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Novel Application of 2D and 3D-Similarity Searches To Identify Substrates among Cytochrome P450 2C9, 2D6, and 3A4

https://doi.org/10.1021/ci900074t
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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/cmdc.200500024openalex-snapshot
Prediction of Small‐Molecule Binding to Cytochrome P450 3A4: Flexible Docking Combined with Multidimensional QSAR
inferredcites →https://doi.org/10.1007/s10822-007-9145-8openalex-snapshot
Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios
inferredcites →https://doi.org/10.1007/s10822-007-9166-3openalex-snapshot
How to do an evaluation: pitfalls and traps
inferredcites →https://doi.org/10.1007/s10822-008-9170-2openalex-snapshot
What do we know and when do we know it?
inferredcites →https://doi.org/10.1016/j.drudis.2006.10.005openalex-snapshot
Similarity-based virtual screening using 2D fingerprints
inferredcites →https://doi.org/10.1016/s0022-3565(24)35117-1openalex-snapshot
Three-Dimensional-Quantitative Structure Activity Relationship Analysis of Cytochrome P-450 3A4 Substrates
inferredcites →https://doi.org/10.1016/s1093-3263(02)00204-8openalex-snapshot
Assessing the performance of OMEGA with respect to retrieving bioactive conformations
inferredcites →https://doi.org/10.1016/s1359-6446(02)02411-xopenalex-snapshot
Why do we need so many chemical similarity search methods?
inferredcites →https://doi.org/10.1021/ci025569topenalex-snapshot
Similarity Metrics for Ligands Reflecting the Similarity of the Target Proteins
inferredcites →https://doi.org/10.1021/ci034231bopenalex-snapshot
Comparison of Fingerprint-Based Methods for Virtual Screening Using Multiple Bioactive Reference Structures
inferredcites →https://doi.org/10.1021/ci0500536openalex-snapshot
Prediction of Cytochrome P450 3A4, 2D6, and 2C9 Inhibitors and Substrates by Using Support Vector Machines
inferredcites →https://doi.org/10.1021/ci0504723openalex-snapshot
Multifingerprint Based Similarity Searches for Targeted Class Compound Selection
inferredcites →https://doi.org/10.1021/ci600426eopenalex-snapshot
Evaluating Virtual Screening Methods: Good and Bad Metrics for the “Early Recognition” Problem
inferredcites →https://doi.org/10.1021/ci700010topenalex-snapshot
Ligand-Based Models for the Isoform Specificity of Cytochrome P450 3A4, 2D6, and 2C9 Substrates
inferredcites →https://doi.org/10.1021/ci700024qopenalex-snapshot
Fast and Efficient in Silico 3D Screening: Toward Maximum Computational Efficiency of Pharmacophore-Based and Shape-Based Approaches
inferredcites →https://doi.org/10.1021/ci700052xopenalex-snapshot
Comparison of Topological, Shape, and Docking Methods in Virtual Screening
inferredcites →https://doi.org/10.1021/ci700130jopenalex-snapshot
A Comparison of Field-Based Similarity Searching Methods: CatShape, FBSS, and ROCS
inferredcites →https://doi.org/10.1021/ci700350nopenalex-snapshot
How To Winnow Actives from Inactives: Introducing Molecular Orthogonal Sparse Bigrams (MOSBs) and Multiclass Winnow
inferredcites →https://doi.org/10.1021/jm020400sopenalex-snapshot
A Model for Predicting Likely Sites of CYP3A4-mediated Metabolism on Drug-like Molecules
inferredcites →https://doi.org/10.1021/jm021104iopenalex-snapshot
Predicting Drug Metabolism: A Site of Metabolism Prediction Tool Applied to the Cytochrome P450 2C9
inferredcites →https://doi.org/10.1021/jm050040jopenalex-snapshot
Parameter Estimation for Scoring Protein−Ligand Interactions Using Negative Training Data
inferredcites →https://doi.org/10.1021/jm0508538openalex-snapshot
Catalytic Site Prediction and Virtual Screening of Cytochrome P450 2D6 Substrates by Consideration of Water and Rescoring in Automated Docking
inferredcites →https://doi.org/10.1021/jm0613471openalex-snapshot
Empirical Regioselectivity Models for Human Cytochromes P450 3A4, 2D6, and 2C9
inferredcites →https://doi.org/10.1021/jm991058vopenalex-snapshot
A Novel Approach to Predicting P450 Mediated Drug Metabolism. CYP2D6 Catalyzed N-Dealkylation Reactions and Qualitative Metabolite Predictions Using a Combined Protein and Pharmacophore Model for CYP2D6
inferredcites →https://doi.org/10.1038/nrd1851openalex-snapshot
Predicting in vivo drug interactions from in vitro drug discovery data
inferredcites →https://doi.org/10.1038/sj.bjp.0707570openalex-snapshot
Insights into drug metabolism by cytochromes P450 from modelling studies of CYP2D6‐drug interactions
inferredcites →https://doi.org/10.1081/dmr-120001392openalex-snapshot
Summary of information on human CYP enzymes: human P450 metabolism data
inferredcites →https://doi.org/10.1093/bioinformatics/19.2.295openalex-snapshot
Matrix2png: a utility for visualizing matrix data
inferredcites →https://doi.org/10.1124/dmd.108.022376openalex-snapshot
The Molecular Basis of CYP2D6-Mediated N-Dealkylation: Balance between Metabolic Clearance Routes and Enzyme Inhibition
inferredcites →https://doi.org/10.2174/157016306776637609openalex-snapshot
Development and Validation of an In Silico P450 Profiler Based on Pharmacophore Models

What points at this work

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

inferred← citeshttps://doi.org/10.1002/9780470921920.edm139openalex-snapshot
QSAR and Molecular Modeling Approaches for Prediction of Drug Metabolism
inferred← citeshttps://doi.org/10.1002/9783527673261.ch12openalex-snapshot
Knowledge‐Based Approaches for Predicting the Sites and Products of Metabolism
inferred← citeshttps://doi.org/10.1002/slct.201601051openalex-snapshot
Advances in Computational Prediction of Regioselective and Isoform‐Specific Drug Metabolism Catalyzed by CYP450s.
inferred← citeshttps://doi.org/10.1007/978-94-017-9245-5_19openalex-snapshot
Recent Progress on Structural Bioinformatics Research of Cytochrome P450 and Its Impact on Drug Discovery
inferred← citeshttps://doi.org/10.1007/s11095-018-2479-1openalex-snapshot
In Silico Prediction of Major Clearance Pathways of Drugs among 9 Routes with Two-Step Support Vector Machines
inferred← citeshttps://doi.org/10.1016/j.bmc.2012.01.049openalex-snapshot
Identification of cytochrome P450 2D6 and 2C9 substrates and inhibitors by QSAR analysis
inferred← citeshttps://doi.org/10.1021/ci100270xopenalex-snapshot
Capturing Structure−Activity Relationships from Chemogenomic Spaces
inferred← citeshttps://doi.org/10.1021/ci500300uopenalex-snapshot
Improving the Use of Ranking in Virtual Screening against HIV-1 Integrase with Triangular Numbers and Including Ligand Profiling with Antitargets
inferred← citeshttps://doi.org/10.1080/17460441.2025.2491669openalex-snapshot
Artificial intelligence to predict inhibitors of drug-metabolizing enzymes and transporters for safer drug design
inferred← citeshttps://doi.org/10.11606/d.75.2011.tde-17042012-103806openalex-snapshot
Sobre os estudos metabólicos de fármacos empregando-se atividade enzimática de CYP450 visando-se estabelecer correlações entre estrutura e atividade
inferred← citeshttps://doi.org/10.11606/d.75.2012.tde-17042012-103806openalex-snapshot
Sobre os estudos metabólicos de fármacos empregando-se atividade enzimática de CYP450 visando-se estabelecer correlações entre estrutura e atividade
inferred← citeshttps://doi.org/10.11606/d.75.2013.tde-04042013-145753openalex-snapshot
Estudo in vitro do metabolismo microssomal hepático de agentes tripanossomicidas
inferred← citeshttps://doi.org/10.11606/d.9.2017.tde-18102017-152832openalex-snapshot
Triagem virtual de inibidores da enzima di-hidrofolato redutase de Schistosoma mansoni (SmDHFR)
inferred← citeshttps://doi.org/10.1517/17425255.2011.611501openalex-snapshot
Computational modeling of P450s for toxicity prediction
inferred← citeshttps://doi.org/10.1517/17425255.2013.800482openalex-snapshot
In vitroapproaches to investigate cytochrome P450 activities: update on current status and their applicability
inferred← citeshttps://doi.org/10.2174/138620711795508412openalex-snapshot
In Silico Prediction of Cytochrome P450-Mediated Drug Metabolism
inferred← citeshttps://doi.org/10.2174/138955712800493807openalex-snapshot
QSAR and QM/MM Approaches Applied to Drug Metabolism Prediction
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