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Method for the Evaluation of Structure–Activity Relationship Information Associated with Coordinated Activity Cliffs

https://doi.org/10.1021/jm500577n
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What this work says

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

inferredcites →https://doi.org/10.1002/3527603743.ch11openalex-snapshot
Structure Modification in Chemical Databases
inferredcites →https://doi.org/10.1021/ci060117sopenalex-snapshot
On Outliers and Activity CliffsWhy QSAR Often Disappoints
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/ci3001138openalex-snapshot
MMP-Cliffs: Systematic Identification of Activity Cliffs on the Basis of Matched Molecular Pairs
inferredcites →https://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
inferredcites →https://doi.org/10.1021/ci300288fopenalex-snapshot
Frequency of Occurrence and Potency Range Distribution of Activity Cliffs in Bioactive Compounds
inferredcites →https://doi.org/10.1021/ci400728ropenalex-snapshot
Composition and Topology of Activity Cliff Clusters Formed by Bioactive Compounds
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/ci900450mopenalex-snapshot
Computationally Efficient Algorithm to Identify Matched Molecular Pairs (MMPs) in Large Data Sets
inferredcites →https://doi.org/10.1021/jm201706bopenalex-snapshot
Exploring Activity Cliffs in Medicinal Chemistry
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/jm9602928openalex-snapshot
The Properties of Known Drugs. 1. Molecular Frameworks
inferredcites →https://doi.org/10.1093/nar/gkr777openalex-snapshot
ChEMBL: a large-scale bioactivity database for drug discovery
inferredcites →https://doi.org/10.1101/gr.1239303openalex-snapshot
Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks
inferredcites →https://doi.org/10.12688/f1000research.2-199.v1openalex-snapshot
Advancing the activity cliff concept
inferredcites →https://doi.org/10.12688/f1000research.4057openalex-snapshot
Advancing the activity cliff concept, part II

What points at this work

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

inferred← citeshttps://doi.org/10.1002/minf.201600023openalex-snapshot
Advances in Activity Cliff Research
inferred← citeshttps://doi.org/10.1007/s10822-020-00319-9openalex-snapshot
Simplified activity cliff network representations with high interpretability and immediate access to SAR information
inferred← citeshttps://doi.org/10.1016/b978-0-443-18638-7.00023-2openalex-snapshot
A systematic chemoinformatic analysis of chemical space, scaffolds and antimicrobial activity of LpxC inhibitors
inferred← citeshttps://doi.org/10.1016/j.drudis.2016.08.009openalex-snapshot
The many roles of molecular complexity in drug discovery
inferred← citeshttps://doi.org/10.1016/j.ejmech.2014.09.087openalex-snapshot
Extraction of SAR information from activity cliff clusters via matching molecular series
inferred← citeshttps://doi.org/10.1016/j.ejmech.2014.11.058openalex-snapshot
Systematic assessment of coordinated activity cliffs formed by kinase inhibitors and detailed characterization of activity cliff clusters and associated SAR information
inferred← citeshttps://doi.org/10.1016/j.ejmech.2024.117051openalex-snapshot
Identification of bioactive compounds with popular single-atom modifications: Comprehensive analysis and implications for compound design
inferred← citeshttps://doi.org/10.1016/j.tox.2025.154064openalex-snapshot
InterDIA: Interpretable prediction of drug-induced autoimmunity through ensemble machine learning approaches
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/10.1039/9781782623731-00120openalex-snapshot
Chemical Similarity, Shape Matching and QSAR
inferred← citeshttps://doi.org/10.1080/17460441.2017.1353494openalex-snapshot
Representation and identification of activity cliffs
inferred← citeshttps://doi.org/10.1080/17460441.2018.1465926openalex-snapshot
Progress with modeling activity landscapes in drug discovery
inferred← citeshttps://doi.org/10.1186/s13321-020-00454-3openalex-snapshot
DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach
inferred← citeshttps://doi.org/10.1517/13543776.2014.964685openalex-snapshot
Novel HIV-1 non-nucleoside reverse transcriptase inhibitors: a patent review (2011 – 2014)
inferred← citeshttps://doi.org/10.1517/17460441.2015.1019861openalex-snapshot
Activity cliff clusters as a source of structure–activity relationship information
inferred← citeshttps://doi.org/10.3390/molecules25030456openalex-snapshot
Cinnamic Derivatives as Antitubercular Agents: Characterization by Quantitative Structure–Activity Relationship Studies
inferred← citeshttps://doi.org/10.4155/fmc-2018-0299openalex-snapshot
Second-generation Activity Cliffs Identified on the Basis of Target set-dependent Potency Difference Criteria
inferred← citeshttps://doi.org/10.4155/fmc.15.89openalex-snapshot
Monitoring Global Growth of Activity Cliff Information over Time and Assessing Activity Cliff Frequencies and Distributions
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