Are these files text or binary? Are they an 8bit character set or Unicode?
Without more information about what these "queries" are, it's not even possible to say whether the above approach could work at all.
Please specify the nature of these queries, and whether all the queries are of the same form. For example, it may be that each of the queries is a simple search string, not containing newline or wildcard.
Or it may be that the queries are arbitrary regular expressions, with some of them potentially matching a multi-line block of text.
Have you implemented the brute-force approach you describe, and is it indeed too slow? By what factor? Does it take 1000 times as long as desired, or 5 times? How about if you do one query for those 52000 files, is it still too slow? And by what factor?
Assuming each of the queries is independent, and that none of them need more than one line to process, it might be possible to combine some or all of those queries into a siimpler filter or filters. Then one could
speed up the process by applying the filter to each line, and only if it triggers, to check the line with the individual queries.
You also don't indicate whether this is a one--time query, or whether the same files might need later to be searched for a different set of queries, or whether the queries might need to be applied to a different set of files. Or whether the same search may need to be repeated on a very similar set of files, or ...
Even in the most ideally placed set of constraints, some queries may produce filters that are either harder to apply than the original queries, or filters that produce so many candidates that this process takes longer than just applying the queries brute-force.
Many times, optimization efforts focus on the wrong problem, or ignore the relative costs of programmer time and machine time. Other times, the problem being optimized is simply intractiable with current