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Exploring Activity Cliffs in Medicinal Chemistry
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Chemoinformatics in Drug Discovery
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Structure Modification in Chemical Databases
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From Structure–Activity to Structure–Selectivity Relationships: Quantitative Assessment, Selectivity Cliffs, and Key Compounds
inferredcites →https://doi.org/10.1002/cmdc.201100179openalex-snapshot
From Activity Cliffs to Target‐Specific Scoring Models and Pharmacophore Hypotheses
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QSAR: Rational approaches to the design of bioactive compounds
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Navigating structure–activity landscapes
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Algorithm for Naming Molecular Equivalence Classes Represented by Labeled Pseudographs
inferredcites →https://doi.org/10.1021/ci060117sopenalex-snapshot
On Outliers and Activity CliffsWhy QSAR Often Disappoints
inferredcites →https://doi.org/10.1021/ci100059qopenalex-snapshot
Molecular Scaffolds with High Propensity to Form Multi-Target Activity Cliffs
inferredcites →https://doi.org/10.1021/ci100091eopenalex-snapshot
Rationalizing Three-Dimensional Activity Landscapes and the Influence of Molecular Representations on Landscape Topology and the Formation of Activity Cliffs
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/ci100477mopenalex-snapshot
Design of Multitarget Activity Landscapes That Capture Hierarchical Activity Cliff Distributions
inferredcites →https://doi.org/10.1021/ci200054uopenalex-snapshot
Single R-Group Polymorphisms (SRPs) and R-Cliffs: An Intuitive Framework for Analyzing and Visualizing Activity Cliffs in a Single Analog Series
inferredcites →https://doi.org/10.1021/ci200081kopenalex-snapshot
Consensus Models of Activity Landscapes with Multiple Chemical, Conformer, and Property Representations
inferredcites →https://doi.org/10.1021/ci2001378openalex-snapshot
Molecular Mechanism-Based Network-like Similarity Graphs Reveal Relationships between Different Types of Receptor Ligands and Structural Changes that Determine Agonistic, Inverse-Agonistic, and Antagonistic Effects
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/ci200281vopenalex-snapshot
Multitarget Structure–Activity Relationships Characterized by Activity-Difference Maps and Consensus Similarity Measure
inferredcites →https://doi.org/10.1021/ci2004434openalex-snapshot
Assessing the Confidence Level of Public Domain Compound Activity Data and the Impact of Alternative Potency Measurements on SAR Analysis
inferredcites →https://doi.org/10.1021/ci7004093openalex-snapshot
Structure−Activity Landscape Index: Identifying and Quantifying Activity Cliffs
inferredcites →https://doi.org/10.1021/ci800379qopenalex-snapshot
Characterization of Activity Landscapes Using 2D and 3D Similarity Methods: Consensus Activity Cliffs
inferredcites →https://doi.org/10.1021/ci900243aopenalex-snapshot
Structural Interpretation of Activity Cliffs Revealed by Systematic Analysis of Structure−Activity Relationships in Analog Series
inferredcites →https://doi.org/10.1021/ci900416aopenalex-snapshot
SARANEA: A Freely Available Program To Mine Structure−Activity and Structure−Selectivity Relationship Information in Compound Data Sets
inferredcites →https://doi.org/10.1021/jm0705713openalex-snapshot
SAR Index: Quantifying the Nature of Structure−Activity Relationships
inferredcites →https://doi.org/10.1021/jm100933wopenalex-snapshot
Activity Landscape Representations for Structure−Activity Relationship Analysis
inferredcites →https://doi.org/10.1021/jm200026bopenalex-snapshot
Local Structural Changes, Global Data Views: Graphical Substructure−Activity Relationship Trailing
inferredcites →https://doi.org/10.1021/jm800867gopenalex-snapshot
Structure−Activity Relationship Anatomy by Network-like Similarity Graphs and Local Structure−Activity Relationship Indices
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The Properties of Known Drugs. 1. Molecular Frameworks
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Network pharmacology: the next paradigm in drug discovery
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BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities
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ChEMBL: a large-scale bioactivity database for drug discovery
inferredcites →https://doi.org/10.1111/j.1747-0285.2011.01150.xopenalex-snapshot
Comprehensive Analysis of Single‐ and Multi‐Target Activity Cliffs Formed by Currently Available Bioactive Compounds
inferredcites →https://doi.org/10.1111/j.1747-0285.2011.01256.xopenalex-snapshot
Exploring SAR Continuity in the Vicinity of Activity Cliffs
inferredcites →https://doi.org/10.1385/1-59259-802-1:131openalex-snapshot
Methods for Applying the Quantitative Structure-Activity Relationship Paradigm
inferredcites →https://doi.org/10.2174/092986709789712862openalex-snapshot
Chemogenomic Strategies to Expand the Bioactive Chemical Space
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Systematic Computational Analysis of Structure–Activity Relationships: Concepts, Challenges and Recent Advances
What points at this work
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Optimal Piecewise Linear Regression Algorithm for QSAR Modelling
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Interaction-profile cheminformatic read-across identifies the UV filter benzophenone-4 as a PPARγ agonist and potential obesogen
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Protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (AILDE) approach
inferred← citeshttps://doi.org/10.1016/j.ymeth.2020.06.016openalex-snapshot
Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition
inferred← citeshttps://doi.org/10.1017/s0031182020000207openalex-snapshot
Computational approaches for drug discovery against trypanosomatid-caused diseases
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.2c00245openalex-snapshot
Navigating Transcriptomic Connectivity Mapping Workflows to Link Chemicals with Bioactivities
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.2c00383openalex-snapshot
The Good, The Bad, and The Perplexing: Structural Alerts and Read-Across for Predicting Skin Sensitization Using Human Data
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.3c00074openalex-snapshot
Machine Learning Model for Screening Thyroid Stimulating Hormone Receptor Agonists Based on Updated Datasets and Improved Applicability Domain Metrics
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.5b00197openalex-snapshot
Mechanism-Based QSAR Modeling of Skin Sensitization
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.9b00498openalex-snapshot
Applicability Domains Enhance Application of PPARγ Agonist Classifiers Trained by Drug-like Compounds to Environmental Chemicals
inferred← citeshttps://doi.org/10.1021/acs.chemrev.5c00828openalex-snapshot
Using Machine Learning for Green Substitution of Industrial Chemicals: Integrating Functionality, Hazard, and Life Cycle Impact
inferred← citeshttps://doi.org/10.1021/acs.jafc.2c01425openalex-snapshot
Drug Chemical Space as a Guide for New Herbicide Development: A Cheminformatic Analysis
inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00502openalex-snapshot
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c00515openalex-snapshot
Predicting the Relative Binding Affinity for Reversible Covalent Inhibitors by Free Energy Perturbation Calculations
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.3c01170openalex-snapshot
A High-Quality Data Set of Protein–Ligand Binding Interactions Via Comparative Complex Structure Modeling
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00415openalex-snapshot
Harmonization of QSAR Best Practices and Molecular Docking Provides an Efficient Virtual Screening Tool for Discovering New G-Quadruplex Ligands
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00570openalex-snapshot
Improved Chemical Structure–Activity Modeling Through Data Augmentation
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c00484openalex-snapshot
Enhancing Drug-Target Interaction Prediction through Transfer Learning from Activity Cliff Prediction Tasks
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c00506openalex-snapshot
iCliff Taylor’s Version: Robust and Efficient Activity Cliff Determination
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c00741openalex-snapshot
Bioactivity Deep Learning for Complex Structure-Free Compound-Protein Interaction Prediction
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c00949openalex-snapshot
Task-Specific Activity Cliff Prediction Method Based on Transfer Learning and a Hyper Connection Graph Model
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c02381openalex-snapshot
Uncertainty Quantification in Molecular Machine Learning for Property Predictions under Data Shifts
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c02755openalex-snapshot
Development of Reaction-Centered Encoders and Benchmarking of Enzyme-Reaction Pair Models
inferred← citeshttps://doi.org/10.1021/acs.jcim.6c00407openalex-snapshot
When Trees Guide Molecules: Multiobjective Search in de Novo Drug Design
inferred← citeshttps://doi.org/10.1021/acs.jcim.6c01026openalex-snapshot
NMR-AI: An Open Platform for NMR-Enhanced Molecular Representations and Physicochemical Property Prediction
inferred← citeshttps://doi.org/10.1021/acs.jcim.6c01230openalex-snapshot
QSAR as a Small-Deformation Theory of Effective Free-Energy Landscapes
inferred← citeshttps://doi.org/10.1021/acs.jcim.6c01237openalex-snapshot
Systematic Multi-Target QSAR Benchmarking: Machine Learning Algorithms, Molecular Descriptors, and Validation
inferred← citeshttps://doi.org/10.1021/acs.jcim.6c01658openalex-snapshot
Diversity-Seeking Docking-Guided Molecular Design Discovers Broader Predicted Interaction Profiles across Protein Families
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00110openalex-snapshot
Theoretical Analysis of Activity Cliffs among Benzofuranone-Class Pim1 Inhibitors Using the Fragment Molecular Orbital Method with Molecular Mechanics Poisson–Boltzmann Surface Area (FMO+MM-PBSA) Approach
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00313openalex-snapshot
Regression Modelability Index: A New Index for Prediction of the Modelability of Data Sets in the Development of QSAR Regression Models
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00376openalex-snapshot
Discovering Highly Potent Molecules from an Initial Set of Inactives Using Iterative Screening
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00661openalex-snapshot
Three-Dimensional Activity Landscape Models of Different Design and Their Application to Compound Mapping and Potency Prediction
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00731openalex-snapshot
Off-Pocket Activity Cliffs: A Puzzling Facet of Molecular Recognition
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00841openalex-snapshot
In Silico Design and Analysis of a Kinase-Focused Combinatorial Library Considering Diversity and Quality
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b01120openalex-snapshot
Deep Generative Models for 3D Linker Design
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.jctc.2c01235openalex-snapshot
A Perspective on Explanations of Molecular Prediction Models
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.0c00385openalex-snapshot
Learning Molecular Representations for Medicinal Chemistry
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.0c01605openalex-snapshot
Evaluation of the Structure–Activity Relationship of Microtubule-Targeting 1,2,4-Triazolo[1,5-a]pyrimidines Identifies New Candidates for Neurodegenerative Tauopathies
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.2c00254openalex-snapshot
Quantitative Structure–Activity Relationship (QSAR) Study Predicts Small-Molecule Binding to RNA Structure
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.2c01787openalex-snapshot
Matched Molecular Pair Analysis in Drug Discovery: Methods and Recent Applications
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5b01875openalex-snapshot
A Real-World Perspective on Molecular Design
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6b00738openalex-snapshot
Design, Synthesis, and Evaluation of Thiophene[3,2-d]pyrimidine Derivatives as HIV-1 Non-nucleoside Reverse Transcriptase Inhibitors with Significantly Improved Drug Resistance Profiles
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6b01837openalex-snapshot
Sustainable Practices in Medicinal Chemistry Part 2: Green by Design
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6c00774openalex-snapshot
From Structure to Selectivity: Integrating CADD and AIDD in Rational Medicinal Chemistry Strategies for DYRK1A Inhibitor Discovery
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.8b01626openalex-snapshot
Computational Method to Evaluate Progress in Lead Optimization
inferred← citeshttps://doi.org/10.1021/acs.jpca.7b08298openalex-snapshot
Characterizing Chemical Similarity with Vibrational Spectroscopy: New Insights into the Substituent Effects in Monosubstituted Benzenes
inferred← citeshttps://doi.org/10.1021/acs.jpcb.8b01172openalex-snapshot
Fragment Molecular Orbital Calculations with Implicit Solvent Based on the Poisson–Boltzmann Equation: Implementation and DNA Study
inferred← citeshttps://doi.org/10.1021/acs.jpcc.5c03868openalex-snapshot
Machine Learning-Based Predictions of Henry Coefficients for Long-Chain Alkanes in One-Dimensional Zeolites: Application to Hydroisomerization
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.9b00634openalex-snapshot
From Target to Drug: Generative Modeling for the Multimodal Structure-Based Ligand Design
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.9b01236openalex-snapshot
Systematic Exploration of Activity Cliffs Containing Privileged Substructures
inferred← citeshttps://doi.org/10.1021/acschembio.6b00538openalex-snapshot
Understanding Cytotoxicity and Cytostaticity in a High-Throughput Screening Collection
inferred← citeshttps://doi.org/10.1021/acschemneuro.5c00861openalex-snapshot
Machine Learning for De Novo Molecular Generation: A Comprehensive Review
inferred← citeshttps://doi.org/10.1021/acsmedchemlett.4c00148openalex-snapshot
FOCUS on NOD2: Advancing IBD Drug Discovery with a User-Informed Machine Learning Framework
inferred← citeshttps://doi.org/10.1021/acsomega.4c06146openalex-snapshot
In Silico Structural Insights and Potential Inhibitor Identification Based on the Benzothiazole Core for Targeting Leishmania major Pteridine Reductase 1
inferred← citeshttps://doi.org/10.1021/acsomega.8b01188openalex-snapshot
Rationalizing the Formation of Activity Cliffs in Different Compound Data Sets
inferred← citeshttps://doi.org/10.1021/acsomega.9b00595openalex-snapshot
Integrating the Structure–Activity Relationship Matrix Method with Molecular Grid Maps and Activity Landscape Models for Medicinal Chemistry Applications
inferred← citeshttps://doi.org/10.1021/acsomega.9b02221openalex-snapshot
Evolving Concept of Activity Cliffs
inferred← citeshttps://doi.org/10.1021/acssynbio.9b00105openalex-snapshot
Exploring Chemical Biosynthetic Design Space with Transform-MinER
inferred← citeshttps://doi.org/10.1021/bk-2016-1222.ch004openalex-snapshot
Network Variants for Analyzing Target-Ligand Interactions
inferred← citeshttps://doi.org/10.1021/bk-2016-1222.ch006openalex-snapshot
Molecular Similarity Approaches in Chemoinformatics: Early History and Literature Status
inferred← citeshttps://doi.org/10.1021/cb3001028openalex-snapshot
Rethinking Molecular Similarity: Comparing Compounds on the Basis of Biological Activity
inferred← citeshttps://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
inferred← citeshttps://doi.org/10.1021/ci3000503openalex-snapshot
Searching for Coordinated Activity Cliffs Using Particle Swarm Optimization
inferred← citeshttps://doi.org/10.1021/ci3001138openalex-snapshot
MMP-Cliffs: Systematic Identification of Activity Cliffs on the Basis of Matched Molecular Pairs
inferred← citeshttps://doi.org/10.1021/ci300158vopenalex-snapshot
Systematic Identification and Classification of Three-Dimensional Activity Cliffs
inferred← citeshttps://doi.org/10.1021/ci3002606openalex-snapshot
Data Mining of Protein-Binding Profiling Data Identifies Structural Modifications that Distinguish Selective and Promiscuous Compounds
inferred← citeshttps://doi.org/10.1021/ci300274copenalex-snapshot
Extending the Activity Cliff Concept: Structural Categorization of Activity Cliffs and Systematic Identification of Different Types of Cliffs in the ChEMBL Database
inferred← citeshttps://doi.org/10.1021/ci3002765openalex-snapshot
Navigating High-Dimensional Activity Landscapes: Design and Application of the Ligand-Target Differentiation Map
inferred← citeshttps://doi.org/10.1021/ci300288fopenalex-snapshot
Frequency of Occurrence and Potency Range Distribution of Activity Cliffs in Bioactive Compounds
inferred← citeshttps://doi.org/10.1021/ci300306aopenalex-snapshot
Prediction of Activity Cliffs Using Support Vector Machines
inferred← citeshttps://doi.org/10.1021/ci300362xopenalex-snapshot
Scanning Structure–Activity Relationships with Structure–Activity Similarity and Related Maps: From Consensus Activity Cliffs to Selectivity Switches
inferred← citeshttps://doi.org/10.1021/ci3003683openalex-snapshot
Identification of Multitarget Activity Ridges in High-Dimensional Bioactivity Spaces
inferred← citeshttps://doi.org/10.1021/ci300602mopenalex-snapshot
Introduction of Target Cliffs as a Concept To Identify and Describe Complex Molecular Selectivity Patterns
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