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Computationally Efficient Algorithm to Identify Matched Molecular Pairs (MMPs) in Large Data Sets
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/3527603743openalex-snapshot
Chemoinformatics in Drug Discovery
inferredcites →https://doi.org/10.1007/s10822-008-9242-3openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.bmc.2009.07.002openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.bmcl.2008.12.003openalex-snapshot
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inferredcites →https://doi.org/10.1021/jm070838yopenalex-snapshot
Statistical Analysis of the Effects of Common Chemical Substituents on Ligand Potency
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inferred← citeshttps://doi.org/10.1016/j.bmc.2011.05.003openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.bmc.2021.116226openalex-snapshot
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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.2c00908openalex-snapshot
KID: A Kinase-Focused Interaction Database and Its Application in the Construction of Kinase-Focused Molecule Databases
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c00982openalex-snapshot
DRlinker: Deep Reinforcement Learning for Optimization in Fragment Linking Design
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.2c01088openalex-snapshot
Structural Analysis and Prediction of Hematotoxicity Using Deep Learning Approaches
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c01376openalex-snapshot
Bioisosteric Design Identifies Inhibitors of Mycobacterium tuberculosis DNA Gyrase ATPase Activity
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c01564openalex-snapshot
Improved GNNs for Log D 7.4 Prediction by Transferring Knowledge from Low-Fidelity Data
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c00015openalex-snapshot
Matcher: An Open-Source Application for Translating Large Structure/Property Data Sets into Insights for Drug Design
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c00355openalex-snapshot
De Novo Design of Molecules with Multiaction Potential from Differential Gene Expression using Variational Autoencoder
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.3c01700openalex-snapshot
GRELinker: A Graph-Based Generative Model for Molecular Linker Design with Reinforcement and Curriculum Learning
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c02030openalex-snapshot
Predicting Elimination of Small-Molecule Drug Half-Life in Pharmacokinetics Using Ensemble and Consensus Machine Learning Methods
inferred← citeshttps://doi.org/10.1021/acs.jcim.4c00159openalex-snapshot
Enhancing Multi-species Liver Microsomal Stability Prediction through Artificial Intelligence
inferred← citeshttps://doi.org/10.1021/acs.jcim.4c01781openalex-snapshot
Combining a Chemical Language Model and the Structure–Activity Relationship Matrix Formalism for Generative Design of Potent Compounds with Core Structure and Substituent Modifications
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00018openalex-snapshot
Strong Nonadditivity as a Key Structure–Activity Relationship Feature: Distinguishing Structural Changes from Assay Artifacts
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00476openalex-snapshot
Matched Peptides: Tuning Matched Molecular Pair Analysis for Biopharmaceutical Applications
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.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.5c01106openalex-snapshot
ERRα-Predictor: A Framework of Ensemble Models for Prediction of ERRα Binders, Antagonists, and Agonists Using Artificial Intelligence
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c01532openalex-snapshot
Uncertainty-Aware Deep Learning and Structural Feature Analysis for Reliable Nephrotoxicity Prediction
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00359openalex-snapshot
Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00371openalex-snapshot
Structural and Physico-Chemical Interpretation (SPCI) of QSAR Models and Its Comparison with Matched Molecular Pair Analysis
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00709openalex-snapshot
Matched Molecular Series: Measuring SAR Similarity
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00092openalex-snapshot
Bioisostere Identification by Determining the Amino Acid Binding Preferences of Common Chemical Fragments
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00298openalex-snapshot
Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00335openalex-snapshot
Turbocharging Matched Molecular Pair Analysis: Optimizing the Identification and Analysis of Pairs
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00173openalex-snapshot
mmpdb: An Open-Source Matched Molecular Pair Platform for Large Multiproperty Data Sets
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00520openalex-snapshot
In-Silico Extraction of Design Ideas Using MMPA-by-QSAR and its Application on ADME Endpoints
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00122openalex-snapshot
Development of R-Group Fingerprints Based on the Local Landscape from an Attachment Point of a Molecular Structure
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00557openalex-snapshot
Method for Systematic Analogue Search Using the Mega SAR Matrix Database
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00718openalex-snapshot
Systematic Modeling of log D7.4 Based on Ensemble Machine Learning, Group Contribution, and Matched Molecular Pair Analysis
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.jmedchem.0c00960openalex-snapshot
Sulfoximines as Rising Stars in Modern Drug Discovery? Current Status and Perspective on an Emerging Functional Group in Medicinal Chemistry
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.0c01148openalex-snapshot
A Turing Test for Molecular Generators
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.0c01607openalex-snapshot
Global Assessment of Substituents on the Basis of Analogue Series
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.0c02076openalex-snapshot
Structure- and Similarity-Based Survey of Allosteric Kinase Inhibitors, Activators, and Closely Related Compounds
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.2c00334openalex-snapshot
Defining Levels of Automated Chemical Design
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.5b01312openalex-snapshot
An Orally Bioavailable, Indole-3-glyoxylamide Based Series of Tubulin Polymerization Inhibitors Showing Tumor Growth Inhibition in a Mouse Xenograft Model of Head and Neck Cancer
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5b01428openalex-snapshot
Monitoring the Progression of Structure–Activity Relationship Information during Lead Optimization
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5b01746openalex-snapshot
Computational Exploration of Molecular Scaffolds in Medicinal Chemistry
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5c00445openalex-snapshot
The Logic of Chemical Optimization
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5c01641openalex-snapshot
A Data-Driven Perspective on Bioisostere Evaluation: Mapping the Benzene Bioisostere Landscape with BioSTAR
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5c03746openalex-snapshot
Integrating Medicinal Chemist Expertise with Deep Learning for Automated Molecular Optimization
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6b00906openalex-snapshot
Computational Method for the Systematic Identification of Analog Series and Key Compounds Representing Series and Their Biological Activity Profiles
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.7b00487openalex-snapshot
In Silico Absorption, Distribution, Metabolism, Excretion, and Pharmacokinetics (ADME-PK): Utility and Best Practices. An Industry Perspective from the International Consortium for Innovation through Quality in Pharmaceutical Development
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.7b00809openalex-snapshot
The Fragment Network: A Chemistry Recommendation Engine Built Using a Graph Database
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.7b00935openalex-snapshot
Learning Medicinal Chemistry Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Rules from Cross-Company Matched Molecular Pairs Analysis (MMPA)
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.9b01931openalex-snapshot
Computational Method for Structure-Based Analysis of SAR Transfer
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.9b01236openalex-snapshot
Systematic Exploration of Activity Cliffs Containing Privileged Substructures
inferred← citeshttps://doi.org/10.1021/acsomega.2c02738openalex-snapshot
Implications of Additivity and Nonadditivity for Machine Learning and Deep Learning Models in Drug Design
inferred← citeshttps://doi.org/10.1021/acsomega.3c09047openalex-snapshot
Generalizability Improvement of Interpretable Symbolic Regression Models for Quantitative Structure–Activity Relationships
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