Computational chemistry-driven decision making in lead generation
about
Computational methods in drug discoveryLead optimization mapper: automating free energy calculations for lead optimization.Perspective: Alchemical free energy calculations for drug discovery.Quantitative high-throughput screening: a titration-based approach that efficiently identifies biological activities in large chemical libraries.Novel Algorithms for the Identification of Biologically Informative Chemical Diversity Metrics.From laptop to benchtop to bedside: structure-based drug design on protein targets.The future of toxicity testing: a focus on in vitro methods using a quantitative high-throughput screening platform.A novel hybrid ultrafast shape descriptor method for use in virtual screening.Indirect similarity based methods for effective scaffold-hopping in chemical compounds.Dehydrogenation of the indoline-containing drug 4-chloro-N-(2-methyl-1-indolinyl)-3-sulfamoylbenzamide (indapamide) by CYP3A4: correlation with in silico predictionsTargeting FtsZ for antibacterial therapy: a promising avenue.High-throughput and in silico screenings in drug discovery.State-of-the-art and dissemination of computational tools for drug-design purposes: a survey among Italian academics and industrial institutions.Symmetric kv1.5 blockers discovered by focused screening.Ligand efficiency indices for effective drug discovery."Plate cherry picking": a novel semi-sequential screening paradigm for cheaper, faster, information-rich compound selection.Advances in the Development of Shape Similarity Methods and Their Application in Drug DiscoveryDeep reinforcement learning for de novo drug design
P2860
Q26997089-439E1AD8-204C-4145-A241-EE6314EF896CQ30410587-48CEBC34-C4F4-441B-9A0C-F7360450AFC6Q30422862-DD41BBEE-B7BC-4197-A685-75FB4EBBD728Q33251617-149227DD-3F56-4E8A-83C7-24E58C19470FQ33507533-53A09F1A-7CEE-47DB-B8FC-48B34EF07830Q34153589-58A7C0A1-739C-4EB8-ADB9-3319006C5E05Q34367618-715BF5EF-F250-4D83-A4FC-6610ECC764DAQ36509526-A5D60227-4555-4C52-A40D-63B3108710E7Q36955807-D8468A89-0D75-4805-807E-47EDA93EAAF5Q37104004-C9B1B95C-8C49-4034-BA13-C0D11F1DC36CQ37573808-AA830FB2-027A-46E4-BD45-619B16DB3813Q38088365-D30D7577-D518-426F-8CF7-2A545AB6315FQ39417388-6B541A99-76BA-487E-B33F-FE95462F8704Q39730948-6BD2C242-8733-4B1F-A097-A3AAA914BBBCQ40228492-74CE5B02-3455-41A9-B5F4-8EE1EBC3CDDEQ51917151-062D9D85-4241-4A55-A7BA-FC71ABB07FE4Q56700832-067152CA-8353-48F0-A995-53F920B2B939Q57425404-E91B26C5-CE15-4AF8-936B-A39101A22264
P2860
Computational chemistry-driven decision making in lead generation
description
2006 nî lūn-bûn
@nan
2006 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2006 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2006年の論文
@ja
2006年論文
@yue
2006年論文
@zh-hant
2006年論文
@zh-hk
2006年論文
@zh-mo
2006年論文
@zh-tw
2006年论文
@wuu
name
Computational chemistry-driven decision making in lead generation
@ast
Computational chemistry-driven decision making in lead generation
@en
Computational chemistry-driven decision making in lead generation
@nl
type
label
Computational chemistry-driven decision making in lead generation
@ast
Computational chemistry-driven decision making in lead generation
@en
Computational chemistry-driven decision making in lead generation
@nl
prefLabel
Computational chemistry-driven decision making in lead generation
@ast
Computational chemistry-driven decision making in lead generation
@en
Computational chemistry-driven decision making in lead generation
@nl
P1433
P1476
Computational chemistry-driven decision making in lead generation
@en
P2093
Volker Schnecke
P356
10.1016/S1359-6446(05)03703-7
P407
P577
2006-01-01T00:00:00Z