[SEQUEST] first_database_name = C:\Xcalibur\database\ecoli_K12.fasta second_database_name = peptide_mass_tolerance = 1.5000 peptide_mass_units = 0 ; 0=amu, 1=mmu, 2=ppm ion_series = 0 1 1 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 fragment_ion_tolerance = 1.0000 ; leave at 0.0 unless you have real poor data num_output_lines = 10 ; # peptide results to show num_results = 500 ; # results to store num_description_lines = 5 ; # full protein descriptions to show for top N peptides show_fragment_ions = 1 ; 0=no, 1=yes print_duplicate_references = 40 ; 0=no, 1=yes enzyme_info = Trypsin(KR) 1 1 KR - max_num_differential_per_peptide = 3 ; max # of diff. mod in a peptide diff_search_options = 0.000000 S 0.000000 C 0.000000 M 0.000000 X 0.000000 T 0.000000 Y term_diff_search_options = 0.000000 0.000000 nucleotide_reading_frame = 0 ; 0=protein db, 1-6, 7 = forward three, 8-reverse three, 9=all six mass_type_parent = 0 ; 0=average masses, 1=monoisotopic masses mass_type_fragment = 0 ; 0=average masses, 1=monoisotopic masses normalize_xcorr = 0 ; use normalized xcorr values in the out file remove_precursor_peak = 0 ; 0=no, 1=yes ion_cutoff_percentage = 0.0000 ; prelim. score cutoff % as a decimal number i.e. 0.30 for 30% max_num_internal_cleavage_sites = 2 ; maximum value is 5 protein_mass_filter = 0 0 ; enter protein mass min & max value ( 0 for both = unused) match_peak_count = 0 ; number of auto-detected peaks to try matching (max 5) match_peak_allowed_error = 1 ; number of allowed errors in matching auto-detected peaks match_peak_tolerance = 1.0000 ; mass tolerance for matching auto-detected peaks partial_sequence = sequence_header_filter = digest_mass_range = 600.0 3500.0 add_Cterm_peptide = 0.0000 ; added to each peptide C-terminus add_Cterm_protein = 0.0000 ; added to each protein C-terminus add_Nterm_peptide = 0.0000 ; added to each peptide N-terminus add_Nterm_protein = 0.0000 ; added to each protein N-terminus add_G_Glycine = 0.0000 ; added to G - avg. 57.0519, mono. 57.02146 add_A_Alanine = 0.0000 ; added to A - avg. 71.0788, mono. 71.03711 add_S_Serine = 0.0000 ; added to S - avg. 87.0782, mono. 87.02303 add_P_Proline = 0.0000 ; added to P - avg. 97.1167, mono. 97.05276 add_V_Valine = 0.0000 ; added to V - avg. 99.1326, mono. 99.06841 add_T_Threonine = 0.0000 ; added to T - avg. 101.1051, mono. 101.04768 add_C_Cysteine = 0.0000 ; added to C - avg. 103.1388, mono. 103.00919 add_L_Leucine = 0.0000 ; added to L - avg. 113.1594, mono. 113.08406 add_I_Isoleucine = 0.0000 ; added to I - avg. 113.1594, mono. 113.08406 add_X_LorI = 0.0000 ; added to X - avg. 113.1594, mono. 113.08406 add_N_Asparagine = 0.0000 ; added to N - avg. 114.1038, mono. 114.04293 add_O_Ornithine = 0.0000 ; added to O - avg. 114.1472, mono 114.07931 add_B_avg_NandD = 0.0000 ; added to B - avg. 114.5962, mono. 114.53494 add_D_Aspartic_Acid = 0.0000 ; added to D - avg. 115.0886, mono. 115.02694 add_Q_Glutamine = 0.0000 ; added to Q - avg. 128.1307, mono. 128.05858 add_K_Lysine = 0.0000 ; added to K - avg. 128.1741, mono. 128.09496 add_Z_avg_QandE = 0.0000 ; added to Z - avg. 128.6231, mono. 128.55059 add_E_Glutamic_Acid = 0.0000 ; added to E - avg. 129.1155, mono. 129.04259 add_M_Methionine = 0.0000 ; added to M - avg. 131.1926, mono. 131.04049 add_H_Histidine = 0.0000 ; added to H - avg. 137.1411, mono. 137.05891 add_F_Phenylalanine = 0.0000 ; added to F - avg. 147.1766, mono. 147.06841 add_R_Arginine = 0.0000 ; added to R - avg. 156.1875, mono. 156.10111 add_Y_Tyrosine = 0.0000 ; added to Y - avg. 163.1760, mono. 163.06333 add_W_Tryptophan = 0.0000 ; added to W - avg. 186.2132, mono. 186.07931 add_J_user_amino_acid = 0.0000 ; added to J add_U_user_amino_acid = 0.0000 ; added to U