Немного биоинформатики

Compute the Score of a Linear Peptide. Чтобы не потерялось

#!/usr/bin/python3

def create_peptide_mass_dict():

    peptide_mass = dict()

    peptide_mass["G"] = 57

    peptide_mass["A"] = 71

    peptide_mass["S"] = 87

    peptide_mass["P"] = 97

    peptide_mass["V"] = 99

    peptide_mass["T"] = 101

    peptide_mass["C"] = 103

    peptide_mass["I"] = 113

    peptide_mass["L"] = 113

    peptide_mass["N"] = 114

    peptide_mass["D"] = 115

    peptide_mass["K"] = 128

    peptide_mass["Q"] = 128

    peptide_mass["E"] = 129

    peptide_mass["M"] = 131

    peptide_mass["H"] = 137

    peptide_mass["F"] = 147

    peptide_mass["R"] = 156

    peptide_mass["Y"] = 163

    peptide_mass["W"] = 186

    return peptide_mass

def peptide_mass(peptide, masses):

    mass = 0

    for i in range(len(peptide)):

        mass += masses[peptide[i]]

    return mass

def gen_spectrum(peptide):

    masses = create_peptide_mass_dict()

    spectrum = [0]

    chank_len = 1

    peptide_len = len(peptide)

    while chank_len < len(peptide):

        start = 0

        while start + chank_len <= peptide_len:

            spectrum.append(peptide_mass(peptide[start:start+chank_len], masses))

            start += 1

        chank_len += 1

    spectrum.append(peptide_mass(peptide, masses))

    return sorted(spectrum)

def score(theorSpectrum, ExpSpectrum):

    score = 0

    for item in theorSpectrum:

        if item in ExpSpectrum:

            score += 1

            ExpSpectrum.remove(item)

    print (score)

    return score

peptide = "NQEL"

experim_spectrum = [0,113,114,128,129,242, 242,257,370,371,484 ]

theorem_spectrum = gen_spectrum(peptide)

score(theorem_spectrum, experim_spectrum)