biomolecular Interaction Modeling
inferredcites →https://doi.org/10.1101/2025.02.03.636309openalex-snapshot
Have protein-ligand cofolding methods moved beyond memorisation?
inferredcites →https://doi.org/10.1107/s0567739476001873openalex-snapshot
A solution for the best rotation to relate two sets of vectors
inferredcites →https://doi.org/10.1126/science.adl2528openalex-snapshot
Generalized biomolecular modeling and design with RoseTTAFold All-Atom
inferredcites →https://doi.org/10.1186/s13321-021-00522-2openalex-snapshot
GNINA 1.0: molecular docking with deep learning
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GNINA 1.3: the next increment in molecular docking with deep learning
inferredcites →https://doi.org/10.26434/chemrxiv.8100203.v1openalex-snapshot
SuCOS is Better than RMSD for Evaluating Fragment Elaboration and Docking Poses
inferredcites →https://doi.org/10.3389/fphar.2021.699535openalex-snapshot
Synthesis, Characterization, and in vivo Evaluation of a Novel Potent Autotaxin-Inhibitor

What points at this work

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

inferred← citeshttps://doi.org/10.1002/jts.70094openalex-snapshot
From therapeutic promise to evidentiary discipline: Reassessing MDMA‐assisted psychotherapy for posttraumatic stress disorder
inferred← citeshttps://doi.org/10.1002/prot.70032openalex-snapshot
Ligand Binding Prediction on Pharmaceutical and Nucleic Acid Targets by the CoDock Group in CASP16
inferred← citeshttps://doi.org/10.1002/prot.70042openalex-snapshot
Updates to the CASP Infrastructure in 2024
inferred← citeshttps://doi.org/10.1002/prot.70053openalex-snapshot
The CASP 16 Experimental Protein–Ligand Datasets
inferred← citeshttps://doi.org/10.1002/prot.70072openalex-snapshot
Assessment of Nucleic Acid Structure Prediction in CASP16
inferred← citeshttps://doi.org/10.1016/j.bpj.2026.04.011openalex-snapshot
Docking-based virtual screening: Past, present, and future
inferred← citeshttps://doi.org/10.1016/j.xcrp.2026.103448openalex-snapshot
Explainable AI reveals the allosteric blind spot in protein-ligand binding predictions
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c01985openalex-snapshot
TEMPL: A Template-Based Protein–Ligand Pose Prediction Baseline
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c02591openalex-snapshot
BA-Pred and RMSD-Pred: Integrated Graph Neural Network Models for Accurate Protein–Ligand Binding Affinity and Binding Pose Prediction
inferred← citeshttps://doi.org/10.1038/s41467-026-73410-8openalex-snapshot
Mapping the avoid-ome: a systematic open-science approach to predictive ADMET
inferred← citeshttps://doi.org/10.1038/s41594-026-01797-5openalex-snapshot
Evaluating generalization in protein–ligand cofolding methods
inferred← citeshttps://doi.org/10.1038/s44386-026-00066-1openalex-snapshot
On the generalization and usability of cofolding models for GPCR drug discovery
inferred← citeshttps://doi.org/10.1101/2025.06.14.659707openalex-snapshot
Boltz-2: Towards Accurate and Efficient Binding Affinity Prediction
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DockFormer: Affinity Prediction and Flexible Docking with Pair Transformer
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FlashBind: Towards Accurate and Efficient Structure-based Virtual Screening
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Decoding the Allosteric Paradox: A Dual Framework Integrating AI Cofolding Models with Landscape-Guided Interpretable AI Framework of Ligand-Protein Binding
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Improving AlphaFold3 by Engineering MSA and Template Inputs
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