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Bio- and Cheminformatics Methods for Mode of Action Analysis
Published on Jun 28, 201984 Views
While phenotypic (such as high-content) screens offer the opportunity for more complex disease-relevant and information-rich - readouts, combining them with an understanding of the mode of action of c
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Chapter list
Mode of Action Analysis Using Chemical and Biological Data00:00
Outline 00:40
Core Data Considered01:27
So what’s the point of it all? 05:31
BUT…This is a very simplified view…07:13
Starting from in vivo efficacy we can predict the MoA, based on ligand chemistry09:23
Exploiting known bioactivity data for new decisions: Target predictions11:09
Prediction Examples: Gleevec, Ruboxistaurin12:27
Problem of representation of chemical structure13:55
How do you describe molecules?16:30
Public target prediction model, based on ~200 mio data points18:10
Training MoA models using in house SAR data18:59
Functional target prediction19:40
Problem: Biased data20:41
Understanding rat sleep data21:51
Compounds classified, followed by pattern discovery in target space24:03
Decision trees learn receptor bioactivity profiles25:28
Bioactivity profiles give 6 MoA hypotheses26:29
Prospective validation on both target and phenotypic level26:59
What did we learn? 28:59
Application: Understanding and predicting cytotoxicity29:35
Cytotoxicity in compound sets29:58
Predicting and understanding cytotoxicity of compound libraries30:16
Chemical fragments, targets can be used for30:18
The problem with ‘modes of action’31:22
Mode of action31:27
Investigating links between indications and neurotransmitter level changes32:42
So what do sedatives, stimulants, antipsychotics, … have in common?33:52
So what do antidepressants, antipsychotics,… have in common?35:05
Neurotransmitter (functional) similarity within and between ATC classes35:24
So… how should we define the mode of action of a CNS active compound?37:50
Novel 2-Amino-Chromene-Nitrile38:28
In Silico Target Predictions39:02
Compound 4g Decreases Expression of Bcl 239:13
Integrated chemical and biological view on compound action..??39:55
Using gene expression data40:11
Note on chemical and biological data40:26
Combined gene expression / on target activity42:32
BioStateConverter43:06
Data Sources43:34
Selected compound induces differentiation of stem cells 44:11
Startup Healx ’ founded, for ‘data driven drug repurposing in rare diseases’44:56
Identifying synergistic combinations with Gemcitabine in Pancreatic cancer45:32
Criteria for selecting combinations46:37
LINCS dataset 47:07
Prospective validation 9/30 combinations synergistic47:25
Conclusions from pancreatic cancer part48:10
Understanding synergy in Shexiang Baoxin Pill (SBP)48:12
Shexiang Baoxin Pill (SBP)49:17
Compounds mapped to targets49:48
SBP targets the central nodes of the angiogenesis50:09
A ginsenoside and an adjuvant compound cholic acid ) or progesterone often show synergy50:30
Rg3/Rb2 combination synergistic in cell proliferation, tube50:44
Using gene expression data for mechanistic insight (2)51:08
Validation by RT PCR eg CXCL8 is synergistically upregulated (etc)51:18
So what did we learn?51:58
Summary52:00