On the public citation graph

Selecting Screening Candidates for Kinase and G Protein-Coupled Receptor Targets Using Neural Networks

https://doi.org/10.1021/ci020267c

0 signed · 101 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

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

inferredcites →https://doi.org/10.1002/(sici)1520-6017(200002)89:2<145::aid-jps2>3.0.co;2-6openalex-snapshot

Role of the Development Scientist in Compound Lead Selection and Optimization

inferredcites →https://doi.org/10.1002/(sici)1521-3773(19991004)38:19<2894::aid-anie2894>3.0.co;2-fopenalex-snapshot

“Scaffold-Hopping” by Topological Pharmacophore Search: A Contribution to Virtual Screening

inferredcites →https://doi.org/10.1002/(sici)1521-3773(19991004)38:19<2896::aid-anie2896>3.0.co;2-3openalex-snapshot

Cascade Reactions in Quantitative Solid-State Syntheses

inferredcites →https://doi.org/10.1016/s0065-7743(00)35018-7openalex-snapshot

Chapter 17. Chemokines: Targets for novel therapeutics

inferredcites →https://doi.org/10.1016/s0065-7743(00)35028-xopenalex-snapshot

Chapter 27. Ex vivo approaches to predicting oral pharmacokinetics in humans

inferredcites →https://doi.org/10.1016/s0169-409x(96)00423-1openalex-snapshot

Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings

inferredcites →https://doi.org/10.1016/s1093-3263(01)00103-6openalex-snapshot

General topological patterns of known drugs

inferredcites →https://doi.org/10.1016/s1359-6446(00)01559-2openalex-snapshot

Predicting human safety: screening and computational approaches

inferredcites →https://doi.org/10.1016/s1359-6446(01)01807-4openalex-snapshot

Miniaturized HTS technologies – uHTS

inferredcites →https://doi.org/10.1016/s1359-6446(01)02085-2openalex-snapshot

Combinatorial chemistry: 20 years on…

inferredcites →https://doi.org/10.1016/s1359-6446(97)01083-0openalex-snapshot

Reactive compounds and in vitro false positives in HTS

inferredcites →https://doi.org/10.1016/s1359-6446(97)01163-xopenalex-snapshot

Virtual screening—an overview

inferredcites →https://doi.org/10.1021/ci0003810openalex-snapshot

Improving the Odds in Discriminating “Drug-like” from “Non Drug-like” Compounds

inferredcites →https://doi.org/10.1021/ci000384copenalex-snapshot

Unsupervised Forward Selection: A Method for Eliminating Redundant Variables

inferredcites →https://doi.org/10.1021/ci000386xopenalex-snapshot

Classification of Kinase Inhibitors Using BCUT Descriptors

inferredcites →https://doi.org/10.1021/ci000397qopenalex-snapshot

Prediction of Biological Activity for High-Throughput Screening Using Binary Kernel Discrimination

inferredcites →https://doi.org/10.1021/ci00063a011openalex-snapshot

Molecular identification number for substructure searches

inferredcites →https://doi.org/10.1021/ci00063a012openalex-snapshot

Topological organic chemistry. 1. Graph theory and topological indices of alkanes

inferredcites →https://doi.org/10.1021/ci960039gopenalex-snapshot

Diversity Profiling and Design Using 3D Pharmacophores: Pharmacophore-Derived Queries (PDQ)

inferredcites →https://doi.org/10.1021/ci970431+openalex-snapshot

Identification of Biological Activity Profiles Using Substructural Analysis and Genetic Algorithms

inferredcites →https://doi.org/10.1021/ci9800211openalex-snapshot

Chemical Similarity Searching

inferredcites →https://doi.org/10.1021/ci980070dopenalex-snapshot

New QSAR Methods Applied to Structure−Activity Mapping and Combinatorial Chemistry

inferredcites →https://doi.org/10.1021/ci980137xopenalex-snapshot

Metric Validation and the Receptor-Relevant Subspace Concept

inferredcites →https://doi.org/10.1021/ci980138popenalex-snapshot

Design and Diversity Analysis of Large Combinatorial Libraries Using Cell-Based Methods

inferredcites →https://doi.org/10.1021/ci990266topenalex-snapshot

Potential Drugs and Nondrugs: Prediction and Identification of Important Structural Features

inferredcites →https://doi.org/10.1021/ci990423oopenalex-snapshot

Strategic Pooling of Compounds for High-Throughput Screening

inferredcites →https://doi.org/10.1021/cr990085qopenalex-snapshot

Combinatorial Chemistry and Mass Spectrometry in the 21st Century Drug Discovery Laboratory

inferredcites →https://doi.org/10.1021/jm0010670openalex-snapshot

Discriminating between Drugs and Nondrugs by Prediction of Activity Spectra for Substances (PASS)

inferredcites →https://doi.org/10.1021/jm015507eopenalex-snapshot

Simple Selection Criteria for Drug-like Chemical Matter

inferredcites →https://doi.org/10.1021/jm9602928openalex-snapshot

The Properties of Known Drugs. 1. Molecular Frameworks

inferredcites →https://doi.org/10.1021/jm970666copenalex-snapshot

Can We Learn To Distinguish between “Drug-like” and “Nondrug-like” Molecules?

inferredcites →https://doi.org/10.1021/jm9706776openalex-snapshot

A Scoring Scheme for Discriminating between Drugs and Nondrugs

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/jm990017wopenalex-snapshot

Designing Libraries with CNS Activity

inferredcites →https://doi.org/10.1021/jm9903996openalex-snapshot

Properties of Known Drugs. 2. Side Chains

inferredcites →https://doi.org/10.1023/a:1008793325522openalex-snapshot

In vitro and in silico affinity fingerprints: Finding similarities beyond structural classes

inferredcites →https://doi.org/10.1093/nar/26.1.275openalex-snapshot

GPCRDB: an information system for G protein-coupled receptors

inferredcites →https://doi.org/10.1093/oso/9780198538493.001.0001openalex-snapshot

Neural Networks for Pattern Recognition

inferredcites →https://doi.org/10.1358/dof.1999.024.05.858622openalex-snapshot

Small molecule inhibitors of receptor tyrosine kinases

inferredcites →https://doi.org/10.2174/138161280305221010100940openalex-snapshot

Inhibitors of Tyrosine Kinases Involved in Inflammation and Autoimmune Disease

inferredcites →https://doi.org/10.2174/1386207003331346openalex-snapshot

A Neural Network Based Virtual High Throughput Screening Test for the Prediction of CNS Activity

inferredcites →https://doi.org/10.2174/1386207003331445openalex-snapshot

Pharmacological Classification of Drugs Based on Neural Network Processing of Molecular Modeling Data

inferredcites →https://doi.org/10.2174/1386207013330850openalex-snapshot

Prediction of Intestinal Absorption and Blood-Brain Barrier Penetration by Computational Methods

inferredcites →https://doi.org/10.2174/1389200003339018openalex-snapshot

Early ADME in Support of Drug Discovery: The Role of Metabolic Stability Studies

What points at this work

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

inferred← citeshttps://doi.org/10.1002/9780470017913.ch9openalex-snapshot

Artificial Intelligence and Friends

inferred← citeshttps://doi.org/10.1002/9780470567623.ch6openalex-snapshot

Chemogenomics‐Based Design of GPCR‐Targeted Libraries Using Data Mining Techniques

inferred← citeshttps://doi.org/10.1002/9780470571224.pse022openalex-snapshot

Combinatorial Chemistry in the Drug Discovery Process

inferred← citeshttps://doi.org/10.1002/9783527619368.ch18openalex-snapshot

Lead Identification by Virtual Screening

inferred← citeshttps://doi.org/10.1002/cbic.200400109openalex-snapshot

Classifying “Kinase Inhibitor‐Likeness” by Using Machine‐Learning Methods

inferred← citeshttps://doi.org/10.1002/chin.200251223openalex-snapshot

Selecting Screening Candidates for Kinase and G Protein‐Coupled Receptor Targets Using Neural Networks.

inferred← citeshttps://doi.org/10.1002/qsar.200420071openalex-snapshot

Identification and Classification of GPCR Ligands Using Self-Organizing Neural Networks

inferred← citeshttps://doi.org/10.1007/978-1-60761-839-3_16openalex-snapshot

Methods for Combinatorial and Parallel Library Design

inferred← citeshttps://doi.org/10.1007/978-1-60761-931-4_8openalex-snapshot

Docking Methods for Structure-Based Library Design

inferred← citeshttps://doi.org/10.1007/s10822-025-00605-4openalex-snapshot

DTBA-net: Drug-Target Binding Affinity prediction using feature selection in hybrid CNN model

inferred← citeshttps://doi.org/10.1007/s12539-022-00523-1openalex-snapshot

Improving the Prediction of Potential Kinase Inhibitors with Feature Learning on Multisource Knowledge

inferred← citeshttps://doi.org/10.1016/b0-08-045044-x/00256-xopenalex-snapshot

Library Design: Ligand and Structure-Based Principles for Parallel and Combinatorial Libraries

inferred← citeshttps://doi.org/10.1016/b0-08-045044-x/00270-4openalex-snapshot

Seven Transmembrane G Protein-Coupled Receptors: Insights for Drug Design from Structure and Modeling

inferred← citeshttps://doi.org/10.1016/bs.armc.2017.08.001openalex-snapshot

Kinase-Centric Computational Drug Development

inferred← citeshttps://doi.org/10.1016/j.bmc.2004.09.016openalex-snapshot

Design, synthesis, computational and biological evaluation of new anxiolytics

inferred← citeshttps://doi.org/10.1016/j.cbpa.2004.06.003openalex-snapshot

Exploring the chemogenomic knowledge space with annotated chemical libraries

inferred← citeshttps://doi.org/10.1016/j.drudis.2006.10.012openalex-snapshot

Knowledge-based chemoinformatic approaches to drug discovery

inferred← citeshttps://doi.org/10.1016/j.jmgm.2004.03.001openalex-snapshot

Design of a gene family screening library targeting G-protein coupled receptors

inferred← citeshttps://doi.org/10.1016/j.jmgm.2004.03.006openalex-snapshot

Selecting compounds for focused screening using linear discriminant analysis and artificial neural networks

inferred← citeshttps://doi.org/10.1016/s1359-6446(05)03703-7openalex-snapshot

Computational chemistry-driven decision making in lead generation

inferred← citeshttps://doi.org/10.1016/s1367-5931(03)00057-7openalex-snapshot

Computational design strategies for combinatorial libraries

inferred← citeshttps://doi.org/10.1016/s1574-1400(05)01013-3openalex-snapshot

Chapter 13 Targeting the Kinome with Computational Chemistry

inferred← citeshttps://doi.org/10.1016/s1741-8364(04)02402-3openalex-snapshot

Using artificial neural networks to drive virtual screening of combinatorial libraries

inferred← citeshttps://doi.org/10.1016/s1877-1173(10)91006-5openalex-snapshot

The T1R2/T1R3 Sweet Receptor and TRPM5 Ion Channel

inferred← citeshttps://doi.org/10.1021/acs.jcim.4c00595openalex-snapshot

The Development and Application of KinomePro-DL: A Deep Learning Based Online Small Molecule Kinome Selectivity Profiling Prediction Platform

inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6b01611openalex-snapshot

Profiling Prediction of Kinase Inhibitors: Toward the Virtual Assay

inferred← citeshttps://doi.org/10.1021/acs.jmedchem.9b00855openalex-snapshot

Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation

inferred← citeshttps://doi.org/10.1021/ci0202741openalex-snapshot

A Consensus Neural Network-Based Technique for Discriminating Soluble and Poorly Soluble Compounds

inferred← citeshttps://doi.org/10.1021/ci025639wopenalex-snapshot

Development of Quantitative Structure−Activity Relationships and Classification Models for Anticonvulsant Activity of Hydantoin Analogues

inferred← citeshttps://doi.org/10.1021/ci0303013openalex-snapshot

GPCR-Tailored Pharmacophore Pattern Recognition of Small Molecular Ligands

inferred← citeshttps://doi.org/10.1021/ci049923uopenalex-snapshot

Validated QSAR Prediction of OH Tropospheric Degradation of VOCs: Splitting into Training−Test Sets and Consensus Modeling

inferred← citeshttps://doi.org/10.1021/ci050471aopenalex-snapshot

Data Visualization during the Early Stages of Drug Discovery

inferred← citeshttps://doi.org/10.1021/ci1005004openalex-snapshot

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

inferred← citeshttps://doi.org/10.1021/ci300403kopenalex-snapshot

Kinome-wide Activity Modeling from Diverse Public High-Quality Data Sets

inferred← citeshttps://doi.org/10.1021/ci700188uopenalex-snapshot

Flexible Web Service Infrastructure for the Development and Deployment of Predictive Models

inferred← citeshttps://doi.org/10.1021/jm0303195openalex-snapshot

Classification of Kinase Inhibitors Using a Bayesian Model

inferred← citeshttps://doi.org/10.1021/jm049092jopenalex-snapshot

Virtual Screening Workflow Development Guided by the “Receiver Operating Characteristic” Curve Approach. Application to High-Throughput Docking on Metabotropic Glutamate Receptor Subtype 4

inferred← citeshttps://doi.org/10.1021/jm101195aopenalex-snapshot

Trends in Kinase Selectivity: Insights for Target Class-Focused Library Screening

inferred← citeshttps://doi.org/10.1021/jm701021bopenalex-snapshot

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

inferred← citeshttps://doi.org/10.1038/nrd941openalex-snapshot

Integration of virtual and high-throughput screening

inferred← citeshttps://doi.org/10.1080/10629360310001623935openalex-snapshot

Prediction of Biological Activity Spectra via The Internet

inferred← citeshttps://doi.org/10.1080/1062936032000169642openalex-snapshot

Performance of (consensus) kNN QSAR for predicting estrogenic activity in a large diverse set of organic compounds

inferred← citeshttps://doi.org/10.1080/17460441.2024.2376643openalex-snapshot

Polypharmacology prediction: the long road toward comprehensively anticipating small-molecule selectivity to de-risk drug discovery

inferred← citeshttps://doi.org/10.1080/20565623.2025.2483631openalex-snapshot

Tracking protein kinase targeting advances: integrating QSAR into machine learning for kinase-targeted drug discovery

inferred← citeshttps://doi.org/10.1093/bib/bbad461openalex-snapshot

KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling

inferred← citeshttps://doi.org/10.1093/bioinformatics/btaa1058openalex-snapshot

IDDkin: network-based influence deep diffusion model for enhancing prediction of kinase inhibitors

inferred← citeshttps://doi.org/10.1093/bioinformatics/btz519openalex-snapshot

KinomeX: a web application for predicting kinome-wide polypharmacology effect of small molecules

inferred← citeshttps://doi.org/10.1093/nar/gkae380openalex-snapshot

KinomeMETA: a web platform for kinome-wide polypharmacology profiling with meta-learning

inferred← citeshttps://doi.org/10.1109/tpami.2021.3120428openalex-snapshot

Co-VAE: Drug-Target Binding Affinity Prediction by Co-Regularized Variational Autoencoders

inferred← citeshttps://doi.org/10.1186/s13321-017-0209-zopenalex-snapshot

SimBoost: a read-across approach for predicting drug–target binding affinities using gradient boosting machines

inferred← citeshttps://doi.org/10.1201/9780203642627.ch7openalex-snapshot

Building QSAR Models

inferred← citeshttps://doi.org/10.1385/1-59259-802-1:355openalex-snapshot

Approaches to Target Class Combinatorial Library Design

inferred← citeshttps://doi.org/10.1385/mb:27:2:139openalex-snapshot

Neural Networks as Robust Tools in Drug Lead Discovery and Development

inferred← citeshttps://doi.org/10.2174/138620711797537148openalex-snapshot

Integration of Virtual and High Throughput Screening in Lead Discovery Settings

inferred← citeshttps://doi.org/10.3389/fgene.2014.00196openalex-snapshot

Computational methods for analysis and inference of kinase/inhibitor relationships

inferred← citeshttps://doi.org/10.4018/978-1-4666-8136-1.ch008openalex-snapshot

Integrated in Silico Methods for the Design and Optimization of Novel Drug Candidates

inferred← citeshttps://doi.org/10.4018/978-1-5225-0549-5.ch016openalex-snapshot

Integrated in Silico Methods for the Design and Optimization of Novel Drug Candidates

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.