How to optimize a python script which runs for 4**k times?

Programming language: Python 3.4

I have written a program for the Bioinformatics 1 course from Coursera. The program is working all right, but is very slow for large datasets. I guess, it is because the loop is running for 4**k times, where k is the length of the sub-string that is passed into the function. Input: Strings Text and Pattern along with an integer d. Output: All starting positions where Pattern appears as a substring of Text with at most d mismatches.

This is my code:

def MotifCount(string1, substring, d):
    k = 4 ** (len(substring))
    codeArray = list(itertools.product(['A', 'C', 'G', 'T'], repeat=len(substring)))
    for i in range(k):
        codeArray2 = ''.join(list(codeArray[i]))
        HammingValue = HammingDistance(codeArray2, substring)
        if HammingValue <= d:
            for j in range(len(string1)):
                if(string1.find(codeArray2, j) == j):
                    print(j)



def HammingDistance(string_1, string_2):
    length_1 = len(string_1)
    length_2 = len(string_2)
    count = 0
    for i in range(length_1):
        if string_1[i] != string_2[i]:
            count += 1
    return count

Sample Input:

CGCCCGAATCCAGAACGCATTCCCATATTTCGGGACCACTGGCCTCCACGGTACGGACGTCAATCAAAT
ATTCTGGA
3

Output:

6 7 26 27

I want to optimize this code for bigger data sets. Is there any way to reduce the run time of the code?