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Can We Learn To Distinguish between “Drug-like” and “Nondrug-like” Molecules?
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Outgoing claims: the papers this work cites, builds on, or argues with.
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An Improved Acceptance Procedure for the Hybrid Monte Carlo Algorithm
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Libraries of non-polymeric organic molecules
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Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
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Topological torsion: a new molecular descriptor for SAR applications. Comparison with other descriptors
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Use of Structure−Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection
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Molecular Diversity in Chemical Databases: Comparison of Medicinal Chemistry Knowledge Bases and Databases of Commercially Available Compounds
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Similarity Measures for Rational Set Selection and Analysis of Combinatorial Libraries: The Diverse Property-Derived (DPD) Approach
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Equation of State Calculations by Fast Computing Machines
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Phasing out Leaded Gasoline Will Not End Lead Poisoning in Developing Countries
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The NIEHS Predictive-Toxicology Evaluation Project.
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Applied Multivariate Statistical Analysis.
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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History of Quantitative Structure–Activity Relationships
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Library Filtering Systems and Prediction of Drug‐Like Properties
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Database Profiling by Neural Networks
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Chemoinformatics and the Quest for Leads in Drug Discovery
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Docking and Scoring for Structure‐based Drug Design
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Lead Identification by Virtual Screening
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The Molecular Basis of Predicting Druggability
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Bioinformatics: From Peptides to Profiled Leads
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Physicochemical Properties in Drug Profiling
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Drug Discovery: An Overview
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Anwendung und Grenzen kristallographischer Daten im strukturbezogenen Liganden‐ und Wirkstoff‐Design
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Computation of the physio‐chemical properties and data mining of large molecular collections
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Deep learning for computational chemistry
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Selection criteria for drug‐like compounds
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Predictivity of Simulated ADME AutoQSAR Models over Time
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Bayesian Inference Network Significantly Improves the Effectiveness of Similarity Searching Using Multiple 2D Fingerprints and Multiple Reference Structures
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Machine Learning and Neural Network Methods Applied to Drug Discovery
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Evolutionary algorithms and de novo peptide design
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Chemogenomics in Drug Discovery – The Druggable Genome and Target Class Properties
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Biology Oriented Synthesis and Diversity Oriented Synthesis in Compound Collection Development
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In Silico Screening
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Quantitative Approaches to Structure–Activity Relationships
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Pharmacological Space
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Quantitative structure-activity relationships (QSARs) in medicinal chemistry
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Natural Products as Lead Sources for Drug Development
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ELECTRONIC SCREENING: LEAD FINDING FROM DATABASE MINING
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HIGH-SPEED CHEMISTRY LIBRARIES: ASSESSMENT OF DRUG-LIKENESS
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Recent Advances in the Assessment of Druglikeness Using 2D-Structural Descriptors
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Pursuing the leadlikeness concept in pharmaceutical research
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Protein structure similarity clustering (PSSC) and natural product structure as inspiration sources for drug development and chemical genomics
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Chemical biology and bacteria: not simply a matter of life or death
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Chemical space of orally active compounds
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A physicochemical descriptor based method for effective and rapid screening of dual inhibitors against BACE-1 and GSK-3β as targets for Alzheimer’s disease
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Structural insights on the interaction potential of natural leads against major protein targets of SARS-CoV-2: Molecular modelling, docking and dynamic simulation studies
inferred← citeshttps://doi.org/10.1016/j.csbj.2021.08.011openalex-snapshot
A review on machine learning approaches and trends in drug discovery
inferred← citeshttps://doi.org/10.1016/j.ddtec.2010.11.010openalex-snapshot
Fragment library design: efficiently hunting drugs in chemical space
inferred← citeshttps://doi.org/10.1016/j.drudis.2006.06.017openalex-snapshot
Synthetic library design
inferred← citeshttps://doi.org/10.1016/j.drudis.2006.07.002openalex-snapshot
Modern agrochemical research: a missed opportunity for drug discovery?
inferred← citeshttps://doi.org/10.1016/j.drudis.2006.10.012openalex-snapshot
Knowledge-based chemoinformatic approaches to drug discovery
inferred← citeshttps://doi.org/10.1016/j.drudis.2007.11.007openalex-snapshot
Assessing drug-likeness – what are we missing?
inferred← citeshttps://doi.org/10.1016/j.drudis.2019.10.014openalex-snapshot
A drug-likeness toolbox facilitates ADMET study in drug discovery
inferred← citeshttps://doi.org/10.1016/j.ejmech.2009.12.055openalex-snapshot
Designing inhibitors against fructose 1,6-bisphosphatase: Exploring natural products for novel inhibitor scaffolds
inferred← citeshttps://doi.org/10.1016/j.ijpharm.2009.01.026openalex-snapshot
An interesting relationship between drug absorption and melting point
inferred← citeshttps://doi.org/10.1016/j.ijpharm.2014.03.050openalex-snapshot
A comparative ex vivo drug permeation study of beta-blockers through porcine buccal mucosa
inferred← citeshttps://doi.org/10.1016/j.jmgm.2004.03.006openalex-snapshot
Selecting compounds for focused screening using linear discriminant analysis and artificial neural networks
inferred← citeshttps://doi.org/10.1016/j.jmgm.2010.05.008openalex-snapshot
Analysis and comparison of 2D fingerprints: Insights into database screening performance using eight fingerprint methods
inferred← citeshttps://doi.org/10.1016/j.jmgm.2016.12.019openalex-snapshot
First protein drug target’s appraisal of lead-likeness descriptors to unfold the intervening chemical space
inferred← citeshttps://doi.org/10.1016/j.lfs.2025.124180openalex-snapshot
Advances in AI for predicting pharmacological properties of natural medicines
inferred← citeshttps://doi.org/10.1016/j.meegid.2021.105155openalex-snapshot
Carbon fullerene and nanotube are probable binders to multiple targets of SARS-CoV-2: Insights from computational modeling and molecular dynamic simulation studies
inferred← citeshttps://doi.org/10.1016/j.pharmthera.2013.01.016openalex-snapshot
Structure and dynamics of molecular networks: A novel paradigm of drug discovery
inferred← citeshttps://doi.org/10.1016/j.tetlet.2013.04.026openalex-snapshot
A facile method for the synthesis of pyridazino[4,5-b][1,4]thiazine-diones via Smiles rearrangement
inferred← citeshttps://doi.org/10.1016/s0006-2952(99)00253-1openalex-snapshot
Use of genomics and combinatorial chemistry in the development of new antimycobacterial drugs
inferred← citeshttps://doi.org/10.1016/s0065-7743(00)35028-xopenalex-snapshot
Chapter 27. Ex vivo approaches to predicting oral pharmacokinetics in humans
inferred← citeshttps://doi.org/10.1016/s0065-7743(05)40022-6openalex-snapshot
Chemical Tools for Indications Discovery
inferred← citeshttps://doi.org/10.1016/s0065-7743(08)60589-8openalex-snapshot
Chapter 27. Application of Combinatorial and Parallel Synthesis to Medicinal Chemistry
inferred← citeshttps://doi.org/10.1016/s0065-7743(08)60590-4openalex-snapshot
Chapter 28. Recent Developments in Molecular Diversity: Computational Approaches to Combinatorial Chemistry
inferred← citeshttps://doi.org/10.1016/s0079-6468(02)41001-6openalex-snapshot
Predicting Oral Absorption and Bioavailability
inferred← citeshttps://doi.org/10.1016/s0079-6468(02)41002-8openalex-snapshot
Virtual Screening of Virtual Libraries
inferred← citeshttps://doi.org/10.1016/s0079-6468(08)70058-4openalex-snapshot
Application of High-throughput Screening Techniques to Drug Discovery
inferred← citeshttps://doi.org/10.1016/s0149-6395(01)80004-0openalex-snapshot
Combinatorial chemistry and high-throughput screening in drug discovery and development
inferred← citeshttps://doi.org/10.1016/s0165-7208(02)80014-9openalex-snapshot
Computational methods for the analysis of molecular diversity
inferred← citeshttps://doi.org/10.1016/s0166-1280(02)00619-xopenalex-snapshot
Artificial neural networks and genetic algorithms in QSAR
inferred← citeshttps://doi.org/10.1016/s0169-409x(02)00003-0openalex-snapshot
Prediction of ‘drug-likeness’
inferred← citeshttps://doi.org/10.1016/s0223-5234(99)80052-xopenalex-snapshot
Neural networks in drug discovery: have they lived up to their promise?
inferred← citeshttps://doi.org/10.1016/s0378-4347(99)00007-9openalex-snapshot
Combinatorial chemistry, automation and molecular diversity: new trends in the pharmaceutical industry
inferred← citeshttps://doi.org/10.1016/s0731-7085(01)00427-7openalex-snapshot
Combining spectroscopic data (MS, IR): exploratory chemometric analysis for characterising similarity/diversity of chemical structures
inferred← citeshttps://doi.org/10.1016/s0893-6080(99)00094-5openalex-snapshot
Neural networks are useful tools for drug design
inferred← citeshttps://doi.org/10.1016/s0958-1669(99)00059-2openalex-snapshot
Chemoinformatics – similarity and diversity in chemical libraries
inferred← citeshttps://doi.org/10.1016/s0960-894x(02)00244-5openalex-snapshot
Drugs, leads, and drug-likeness: an analysis of some recently launched drugs
inferred← citeshttps://doi.org/10.1016/s0968-0896(03)00480-2openalex-snapshot
Synthesis and antimycobacterial activity of 3,5-disubstituted thiadiazine thiones
inferred← citeshttps://doi.org/10.1016/s1056-8719(00)00107-6openalex-snapshot
Drug-like properties and the causes of poor solubility and poor permeability
inferred← citeshttps://doi.org/10.1016/s1056-8719(00)00108-8openalex-snapshot
HTS in the new millennium
inferred← citeshttps://doi.org/10.1016/s1074-5521(00)00106-xopenalex-snapshot
Antagonists of protein–protein interactions
inferred← citeshttps://doi.org/10.1016/s1093-3263(00)00059-0openalex-snapshot
Applications of random sampling to virtual screening of combinatorial libraries
inferred← citeshttps://doi.org/10.1016/s1093-3263(00)00066-8openalex-snapshot
Chemical information management in drug discovery: optimizing the computational and combinatorial chemistry interfaces
inferred← citeshttps://doi.org/10.1016/s1093-3263(01)00103-6openalex-snapshot
General topological patterns of known drugs
inferred← citeshttps://doi.org/10.1016/s1093-3263(01)00122-xopenalex-snapshot
Enhancement of binary QSAR analysis by a GA-based variable selection method
inferred← citeshttps://doi.org/10.1016/s1093-3263(01)00149-8openalex-snapshot
Subcellular pharmacokinetics and its potential for library focusing
inferred← citeshttps://doi.org/10.1016/s1359-6446(00)00061-1openalex-snapshot
Combining high-throughput pharmacokinetic screens at the hits-to-leads stage of drug discovery
inferred← citeshttps://doi.org/10.1016/s1359-6446(00)01516-6openalex-snapshot
The in silico world of virtual libraries
inferred← citeshttps://doi.org/10.1016/s1359-6446(00)01616-0openalex-snapshot
Library design for NMR-based screening
inferred← citeshttps://doi.org/10.1016/s1359-6446(00)80067-7openalex-snapshot
Combining high-throughput pharmacokinetic screens at the hits-to-leads stage of drug discovery
inferred← citeshttps://doi.org/10.1016/s1359-6446(01)02093-1openalex-snapshot
Statistical design and application to combinatorial chemistry
inferred← citeshttps://doi.org/10.1016/s1359-6446(02)02371-1openalex-snapshot
Chemoproteomics as a basis for post-genomic drug discovery
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