selecting dataframe columns based on substring of col name(s)

Suppose I have the following sort of dataframe, where each column name has a
common structure: prefix, followed by a number (for this example, col1,
col2, col3 and col4):

 d = data.frame( col1=runif(10), col2=runif(10),
col3=runif(10),col4=runif(10))

What I haven't been able to suss out is how to efficiently
'extract/manipulate/play with' columns from the data frame, making use of
this common structure.

Suppose, for example, I want to 'work with' col2, col3, and col4. Now, I
could subset the dataframe d in any number of ways -- for example

piece <- d[,c("col2","col3","col4")]

Works as expected, but for *big* problems (where I might have dozens ->
hundreds of columns -- often the case with big design matrices output by
some linear models program or another), having to write them all out using
c("col2","col3",...."colXXXXX") takes a lot of time. What I'm wondering
about is if there is a way to simply select over the "changing part" of the
column name (you can do this relatively easily in a data step in SAS, for
example). Heuristically, something like:

piece <- df[,col2:col4]

where the heuristic col2:col4 is interpreted as col2 -> col4 (parse the
prefix 'col', and then simply select over the changing suffic -- i.e.,
column number).

Now, if I use the "to" function in the lessR package, I can get there from
here fairly easily:

piece <- d[,to("col",4,from=2,same.size=FALSE)]

But, is there a better way? Beyond 'efficiency' (ease of implementation),
part of what constitutes 'better' might be something in base R, rather than
relying on a package?

Thanks in advance...