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Predicting Binding Affinity of CSAR Ligands Using Both Structure-Based and Ligand-Based Approaches

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What this work says

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

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Handbook of Molecular Descriptors

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Best Practices for QSAR Model Development, Validation, and Exploitation

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The Nature of Statistical Learning Theory

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Hierarchical QSAR technology based on the Simplex representation of molecular structure

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On Outliers and Activity CliffsWhy QSAR Often Disappoints

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Trust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling Research

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Rapid Flexible Docking Using a Stochastic Rotamer Library of Ligands

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Combined Application of Cheminformatics- and Physical Force Field-Based Scoring Functions Improves Binding Affinity Prediction for CSAR Data Sets

inferredcites →https://doi.org/10.1021/ci300478yopenalex-snapshot

Incorporating Backbone Flexibility in MedusaDock Improves Ligand-Binding Pose Prediction in the CSAR2011 Docking Benchmark

inferredcites →https://doi.org/10.1021/ci400025fopenalex-snapshot

CSAR Benchmark Exercise 2011–2012: Evaluation of Results from Docking and Relative Ranking of Blinded Congeneric Series

inferredcites →https://doi.org/10.1021/ci8001167openalex-snapshot

MedusaScore: An Accurate Force Field-Based Scoring Function for Virtual Drug Screening

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Application of Random Forest Approach to QSAR Prediction of Aquatic Toxicity

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A Critical Assessment of Docking Programs and Scoring Functions

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Quantitative Structure−Activity Relationship Studies of [(Biphenyloxy)propyl]isoxazole Derivatives. Inhibitors of Human Rhinovirus 2 Replication

inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot

Random Forests

inferredcites →https://doi.org/10.1023/b:jcam.0000017496.76572.6fopenalex-snapshot

Comparative study of several algorithms for flexible ligand docking

inferredcites →https://doi.org/10.1038/nchembio.155openalex-snapshot

Molecular docking and ligand specificity in fragment-based inhibitor discovery

inferredcites →https://doi.org/10.1080/1062936x.2011.569950openalex-snapshot

QSAR analysis of the toxicity of nitroaromatics inTetrahymena pyriformis: structural factors and possible modes of action

inferredcites →https://doi.org/10.1093/jac/dkm172openalex-snapshot

Identification of individual structural fragments of N,N′-(bis-5-nitropyrimidyl)dispirotripiperazine derivatives for cytotoxicity and antiherpetic activity allows the prediction of new highly active compounds

inferredcites →https://doi.org/10.1186/1479-7364-5-5-497openalex-snapshot

Survey of public domain software for docking simulations and virtual screening

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2D, 3D-QSAR and docking studies of 1,2,3-thiadiazole thioacetanilides analogues as potent HIV-1 non-nucleoside reverse transcriptase inhibitors

inferredcites →https://doi.org/10.2174/138161207782794257openalex-snapshot

Predictive QSAR Modeling Workflow, Model Applicability Domains, and Virtual Screening

inferredcites →https://doi.org/10.2174/1568026611212240007openalex-snapshot

SAR, QSAR and Docking of Anticancer Flavonoids and Variants: A Review

inferredcites →https://doi.org/10.2307/2288003openalex-snapshot

Classification and Regression Trees.

inferredcites →https://doi.org/10.4155/fmc.10.194openalex-snapshot

Per Aspera Ad Astra : Application of Simplex Qsar Approach in Antiviral Research

What points at this work

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

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Review structure‐ and dynamics‐based computational design of anticancer drugs

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In Silico Studies Designed to Select Sesquiterpene Lactones with Potential Antichagasic Activity from an In‐House Asteraceae Database

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Improvements, trends, and new ideas in molecular docking: 2012–2013 in review

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Quantitative Nanostructure–Activity Relationships: Methods, Case Studies, and Perspectives

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Use of bacteriophage to target bacterial surface structures required for virulence: a systematic search for antibiotic alternatives

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Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2

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Simplex representation of molecular structure as universal QSAR/QSPR tool

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Reaction: Molecular Modeling for Novel Antibacterials

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Binding of peanut allergen Ara h 2 with Vaccinium fruit polyphenols

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Predicting Protein–Ligand Docking Structure with Graph Neural Network

inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00275openalex-snapshot

HybridDock: A Hybrid Protein–Ligand Docking Protocol Integrating Protein- and Ligand-Based Approaches

inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00751openalex-snapshot

Docking and Scoring with Target-Specific Pose Classifier Succeeds in Native-Like Pose Identification But Not Binding Affinity Prediction in the CSAR 2014 Benchmark Exercise

inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00129openalex-snapshot

Trust, but Verify II: A Practical Guide to Chemogenomics Data Curation

inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00048openalex-snapshot

Characterizing the Chemical Space of ERK2 Kinase Inhibitors Using Descriptors Computed from Molecular Dynamics Trajectories

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SAR-Guided Scoring Function and Mutational Validation Reveal the Binding Mode of CGS-8216 at the α1+/γ2– Benzodiazepine Site

inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00765openalex-snapshot

Energetic Fingerprinting of Ligand Binding to Paralogous Proteins: The Case of the Apoptotic Pathway

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/10.1080/17460441.2019.1664467openalex-snapshot

4D- quantitative structure–activity relationship modeling: making a comeback

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Adverse drug reactions triggered by the common HLA-B*57:01 variant: a molecular docking study

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Adverse drug reactions triggered by the common HLA-B*57:01 variant: virtual screening of DrugBank using 3D molecular docking

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Development of novel algorithms for data-driven prediction of interactions between proteins and small molecules

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