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QSAR Models for Predicting the Similarity in Binding Profiles for Pairs of Protein Kinases and the Variation of Models between Experimental Data Sets

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What this work says

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

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Ruthenium Half‐Sandwich Complexes Bound to Protein Kinase Pim‐1

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ICM—A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation

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Structure-based design of a new class of highly selective aminoimidazo[1,2-a]pyridine-based inhibitors of cyclin dependent kinases

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Structural basis for the GSK-3β binding affinity and selectivity against CDK-2 of 1-(4-aminofurazan-3yl)-5-dialkylaminomethyl-1H-[1,2,3] triazole-4-carboxylic acid derivatives

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Identification and structure–activity relationships of substituted pyridones as inhibitors of Pim-1 kinase

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Inverse In Silico Screening for Identification of Kinase Inhibitor Targets

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High Affinity Targets of Protein Kinase Inhibitors Have Similar Residues at the Positions Energetically Important for Binding

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Kinase inhibitor recognition by use of a multivariable QSAR model

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Kinomics: characterizing the therapeutically validated kinase space

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Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling

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Predicting Kinase Selectivity Profiles Using Free-Wilson QSAR Analysis

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Binding Site Similarity Analysis for the Functional Classification of the Protein Kinase Family

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Rapid Computational Identification of the Targets of Protein Kinase Inhibitors

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Toward a Pharmacophore for Kinase Frequent Hitters

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Novel Structural Features of CDK Inhibition Revealed by an ab Initio Computational Method Combined with Dynamic Simulations

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An Integrated Computational Approach to the Phenomenon of Potent and Selective Inhibition of Aurora Kinases B and C by a Series of 7-Substituted Indirubins

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Discovery and Optimization of p38 Inhibitors via Computer-Assisted Drug Design

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Gini Coefficient: A New Way To Express Selectivity of Kinase Inhibitors against a Family of Kinases

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Kinase-likeness and Kinase-Privileged Fragments: Toward Virtual Polypharmacology

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Development and Experimental Validation of a Docking Strategy for the Generation of Kinase-Targeted Libraries

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Chemical Fragments as Foundations for Understanding Target Space and Activity Prediction

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Assessment of Chemical Coverage of Kinome Space and Its Implications for Kinase Drug Discovery

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A small molecule–kinase interaction map for clinical kinase inhibitors

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A quantitative analysis of kinase inhibitor selectivity

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Structural basis for p38α MAP kinase quinazolinone and pyridol-pyrimidine inhibitor specificity

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Activation of tyrosine kinases by mutation of the gatekeeper threonine

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The selectivity of protein kinase inhibitors: a further update

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An efficient rapid system for profiling the cellular activities of molecular libraries

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The gatekeeper residue controls autoactivation of ERK2 via a pathway of intramolecular connectivity

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A systematic interaction map of validated kinase inhibitors with Ser/Thr kinases

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Structural Analysis of Protein Kinase A Mutants with Rho-kinase Inhibitor Specificity

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Molecular basis for specificity in the druggable kinome: sequence-based analysis

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Sequence logos: a new way to display consensus sequences

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WebLogo: A Sequence Logo Generator: Figure 1

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Research Article: Selectivity‐determining Residues in Plk1

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The Protein Kinase Complement of the Human Genome

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Structural Bioinformatics-Based Design of Selective, Irreversible Kinase Inhibitors

inferredcites →https://doi.org/10.2174/0929867043455684openalex-snapshot

Virtual Screening for Kinase Targets

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Recent Kinase and Kinase Inhibitor X-ray Structures: Mechanisms of Inhibition and Selectivity Insights

What points at this work

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

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Network Measures for Chemical Library Design

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A Risk Assessment Perspective of Current Practice in Characterizing Uncertainties in QSAR Regression Predictions

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Quantitative Structure‐activity Relationship (QSAR) Models for Docking Score Correction

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Prediction of Protein−compound Binding Energies from Known Activity Data: Docking‐score‐based Method and its Applications

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How to design potent and selective DYRK1B inhibitors? Molecular modeling study

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Knowledge-Based Approaches to Off-Target Screening

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3D QSAR and pharmacophore studies on inhibitors of insuline like growth factor 1 receptor (IGF-1R) and insulin receptor (IR) as potential anti-cancer agents

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Computational toxicology—a tool for early safety evaluation

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Web support for the more efficient discovery of kinase inhibitors

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Compound Collection Enhancement and Paradigms for High-Throughput Screening — an Update

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Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model

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On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction

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Implications of the Essential Role of Small Molecule Ligand Binding Pockets in Protein–Protein Interactions

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Profile-QSAR: A Novel meta-QSAR Method that Combines Activities across the Kinase Family To Accurately Predict Affinity, Selectivity, and Cellular Activity

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Dissecting Kinase Profiling Data to Predict Activity and Understand Cross-Reactivity of Kinase Inhibitors

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Feasibility of Using Molecular Docking-Based Virtual Screening for Searching Dual Target Kinase Inhibitors

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Identification of Binding Specificity-Determining Features in Protein Families

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Computational Modeling of Kinase Inhibitor Selectivity

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Azaindole-Based Inhibitors of Cdc7 Kinase: Impact of the Pre-DFG Residue, Val 195

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Cross-Reactivity Virtual Profiling of the Human Kinome by X-ReactKIN: A Chemical Systems Biology Approach

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Computational analysis of kinase inhibitor selectivity using structural knowledge

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A theoretical entropy score as a single value to express inhibitor selectivity

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Modeling bioavailability to organs protected by biological barriers

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Multi-task learning with a natural metric for quantitative structure activity relationship learning

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Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors

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Using Multiple Microenvironments to Find Similar Ligand-Binding Sites: Application to Kinase Inhibitor Binding

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Role of simple descriptors and applicability domain in predicting change in protein thermostability

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Recent Advances in Drug Design and Delivery Across Biological Barriers Using Computational Models

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Descriptor-Based Profile Analysis of Kinase Inhibitors to Predict Inhibitory Activity and to Grasp Kinase Selectivity

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Prediction of kinase-inhibitor binding affinity using energetic parameters

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Additional file 1 of Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors

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Additional file 2 of Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors

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