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Chemical Substitutions That Introduce Activity Cliffs Across Different Compound Classes and Biological Targets

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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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Navigating structure–activity landscapes

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The Most Common Chemical Replacements in Drug-Like Compounds

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On Outliers and Activity CliffsWhy QSAR Often Disappoints

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Molecular Scaffolds with High Propensity to Form Multi-Target Activity Cliffs

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A Database of Historically-Observed Chemical Replacements

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Rationalizing Lead Optimization by Associating Quantitative Relevance with Molecular Structure Modification

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Computationally Efficient Algorithm to Identify Matched Molecular Pairs (MMPs) in Large Data Sets

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Utilization of operational schemes for analog synthesis in drug design

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Statistical Analysis of the Effects of Common Chemical Substituents on Ligand Potency

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The Properties of Known Drugs. 1. Molecular Frameworks

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The Binding Database: data management and interface design

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BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities

What points at this work

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

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Structure–Activity Relationship Data Analysis: Activity Landscapes and Activity Cliffs

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EXPLORATION OF STRUCTURE–ACTIVITY RELATIONSHIPS (SARs) AND TRANSFER OF KEY ELEMENTS IN LEAD OPTIMIZATION

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MOLECULAR SIMILARITY ANALYSIS

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Chiral Cliffs: Investigating the Influence of Chirality on Binding Affinity

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Advances in Computational Medicinal Chemistry: Matched Molecular Pair Analysis

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Hierarchical Analysis of Bioactive Matched Molecular Pairs, Encoded Chemical Transformations, and Associated Substructures

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Exploring structure–activity data using the landscape paradigm

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In silico applications of bioisosterism in contemporary medicinal chemistry practice

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SAR Matrix Method for Large-Scale Analysis of Compound Structure–Activity Relationships and Exploration of Multitarget Activity Spaces

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GraphBioisostere: General Bioisostere Prediction Model with Deep Graph Neural Network

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Quantitative Structure-Epigenetic Activity Relationships

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Harnessing the necessary nitrogen atom in chemical biology and drug discovery

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From animal testing to in Silico models: a systematic review and practical guide to cosmetic assessment

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GraphBioisostere: general bioisostere prediction model with deep graph neural network

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Extraction of tacit knowledge from large ADME data sets via pairwise analysis

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Chemoinformatics: A view of the field and current trends in method development

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Substituents of life: The most common substituent patterns present in natural products

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Methyl-containing pharmaceuticals: Methylation in drug design

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Matched Molecular Pair Analysis in Short: Algorithms, Applications and Limitations

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Flexible Analog Search with Kernel PCA Embedded Molecule Vectors

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Large-scale SAR analysis

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Classification of scaffold-hopping approaches

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Matched Molecular Pair Analysis in drug discovery

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Activity cliffs in drug discovery: Dr Jekyll or Mr Hyde?

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Extreme modulation properties of aromatic fluorine

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Building Chemical Property Models for Energetic Materials from Small Datasets Using a Transfer Learning Approach

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Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization

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Global Assessment of Substituents on the Basis of Analogue Series

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Matched Molecular Pair Analysis in Drug Discovery: Methods and Recent Applications

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The Necessary Nitrogen Atom: A Versatile High-Impact Design Element for Multiparameter Optimization

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Exploration of 3D Activity Cliffs on the Basis of Compound Binding Modes and Comparison of 2D and 3D Cliffs

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Exploring Uncharted Territories: Predicting Activity Cliﬀs in Structure–Activity Landscapes

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MMP-Cliffs: Systematic Identification of Activity Cliffs on the Basis of Matched Molecular Pairs

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Extending the Activity Cliff Concept: Structural Categorization of Activity Cliffs and Systematic Identification of Different Types of Cliffs in the ChEMBL Database

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Frequency of Occurrence and Potency Range Distribution of Activity Cliffs in Bioactive Compounds

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Compound Optimization through Data Set-Dependent Chemical Transformations

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Structure-Based Predictions of Activity Cliffs

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Activity Landscape Representations for Structure−Activity Relationship Analysis

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Matched Molecular Pairs as a Medicinal Chemistry Tool

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Exploring Activity Cliffs in Medicinal Chemistry

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Discovery of Selective LRRK2 Inhibitors Guided by Computational Analysis and Molecular Modeling

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Matched Molecular Pair Analysis of Small Molecule Microarray Data Identifies Promiscuity Cliffs and Reveals Molecular Origins of Extreme Compound Promiscuity

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Chemical Transformations That Yield Compounds with Distinct Activity Profiles

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Targeted Kinase Selectivity from Kinase Profiling Data

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Identification of target family directed bioisosteric replacements

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Specific chemical changes leading to consistent potency increases in structurally diverse active compounds

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Data-driven assessment of bioisosteric replacements and their influence on off-target activity profiles

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Toward an Efficient Approach to Identify Molecular Scaffolds Possessing Selective or Promiscuous Compounds

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PubChem3D: Biologically relevant 3-D similarity

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On the validity versus utility of activity landscapes: are all activity cliffs statistically significant?

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Structure-activity relationship analysis on the basis of matched molecular pairs

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Compound optimization through data set-dependent chemical transformations

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Semi-automated workflow for molecular pair analysis and QSAR-assisted transformation space expansion

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Structure-Promiscuity Relationship Puzzles—Extensively Assayed Analogs with Large Differences in Target Annotations

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Freely available compound data sets and software tools for chemoinformatics and computational medicinal chemistry applications

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Compound data sets and software tools for chemoinformatics and medicinal chemistry applications: update and data transfer

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Challenges for computational structure–activity modelling for predicting chemical toxicity: future improvements?

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Strategies for the generation, validation and application ofin silicoADMET models in lead generation and optimization

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Navigating the Chemical Space of ENR Inhibitors: A Comprehensive Analysis

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Automatic Identification of Analogue Series from Large Compound Data Sets: Methods and Applications

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Freely available compound data sets and software tools for chemoinformatics and computational medicinal chemistry applications

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Large-Scale Exploration of Bioisosteric Replacements on the Basis of Matched Molecular Pairs

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