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Gradual in Silico Filtering for Druglike Substances
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Outgoing claims: the papers this work cites, builds on, or argues with.
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VESPA: A new, fast approach to electrostatic potential-derived atomic charges from semiempirical methods
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Molecular mechanics and molecular shape. V. on the computation of the bare surface area of molecules
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Selection criteria for drug‐like compounds
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CNS Permeability of Drugs Predicted by a Decision Tree
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Impact of descriptor vector scaling on the classification of drugs and nondrugs with artificial neural networks
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Prediction of the n-Octanol/Water Partition Coefficient, logP, Using a Combination of Semiempirical MO-Calculations and a Neural Network
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Lead-like, drug-like or “Pub-like”: how different are they?
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Quantum chemical parameters in correlation analysis of gas-liquid chromatographic retention indices of amines
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Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
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Drug-like properties and the causes of poor solubility and poor permeability
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General topological patterns of known drugs
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DISSIM: a program for the analysis of chemical diversity
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Reactive compounds and in vitro false positives in HTS
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Visual and computational analysis of structure–activity relationships in high-throughput screening data
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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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Improving the Odds in Discriminating “Drug-like” from “Non Drug-like” Compounds
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Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships. 4. Additional parameters for hydrophobic and dispersive interactions and their application for an automated superposition of certain naturally occurring nucleoside antibiotics
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Review of ring perception algorithms for chemical graphs
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Cheminformatics Analysis of Organic Substituents: Identification of the Most Common Substituents, Calculation of Substituent Properties, and Automatic Identification of Drug-like Bioisosteric Groups
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Finding Multiactivity Substructures by Mining Databases of Drug-Like Compounds
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Drugs and Nondrugs: An Effective Discrimination with Topological Methods and Artificial Neural Networks
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Drug Discovery Using Support Vector Machines. The Case Studies of Drug-likeness, Agrochemical-likeness, and Enzyme Inhibition Predictions
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Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification
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A New Rapid and Effective Chemistry Space Filter in Recognizing a Druglike Database
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Comparative QSAR- and Fragments Distribution Analysis of Drugs, Druglikes, Metabolic Substances, and Antimicrobial Compounds
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Separating Drugs from Nondrugs: A Statistical Approach Using Atom Pair Distributions
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Identification of Biological Activity Profiles Using Substructural Analysis and Genetic Algorithms
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Structural Features of Toxic Chemicals for Specific Toxicity
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Potential Drugs and Nondrugs: Prediction and Identification of Important Structural Features
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Strategic Pooling of Compounds for High-Throughput Screening
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Fast Calculation of Molecular Polar Surface Area as a Sum of Fragment-Based Contributions and Its Application to the Prediction of Drug Transport Properties
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Discriminating between Drugs and Nondrugs by Prediction of Activity Spectra for Substances (PASS)
inferredcites →https://doi.org/10.1021/jm011027bopenalex-snapshot
Descriptors, Physical Properties, and Drug-Likeness
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Simple Selection Criteria for Drug-like Chemical Matter
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The Properties of Known Drugs. 1. Molecular Frameworks
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A Scoring Scheme for Discriminating between Drugs and Nondrugs
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Properties of Known Drugs. 2. Side Chains
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Correlation of Boiling Points with Molecular Structure. 1. A Training Set of 298 Diverse Organics and a Test Set of 9 Simple Inorganics
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Property distribution of drug-related chemical databases*
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Calculating partition coefficient by atom-additive method
inferredcites →https://doi.org/10.1023/a:1015040217741openalex-snapshot
Polar Molecular Surface as a Dominating Determinant for Oral Absorption and Brain Penetration of Drugs
inferredcites →https://doi.org/10.1038/nrd1032openalex-snapshot
ADMET in silico modelling: towards prediction paradise?
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Theoretical models of charge-transfer complexes
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Proceedings 2002 IEEE International Conference on Data Mining. ICDM 2002
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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In SilicoADME/Tox Predictions
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ChemInform Abstract: Gradual in silico Filtering for Druglike Substances.
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Selecting Relevant Descriptors for Classification by Bayesian Estimates: A Comparison with Decision Trees and Support Vector Machines Approaches for Disparate Data Sets
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Validation Aspects in Structure-Based Drug Design
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Recent Developments in the Application of Computer-Aided Drug Design in Neurodegenerative Disorders
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Recent Advances in the Assessment of Druglikeness Using 2D-Structural Descriptors
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The application of in silico drug-likeness predictions in pharmaceutical research
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Drug/nondrug classification using Support Vector Machines with various feature selection strategies
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Classification of nervous system withdrawn and approved drugs with ToxPrint features via machine learning strategies
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Herbal concoction Unveiled: A computational analysis of phytochemicals' pharmacokinetic and toxicological profiles using novel approach methodologies (NAMs)
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