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Comparative Analysis of Pharmacophore Screening Tools
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Pharmacophores in Drug Research
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Structure-based and shape-complemented pharmacophore modeling for the discovery of novel checkpoint kinase 1 inhibitors
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Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection—What can we learn from earlier mistakes?
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Recommendations for evaluation of computational methods
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Docking and chemoinformatic screens for new ligands and targets
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PTP1B as a drug target: recent developments in PTP1B inhibitor discovery
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Molecule-pharmacophore superpositioning and pattern matching in computational drug design
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Pharao: Pharmacophore alignment and optimization
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Towards more accurate pharmacophore modeling: Multicomplex-based comprehensive pharmacophore map and most-frequent-feature pharmacophore model of CDK2
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ZINC − A Free Database of Commercially Available Compounds for Virtual Screening
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LigandScout: 3-D Pharmacophores Derived from Protein-Bound Ligands and Their Use as Virtual Screening Filters
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The Impact of Tautomer Forms on Pharmacophore-Based Virtual Screening
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ConfGen: A Conformational Search Method for Efficient Generation of Bioactive Conformers
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One Concept, Three Implementations of 3D Pharmacophore-Based Virtual Screening: Distinct Coverage of Chemical Search Space
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Snooker: A Structure-Based Pharmacophore Generation Tool Applied to Class A GPCRs
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Pharmer: Efficient and Exact Pharmacophore Search
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Conformational Sampling of Bioactive Molecules: A Comparative Study
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Maximum Unbiased Validation (MUV) Data Sets for Virtual Screening Based on PubChem Bioactivity Data
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Influence of Protonation, Tautomeric, and Stereoisomeric States on Protein−Ligand Docking Results
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Conformational Sampling for Large-Scale Virtual Screening: Accuracy versus Ensemble Size
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Comparison of 2D Fingerprint Types and Hierarchy Level Selection Methods for Structural Grouping Using Ward's Clustering
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Fuzzy Pharmacophore Models from Molecular Alignments for Correlation-Vector-Based Virtual Screening
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Structure-Based Design of Potent Aromatase Inhibitors by High-Throughput Docking
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Large-Scale Application of High-Throughput Molecular Mechanics with Poisson−Boltzmann Surface Area for Routine Physics-Based Scoring of Protein−Ligand Complexes
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Three-Dimensional Pharmacophore Methods in Drug Discovery
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A comparison of the pharmacophore identification programs: Catalyst, DISCO and GASP
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Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets
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Virtual screening: an endless staircase?
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Chemoinformatics Approaches to Virtual Screening
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CoCoCo: a free suite of multiconformational chemical databases for high-throughput virtual screening purposes
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A self-organizing principle for learning nonlinear manifolds
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UniProt: the Universal Protein knowledgebase
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MMsINC: a large-scale chemoinformatics database
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Prospective virtual screening with Ultrafast Shape Recognition: the identification of novel inhibitors of arylamine N -acetyltransferases
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Conservation of the Chk1 Checkpoint Pathway in Mammals: Linkage of DNA Damage to Cdk Regulation Through Cdc25
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Increased Insulin Sensitivity and Obesity Resistance in Mice Lacking the Protein Tyrosine Phosphatase-1B Gene
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CYCLIN-DEPENDENT KINASES: Engines, Clocks, and Microprocessors
inferredcites →https://doi.org/10.1186/1758-2946-1-6openalex-snapshot
Combining docking with pharmacophore filtering for improved virtual screening
inferredcites →https://doi.org/10.1186/1758-2946-3-s1-p27openalex-snapshot
Use of large multiconformational databases with structure-based pharmacophore models for fast screening of commercial compound collections
inferredcites →https://doi.org/10.2174/092986708784049630openalex-snapshot
Pharmacophore-Based Virtual Screening
inferredcites →https://doi.org/10.2174/092986711795933669openalex-snapshot
Pharmacophore Modelling: A Forty Year Old Approach and its Modern Synergies
inferredcites →https://doi.org/10.2174/138920307781369391openalex-snapshot
Free Resources to Assist Structure-Based Virtual Ligand Screening Experiments
inferredcites →https://doi.org/10.2174/156802609789207091openalex-snapshot
Docking Screens: Right for the Right Reasons?
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Freely Accessible Databases of Commercial Compounds For High- Throughput Virtual Screenings
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Molecular Design. Concepts and Applications
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Urokinase Inhibitor Design Based on Pharmacophore Model Derived from Diverse Classes of Inhibitors
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Computer-Aided Discovery of Glycogen Phosphorylase Inhibitors Exploiting Natural Products
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Prospective performance evaluation of selected common virtual screening tools. Case study: Cyclooxygenase (COX) 1 and 2
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Mapping of Protein Binding Sites using clustering algorithms - Development of a pharmacophore based drug discovery tool
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In vitro antibacterial efficacy of plants used by an Indian aboriginal tribe against pathogenic bacteria isolated from clinical samples
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Interaction-related volumetric and some other properties of urea solutions in aqueous N-tetramethylglycoluril (the mebicar drug) at different temperatures and under the ambient pressure
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Volume-related interaction properties of the pharmaceutical mebicar (N-tetramethylglycoluril) in aqueous sucrose solutions between (278.15 and 318.15) K and at ambient pressure
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Hybrid pharmacophore-based design of novel 5-lipoxygenase inhibitors: Molecular docking and dynamics simulation studies
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Computational methods for drug design and discovery: focus on China
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Hierarchical virtual screening approaches in small molecule drug discovery
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Methods for generating and applying pharmacophore models as virtual screening filters and for bioactivity profiling
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Benchmarking methods and data sets for ligand enrichment assessment in virtual screening
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AutoPH4: An Automated Method for Generating Pharmacophore Models from Protein Binding Pockets
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ePharmaLib: A Versatile Library of e-Pharmacophores to Address Small-Molecule (Poly-)Pharmacology
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Discovery of Potent Soluble Epoxide Hydrolase (sEH) Inhibitors by Pharmacophore-Based Virtual Screening
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From Homology Models to a Set of Predictive Binding Pockets–a 5-HT1A Receptor Case Study
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Computational Modeling of β-Secretase 1 (BACE-1) Inhibitors Using Ligand Based Approaches
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Conservation and Relevance of Pharmacophore Point Types
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Ligand-Based Virtual Screening Using Graph Edit Distance as Molecular Similarity Measure
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Conditional Probabilistic Analysis for Prediction of the Activity Landscape and Relative Compound Activities
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Pharmacophore-Based Similarity Scoring for DOCK
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Pharmit: interactive exploration of chemical space
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Benchmarking platform for ligand-based virtual screening
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Using Bayesian modeling on molecular fragments features for virtual screening
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Structure-based three-dimensional pharmacophores as an alternative to traditional methodologies
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Integration of the Butina algorithm and ensemble learning strategies for the advancement of a pharmacophore ligand-based model: an in silico investigation of apelin agonists
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Computer-Aided Drug Design towards New Psychotropic and Neurological Drugs
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inferred← citeshttps://doi.org/10.4155/fmc-2018-0076openalex-snapshot
A Review of Ligand-Based Virtual Screening Web Tools and Screening Algorithms in Large Molecular Databases in the Age of Big Data
inferred← citeshttps://doi.org/10.4155/fmc.14.114openalex-snapshot
Pharmacophore Modeling for Cox-1 and -2 Inhibitors with Ligandscout in Comparison to Discovery Studio
inferred← citeshttps://doi.org/10.5281/zenodo.193460openalex-snapshot
FIGURE 20 in Ochthebius (Enicocerus) aguilerai sp. n. from central Spain, with a molecular phylogeny of the Western Palaearctic species of Enicocerus (Coleoptera, Hydraenidae)
inferred← citeshttps://doi.org/10.58837/chula.the.2018.16openalex-snapshot
Molecular modeling on potent compounds toward envelope proteins of dengue and zika viruses
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430713openalex-snapshot
Additional file 1 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430716openalex-snapshot
Additional file 2 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430719openalex-snapshot
Additional file 3 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430722openalex-snapshot
Additional file 4 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430725openalex-snapshot
Additional file 5 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430728openalex-snapshot
Additional file 6 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430731openalex-snapshot
Additional file 7 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
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