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Discovery of Novel Antimalarial Compounds Enabled by QSAR-Based Virtual Screening

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

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Handbook of Molecular Descriptors
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The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models
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A study on antimalarial artemisinin derivatives using MEP maps and multivariate QSAR
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Substructural fragments: an universal language to encode reactions, molecular and supramolecular structures
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What do we know and when do we know it?
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QSAR Modeling of the Blood–Brain Barrier Permeability for Diverse Organic Compounds
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Chloroquine: Mechanism of drug action and resistance in plasmodium falciparum
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Antimalarial activity: A QSAR modeling using CODESSA PRO software
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3D-QSAR analysis of antimalarial farnesyltransferase inhibitors based on a 2,5-diaminobenzophenone scaffold
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Computational modeling tools for the design of potent antimalarial bisbenzamidines: Overcoming the antimalarial potential of pentamidine
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Evolving molecules using multi-objective optimization: applying to ADME/Tox
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3D QSAR studies on antimalarial alkoxylated and hydroxylated chalcones by CoMFA and CoMSIA
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Non-stochastic quadratic fingerprints and LDA-based QSAR models in hit and lead generation through virtual screening: theoretical and experimental assessment of a promising method for the discovery of new antimalarial compounds
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QSAR Studies on Antimalarial Substituted Phenyl Analogues and Their Nω-Oxides
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Beware of q2!
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A Knowledge-Based Approach in Designing Combinatorial or Medicinal Chemistry Libraries for Drug Discovery. 1. A Qualitative and Quantitative Characterization of Known Drug Databases
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Combinatorial QSAR of Ambergris Fragrance Compounds
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ZINC − A Free Database of Commercially Available Compounds for Virtual Screening
inferredcites →https://doi.org/10.1021/ci050085topenalex-snapshot
Ligand-Based Virtual Screening and in Silico Design of New Antimalarial Compounds Using Nonstochastic and Stochastic Total and Atom-Type Quadratic Maps
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Combinatorial QSAR Modeling of P-Glycoprotein Substrates
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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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Trust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling Research
inferredcites →https://doi.org/10.1021/ci700443vopenalex-snapshot
Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis
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Novel Variable Selection Quantitative Structure−Property Relationship Approach Based on the k -Nearest-Neighbor Principle
inferredcites →https://doi.org/10.1021/jm010488uopenalex-snapshot
Quantitative Structure−Activity Relationship Analysis of Functionalized Amino Acid Anticonvulsant Agents Using k Nearest Neighbor and Simulated Annealing PLS Methods
inferredcites →https://doi.org/10.1021/jm0105427openalex-snapshot
Antitumor Agents. 213. Modeling of Epipodophyllotoxin Derivatives Using Variable SelectionkNearest Neighbor QSAR Method
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Application of Validated QSAR Models of D1Dopaminergic Antagonists for Database Mining
inferredcites →https://doi.org/10.1021/jm970732aopenalex-snapshot
Three-Dimensional Quantitative Similarity−Activity Relationships (3D QSiAR) from SEAL Similarity Matrices
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Cheminformatics Analysis of Assertions Mined from Literature That Describe Drug-Induced Liver Injury in Different Species
inferredcites →https://doi.org/10.1023/a:1025386326946openalex-snapshot
Rational selection of training and test sets for the development of validated QSAR models
inferredcites →https://doi.org/10.1038/nature09099openalex-snapshot
Chemical genetics of Plasmodium falciparum
inferredcites →https://doi.org/10.1038/nature09107openalex-snapshot
Thousands of chemical starting points for antimalarial lead identification
inferredcites →https://doi.org/10.1038/nchembio806openalex-snapshot
A clinical drug library screen identifies astemizole as an antimalarial agent
inferredcites →https://doi.org/10.1038/nrd2972openalex-snapshot
New medicines to improve control and contribute to the eradication of malaria
inferredcites →https://doi.org/10.1039/9781847558879openalex-snapshot
Chemoinformatics Approaches to Virtual Screening
inferredcites →https://doi.org/10.1039/b917760bopenalex-snapshot
Precompetitive preclinical ADME/Tox data: set it free on the web to facilitate computational model building and assist drug development
inferredcites →https://doi.org/10.1093/jac/dki470openalex-snapshot
Identification of new antimalarial drugs by linear discriminant analysis and topological virtual screening
inferredcites →https://doi.org/10.1111/j.1747-0285.2006.00391.xopenalex-snapshot
Searching for New Antimalarial Therapeutics amongst Known Drugs
inferredcites →https://doi.org/10.1126/science.1205216openalex-snapshot
Chemical Genomic Profiling for Antimalarial Therapies, Response Signatures, and Molecular Targets
inferredcites →https://doi.org/10.1145/1961189.1961199openalex-snapshot
LIBSVM
inferredcites →https://doi.org/10.1172/jci115456openalex-snapshot
Antimalarial effects of peptide inhibitors of a Plasmodium falciparum cysteine proteinase.
inferredcites →https://doi.org/10.1242/jeb.00589openalex-snapshot
Antimalarial drug discovery: old and new approaches
inferredcites →https://doi.org/10.2174/138161207782794257openalex-snapshot
Predictive QSAR Modeling Workflow, Model Applicability Domains, and Virtual Screening
inferredcites →https://doi.org/10.2174/157340908785747465openalex-snapshot
ISIDA - Platform for Virtual Screening Based on Fragment and Pharmacophoric Descriptors

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