bipredict: moe/web server enabled delivery of in silico properties and models
DESCRIPTION
Presentation at the Chemical Computing Group UGM in 2011. I describe my use of the MOE/web SOAP server and the model of delivering physico-chemical properties onto the medicinal chemists desktop.TRANSCRIPT
BI di MOE/ b S E bl d D li BIpredict: MOE/web Server Enabled Delivery of In Silico Properties and Models
David C. Thompson, Ph.D
125 Years of Innovating for Patients and Their Families
Founded 1885 in Ingelheim, Germany
Family-owned global company
Privately-heldfor 125 years
$17.7 billion 2009 net sales
Products marketed in
150+ countries41,500
employees worldwide
g p y y
2009 net sales150+ countries
142 ffili t
employees worldwide
Focus on 142 affiliates
in
50 countries
Human Pharmaceuticals& Animal Health
2
One Pill Makes You Larger [*]
My favourite papers from each period:[1] J. Chem. Phys. 122, 124107 (2005)[2] J. Chem. Phys. 128, 224103 (2008)[3] J. Chem. Inf. Model. 49, 1889 (2009)[4] J. Chem. Inf. Model. 51, 93 (2011)[*] This slide title brought to you courtesy of Lewis Carroll
The Magic of Clip Art
What are we trying to do in the pharmaceutical industry?
[*]
+ =[*]
What are we trying to do as computational scientists working in the pharmaceutical industry?
+ =
We build models to try and expedite the drug
Chemical space
4
discovery process
[*] Side effects may include changing hair colour
Shameless slide reuse … [5]
“All models are wrong, but some models are useful”– G. E. P. Box
“…the validity of any given model is of limited scope, as is the case with any mental construct
that we have about what our molecules are doing, whether we used a software package or waved our whether we used a software package or waved our
hands around in the air.” – D. Lowe
Simulation and its discontents, Sherry Turkle, Cambridge, MA: MIT Press (2009)
[5] D. C. Thompson et al. Schrödinger Regional User Meeting, New York, NY 2009
Taxonomy of Risk [6]
Risk Uncertainty
Randomness amenable to formal Randomness not amenable to formalRandomness amenable to formalstatistical analysis
Randomness not amenable to formalstatistical analysis
“ … a given phenomenon may contain several levels of uncertainty at once, with some components being completelycertain and others irreducibly uncertain”
“In fact, we propose that the failure of quantitative models [in economics and finance] is almost always attributable to a mismatch between the level of uncertainty and the methods used to model it.”to a mismatch between the level of uncertainty and the methods used to model it.
6[6] “WARNING: Physics Envy May be Hazardous To Your Wealth!”, A. W. Lo, and M. T. Mueller arXiv:1003.2688v3 [q-fin.RM]
Okay, now what?
• Focus on physicochemical properties [7, 8]
• Enable scientists through light-weight clientsEnable scientists through light weight clients
• Provide core scientific functionality through web services architecture
=+
Chemical space
We build models to try and expedite the drug discovery process
7[7] Nature Rev. Drug. Discov. 10, 197 (2011)[8] Med. Chem. Comm., 2011 (DOI: 10.1039/c1md00017a)
The Internet …
8
… is here to stay [*]
9* Probably
If it’s going to stay, we might as well use it
A Web Service is a method of communication between two electronic devices over a network[9]
Example*:
Web Service
10* Probably[9] http://en.wikipedia.org/wiki/Web_service
BIpredict: An in silico molecular property prediction framework
Initial requirement: Build a real-time physchem. property calculator engine that could be used to address project concerns and issues at the medicinal chemistry desktop
Buy or Build?
Offer multiple interfaces to complement users preferred workflow
Proposal: Rapid development of an in-house solution to allow us to focus on optimizing the interaction between a web services layer and other BI systems and, most importantly, the y y , p y,scientists
• Leverage Molecular Operating Environment (MOE), and newly developed MOE/web SOAP application server technologypp gy
— Java-based web server— No Apache setup
M OEM OE
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• Focus on flexibility, ease of deployment, and extensibilitySOA P
M OEPipeline
Pilot®
ba tc h
M OE
BIpredict architecture:How you consume, depends on what you see
MOE BIDATA Pipelining tools Web Apps.BIModel Command Line(G) (G)
Multiple front-ends(d t )
(G + A) (G)(G + A) (G +A)
BIpredict
(data consumers)
Single back-end(data producer)
(web services layer)
General (G): Advanced (A):
Synchronous
( )Intended for
general consumption
( )Abstract
descriptors for comp. chem.
Interface determines which descriptors are exposed
Development:Oct. 2009 – Jan. 2010Production:Jan. 2010
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“One of the things about a real-time system is everything has to be timed out” [10]
BIpredict(web services layer)
single back-end(data producer)
y
Asynchronous / Batched
Descriptor l Scatterclasses
User IDJob IDGeneral:
Y
42 descriptors8 engines
Advanced:
Development:Jan 2010 June 2010
Gather
Collect outputN?Y
Descriptor names
Advanced:3431 descriptors15 engines
Jan. 2010 – June 2010Production:June 2010
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Packaged output
Job ID
[10] Bernie Cosell, “Czar of the PDP-1 timesharing system”
What does this magic look like?
With BIpredict panel open, workspace is ‘live’
Physicochemical properties are updated
l l i b ilas molecule is built
Atomistic descriptor values are appended values are appended directly to the molecule
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Accessing Models in BIpredict
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Reimplementation of Pfizer CNS Multi-Parameter Optimization design tool [11,12]
• Driven by the scientists, turnaround of days
G h 9 li d i ll i d i• Gather 119 literature compounds, visually inspect and triage
• Identify physicochemical property Descriptorsy p y p p y p• Sybyl clogP• ACD logD (@ pH 7.4)• MOE MW
6
7
• MOE MW• CADD TPSA• MOE Lipinski HB donors
ACD M B i K
R² = 0.9834
3
4
5-i
mpl
emen
tatio
n
• ACD Most Basic pKa
• Enable model through BIpredict1
2
Re-
g p0
0 1 2 3 4 5 6 7
Literature
16[11] ACS Chem. Neurosci., 1, 435 (2010)[12] Bioorg. Med. Chem. Lett, 18, 4872 (2008)
Begin at the beginning and go on till you come to the end: then stop [*]
• All models are wrong• Expose those models that we think will expedite the p p
drug discovery process• Focus on extensible, light-weight, service delivery, g g , y
[*] This slide title brought to you courtesy of Lewis Carroll
Cultural Highlight
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Acknowledgements
Dr. Jörg BentzienDr. Alex ClarkC th F llCathy FarrellDr. Sandy FarmerAmy GaoDr Scott OloffDr. Scott OloffDr. Miguel Teodoro