If you can make a data frame of your custom annotations (i.e. a table), then you can simply convert the relevant fields to a RangedData object for ChIPpeakAnno. For instance, if you want to get all c elegans genes, you can grab them using the biomaRt library in R with just a few lines of code:

library(biomaRt)
library(ChIPpeakAnno)

# create a biomart object and select a mart to use
ensembl <- useDataset("celegans_gene_ensembl", mart=useMart("ensembl"))

# what kind of attributes can we retrieve?
listAttributes(ensembl)

# set the properties to extract
props <- c("ensembl_gene_id", "external_gene_id", "transcript_biotype", "chromosome_name", "start_position", "end_position", "strand")

# get the information
genes <- getBM(attributes=props, mart=ensembl)

# create a RangedData object with my custom annotations
myCustomAnno <- RangedData(IRanges(start=genes[,"start_position"], end=genes[,"end_position"], names=genes[,"external_gene_id"]), space=genes[,"chromosome_name"], strand=genes[,"strand"])

# annotate my peaks with my custom annotations
annotatedPeaks <- annotatePeakInBatch(myPeakList, AnnotationData=myCustomAnno)

There are quite a few things you can look up in biomart, or you can curate your own table. The trick is simply getting the information into the form of a RangedData object, which may seem a little scary, but as you can see in the example above, is actually pretty straightforward.