stepwise variable selection with multiple dependent variables

Good Day,

I fit a multivariate linear regression model with 3 dependent variables and several predictors using the lm function. ?I would like to use stepwise variable selection to produce a set of candidate models. ?However, when I pass the fitted lm object to step() I get the following error:

Error from R:
Error in drop1.mlm(fit, scope$drop, scale = scale, trace = trace, k = k, ?:
?no 'drop1' method for "mlm" models

My dependent data is in the matrix ymat where ymat is 35 rows by 3 columns. ?The predictors are in X where X is 35 by 6

The steps I used were:
m.fit <- lm(ymat ~ ., data=X)
m.step <- step(m.fit)

If variable selection is not possible with step() is there another package that will perform variable selection in a multivariate setting?

System information:
platform ? ? ? x86_64-apple-darwin9.8.0
arch ? ? ? ? ? x86_64
os ? ? ? ? ? ? darwin9.8.0
system ? ? ? ? x86_64, darwin9.8.0
status
major ? ? ? ? ?2
minor ? ? ? ? ?13.1
year ? ? ? ? ? 2011
month ? ? ? ? ?07
day ? ? ? ? ? ?08
svn rev ? ? ? ?56322
language ? ? ? R
version.string R version 2.13.1 (2011-07-08)

Thanks in advance.