基于药效团的药物分子设计

Pharmacophore Modeling
• Use hypotheses as a query to search databases for molecules with similar pharmacophore patterns and activity Explain structure-activity relationships (SAR) of a set of compounds Form a basis for the design of new building blocks for novel lead 单击此处编辑母版副标题样式 candidates
User defined energy range
Functionality modules
Catalyst
Database •National Cancer Institute Database (NCI) •Maybridge 2004
Discovery Studio
Database
•National Cancer 单击此处编辑母版标题样式 Institute Database (NCI) •Maybridge 2004 •Ligand Profiler 单击此处编辑母版副标题样式 Pdatabase •HypoDB
单击此处编辑母版标题样式 Overview of Pharmacophore
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Pharmacophore Model
• Chemical features • Location and orientation in 3D space
– position of features defined by absolute coordinates – discriminates between enantiomers
Catalyst
Conformer Generation: •FAST •BEST
Discovery Studio
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Conformer Generation: •FAST •BEST •CAESAR Pole •Random sampling (DS2.5) 单击此处编辑母版副标题样式 •Grid Scan (DS2.5)
Functionality modules
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Mapping of a tyrosine kinase inhibitor, Imatinib mesylate, derived from pharmacophore based de-novo fragment screening against known crystal structure ligand orientation.
Functionality modules
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Rapidly visualize each feature’s contributions to the binding interaction with the heat map charting.
Functionality modules
• Activities (IC50, Ki)
– smaller values mean more active – always use the same unit – no log values
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• Uncertainties 单击此处编辑母版副标题样式
– relates to the degree of confidence about the biological data – tolerance factor for activity values – value of 3 (default) means that the actual activity probably falls in a range that is 3 times more or less than the reported value
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• SAR predicative model – finds features that relate to activity 单击此处编辑母版副标题样式 – predicative model – uses HypoGen
HipHop
• Finds common feature-based overlays • No SAR information required
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Automatic Construction of Pharmacophores
• Common features hypothesis – finds chemical features shared by a set of compounds – uses HipHop
• Example: an activity of 6 and uncertainty of 3 will set up a range of activity values for a given compound as 2 - 18
Comparing HipHop and HypoGen
HipHop Number of compounds Actives 2-32 HypoGen more than 10
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单击此处编辑母版文本样式 基于药效团的药物分子设计 第二级 第三级 第四级 王占黎 第五级
Agenda
• Overview of Discovery Studio (~5 min) • Overview of Pharmacophore(~25 min) • Demonstration (~50 min) 单击此处编辑母版标题样式 a) HypoGen and HipHop b) Creating custom features 单击此处编辑母版副标题样式 c) Structure-based pharmacophores d) Pharmacophore-Based De Novo Design e) Ligand Profiler • Open discussion (~20min)
Functionality modules
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Structure based pharmacophore allows you to elucidate essential features representing binding interactions from known or putative protein active site.
单击此处编辑母版标题样式 Overview of Discovery Studio
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Catalyst
Discovery Studio
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Functionality modules
Catalyst
HypoGen HipHop Shape HypoRefine & HipHopRefine
Discovery Studio
HipHop HypoGen HypoRefine and Steric Refinement Shape Structure-Based Pharmacophore
Ligand Profiler
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Pharmacophore-Based De Novo Design 单击此处编辑母版副标题样式
– maximum of 单击此处编辑母版副标题样式 10 features (20 points) per hypothesis
• Hypotheses ranked by scores • Can handle larger molecules than HypoGen
– pentapeptides
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• Include 4-5 pairs that ‘teach’ HypoGen something specific about the SAR 单击此处编辑母版副标题样式
– compounds with similar structures should differ in activity by at least an order of magnitude – compounds with similar activity must be structurally distinct
• Can use different multi-conformer files
– *.cpd, *.mol2, *.mmod
The Ideal HipHop Training Set
• 2 - 32 compounds • Structurally diverse set of input molecules • Include only active compounds provided that you have 单击此处编辑母版标题样式 that information 单击此处编辑母版副标题样式
– use of compounds from HTS
• Maximum of 32 molecules
– not limited to 255 conformers per molecule (memory dependent)
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• Returns a user defined number of hypotheses • Hypotheses are generated from a maximum of ten features
HypoGen Training Sets
• 18 - 25 molecules structurally diverse
– ≥ 15 compounds necessary to assure statistical power – mixture of actives and inactives
• No compounds violating excluded volumes • No redundant information
Spreadsheet Setup for HypoGen
• Molecules
– Hypothesis Generation Workbench – imported into spreadsheet
• Activities should span ≥ 4 log units (orders of magnitude)
– smaller activity range allowed by a .Catalyst setting – each order of magnitude represented by ≥ 3 compounds
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• Tolerance 单击此处编辑母版副标题样式 – size of sphere represents precision needed for location of a particular feature • Weight
– describes relative importance of each chemical function in conferring activity
单击此处编辑母版标题样式 all active actives and inactives
no data required activity values required wide range of activity maximum of 10 best
Activity data
Type of model 单击此处编辑母版副标题样式 feature-based predictive model Differences in models Number of hypotheses structurally diverse user defined