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Combinatorial QSAR Modeling of P-Glycoprotein Substrates

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

inferredcites →https://doi.org/10.1002/j.1538-7305.1948.tb00917.xopenalex-snapshot
A Mathematical Theory of Communication
inferredcites →https://doi.org/10.1002/jcc.10175openalex-snapshot
Conformational analysis by intersection: CONAN
inferredcites →https://doi.org/10.1002/jcc.540020202openalex-snapshot
Isomer discrimination by topological information approach
inferredcites →https://doi.org/10.1002/jps.2600760325openalex-snapshot
Molecular Connectivity in Structure–activity Analysis
inferredcites →https://doi.org/10.1002/qsar.19850040304openalex-snapshot
A Method for Determining the Theoretical Carcinogenicity of Polycyclic Aromatic Hydrocarbons
inferredcites →https://doi.org/10.1002/qsar.19860050105openalex-snapshot
A Comparison of Some Measures for the Determination of Inter‐Molecular Structural Similarity Measures of Inter‐Molecular Structural Similarity
inferredcites →https://doi.org/10.1002/qsar.19870060104openalex-snapshot
Hydrophobic Properties of Chromones and Flavones. Relationships Between Octanol/Water Partition Coefficients and RP‐HPLC Capacity Factors
inferredcites →https://doi.org/10.1002/qsar.200390007openalex-snapshot
The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models
inferredcites →https://doi.org/10.1007/978-1-4757-3264-1openalex-snapshot
The Nature of Statistical Learning Theory
inferredcites →https://doi.org/10.1007/bf00134175openalex-snapshot
E-state fields: Applications to 3D QSAR
inferredcites →https://doi.org/10.1007/bf00555695openalex-snapshot
Chemical graphs
inferredcites →https://doi.org/10.1007/s002329900305openalex-snapshot
The P-Glycoprotein Efflux Pump: How Does it Transport Drugs?
inferredcites →https://doi.org/10.1016/0009-2614(82)80009-2openalex-snapshot
Highly discriminating distance-based topological index
inferredcites →https://doi.org/10.1016/0040-4020(80)80168-2openalex-snapshot
Iterative partial equalization of orbital electronegativity—a rapid access to atomic charges
inferredcites →https://doi.org/10.1016/b978-0-12-406560-4.x5001-6openalex-snapshot
Molecular Connectivity in Chemistry and Drug Research
inferredcites →https://doi.org/10.1016/s0006-8993(03)02401-6openalex-snapshot
Characterisation of the brain multidrug resistance protein (BMDP/ABCG2/BCRP) expressed at the blood–brain barrier
inferredcites →https://doi.org/10.1016/s0166-1280(99)00360-7openalex-snapshot
Molecular fields in quantitative structure–permeation relationships: the VolSurf approach
inferredcites →https://doi.org/10.1016/s0169-409x(02)00006-6openalex-snapshot
Progress in understanding the structure–activity relationships of P-glycoprotein
inferredcites →https://doi.org/10.1016/s1093-3263(01)00123-1openalex-snapshot
Beware of q2!
inferredcites →https://doi.org/10.1021/ci00001a013openalex-snapshot
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inferredcites →https://doi.org/10.1021/ci00008a012openalex-snapshot
Applications of the radius-diameter diagram to the classification of topological and geometrical shapes of chemical compounds
inferredcites →https://doi.org/10.1021/ci00046a002openalex-snapshot
Atom pairs as molecular features in structure-activity studies: definition and applications
inferredcites →https://doi.org/10.1021/ci00046a003openalex-snapshot
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inferredcites →https://doi.org/10.1021/ci00057a006openalex-snapshot
CHEMTEXT
inferredcites →https://doi.org/10.1021/ci034203topenalex-snapshot
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inferredcites →https://doi.org/10.1021/ci980033mopenalex-snapshot
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inferredcites →https://doi.org/10.1021/ci980159jopenalex-snapshot
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inferredcites →https://doi.org/10.1021/ja00856a001openalex-snapshot
Characterization of molecular branching
inferredcites →https://doi.org/10.1021/ja00856a002openalex-snapshot
Importance of nonbonded attraction in the stereochemistry of the SN2' reaction
inferredcites →https://doi.org/10.1021/ja01193a006openalex-snapshot
Raman Spectra of Aqueous Solutions of Potassium Thiocyanate
inferredcites →https://doi.org/10.1021/jm010488uopenalex-snapshot
Quantitative Structure−Activity Relationship Analysis of Functionalized Amino Acid Anticonvulsant Agents Using k Nearest Neighbor and Simulated Annealing PLS Methods
inferredcites →https://doi.org/10.1021/jm020941hopenalex-snapshot
Pharmacophore Model of Drugs Involved in P-Glycoprotein Multidrug Resistance: Explanation of Structural Variety (Hypothesis)
inferredcites →https://doi.org/10.1021/jm0255062openalex-snapshot
A Computational Ensemble Pharmacophore Model for Identifying Substrates of P-Glycoprotein
inferredcites →https://doi.org/10.1021/jm970732aopenalex-snapshot
Three-Dimensional Quantitative Similarity−Activity Relationships (3D QSiAR) from SEAL Similarity Matrices
inferredcites →https://doi.org/10.1021/jm9806998openalex-snapshot
New 4-Point Pharmacophore Method for Molecular Similarity and Diversity Applications: Overview of the Method and Applications, Including a Novel Approach to the Design of Combinatorial Libraries Containing Privileged Substructures
inferredcites →https://doi.org/10.1021/jm990578nopenalex-snapshot
A Rapid Computational Method for Lead Evolution: Description and Application to α1-Adrenergic Antagonists
inferredcites →https://doi.org/10.1046/j.1432-1327.1998.2510252.xopenalex-snapshot
A general pattern for substrate recognition by P‐glycoprotein
inferredcites →https://doi.org/10.1067/mcp.2000.107912openalex-snapshot
Effect of intestinal P-glycoprotein on daily tacrolimus trough level in a living-donor small bowel recipient
inferredcites →https://doi.org/10.1073/pnas.84.21.7735openalex-snapshot
Cellular localization of the multidrug-resistance gene product P-glycoprotein in normal human tissues.
inferredcites →https://doi.org/10.1080/10629369808039146openalex-snapshot
Addressing the Challenges Posed by Combinatorial Chemistry: 3D Databases, Pharmacophore Recognition and Beyond
inferredcites →https://doi.org/10.1177/107327480301000207openalex-snapshot
Overcoming Multidrug Resistance in Cancer: An Update on the Clinical Strategy of Inhibiting P-Glycoprotein
inferredcites →https://doi.org/10.2307/2530946openalex-snapshot
Classification and Regression Trees.

What points at this work

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

inferred← citeshttps://doi.org/10.1002/0471266949.bmc002.pub2openalex-snapshot
Recent Advances in Development, Validation, and Exploitation of QSAR Models
inferred← citeshttps://doi.org/10.1002/0471266949.bmc002.pub3openalex-snapshot
Recent Advances in Development, Validation, and Exploitation of QSAR Models
inferred← citeshttps://doi.org/10.1002/9780470175668.ch3openalex-snapshot
Graph Theoretic Models in Chemistry and Molecular Biology
inferred← citeshttps://doi.org/10.1002/9780470915110.ch2openalex-snapshot
In SilicoADME/Tox Predictions
inferred← citeshttps://doi.org/10.1002/9783527621286.ch2openalex-snapshot
Physicochemical Properties in Drug Profiling
inferred← citeshttps://doi.org/10.1002/9783527623860.ch5openalex-snapshot
Physicochemical Approaches to Drug Absorption
inferred← citeshttps://doi.org/10.1002/9783527627424.ch13openalex-snapshot
ABC Transporters – From Targets to Antitargets?
inferred← citeshttps://doi.org/10.1002/9783527628766.biblioopenalex-snapshot
Bibliography
inferred← citeshttps://doi.org/10.1002/9783527816880.ch12openalex-snapshot
QSAR/QSPR Revisited
inferred← citeshttps://doi.org/10.1002/ardp.201200088openalex-snapshot
Quantitative Structure–Activity Relationship Analysis of a Series of Human Renal Organic Anion Transporter Inhibitors
inferred← citeshttps://doi.org/10.1002/cbdv.202401674openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/cem.1376openalex-snapshot
Development of a highly specific ensemble of topological models for early identification of P‐glycoprotein substrates
inferred← citeshttps://doi.org/10.1002/cem.2415openalex-snapshot
Novel algorithm to select basis functions in spline regression: applications in quantitative structure–activity relationship studies
inferred← citeshttps://doi.org/10.1002/chin.200631197openalex-snapshot
Combinatorial QSAR Modeling of P‐Glycoprotein Substrates.
inferred← citeshttps://doi.org/10.1002/hep.26208openalex-snapshot
High lipophilicity and high daily dose of oral medications are associated with significant risk for drug-induced liver injury
inferred← citeshttps://doi.org/10.1002/minf.200900079openalex-snapshot
Ensemble Rule‐Based Classification of Substrates of the Human ABC‐Transporter ABCB1 Using Simple Physicochemical Descriptors
inferred← citeshttps://doi.org/10.1002/minf.201300165openalex-snapshot
The Development of Novel Chemical Fragment‐Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling
inferred← citeshttps://doi.org/10.1002/minf.201500038openalex-snapshot
Comparative Analysis of QSAR‐based vs. Chemical Similarity Based Predictors of GPCRs Binding Affinity
inferred← citeshttps://doi.org/10.1002/minf.201800152openalex-snapshot
Value of p‐Value
inferred← citeshttps://doi.org/10.1002/qsar.200630094openalex-snapshot
In Silico ADME Modeling 3: Computational Models to Predict Human Intestinal Absorption Using Sphere Exclusion and kNN QSAR Methods
inferred← citeshttps://doi.org/10.1002/qsar.200810009openalex-snapshot
Quantitative Structure–Property Relationship Studies for Predicting Flash Points of Organic Compounds using Support Vector Machines
inferred← citeshttps://doi.org/10.1002/qsar.200810072openalex-snapshot
Prediction of hERG Potassium Channel Blockade Using kNN‐QSAR and Local Lazy Regression Methods
inferred← citeshttps://doi.org/10.1002/qsar.200860065openalex-snapshot
Estimation of Soil Organic Carbon Normalized Sorption Coefficient (Koc) Using Least Squares‐Support Vector Machine
inferred← citeshttps://doi.org/10.1002/qsar.200860191openalex-snapshot
Comparison of Contemporary Feature Selection Algorithms: Application to the Classification of ABC‐Transporter Substrates
inferred← citeshttps://doi.org/10.1002/qsar.200960051openalex-snapshot
Similarity Based Descriptors – Useful for Classification of Substrates of the Human Multidrug Transporter P‐Glycoprotein?
inferred← citeshttps://doi.org/10.1002/slct.202302813openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/slct.202401016openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/slct.202402567openalex-snapshot
Computational Studies of Novel Aniline Pyrimidine WDR5‐MLL1 Inhibitors: QSAR, Molecular Docking, and Molecular Dynamics Simulation
inferred← citeshttps://doi.org/10.1007/2789_2006_003openalex-snapshot
QSAR Modeling of GPCR Ligands: Methodologies and Examples of Applications
inferred← citeshttps://doi.org/10.1007/978-0-387-30440-3_422openalex-snapshot
QSAR Modeling and QSAR Based Virtual Screening, Complexity and Challenges of Modern
inferred← citeshttps://doi.org/10.1007/978-1-0716-3441-7_17openalex-snapshot
Artificial Intelligence in ADME Property Prediction
inferred← citeshttps://doi.org/10.1007/978-1-4899-7445-7_7openalex-snapshot
Modelability Criteria: Statistical Characteristics Estimating Feasibility to Build Predictive QSAR Models for a Dataset
inferred← citeshttps://doi.org/10.1007/978-1-60761-700-6_4openalex-snapshot
Targeting Drug Transporters – Combining In Silico and In Vitro Approaches to Predict In Vivo
inferred← citeshttps://doi.org/10.1007/978-3-030-33582-3_25openalex-snapshot
Methods to Improve Ranking Chemical Structures in Ligand-Based Virtual Screening
inferred← citeshttps://doi.org/10.1007/978-3-030-83244-5_7openalex-snapshot
Dataset Modelability by QSAR: Continuous Response Variable
inferred← citeshttps://doi.org/10.1007/978-3-319-27282-5_37openalex-snapshot
Predictive QSAR Modeling: Methods and Applications in Drug Discovery and Chemical Risk Assessment
inferred← citeshttps://doi.org/10.1007/978-3-7643-8340-4_13openalex-snapshot
Recent Trends in Statistical QSAR Modeling of Environmental Chemical Toxicity
inferred← citeshttps://doi.org/10.1007/978-94-007-0711-5_37openalex-snapshot
Predictive QSAR Modeling: Methods and Applications in Drug Discovery and Chemical Risk Assessment
inferred← citeshttps://doi.org/10.1007/978-94-007-6169-8_37-2openalex-snapshot
Predictive QSAR Modeling: Methods and Applications in Drug Discovery and Chemical Risk Assessment
inferred← citeshttps://doi.org/10.1007/978-94-007-6169-8_37-3openalex-snapshot
Predictive QSAR Modeling: Methods and Applications in Drug Discovery and Chemical Risk Assessment
inferred← citeshttps://doi.org/10.1007/978-981-10-7455-4_9openalex-snapshot
Drug Transporters as Therapeutic Targets: Computational Models, Challenges, and Future Perspective
inferred← citeshttps://doi.org/10.1007/s00044-016-1556-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10337-013-2492-9openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10337-014-2819-1openalex-snapshot
Support Vector Regression Based QSPR for the Prediction of Retention Time of Peptides in Reversed-Phase Liquid Chromatography
inferred← citeshttps://doi.org/10.1007/s10517-013-1992-9openalex-snapshot
Computer Evaluation of Drug Interactions with P-Glycoprotein
inferred← citeshttps://doi.org/10.1007/s10822-007-9102-6openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10822-007-9108-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10822-008-9193-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10822-008-9199-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10822-018-0171-5openalex-snapshot
Boosted feature selectors: a case study on prediction P-gp inhibitors and substrates
inferred← citeshttps://doi.org/10.1007/s10973-013-3587-0openalex-snapshot
Evaluations of thermal decomposition properties for optically active polymers based on support vector machine
inferred← citeshttps://doi.org/10.1007/s10973-016-5922-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11030-015-9608-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11095-007-9285-5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11095-008-9609-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11095-016-2029-7openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11224-022-01909-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-0-12-374194-3.00023-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-0-443-18638-7.00020-7openalex-snapshot
Machine learning methods in drug design
inferred← citeshttps://doi.org/10.1016/j.addr.2008.10.004openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.biopha.2015.02.009openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.chemolab.2015.06.016openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cjac.2021.09.006openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.dmpk.2026.101532openalex-snapshot
Advances in In silico predictive models for DDI prediction: Implications and practical applications in drug discovery
inferred← citeshttps://doi.org/10.1016/j.drudis.2007.12.012openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.drudis.2008.11.015openalex-snapshot
Novel web-based tools combining chemistry informatics, biology and social networks for drug discovery
inferred← citeshttps://doi.org/10.1016/j.drudis.2011.11.003openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.drudis.2014.10.012openalex-snapshot
Machine-learning approaches in drug discovery: methods and applications
inferred← citeshttps://doi.org/10.1016/j.drudis.2017.05.008openalex-snapshot
From flamingo dance to (desirable) drug discovery: a nature-inspired approach
inferred← citeshttps://doi.org/10.1016/j.ejps.2012.06.021openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ijpharm.2016.02.022openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jfutfo.2024.11.002openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jhazmat.2009.02.122openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jtice.2013.09.033openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.lddd.2026.100408openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.microc.2012.05.003openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.molliq.2021.116235openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.talanta.2010.11.039openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.tca.2012.03.017openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/s0065-7743(07)42029-2openalex-snapshot
Chapter 29 Computational Models for ADME
inferred← citeshttps://doi.org/10.1016/s0079-6468(10)49004-9openalex-snapshot
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inferred← citeshttps://doi.org/10.1017/cbo9780511730412.012openalex-snapshot
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inferred← citeshttps://doi.org/10.1017/cbo9780511730412.013openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acs.iecr.6b04347openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00462openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acs.jcim.6c00364openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acsomega.0c00857openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acsomega.1c03689openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci2001583openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci3002809openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci300421nopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci300516wopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci400460qopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci400572xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci700047xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci700083nopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci700284popenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci700404copenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/jm100600yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/jm400328sopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ml300314hopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/mp300555nopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/mp400450mopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/tx900451ropenalex-snapshot
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inferred← citeshttps://doi.org/10.1039/9781847558879-00240openalex-snapshot
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inferred← citeshttps://doi.org/10.1039/c5cp03218kopenalex-snapshot
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inferred← citeshttps://doi.org/10.1039/c5ra05663bopenalex-snapshot
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inferred← citeshttps://doi.org/10.1039/c8ra01206gopenalex-snapshot
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inferred← citeshttps://doi.org/10.1063/1.4832740openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/10629361003773955openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/1062936x.2014.942357openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/1062936x.2014.976265openalex-snapshot
Computational classification models for predicting the interaction of drugs with P-glycoprotein and breast cancer resistance protein
inferred← citeshttps://doi.org/10.1080/1062936x.2014.995701openalex-snapshot
Three- and four-class classification models for P-glycoprotein inhibitors using counter-propagation neural networks
inferred← citeshttps://doi.org/10.1080/1062936x.2021.1999317openalex-snapshot
Theoretically exploring selective-binding mechanisms of BRD4 through integrative computational approaches
inferred← citeshttps://doi.org/10.1093/bioinformatics/btq556openalex-snapshot
Chembench: a cheminformatics workbench
inferred← citeshttps://doi.org/10.1186/s12906-018-2116-xopenalex-snapshot
Computational investigations of physicochemical, pharmacokinetic, toxicological properties and molecular docking of betulinic acid, a constituent of Corypha taliera (Roxb.) with Phospholipase A2 (PLA2)
inferred← citeshttps://doi.org/10.1289/ehp.10573openalex-snapshot
Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1002083openalex-snapshot
Predicting Binding to P-Glycoprotein by Flexible Receptor Docking
inferred← citeshttps://doi.org/10.1371/journal.pone.0025815openalex-snapshot
Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein
inferred← citeshttps://doi.org/10.1517/17425250902753261openalex-snapshot
The use of machine learning and nonlinear statistical tools for ADME prediction
inferred← citeshttps://doi.org/10.1517/17425255.4.9.1167openalex-snapshot
In silicoprediction of substrate properties for ABC-multidrug transporters
inferred← citeshttps://doi.org/10.1517/17460441.2012.668182openalex-snapshot
Decision tree models for data mining in hit discovery
inferred← citeshttps://doi.org/10.17615/tkd5-e303openalex-snapshot
Cheminformatics Modeling of Diverse and Disparate Biological Data and the Use of Models to Discover Novel Bioactive Molecules
inferred← citeshttps://doi.org/10.17615/w4vm-f755openalex-snapshot
The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors
inferred← citeshttps://doi.org/10.17615/xtc7-2969openalex-snapshot
In silico strategies to study polypharmacology of G-protein-coupled receptors
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2597265/v1openalex-snapshot
Exploring the Binding Mechanism of Novel T. Brucei Leucine tRNA Synthase Inhibitors Based on QSAR Modeling, Molecular Docking, ADMET Prediction and Molecular Dynamics Simulations
inferred← citeshttps://doi.org/10.2174/1386207318666150703113948openalex-snapshot
Discovery of Natural Product-Derived 5-HT1A Receptor Binders by Cheminfomatics Modeling of Known Binders, High Throughput Screening and Experimental Validation
inferred← citeshttps://doi.org/10.2174/1568026611212240005openalex-snapshot
Abelson Tyrosine-Protein Kinase 1 as Principal Target for Drug Discovery Against Leukemias. Role of the Current Computer-Aided Drug Design Methodologies
inferred← citeshttps://doi.org/10.2174/1570163815666180913122542openalex-snapshot
Molecular Docking, G-QSAR Studies, Synthesis and Anticancer Screening of Some New 2-Phenazinamines as Bcr-Abl Tyrosine Kinase Inhibitors
inferred← citeshttps://doi.org/10.25365/thesis.23872openalex-snapshot
Development and application of distributed computing tools for virtual screening of large compound libraries
inferred← citeshttps://doi.org/10.3390/molecules23071820openalex-snapshot
Theoretical Prediction of the Complex P-Glycoprotein Substrate Efflux Based on the Novel Hierarchical Support Vector Regression Scheme
inferred← citeshttps://doi.org/10.4018/978-1-60960-818-7.ch517openalex-snapshot
Application of Machine Leaning in Drug Discovery and Development
inferred← citeshttps://doi.org/10.4018/978-1-61520-911-8.ch012openalex-snapshot
Application of Machine Leaning in Drug Discovery and Development
inferred← citeshttps://doi.org/10.4155/fmc.11.58openalex-snapshot
Use of Shape Similarities for the Classification of P-Glycoprotein Substrates and Nonsubstrates
inferred← citeshttps://doi.org/10.5012/bkcs.2012.33.4.1123openalex-snapshot
Prediction Models of P-Glycoprotein Substrates Using Simple 2D and 3D Descriptors by a Recursive Partitioning Approach
inferred← citeshttps://doi.org/10.5451/unibas-005159310openalex-snapshot
Prediction of transport, pharmacokinetics, and effect of drugs
inferred← citeshttps://doi.org/10.5937/arhfarm1502089eopenalex-snapshot
Computational models for predicting drug transport mediated by P-glycoprotein
inferred← citeshttps://doi.org/10.7324/japs.2022.120509openalex-snapshot
In silico screening of hispolon and its analogs: Pharmacokinetics and molecular docking studies with cyclooxygenase-2 enzyme
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