Program to find dollar words
Strategic themes


Prefer comprehensions to loops: List comprehensions and dict comprehensions let you compress loops into one-liners.  It's also a nice feeling to initialize an object "all at once" rather than building it little by little.
Avoid special cases: if n in valMap is annoying.  If valMap were a defaultdict, then a failed lookup would naturally have a value of 0.
Use built-in functions: To compute a sum, use sum().  Converting the valMap to a defaultdict enables this further simplification.
Obey the single-responsibility principle: The isDollarWord() function does too much, and should be split up.  A word_value() function would be more useful than isDollarWord() — at the least, it allows for more interesting unit tests.  Once word_value() has been defined, comparison with 100 is trivial.


Localized issues


valMap is not descriptive enough for my taste.  I suggest LETTER_VALUES, in all caps to identify it as a constant.
isDollarWord() should be named is_dollar_word().  (You named remove_marks() correctly, though.)


File handling


You have a file descriptor leak.  Opening files using a with block is almost always preferable to a regular open() call.
Better yet, avoid hard-coding filenames, and let the input be specified on the command line or through standard input.  fileinput.input() is useful for this.


Internationalization and Python 3 compatibility


string.lowercase is locale-dependent, which, according to your specification, you don't want.  Furthermore, it has been removed in Python 3.  You want string.ascii_lowercase instead.
If you want to interpret the input as CP1252, specify an encoding when opening the file, so that it is decoded correctly even before your application even has a chance to get to the data.  If using fileinput.input(), use an openhook parameter (but beware of a bug in Python 2).
For Python 3 compatibility, remove_marks() should also call .decode('ascii') on its return value, to convert the byte string back into a text string.
Alternate ways to handle the internationalization problem include transliteration using transliterate or Unidecode.  German convention, for example, treats ö as oe and ß as ss.


Suggested implementation

from collections import defaultdict
import fileinput
from string import ascii_lowercase
from unicodedata import normalize

LETTER_VALUES = defaultdict(int,
    ((letter, index + 1) for index, letter in enumerate(ascii_lowercase))
)

def remove_marks(word):
    return normalize('NFKD', word).encode('ascii', 'ignore').decode('ascii')

def word_value(word):
    return sum(LETTER_VALUES[c] for c in remove_marks(word.lower()))

for line in fileinput.input(openhook=fileinput.hook_encoded('cp1252')):
    if word_value(line) == 100:
        print(line.strip())