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NPred: QSAR classification model for identifying plant based naturally occurring anti-cancerous inhibitors

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What this work says

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

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PaDEL‐descriptor: An open source software to calculate molecular descriptors and fingerprints

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Strategies for the Optimization of Natural Leads to Anticancer Drugs or Drug Candidates

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The perspectives of computational chemistry modeling

inferredcites →https://doi.org/10.1016/j.bbagen.2013.02.008openalex-snapshot

Natural products: A continuing source of novel drug leads

inferredcites →https://doi.org/10.1016/j.cbi.2006.12.006openalex-snapshot

Computer-aided drug discovery and development (CADDD): In silico-chemico-biological approach

inferredcites →https://doi.org/10.1016/j.ejmech.2010.11.029openalex-snapshot

Ligand - based virtual screening procedure for the prediction and the identification of novel β-amyloid aggregation inhibitors using Kohonen maps and Counterpropagation Artificial Neural Networks

inferredcites →https://doi.org/10.1016/j.gene.2014.01.056openalex-snapshot

Ensemble docking and molecular dynamics identify knoevenagel curcumin derivatives with potent anti-EGFR activity

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A Novel Automated Lazy Learning QSAR (ALL-QSAR) Approach: Method Development, Applications, and Virtual Screening of Chemical Databases Using Validated ALL-QSAR Models

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Molecular Modeling on Pyrimidine-Urea Inhibitors of TNF-α Production: An Integrated Approach Using a Combination of Molecular Docking, Classification Techniques, and 3D-QSAR CoMSIA

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Natural Products As Sources of New Drugs over the 30 Years from 1981 to 2010

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The re-emergence of natural products for drug discovery in the genomics era

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LIBP-Pred: web server for lipid bindingproteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria

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Enalos InSilicoNano platform: an online decision support tool for the design and virtual screening of nanoparticles

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Current status and prospects of computational resources for natural product dereplication: a review

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Data mining in bioinformatics using Weka

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CypRules: a rule-based P450 inhibition prediction server

inferredcites →https://doi.org/10.1093/nar/gks1047openalex-snapshot

NPACT: Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target database

inferredcites →https://doi.org/10.1111/j.1747-0285.2010.01029.xopenalex-snapshot

In Silico Exploration for Identifying Structure–Activity Relationship of MEK Inhibition and Oral Bioavailability for Isothiazole Derivatives

inferredcites →https://doi.org/10.1111/j.1747-0285.2011.01291.xopenalex-snapshot

3D‐QSAR and Molecular Docking Studies on 3‐Anilino‐4‐Arylmaleimide Derivatives as Glycogen Synthase Kinase‐3β Inhibitors

inferredcites →https://doi.org/10.1126/science.1168243openalex-snapshot

Drug Discovery and Natural Products: End of an Era or an Endless Frontier?

inferredcites →https://doi.org/10.1186/s13062-015-0046-9openalex-snapshot

QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest

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QSAR-Based Models for Designing Quinazoline/Imidazothiazoles/Pyrazolopyrimidines Based Inhibitors against Wild and Mutant EGFR

inferredcites →https://doi.org/10.2174/1568026615666150506144536openalex-snapshot

A Risk Assessment Tool for the Virtual Screening of Metal Oxide Nanoparticles through Enalos InSilicoNano Platform

inferredcites →https://doi.org/10.2174/1871520615666150629101827openalex-snapshot

Acetogenins as Potential Anticancer Agents

What points at this work

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

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Indicators for the medicinal and aromatic potential of endemic plants in the Peloponnese (Greece)

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Machine Learning‐Based High‐Throughput Screening, Molecular Modeling and Quantum Chemical Analysis to Investigate Mycobacterium tuberculosis MetRS Inhibitors

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Pharmacokinetic profiling of anticancer phytocompounds using computational approach

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Computational Modeling of Nonlinear Phenomena Using Machine Learning

inferred← citeshttps://doi.org/10.1007/s11030-021-10284-6openalex-snapshot

EGFRisopred: a machine learning-based classification model for identifying isoform-specific inhibitors against EGFR and HER2

inferred← citeshttps://doi.org/10.1007/s11030-022-10590-7openalex-snapshot

Recent advances in the area of plant-based anti-cancer drug discovery using computational approaches

inferred← citeshttps://doi.org/10.1016/b978-0-12-821783-2.00009-1openalex-snapshot

Natural products in chemotherapy of cancers

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Synthesis of metronidazole based thiazolidinone analogs as promising antiamoebic agents

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2025.110442openalex-snapshot

DFT_ANPD: A dual-feature two-sided attention network for anticancer natural products detection

inferred← citeshttps://doi.org/10.1021/acs.jcim.1c00920openalex-snapshot

iANP-EC: Identifying Anticancer Natural Products Using Ensemble Learning Incorporated with Evolutionary Computation

inferred← citeshttps://doi.org/10.1021/acs.jcim.4c00643openalex-snapshot

Multitask Learning on Graph Convolutional Residual Neural Networks for Screening of Multitarget Anticancer Compounds

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Machine Learning, Molecular Docking, and Dynamics-Based Computational Identification of Potential Inhibitors against Lung Cancer

inferred← citeshttps://doi.org/10.1039/9781837070206-00386openalex-snapshot

Machine Learning in Natural Product-based Drug Discovery

inferred← citeshttps://doi.org/10.1039/c6ra08517bopenalex-snapshot

Structure guided design and binding analysis of EGFR inhibiting analogues of erlotinib and AEE788 using ensemble docking, molecular dynamics and MM-GBSA

inferred← citeshttps://doi.org/10.1039/c6ra24414aopenalex-snapshot

VOCC: a database of volatile organic compounds in cancer

inferred← citeshttps://doi.org/10.1039/d2ra00373bopenalex-snapshot

Computational identification of natural product inhibitors against EGFR double mutant (T790M/L858R) by integrating ADMET, machine learning, molecular docking and a dynamics approach

inferred← citeshttps://doi.org/10.1080/07391102.2023.2293265openalex-snapshot

Integrating machine learning and high throughput screening for the discovery of allosteric AKT1 inhibitors

inferred← citeshttps://doi.org/10.1080/10799893.2018.1494740openalex-snapshot

Unraveling structural requirements of amino-pyrimidine T790M/L858R double mutant EGFR inhibitors: 2D and 3D QSAR study

inferred← citeshttps://doi.org/10.1080/10799893.2019.1660896openalex-snapshot

Exploring structural features of EGFR–HER2 dual inhibitors as anti-cancer agents using G-QSAR approach

inferred← citeshttps://doi.org/10.1111/cbdd.13343openalex-snapshot

Insight into structural requirements of antiamoebic flavonoids: 3D‐QSAR and G‐QSAR studies

inferred← citeshttps://doi.org/10.1111/cbdd.13505openalex-snapshot

QSAR of clinically important EGFR mutant L858R/T790M pyridinylimidazole inhibitors

inferred← citeshttps://doi.org/10.1111/cbdd.13697openalex-snapshot

TMLRpred: A machine learning classification model to distinguish reversible EGFR double mutant inhibitors

inferred← citeshttps://doi.org/10.1155/2017/3789856openalex-snapshot

The Correlation between Chemical Structures and Antioxidant, Prooxidant, and Antitrypanosomatid Properties of Flavonoids

inferred← citeshttps://doi.org/10.2174/1389450119666180809122244openalex-snapshot

Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs

inferred← citeshttps://doi.org/10.3390/ijms27167122openalex-snapshot

From Descriptor Learning to Binding Stability: An Explainable Machine Learning Pipeline for EGFR Double-Mutant Inhibitor Discovery

inferred← citeshttps://doi.org/10.4155/fmc-2019-0206openalex-snapshot

ADMET Profiling of Geographically Diverse Phytochemical Using Chemoinformatic Tools

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