This document discusses using PMML (Predictive Model Markup Language) for exchanging QSAR (Quantitative Structure-Activity Relationship) models between different software. It notes that hundreds of QSAR models have been published but are difficult to reproduce. Using PMML allows building models in one program, saving them in PMML format, distributing them, and evaluating descriptors for new observations. The R packages rcdk and pmml provide cheminformatics support in R and can be used to take in molecules, output descriptors, build a model, and encode it in PMML format for exchange.

1. PMML
for
QSAR
Model
Exchange
Rajarshi
Guha,
Ph.D.
NIH
Center
for
Advancing
TranslaEonal
Sciences
guhar@mail.nih.gov
/
h0p://rguha.net

2. Background
• CheminformaEcs
– QSAR,
diversity
analysis,
virtual
screening,
fragments,
polypharmacology,
networks
• RNAi
screening,
high
content
imaging
• Extensive
use
of
machine
learning
• All
Eed
together
with
soLware
development
(GUI’s,
libraries)
• Contributed
pmml.lm
to
the
PMML
package

3. QuanEtaEve
Structure
AcEvity
RelaEonships

4. Why
is
QSAR
Useful?
• Lets
us
predict
whether
a
chemical
is
likely
to
be
toxic,
avoiding
animal
tesEng
• PrioriEze
molecules
from
a
high
throughput
screen
of
300K
molecules
• Predict
whether
a
molecule
will
be
(sufficiently)
soluble
in
water
• IdenEfy
molecules
with
anE-­‐malarial
properEes
• Accurate,
predic-ve
models
can
save
significant
-me
and
money
(and
cute
bunnies)

5. Lots
and
Lots
of
Models
• Hundreds
of
such
models
published
in
the
literature
– Usually
in
the
form
of
tables
of
regression
coefficients
(if
we’re
lucky)
– If
the
paper
describes
an
SVM
model,
no
chance
of
reproducing
the
results
• How
can
we
exchange
QSAR
models?

6. QSAR
Model
Exchange
• Build
models
in
….,
• Save
them
in
PMML
• Distribute
• …
• Profit?
– Not
always
The
bo0leneck
is
evalua:ng
descriptors
for
the
new
observa:ons
to
supply
to
the
model

7. CheminformaEcs
in
R
• rcdk
provides
cheminformaEcs
support
in
R
– Load
and
parse
molecular
file
formats
– Evaluate
numerical
descriptors
from
chemical
structures
rcdk
CDK Jmol rpubchem
rJava fingerprint XML
R Programming Environment

8. CheminformaEcs
in
R
library(pmml)!
library(rcdk)!
data(bpdata)!
mols <- parse.smiles(bpdata[, 1])!
descNames <- unique(unlist(sapply('topological', !
get.desc.names)))!
descs <- eval.desc(mols, descNames)!
model <- lm(BP ~ khs.sCH3 + khs.sF + TopoPSA + VABC,
data.frame(bpdata,descs))!
pmml(model)!

9. R,
rcdk,
PMML
• rcdk
provides
the
means
to
take
in
molecules
and
output
a
PMML
encoded
model
• One
could
record
appropriate
funcEons/classes
in
the
document
and
use
that
info
to
evaluate
descriptor
for
new
observaEons
• Since
rcdk
is
based
on
the
Java
CDK
library,
could
also
use
jpmml,
a
Java
API
for
PMML
documents