On the public citation graph
Predicting Ligand Binding Modes from Neural Networks Trained on Protein–Ligand Interaction Fingerprints
0 signed · 87 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.
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known work and none has been retracted — and get a dated CiteStamped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.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/9783527633326.ch6openalex-snapshot
Docking Methods for Virtual Screening: Principles and Recent Advances
inferredcites →https://doi.org/10.1002/cmdc.201100317openalex-snapshot
Structure‐Based Discovery of Allosteric Modulators of Two Related Class B G‐Protein‐Coupled Receptors
inferredcites →https://doi.org/10.1002/minf.201000068openalex-snapshot
An Improved Weighted‐Residue Profile Based Method of Using Protein–Ligand Interaction Information in Increasing Hits Selection from Virtual Screening: A Study on Virtual Screening of Human GPCR A2A Receptor Antagonists
inferredcites →https://doi.org/10.1007/s10822-005-9008-0openalex-snapshot
Substructural fragments: an universal language to encode reactions, molecular and supramolecular structures
inferredcites →https://doi.org/10.1016/j.drudis.2009.01.003openalex-snapshot
Managing protein flexibility in docking and its applications
inferredcites →https://doi.org/10.1016/j.drudis.2011.07.006openalex-snapshot
Structure-based drug design to augment hit discovery
inferredcites →https://doi.org/10.1016/s0022-2836(95)80037-9openalex-snapshot
Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation
inferredcites →https://doi.org/10.1021/ci050372xopenalex-snapshot
sc-PDB: an Annotated Database of Druggable Binding Sites from the Protein Data Bank
inferredcites →https://doi.org/10.1021/ci050420dopenalex-snapshot
Knowledge-Based Interaction Fingerprint Scoring: A Simple Method for Improving the Effectiveness of Fast Scoring Functions
inferredcites →https://doi.org/10.1021/ci200034yopenalex-snapshot
CSAR Scoring Challenge Reveals the Need for New Concepts in Estimating Protein–Ligand Binding Affinity
inferredcites →https://doi.org/10.1021/ci200269qopenalex-snapshot
CSAR Benchmark Exercise of 2010: Combined Evaluation Across All Submitted Scoring Functions
inferredcites →https://doi.org/10.1021/ci300566nopenalex-snapshot
Encoding Protein–Ligand Interaction Patterns in Fingerprints and Graphs
inferredcites →https://doi.org/10.1021/ci600342eopenalex-snapshot
Optimizing Fragment and Scaffold Docking by Use of Molecular Interaction Fingerprints
inferredcites →https://doi.org/10.1021/ci900043ropenalex-snapshot
APIF: A New Interaction Fingerprint Based on Atom Pairs and Its Application to Virtual Screening
inferredcites →https://doi.org/10.1021/ci900349yopenalex-snapshot
Alignment-Free Ultra-High-Throughput Comparison of Druggable Protein−Ligand Binding Sites
inferredcites →https://doi.org/10.1021/jm030331xopenalex-snapshot
Structural Interaction Fingerprint (SIFt): A Novel Method for Analyzing Three-Dimensional Protein−Ligand Binding Interactions
inferredcites →https://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
inferredcites →https://doi.org/10.1021/jm049312topenalex-snapshot
Interaction Profiles of Protein Kinase−Inhibitor Complexes and Their Application to Virtual Screening
inferredcites →https://doi.org/10.1021/jm050381xopenalex-snapshot
Knowledge-Based Design of Target-Focused Libraries Using Protein−Ligand Interaction Constraints
inferredcites →https://doi.org/10.1021/jm0608356openalex-snapshot
Benchmarking Sets for Molecular Docking
inferredcites →https://doi.org/10.1021/jm200558uopenalex-snapshot
Docking Performance of Fragments and Druglike Compounds
inferredcites →https://doi.org/10.1021/jm8001058openalex-snapshot
Assessment of Scaffold Hopping Efficiency by Use of Molecular Interaction Fingerprints
inferredcites →https://doi.org/10.1021/jm800710xopenalex-snapshot
Selective Structure-Based Virtual Screening for Full and Partial Agonists of the β2 Adrenergic Receptor
inferredcites →https://doi.org/10.1021/jm900357yopenalex-snapshot
Combining Hit Identification Strategies: Fragment-Based and in Silico Approaches to Orally Active 2-Aminothieno[2,3-d]pyrimidine Inhibitors of the Hsp90 Molecular Chaperone
inferredcites →https://doi.org/10.1038/sj.bjp.0707515openalex-snapshot
Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go
inferredcites →https://doi.org/10.1093/bioinformatics/btq112openalex-snapshot
A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking
inferredcites →https://doi.org/10.1093/bioinformatics/btr120openalex-snapshot
sc-PDB: a database for identifying variations and multiplicity of ‘druggable’ binding sites in proteins
inferredcites →https://doi.org/10.1093/nar/gkr777openalex-snapshot
ChEMBL: a large-scale bioactivity database for drug discovery
inferredcites →https://doi.org/10.1146/annurev.biophys.32.110601.142532openalex-snapshot
Molecular Recognition and Docking Algorithms
inferredcites →https://doi.org/10.1371/journal.pone.0008554openalex-snapshot
Estrogen Receptor Alpha as a Key Target of Red Wine Polyphenols Action on the Endothelium
inferredcites →https://doi.org/10.5555/1046920.1088693openalex-snapshot
Learning Multiple Tasks with Kernel Methods
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/jmr.2471openalex-snapshot
Improvements, trends, and new ideas in molecular docking: 2012–2013 in review
inferred← citeshttps://doi.org/10.1002/minf.201900062openalex-snapshot
A Machine Learning Approach for Drug‐target Interaction Prediction using Wrapper Feature Selection and Class Balancing
inferred← citeshttps://doi.org/10.1002/minf.202300167openalex-snapshot
Accelerating Molecular Docking using Machine Learning Methods
inferred← citeshttps://doi.org/10.1007/978-1-0716-1787-8_11openalex-snapshot
Deep Learning in Structure-Based Drug Design
inferred← citeshttps://doi.org/10.1007/s10822-016-9960-xopenalex-snapshot
A D3R prospective evaluation of machine learning for protein-ligand scoring
inferred← citeshttps://doi.org/10.1007/s10822-018-0133-yopenalex-snapshot
Convolutional neural network scoring and minimization in the D3R 2017 community challenge
inferred← citeshttps://doi.org/10.1007/s12539-019-00327-wopenalex-snapshot
An Overview of Scoring Functions Used for Protein–Ligand Interactions in Molecular Docking
inferred← citeshttps://doi.org/10.1016/b978-0-12-820472-6.00048-7openalex-snapshot
Targeting GPCRs Via Multi-Platform Arrays and AI
inferred← citeshttps://doi.org/10.1016/bs.apcsb.2014.06.001openalex-snapshot
The Interplay Between Molecular Modeling and Chemoinformatics to Characterize Protein–Ligand and Protein–Protein Interactions Landscapes for Drug Discovery
inferred← citeshttps://doi.org/10.1016/bs.armc.2017.08.001openalex-snapshot
Kinase-Centric Computational Drug Development
inferred← citeshttps://doi.org/10.1016/j.bmcl.2013.12.017openalex-snapshot
An application of machine learning methods to structural interaction fingerprints—a case study of kinase inhibitors
inferred← citeshttps://doi.org/10.1016/j.compbiolchem.2021.107529openalex-snapshot
Ensembling machine learning models to boost molecular affinity prediction
inferred← citeshttps://doi.org/10.1016/j.coph.2016.07.007openalex-snapshot
Molecular interaction fingerprint approaches for GPCR drug discovery
inferred← citeshttps://doi.org/10.1016/j.csbj.2014.05.004openalex-snapshot
Simple Ligand–Receptor Interaction Descriptor (SILIRID) for alignment-free binding site comparison
inferred← citeshttps://doi.org/10.1016/j.drudis.2022.07.004openalex-snapshot
Harnessing systematic protein–ligand interaction fingerprints for drug discovery
inferred← citeshttps://doi.org/10.1016/j.drudis.2022.103356openalex-snapshot
Concepts and applications of chemical fingerprint for hit and lead screening
inferred← citeshttps://doi.org/10.1016/j.ejmech.2017.07.067openalex-snapshot
Recent advances on CDK inhibitors: An insight by means of in silico methods
inferred← citeshttps://doi.org/10.1016/j.jmgm.2018.06.005openalex-snapshot
Visualizing convolutional neural network protein-ligand scoring
inferred← citeshttps://doi.org/10.1016/j.molliq.2022.118759openalex-snapshot
Machine learning assessment of the binding region as a tool for more efficient computational receptor-ligand docking
inferred← citeshttps://doi.org/10.1016/j.pbiomolbio.2014.05.006openalex-snapshot
Polypharmacology rescored: Protein–ligand interaction profiles for remote binding site similarity assessment
inferred← citeshttps://doi.org/10.1016/j.str.2018.02.009openalex-snapshot
Ranking Enzyme Structures in the PDB by Bound Ligand Similarity to Biological Substrates
inferred← citeshttps://doi.org/10.1021/acs.jcim.0c01452openalex-snapshot
Lean-Docking: Exploiting Ligands’ Predicted Docking Scores to Accelerate Molecular Docking
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00444openalex-snapshot
Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00740openalex-snapshot
Protein–Ligand Scoring with Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b01145openalex-snapshot
libmolgrid: Graphics Processing Unit Accelerated Molecular Gridding for Deep Learning Applications
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b01202openalex-snapshot
Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5b02041openalex-snapshot
Delineation of Polypharmacology across the Human Structural Kinome Using a Functional Site Interaction Fingerprint Approach
inferred← citeshttps://doi.org/10.1021/acs.jpcc.0c01106openalex-snapshot
Optimization of Work Function via Bayesian Machine Learning Combined with First-Principles Calculation
inferred← citeshttps://doi.org/10.1021/ci500519wopenalex-snapshot
Target-Specific Native/Decoy Pose Classifier Improves the Accuracy of Ligand Ranking in the CSAR 2013 Benchmark
inferred← citeshttps://doi.org/10.1038/s41576-020-00292-xopenalex-snapshot
Deciphering cell–cell interactions and communication from gene expression
inferred← citeshttps://doi.org/10.1073/pnas.2112621118openalex-snapshot
Leveraging nonstructural data to predict structures and affinities of protein–ligand complexes
inferred← citeshttps://doi.org/10.1080/17460441.2021.1929921openalex-snapshot
Computational representations of protein–ligand interfaces for structure-based virtual screening
inferred← citeshttps://doi.org/10.1080/17568919.2025.2592531openalex-snapshot
Cheminformatic analysis of protein surfaces provides binding site insights and informs identification strategies
inferred← citeshttps://doi.org/10.1089/adt.2014.1507.abstractsopenalex-snapshot
AbstractsICBS 3rd Annual Conference Driving Biology with Chemistry November 17–19, 2014San Francisco, California
inferred← citeshttps://doi.org/10.1093/bib/bbw048openalex-snapshot
The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug–drug interactions
inferred← citeshttps://doi.org/10.1093/bioinformatics/bty757openalex-snapshot
Development of a protein–ligand extended connectivity (PLEC) fingerprint and its application for binding affinity predictions
inferred← citeshttps://doi.org/10.1101/2020.06.01.128181openalex-snapshot
Leveraging non-structural data to predict structures of protein–ligand complexes
inferred← citeshttps://doi.org/10.1111/cbdd.13750openalex-snapshot
The rise of deep learning and transformations in bioactivity prediction power of molecular modeling tools
inferred← citeshttps://doi.org/10.1186/s12859-018-2093-6openalex-snapshot
Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis
inferred← citeshttps://doi.org/10.1186/s13062-016-0118-5openalex-snapshot
A web server for analysis, comparison and prediction of protein ligand binding sites
inferred← citeshttps://doi.org/10.1186/s13293-022-00420-8openalex-snapshot
Considerations and challenges for sex-aware drug repurposing
inferred← citeshttps://doi.org/10.1186/s13321-020-00434-7openalex-snapshot
Assessing the information content of structural and protein–ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning
inferred← citeshttps://doi.org/10.1186/s13321-021-00507-1openalex-snapshot
SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors
inferred← citeshttps://doi.org/10.1186/s13321-022-00592-wopenalex-snapshot
Decomposing compounds enables reconstruction of interaction fingerprints for structure-based drug screening
inferred← citeshttps://doi.org/10.20944/preprints202112.0380.v1openalex-snapshot
Considerations and Challenges for Sex-Aware Drug Repurposing
inferred← citeshttps://doi.org/10.20944/preprints202112.0380.v2openalex-snapshot
Considerations and Challenges for Sex-Aware Drug Repurposing
inferred← citeshttps://doi.org/10.2174/1381612822666160224143008openalex-snapshot
Computational Drug Repositioning by Target Hopping: A Use Case in Chagas Disease
inferred← citeshttps://doi.org/10.26434/chemrxiv.11910870openalex-snapshot
Learning RMSD to Improve Protein-Ligand Scoring and Pose Selection
inferred← citeshttps://doi.org/10.26434/chemrxiv.11910870.v2openalex-snapshot
Learning RMSD to Improve Protein-Ligand Scoring and Pose Selection
inferred← citeshttps://doi.org/10.31891/2307-5732-2022-307-2-14-24openalex-snapshot
METHOD SUPER LEARNING FOR DETERMINATION OF MOLECULAR RELATIONSHIP
inferred← citeshttps://doi.org/10.4018/978-1-4666-8136-1.ch001openalex-snapshot
An Introduction to the Basic Concepts in QSAR-Aided Drug Design
inferred← citeshttps://doi.org/10.4018/978-1-5225-0549-5.ch002openalex-snapshot
An Introduction to the Basic Concepts in QSAR-Aided Drug Design
inferred← citeshttps://doi.org/10.48550/arxiv.1710.07400openalex-snapshot
Ligand Pose Optimization with Atomic Grid-Based Convolutional Neural Networks
inferred← citeshttps://doi.org/10.48550/arxiv.1912.04822openalex-snapshot
libmolgrid: GPU Accelerated Molecular Gridding for Deep Learning Applications
inferred← citeshttps://doi.org/10.6084/m9.figshare.14313856openalex-snapshot
Additional file 1 of SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors
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.