Current trends in ligand-based virtual screening: molecular representations, data mining methods, new application areas, and performance evaluation.
about
Molecular docking and structure-based drug design strategiesChemDes: an integrated web-based platform for molecular descriptor and fingerprint computationBioTriangle: a web-accessible platform for generating various molecular representations for chemicals, proteins, DNAs/RNAs and their interactionsWeb-based 3D-visualization of the DrugBank chemical spaceA network-based multi-target computational estimation scheme for anticoagulant activities of compoundsThe power metric: a new statistically robust enrichment-type metric for virtual screening applications with early recovery capabilityExploring chemical space for drug discovery using the chemical universe database.Systematic assessment of scaffold distances in ChEMBL: prioritization of compound data sets for scaffold hopping analysis in virtual screening.Molpher: a software framework for systematic chemical space explorationFusing dual-event data sets for Mycobacterium tuberculosis machine learning models and their evaluation.PASS Targets: Ligand-based multi-target computational system based on a public data and naïve Bayes approach.A multi-fingerprint browser for the ZINC databaseVisualisation of the chemical space of fragments, lead-like and drug-like molecules in PubChem.Computational chemical biology: identification of small molecular probes that discriminate between members of target protein families.In silico approach to screen compounds active against parasitic nematodes of major socio-economic importance.Identification of novel antimalarial chemotypes via chemoinformatic compound selection methods for a high-throughput screening program against the novel malarial target, PfNDH2: increasing hit rate via virtual screening methods.Hierarchical virtual screening: identification of potential high-affinity and selective β(3)-adrenergic receptor agonists.Analysis of structure-based virtual screening studies and characterization of identified active compounds.How similar are those molecules after all? Use two descriptors and you will have three different answers.Optimization and visualization of the edge weights in optimal assignment methods for virtual screening.The influence of the inactives subset generation on the performance of machine learning methodsA rapid identification of hit molecules for target proteins via physico-chemical descriptors.Computational ligand-based rational design: Role of conformational sampling and force fields in model development.Focused chemical libraries--design and enrichment: an example of protein-protein interaction chemical space.Structural diversity and potency range distribution of scaffolds from compounds active against current pharmaceutical targets.3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors.Identification of a Selective G1-Phase Benzimidazolone Inhibitor by a Senescence-Targeted Virtual Screen Using Artificial Neural Networks.Identification, design and biological evaluation of bisaryl quinolones targeting Plasmodium falciparum type II NADH:quinone oxidoreductase (PfNDH2).Identification, design and biological evaluation of heterocyclic quinolones targeting Plasmodium falciparum type II NADH:quinone oxidoreductase (PfNDH2).Generation of quinolone antimalarials targeting the Plasmodium falciparum mitochondrial respiratory chain for the treatment and prophylaxis of malariaCompound Data Mining for Drug Discovery.Structure-Based Virtual Screening.Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles.Predicting Subtype Selectivity for Adenosine Receptor Ligands with Three-Dimensional Biologically Relevant Spectrum (BRS-3D).Molecular Mechanism of Action of Antimalarial Benzoisothiazolones: Species-Selective Inhibitors of the Plasmodium spp. MEP Pathway enzyme, IspDMolecular topology as a novel approach for drug discovery.Modeling of activity landscapes for drug discovery.Computational methods for the discovery of mood disorder therapies.Fingerprint design and engineering strategies: rationalizing and improving similarity search performance.Novel inhibitors of the Plasmodium falciparum electron transport chain.
P2860
Q26800097-F393751E-93FC-44BE-BB71-C76E0336DA95Q27902247-5C1DE20C-47BD-475F-9A6A-D4BFE6294A18Q27902315-2521C497-A79A-443F-A10A-B80FF0DFF51AQ27902318-6D2FAB70-EB18-41F9-B1EA-70DA909EE8ADQ28477458-84089557-AE37-457B-8FA7-A5B2774593BEQ28745255-DEE8245A-56DA-4317-BCA5-47440511A690Q30485721-20BAA06E-D88E-4C85-8B80-1C64E3C825A0Q30564569-076FD2D6-88BD-43EF-8AD7-C6F870FD36D3Q30576905-7A343671-90CA-4179-AE20-F3618B124A8FQ30681280-D06CDC5E-810E-4555-820D-A2F88D7DFF99Q30989605-9A0DAF6B-BFB3-43EB-A285-CC3F08F6A4F9Q33860664-E1D2755D-E96C-42A6-B051-D0535DD1CB0CQ33913583-DA666012-F863-4F5E-9A08-5D1A8466D46EQ34101738-D651E2F7-22D6-4DF4-A4FE-092B7CC16158Q34176063-944CEDBF-2BB9-4252-AF04-CE7A3214B300Q34180451-26F81ED9-0144-46CE-B7A8-BCAC7254BD74Q34209301-B14E978F-E26B-47CD-8979-0029244E39B2Q34212790-6CC3885D-93D0-4FAE-9C18-5078B87C1657Q34347842-330316A2-EA7B-4223-BC07-54657896A697Q34637014-CA215FC9-D3FA-48AB-B6F9-C7364816CA08Q34657005-87BD3A88-0D02-41A9-A753-068FFC7A9A6BQ34707166-025E273C-DE16-4D0F-BC08-FA3C5A60D063Q35069159-93E47116-6F8E-4030-A23D-53896E056684Q35158672-D5488FF7-EC18-45E0-B90C-F2E811E5F1D2Q35562106-3A82872E-1A9C-4C29-9C66-A5FC727DE192Q35669549-A17100C8-0474-4539-97CD-3AE81BF3FCF1Q35811361-2E03C732-D2B5-46AB-9663-B4B1EAC61206Q35814421-EAEC7055-57B3-49A0-85E8-5636564706A9Q35958086-92C6B037-D80C-4E9A-B354-A0AB744B9517Q35991425-D9136FF9-C054-4A36-92C3-743993D1CEA2Q36206434-6F2BDD34-13A6-4AAC-8C06-FFA13E56F7A9Q36267055-4C2F4097-7294-4BCD-B79D-A4521A585101Q36938240-2B070D2D-44C0-42CE-A56C-E01243F3726EQ37393936-383674FA-EB2A-4227-BF90-445CB5169DF1Q37421946-F0F76E7E-0823-4EFF-8ADC-E8F4E9749002Q37999095-6289E7D1-363F-408B-BC6C-C5E493D0AEC2Q37999871-5081BF09-4E9A-44E8-8344-AECA00189968Q38014572-88055939-5063-4F5D-8B6C-9A464626844DQ38054132-4D2ED842-E264-4F1F-9624-CC1F9675236FQ38176703-4F8CC8D3-E4B9-43AA-B35E-ADA5AA84834E
P2860
Current trends in ligand-based virtual screening: molecular representations, data mining methods, new application areas, and performance evaluation.
description
2010 nî lūn-bûn
@nan
2010 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Current trends in ligand-based ...... s, and performance evaluation.
@ast
Current trends in ligand-based ...... s, and performance evaluation.
@en
Current trends in ligand-based ...... s, and performance evaluation.
@nl
type
label
Current trends in ligand-based ...... s, and performance evaluation.
@ast
Current trends in ligand-based ...... s, and performance evaluation.
@en
Current trends in ligand-based ...... s, and performance evaluation.
@nl
prefLabel
Current trends in ligand-based ...... s, and performance evaluation.
@ast
Current trends in ligand-based ...... s, and performance evaluation.
@en
Current trends in ligand-based ...... s, and performance evaluation.
@nl
P50
P356
P1476
Current trends in ligand-based ...... s, and performance evaluation.
@en
P304
P356
10.1021/CI900419K
P577
2010-02-01T00:00:00Z