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Structure-Based Predictions of Activity Cliffs
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94
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Contribution of Explicit Solvent Effects to the Binding Affinity of Small‐Molecule Inhibitors in Blood Coagulation Factor Serine Proteases
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From Activity Cliffs to Target‐Specific Scoring Models and Pharmacophore Hypotheses
inferredcites →https://doi.org/10.1002/jcc.540150503openalex-snapshot
ICM—A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation
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Identifying Activity Cliff Generators of PPAR Ligands Using SAS Maps
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Development of a new physics‐based internal coordinate mechanics force field and its application to protein loop modeling
inferredcites →https://doi.org/10.1007/0-306-46857-3_13openalex-snapshot
Similarity and Dissimilarity: A Medicinal Chemist’s View
inferredcites →https://doi.org/10.1007/978-1-60761-839-3_3openalex-snapshot
The Ups and Downs of Structure–Activity Landscapes
inferredcites →https://doi.org/10.1007/978-1-61779-588-6_10openalex-snapshot
Methods of Protein Structure Comparison
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A new method for ligand docking to flexible receptors by dual alanine scanning and refinement (SCARE)
inferredcites →https://doi.org/10.1007/s10822-008-9196-5openalex-snapshot
Recommendations for evaluation of computational methods
inferredcites →https://doi.org/10.1007/s10822-012-9547-0openalex-snapshot
Docking and scoring with ICM: the benchmarking results and strategies for improvement
inferredcites →https://doi.org/10.1016/j.bmcl.2010.07.129openalex-snapshot
Optimization of N-benzyl-benzoxazol-2-ones as receptor antagonists of macrophage migration inhibitory factor (MIF)
inferredcites →https://doi.org/10.1016/j.chembiol.2004.03.033openalex-snapshot
Structure-Activity Relationships in Purine-Based Inhibitor Binding to HSP90 Isoforms
inferredcites →https://doi.org/10.1016/j.chembiol.2007.03.011openalex-snapshot
Molecular Similarity Analysis Uncovers Heterogeneous Structure-Activity Relationships and Variable Activity Landscapes
inferredcites →https://doi.org/10.1016/j.drudis.2013.03.003openalex-snapshot
Matched Molecular Pair Analysis in drug discovery
inferredcites →https://doi.org/10.1016/j.drudis.2014.02.003openalex-snapshot
Activity cliffs in drug discovery: Dr Jekyll or Mr Hyde?
inferredcites →https://doi.org/10.1016/j.ejmech.2012.10.024openalex-snapshot
Application of a post-docking procedure based on MM-PBSA and MM-GBSA on single and multiple protein conformations
inferredcites →https://doi.org/10.1016/j.sbi.2008.01.004openalex-snapshot
Flexible ligand docking to multiple receptor conformations: a practical alternative
inferredcites →https://doi.org/10.1016/j.str.2011.05.012openalex-snapshot
Status of GPCR Modeling and Docking as Reflected by Community-wide GPCR Dock 2010 Assessment
inferredcites →https://doi.org/10.1021/ci060117sopenalex-snapshot
On Outliers and Activity CliffsWhy QSAR Often Disappoints
inferredcites →https://doi.org/10.1021/ci1001845openalex-snapshot
Chemical Substitutions That Introduce Activity Cliffs Across Different Compound Classes and Biological Targets
inferredcites →https://doi.org/10.1021/ci2002473openalex-snapshot
From Activity Cliffs to Activity Ridges: Informative Data Structures for SAR Analysis
inferredcites →https://doi.org/10.1021/ci2005934openalex-snapshot
Potential and Limitations of Ensemble Docking
inferredcites →https://doi.org/10.1021/ci300033eopenalex-snapshot
Exploration of 3D Activity Cliffs on the Basis of Compound Binding Modes and Comparison of 2D and 3D Cliffs
inferredcites →https://doi.org/10.1021/ci3001088openalex-snapshot
ALiBERO: Evolving a Team of Complementary Pocket Conformations Rather than a Single Leader
inferredcites →https://doi.org/10.1021/ci3001138openalex-snapshot
MMP-Cliffs: Systematic Identification of Activity Cliffs on the Basis of Matched Molecular Pairs
inferredcites →https://doi.org/10.1021/ci3001277openalex-snapshot
ZINC: A Free Tool to Discover Chemistry for Biology
inferredcites →https://doi.org/10.1021/ci300158vopenalex-snapshot
Systematic Identification and Classification of Three-Dimensional Activity Cliffs
inferredcites →https://doi.org/10.1021/ci3003683openalex-snapshot
Identification of Multitarget Activity Ridges in High-Dimensional Bioactivity Spaces
inferredcites →https://doi.org/10.1021/ci4004199openalex-snapshot
Accuracy Assessment and Automation of Free Energy Calculations for Drug Design
inferredcites →https://doi.org/10.1021/ci4007326openalex-snapshot
Application of Docking and QM/MM-GBSA Rescoring to Screen for Novel Myt1 Kinase Inhibitors
inferredcites →https://doi.org/10.1021/ci5003735openalex-snapshot
Improving Docking Results via Reranking of Ensembles of Ligand Poses in Multiple X-ray Protein Conformations with MM-GBSA
inferredcites →https://doi.org/10.1021/ci6004993openalex-snapshot
Supervised Consensus Scoring for Docking and Virtual Screening
inferredcites →https://doi.org/10.1021/ci7004093openalex-snapshot
Structure−Activity Landscape Index: Identifying and Quantifying Activity Cliffs
inferredcites →https://doi.org/10.1021/ci700470copenalex-snapshot
Investigation of MM-PBSA Rescoring of Docking Poses
inferredcites →https://doi.org/10.1021/ci9003943openalex-snapshot
Recipes for the Selection of Experimental Protein Conformations for Virtual Screening
inferredcites →https://doi.org/10.1021/ct300899nopenalex-snapshot
Free Energy Calculations Reveal the Origin of Binding Preference for Aminoadamantane Blockers of Influenza A/M2TM Pore
inferredcites →https://doi.org/10.1021/ja512751qopenalex-snapshot
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/10.1021/jm048972vopenalex-snapshot
Unveiling the Full Potential of Flexible Receptor Docking Using Multiple Crystallographic Structures
inferredcites →https://doi.org/10.1021/jm050540copenalex-snapshot
Novel Procedure for Modeling Ligand/Receptor Induced Fit Effects
inferredcites →https://doi.org/10.1021/jm0582165openalex-snapshot
Searching Techniques for Databases of Two- and Three-Dimensional Chemical Structures
inferredcites →https://doi.org/10.1021/jm0608356openalex-snapshot
Benchmarking Sets for Molecular Docking
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/jm0705713openalex-snapshot
SAR Index: Quantifying the Nature of Structure−Activity Relationships
inferredcites →https://doi.org/10.1021/jm200452dopenalex-snapshot
Matched Molecular Pairs as a Medicinal Chemistry Tool
inferredcites →https://doi.org/10.1021/jm201706bopenalex-snapshot
Exploring Activity Cliffs in Medicinal Chemistry
inferredcites →https://doi.org/10.1021/jm300687eopenalex-snapshot
Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking
inferredcites →https://doi.org/10.1021/jm401120gopenalex-snapshot
Recent Progress in Understanding Activity Cliffs and Their Utility in Medicinal Chemistry
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/10.1021/jm901647popenalex-snapshot
Structure-Based Discovery of Novel Chemotypes for Adenosine A2AReceptor Antagonists
inferredcites →https://doi.org/10.1023/a:1027221424359openalex-snapshot
Similarity and Dissimilarity: A Medicinal Chemist's View
inferredcites →https://doi.org/10.1038/nrd1549openalex-snapshot
Docking and scoring in virtual screening for drug discovery: methods and applications
inferredcites →https://doi.org/10.1038/nrd3139openalex-snapshot
Virtual screening: an endless staircase?
inferredcites →https://doi.org/10.1038/sj.bjp.0707515openalex-snapshot
Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go
inferredcites →https://doi.org/10.1093/bioinformatics/bts249openalex-snapshot
DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets
inferredcites →https://doi.org/10.1093/nar/gkl999openalex-snapshot
BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities
inferredcites →https://doi.org/10.1093/nar/gkr777openalex-snapshot
ChEMBL: a large-scale bioactivity database for drug discovery
inferredcites →https://doi.org/10.1093/nar/gkr825openalex-snapshot
Pocketome: an encyclopedia of small-molecule binding sites in 4D
inferredcites →https://doi.org/10.1111/cbdd.12115openalex-snapshot
Activity Cliffs: Facts or Artifacts?
inferredcites →https://doi.org/10.1111/j.1747-0285.2007.00605.xopenalex-snapshot
Atomic Property Fields: Generalized 3D Pharmacophoric Potential for Automated Ligand Superposition, Pharmacophore Elucidation and 3D QSAR
inferredcites →https://doi.org/10.1186/1758-2946-6-11openalex-snapshot
On the validity versus utility of activity landscapes: are all activity cliffs statistically significant?
inferredcites →https://doi.org/10.12688/f1000research.2-199.v1openalex-snapshot
Advancing the activity cliff concept
inferredcites →https://doi.org/10.1371/journal.pone.0018845openalex-snapshot
Systematic Exploitation of Multiple Receptor Conformations for Virtual Ligand Screening
inferredcites →https://doi.org/10.1517/17460441.2012.679616openalex-snapshot
Modeling of activity landscapes for drug discovery
inferredcites →https://doi.org/10.2174/13816128113199990604openalex-snapshot
Free Energy Calculations to Estimate Ligand-Binding Affinities in Structure-Based Drug Design
inferredcites →https://doi.org/10.2174/138920306778559395openalex-snapshot
Scoring Functions for Protein-Ligand Docking
inferredcites →https://doi.org/10.2174/156802610790232288openalex-snapshot
The Role of Water Molecules in Computational Drug Design
inferredcites →https://doi.org/10.2174/156802612804547335openalex-snapshot
Compound Activity Prediction Using Models of Binding Pockets or Ligand Properties in 3D
inferredcites →https://doi.org/10.3390/ijms15023253openalex-snapshot
Rationalization of Activity Cliffs of a Sulfonamide Inhibitor of DNA Methyltransferases with Induced-Fit Docking
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Pharmacophore Modeling of Targets Infested with Activity Cliffs via Molecular Dynamics Simulation Coupled with QSAR and Comparison with other Pharmacophore Generation Methods: KDR as Case Study
inferred← citeshttps://doi.org/10.1007/s00044-019-02377-7openalex-snapshot
QSAR-guided pharmacophore modeling and subsequent virtual screening identify novel TYK2 inhibitor
inferred← citeshttps://doi.org/10.1007/s10822-017-0058-xopenalex-snapshot
Ligand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach
inferred← citeshttps://doi.org/10.1007/s10822-019-00225-9openalex-snapshot
Macrocycle modeling in ICM: benchmarking and evaluation in D3R Grand Challenge 4
inferred← citeshttps://doi.org/10.1007/s10822-020-00315-zopenalex-snapshot
Advances in exploring activity cliffs
inferred← citeshttps://doi.org/10.1007/s10822-025-00721-1openalex-snapshot
Deep learning model for activity cliffs prediction: a comprehensive approach to protein kinase inhibitors
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Matched Molecular Pair Analysis in Short: Algorithms, Applications and Limitations
inferred← citeshttps://doi.org/10.1016/j.jmgm.2020.107615openalex-snapshot
Pharmacophore modeling of JAK1: A target infested with activity-cliffs
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ACtriplet: An improved deep learning model for activity cliffs prediction by integrating triplet loss and pre-training
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OptiMol : Optimization of Binding Affinities in Chemical Space for Drug Discovery
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c00327openalex-snapshot
ACGCN: Graph Convolutional Networks for Activity Cliff Prediction between Matched Molecular Pairs
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c01073openalex-snapshot
Exposing the Limitations of Molecular Machine Learning with Activity Cliffs
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c01530openalex-snapshot
Anatomy of Potency Predictions Focusing on Structural Analogues with Increasing Potency Differences Including Activity Cliffs
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00477openalex-snapshot
Integration of Ligand and Structure Based Approaches for CSAR-2014
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00227openalex-snapshot
Structure-Based Kinase Profiling To Understand the Polypharmacological Behavior of Therapeutic Molecules
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b01123openalex-snapshot
Quantum Mechanical Investigation of Three-Dimensional Activity Cliffs Using the Molecules-in-Molecules Fragmentation-Based Method
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.1c00575openalex-snapshot
Discovery and SAR Evolution of Pyrazole Azabicyclo[3.2.1]octane Sulfonamides as a Novel Class of Non-Covalent N-Acylethanolamine-Hydrolyzing Acid Amidase (NAAA) Inhibitors for Oral Administration
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5b01849openalex-snapshot
De Novo Design at the Edge of Chaos
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.8b01105openalex-snapshot
Nuclear Receptors Database Including Negative Data (NR-DBIND): A Database Dedicated to Nuclear Receptors Binding Data Including Negative Data and Pharmacological Profile
inferred← citeshttps://doi.org/10.1021/acsomega.9b02221openalex-snapshot
Evolving Concept of Activity Cliffs
inferred← citeshttps://doi.org/10.1021/bk-2016-1222.ch008openalex-snapshot
Coping with Complexity in Ligand-Based De Novo Design
inferred← citeshttps://doi.org/10.1038/s41467-025-57582-3openalex-snapshot
A data-driven generative strategy to avoid reward hacking in multi-objective molecular design
inferred← citeshttps://doi.org/10.1039/9781782623731-00120openalex-snapshot
Chemical Similarity, Shape Matching and QSAR
inferred← citeshttps://doi.org/10.1039/c5ra12339aopenalex-snapshot
Activity landscape sweeping: insights into the mechanism of inhibition and optimization of DNMT1 inhibitors
inferred← citeshttps://doi.org/10.1039/c6ra26230aopenalex-snapshot
Getting SMARt in drug discovery: chemoinformatics approaches for mining structure–multiple activity relationships
inferred← citeshttps://doi.org/10.1039/c8cp03320jopenalex-snapshot
Experimental study and computational modelling of cruzain cysteine protease inhibition by dipeptidyl nitriles
inferred← citeshttps://doi.org/10.1039/c9md00463gopenalex-snapshot
Introducing a new category of activity cliffs combining different compound similarity criteria
inferred← citeshttps://doi.org/10.1039/d2dd00077fopenalex-snapshot
DeepAC – conditional transformer-based chemical language model for the prediction of activity cliffs formed by bioactive compounds
inferred← citeshttps://doi.org/10.1080/17460441.2017.1353494openalex-snapshot
Representation and identification of activity cliffs
inferred← citeshttps://doi.org/10.1101/2020.05.04.077701openalex-snapshot
JavaDL: a Java-based Deep Learning Tool to Predict Drug Responses
inferred← citeshttps://doi.org/10.1145/3770855.3819046openalex-snapshot
Incorporating 3D Structural Information for Activity Cliff Analysis
inferred← citeshttps://doi.org/10.1186/s13321-021-00516-0openalex-snapshot
Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study
inferred← citeshttps://doi.org/10.1186/s13321-022-00676-7openalex-snapshot
Large-scale prediction of activity cliffs using machine and deep learning methods of increasing complexity
inferred← citeshttps://doi.org/10.1186/s13321-023-00708-wopenalex-snapshot
Exploring QSAR models for activity-cliff prediction
inferred← citeshttps://doi.org/10.1186/s13321-025-01006-3openalex-snapshot
Activity cliff-aware reinforcement learning for de novo drug design
inferred← citeshttps://doi.org/10.3389/fphys.2015.00371openalex-snapshot
Historeceptomic Fingerprints for Drug-Like Compounds
inferred← citeshttps://doi.org/10.3389/frai.2023.1069353openalex-snapshot
Development and evaluation of a java-based deep neural network method for drug response predictions
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Comparative Study of Genetic and Antibacterial Profiles of Nigerian Indigenous and Exotic Varieties of Garlic (Allium sativum)
inferred← citeshttps://doi.org/10.6084/m9.figshare.26559899openalex-snapshot
Additional file 1 of Large-scale prediction of activity cliffs using machine and deep learning methods of increasing complexity
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