achrom  additive model of polypeptide chromatography¶
Summary¶
The additive model of polypeptide chromatography, or achrom, is the most basic model for peptide retention time prediction. The main equation behind achrom has the following form:
Here, is the retention coefficient of the amino acid residues of the ith type, corresponds to the number of amino acid residues of type in the peptide sequence, N is the total number of different types of amino acid residues present, and is a constant retention time shift.
In order to use achrom, one needs to find the retention coeffcients, using experimentally determined retention times for a training set of peptide retention times, i.e. to calibrate the model.
Calibration¶
get_RCs()
 find a set of retention coefficients using a given set of peptides with known retention times and a fixed value of length correction parameter.
get_RCs_vary_lcp()
 find the best length correction parameter and a set of retention coefficients for a given peptide sample.
Retention time calculation¶
calculate_RT()
 calculate the retention time of a peptide using a given set of retention coefficients.
Data¶
RCs_guo_ph2_0
 a set of retention coefficients (RCs) from [2]. Conditions: Synchropak RPP C18 column (250 x 4.1 mm I.D.), gradient (A = 0.1% aq. TFA, pH 2.0; B = 0.1% TFA in acetonitrile) at 1% B/min, flow rate 1 ml/min, 26 centigrades.
RCs_guo_ph7_0
 a set of retention coefficients (RCs) from [2]. Conditions: Synchropak RPP C18 column (250 x 4.1 mm I.D.), gradient (A = aq. 10 mM (NH4)2HPO4  0.1 M NaClO4, pH 7.0; B = 0.1 M NaClO4 in 60% aq. acetonitrile) at 1.67% B/min, flow rate 1 ml/min, 26 centigrades.
RCs_meek_ph2_1
 a set of RCs from [1]. Conditions: BioRad “ODS” column, gradient (A = 0.1 M NaClO4, 0.1% phosphoric acid in water; B = 0.1 M NaClO4, 0.1% phosphoric acid in 60% aq. acetonitrile) at 1.25% B/min, room temperature.
RCs_meek_ph7_4
 a set of RCs from [1]. Conditions: BioRad “ODS” column, gradient (A = 0.1 M NaClO4, 5 mM phosphate buffer in water; B = 0.1 M NaClO4, 5 mM phosphate buffer in 60% aq. acetonitrile) at 1.25% B/min, room temperature.
RCs_browne_tfa
 a set of RCs found in [7]. Conditions: Waters mjuBondapak C18 column, gradient (A = 0.1% aq. TFA, B = 0.1% TFA in acetonitrile) at 0.33% B/min, flow rate 1.5 ml/min.
RCs_browne_hfba
 a set of RCs found in [7]. Conditions: Waters mjuBondapak C18 column, gradient (A = 0.13% aq. HFBA, B = 0.13% HFBA in acetonitrile) at 0.33% B/min, flow rate 1.5 ml/min.
RCs_palmblad
 a set of RCs from [8]. Conditions: a fused silica column (80100 x 0.200 mm I.D.) packed inhouse with C18 ODSAQ; solvent A = 0.5% aq. HAc, B = 0.5% HAc in acetonitrile.
RCs_yoshida
 a set of RCs for normal phase chromatography from [9]. Conditions: TSK gel Amide80 column (250 x 4.6 mm I.D.), gradient (A = 0.1% TFA in ACNwater (90:10); B = 0.1% TFA in ACNwater (55:45)) at 0.6% water/min, flow rate 1.0 ml/min, 40 centigrades.
RCs_yoshida_lc
 a set of lengthcorrected RCs for normal phase chromatography. The set was calculated in [10] for the data from [9]. Conditions: TSK gel Amide80 column (250 x 4.6 mm I.D.), gradient (A = 0.1% TFA in ACNwater (90:10); B = 0.1% TFA in ACNwater (55:45)) at 0.6% water/min, flow rate 1.0 ml/min, 40 centigrades.
RCs_zubarev
 a set of lengthcorrected RCs calculated on a dataset used in [11]. Conditions: ReprosilPur C18AQ column (150 x 0.075 mm I.D.), gradient (A = 0.5% AA in water; B = 0.5% AA in ACNwater (90:10)) at 0.5% water/min, flow rate 200.0 nl/min, room temperature.
RCs_gilar_atlantis_ph3_0
 a set of retention coefficients obtained in [12]. Conditions: Atlantis HILIC silica column, (150 x 2.1 mm I.D.), 3 um, 100 A, gradient (A = water, B = ACN, C = 200 mM ammonium formate): 0 min, 5% A, 90% B, 5% C; 62.5 min, 55% A, 40% B, 5% C at 0.2 ml/min, temperature 40 C, pH 3.0
RCs_gilar_atlantis_ph4_5
 a set of retention coefficients obtained in [12]. Conditions: Atlantis HILIC silica column, (150 x 2.1 mm I.D.), 3 um, 100 A, gradient (A = water, B = ACN, C = 200 mM ammonium formate): 0 min, 5% A, 90% B, 5% C; 62.5 min, 55% A, 40% B, 5% C at 0.2 ml/min, temperature 40 C, pH 4.5
RCs_gilar_atlantis_ph10_0
 a set of retention coefficients obtained in [12]. Conditions: Atlantis HILIC silica column, (150 x 2.1 mm I.D.), 3 um, 100 A, gradient (A = water, B = ACN, C = 200 mM ammonium formate): 0 min, 5% A, 90% B, 5% C; 62.5 min, 55% A, 40% B, 5% C at 0.2 ml/min, temperature 40 C, pH 10.0
RCs_gilar_beh
 a set of retention coefficients obtained in [12]. Conditions: ACQUITY UPLC BEH HILIC column (150 x 2.1 mm I.D.), 1.7 um, 130 A, Mobile phase A: 10 mM ammonium formate buffer, pH 4.5 prepared by titrating 10 mM solution of FA with ammonium hydroxide. Mobile phase B: 90% ACN, 10% mobile phase A (v:v). Gradient: 9060% B in 50 min.
RCs_gilar_beh_amide
 a set of retention coefficients obtained in [12]. Conditions: ACQUITY UPLC BEH glycan column (150 x 2.1 mm I.D.), 1.7 um, 130 A, Mobile phase A: 10 mM ammonium formate buffer, pH 4.5 prepared by titrating 10 mM solution of FA with ammonium hydroxide. Mobile phase B: 90% ACN, 10% mobile phase A (v:v). Gradient: 9060% B in 50 min.
RCs_gilar_rp
 a set of retention coefficients obtained in [12]. Conditions: ACQUITY UPLC BEH C18 column (100 mm x 2.1 mm I.D.), 1.7 um, 130 A. Mobile phase A: 0.02% TFA in water, mobile phase B: 0.018% TFA in ACN. Gradient: 0 to 50% B in 50 min, flow rate 0.2 ml/min, temperature 40 C., pH 2.6.
RCs_krokhin_100A_fa
 a set of retention coefficients obtained in [13]. Conditions: 300 um x 150mm PepMap100 (Dionex, 0.1% FA), packed with 5um Luna C18(2) (Phenomenex, Torrance, CA), pH=2.0. Both eluents A (2% ACN in water) and B (98% ACN) contained 0.1% FA as ionpairing modifier. 0.33% ACN/min linear gradient (030% B).
RCs_krokhin_100A_tfa
 a set of retention coefficients obtained in [13]. Conditions: 300 um x 150mm PepMap100 (Dionex, 0.1% TFA), packed with 5um Luna C18(2) (Phenomenex, Torrance, CA), pH=2.0. Both eluents A (2% ACN in water) and B (98% ACN) contained 0.1% TFA as ionpairing modifier. 0.33% ACN/min linear gradient (030% B).
Theory¶
The additive model of polypeptide chromatography, or the model of retention coefficients was the earliest attempt to describe the dependence of retention time of a polypeptide in liquid chromatography on its sequence [1], [2]. In this model, each amino acid is assigned a number, or a retention coefficient (RC) describing its retention properties. The retention time (RT) during a gradient elution is then calculated as:
which is the sum of retention coefficients of all amino acid residues in a polypeptide. This equation can also be expressed in terms of linear algebra:
where is a vector of amino acid composition, i.e. is the number of amino acid residues of ith type in a polypeptide; is a vector of respective retention coefficients.
In this formulation, it is clear that additive model gives the same results for any two peptides with different sequences but the same amino acid composition. In other words, additive model is not sequencespecific.
The additive model has two advantages over all other models of chromatography  it is easy to understand and use. The rule behind the additive model is as simple as it could be: each amino acid residue shifts retention time by a fixed value, depending only on its type. This rule allows geometrical interpretation. Each peptide may be represented by a point in 21dimensional space, with first 20 coordinates equal to the amounts of corresponding amino acid residues in the peptide and 21st coordinate equal to RT. The additive model assumes that a line may be drawn through these points. Of course, this assumption is valid only partially, and most points would not lie on the line. But the line would describe the main trend and could be used to estimate retention time for peptides with known amino acid composition.
This best fit line is described by retention coefficients and . The procedure of finding these coefficients is called calibration. There is an analytical solution to calibration of linear models, which makes them especially useful in real applications.
Several attempts were made in order to improve the accuracy of prediction by the additive model (for a review of the field we suggest to read [3] and [4]). The two implemented in this module are the logarithmic length correction term described in [5] and additional sets of retention coefficients for terminal amino acid residues [6].
Logarithmic length correction¶
This enhancement was firstly described in [5]. Briefly, it was found that the following equation better describes the dependence of RT on the peptide sequence:
We would call the second term the length correction term and m  the length correction parameter. The simplified and vectorized form of this equation would be:
This equation may be reduced to a linear form and solved by the standard methods.
Terminal retention coefficients¶
Another significant improvement may be obtained through introduction of separate sets of retention coefficients for terminal amino acid residues [6].
References
[1]  (1, 2, 3) Meek, J. L. Prediction of peptide retention times in highpressure liquid chromatography on the basis of amino acid composition. PNAS, 1980, 77 (3), 16321636. 
[2]  (1, 2, 3) Guo, D.; Mant, C. T.; Taneja, A. K.; Parker, J. M. R.; Hodges, R. S. Prediction of peptide retention times in reversedphase highperformance liquid chromatography I. Determination of retention coefficients of amino acid residues of model synthetic peptides. Journal of Chromatography A, 1986, 359, 499518. 
[3]  Baczek, T.; Kaliszan, R. Predictions of peptides’ retention times in reversedphase liquid chromatography as a new supportive tool to improve protein identification in proteomics. Proteomics, 2009, 9 (4), 83547. 
[4]  Babushok, V. I.; Zenkevich, I. G. Retention Characteristics of Peptides in RPLC: Peptide Retention Prediction. Chromatographia, 2010, 72 (910), 781797. 
[5]  (1, 2) Mant, C. T.; Zhou, N. E.; Hodges, R. S. Correlation of protein retention times in reversedphase chromatography with polypeptide chain length and hydrophobicity. Journal of Chromatography A, 1989, 476, 363375. 
[6]  (1, 2) Tripet, B.; Cepeniene, D.; Kovacs, J. M.; Mant, C. T.; Krokhin, O. V.; Hodges, R. S. Requirements for prediction of peptide retention time in reversedphase highperformance liquid chromatography: hydrophilicity/hydrophobicity of sidechains at the N and Ctermini of peptides are dramatically affected by the endgroups and location. Journal of chromatography A, 2007, 1141 (2), 21225. 
[7]  (1, 2) Browne, C. A.; Bennett, H. P. J.; Solomon, S. The isolation of peptides by highperformance liquid chromatography using predicted elution positions. Analytical Biochemistry, 1982, 124 (1), 201208. 
[8]  Palmblad, M.; Ramstrom, M.; Markides, K. E.; Hakansson, P.; Bergquist, J. Prediction of Chromatographic Retention and Protein Identification in Liquid Chromatography/Mass Spectrometry. Analytical Chemistry, 2002, 74 (22), 58265830. 
[9]  (1, 2) Yoshida, T. Calculation of peptide retention coefficients in normalphase liquid chromatography. Journal of Chromatography A, 1998, 808 (12), 105112. 
[10]  Moskovets, E.; Goloborodko A. A.; Gorshkov A. V.; Gorshkov M.V. Limitation of predictive 2D liquid chromatography in reducing the database search space in shotgun proteomics: In silico studies. Journal of Separation Science, 2012, 35 (14), 17711778. 
[11]  Goloborodko A. A.; Mayerhofer C.; Zubarev A. R.; Tarasova I. A.; Gorshkov A. V.; Zubarev, R. A.; Gorshkov, M. V. Empirical approach to false discovery rate estimation in shotgun proteomics. Rapid communications in mass spectrometry, 2010, 24(4), 45462. 
[12]  (1, 2, 3, 4, 5, 6) Gilar, M., & Jaworski, A. (2011). Retention behavior of peptides in hydrophilicinteraction chromatography. Journal of chromatography A, 1218(49), 88906. 
[13]  (1, 2) Dwivedi, R. C.; Spicer, V.; Harder, M.; Antonovici, M.; Ens, W.; Standing, K. G.; Wilkins, J. A.; Krokhin, O. V. (2008). Practical implementation of 2D HPLC scheme with accurate peptide retention prediction in both dimensions for highthroughput bottomup proteomics. Analytical Chemistry, 80(18), 703642. 
Dependencies¶
This module requires numpy
.

pyteomics.achrom.
RCs_browne_hfba
¶ A set of retention coefficients determined in Browne, C. A.; Bennett, H. P. J.; Solomon, S. The isolation of peptides by highperformance liquid chromatography using predicted elution positions. Analytical Biochemistry, 1982, 124 (1), 201208.
Conditions: Waters mjuBondapak C18 column, gradient (A = 0.13% aq. HFBA, B = 0.13% HFBA in acetonitrile) at 0.33% B/min, flow rate 1.5 ml/min.

pyteomics.achrom.
RCs_browne_tfa
¶ A set of retention coefficients determined in Browne, C. A.; Bennett, H. P. J.; Solomon, S. The isolation of peptides by highperformance liquid chromatography using predicted elution positions. Analytical Biochemistry, 1982, 124 (1), 201208.
Conditions: Waters mjuBondapak C18 column, gradient (A = 0.1% aq. TFA, B = 0.1% TFA in acetonitrile) at 0.33% B/min, flow rate 1.5 ml/min.

pyteomics.achrom.
RCs_gilar_atlantis_ph10_0
¶ A set of retention coefficients for normal phase chromatography obtained in Gilar, M., & Jaworski, A. (2011). Retention behavior of peptides in hydrophilicinteraction chromatography. Journal of chromatography A, 1218(49), 88906.
Note
Cysteine is Carbamidomethylated.
Conditions: Atlantis HILIC silica column (150 x 2.1 mm I.D.), 3 um, 100 A, gradient (A = water, B = ACN, C = 200 mM ammonium formate): 0 min, 5% A, 90% B, 5% C; 62.5 min, 55% A, 40% B, 5% C at 0.2 ml/min, temperature 40 C, pH 10.0

pyteomics.achrom.
RCs_gilar_atlantis_ph3_0
¶ A set of retention coefficients for normal phase chromatography obtained in Gilar, M., & Jaworski, A. (2011). Retention behavior of peptides in hydrophilicinteraction chromatography. Journal of chromatography A, 1218(49), 88906.
Note
Cysteine is Carbamidomethylated.
Conditions: Atlantis HILIC silica column (150 x 2.1 mm I.D.), 3 um, 100 A, gradient (A = water, B = ACN, C = 200 mM ammonium formate): 0 min, 5% A, 90% B, 5% C; 62.5 min, 55% A, 40% B, 5% C at 0.2 ml/min, temperature 40 C, pH 3.0

pyteomics.achrom.
RCs_gilar_atlantis_ph4_5
¶ A set of retention coefficients for normal phase chromatography obtained in Gilar, M., & Jaworski, A. (2011). Retention behavior of peptides in hydrophilicinteraction chromatography. Journal of chromatography A, 1218(49), 88906.
Note
Cysteine is Carbamidomethylated.
Conditions: Atlantis HILIC silica column (150 x 2.1 mm I.D.), 3 um, 100 A, gradient (A = water, B = ACN, C = 200 mM ammonium formate): 0 min, 5% A, 90% B, 5% C; 62.5 min, 55% A, 40% B, 5% C at 0.2 ml/min, temperature 40 C, pH 4.5

pyteomics.achrom.
RCs_gilar_beh
¶ A set of retention coefficients for normal phase chromatography obtained in Gilar, M., & Jaworski, A. (2011). Retention behavior of peptides in hydrophilicinteraction chromatography. Journal of chromatography A, 1218(49), 88906.
Note
Cysteine is Carbamidomethylated.
Conditions: ACQUITY UPLC BEH HILIC column (150 x 2.1 mm I.D.), 1.7 um, 130 A, Mobile phase A: 10 mM ammonium formate buffer, pH 4.5 prepared by titrating 10 mM solution of FA with ammonium hydroxide. Mobile phase B: 90% ACN, 10% mobile phase A (v:v). Gradient: 9060% B in 50 min.

pyteomics.achrom.
RCs_gilar_beh_amide
¶ A set of retention coefficients for normal phase chromatography obtained in Gilar, M., & Jaworski, A. (2011). Retention behavior of peptides in hydrophilicinteraction chromatography. Journal of chromatography A, 1218(49), 88906.
Note
Cysteine is Carbamidomethylated.
Conditions: ACQUITY UPLC BEH glycan column (150 x 2.1 mm I.D.), 1.7 um, 130 A, Mobile phase A: 10 mM ammonium formate buffer, pH 4.5 prepared by titrating 10 mM solution of FA with ammonium hydroxide. Mobile phase B: 90% ACN, 10% mobile phase A (v:v). Gradient: 9060% B in 50 min.

pyteomics.achrom.
RCs_gilar_rp
¶ A set of retention coefficients for normal phase chromatography obtained in Gilar, M., & Jaworski, A. (2011). Retention behavior of peptides in hydrophilicinteraction chromatography. Journal of chromatography A, 1218(49), 88906.
Note
Cysteine is Carbamidomethylated.
Conditions: ACQUITY UPLC BEH C18 column (100 mm x 2.1 mm I.D.), 1.7 um, 130 A. Mobile phase A: 0.02% TFA in water, mobile phase B: 0.018% TFA in ACN. Gradient: 0 to 50% B in 50 min, flow rate 0.2 ml/min, temperature 40 C., pH 2.6.

pyteomics.achrom.
RCs_guo_ph2_0
¶ A set of retention coefficients from Guo, D.; Mant, C. T.; Taneja, A. K.; Parker, J. M. R.; Hodges, R. S. Prediction of peptide retention times in reversedphase highperformance liquid chromatography I. Determination of retention coefficients of amino acid residues of model synthetic peptides. Journal of Chromatography A, 1986, 359, 499518.
Conditions: Synchropak RPP C18 column (250 x 4.1 mm I.D.), gradient (A = 0.1% aq. TFA, pH 2.0; B = 0.1% TFA in acetonitrile) at 1% B/min, flow rate 1 ml/min, 26 centigrades.

pyteomics.achrom.
RCs_guo_ph7_0
¶ A set of retention coefficients from Guo, D.; Mant, C. T.; Taneja, A. K.; Parker, J. M. R.; Hodges, R. S. Prediction of peptide retention times in reversedphase highperformance liquid chromatography I. Determination of retention coefficients of amino acid residues of model synthetic peptides. Journal of Chromatography A, 1986, 359, 499518.
Conditions: Synchropak RPP C18 column (250 x 4.1 mm I.D.), gradient (A = aq. 10 mM (NH4)2HPO4  0.1 M NaClO4, pH 7.0; B = 0.1 M NaClO4 in 60% aq. acetonitrile) at 1.67% B/min, flow rate 1 ml/min, 26 centigrades.

pyteomics.achrom.
RCs_krokhin_100A_fa
¶ A set of retention coefficients from R.C. Dwivedi, V. Spicer, M. Harder, M. Antonovici, W. Ens, K.G. Standing, J.A. Wilkins, and O.V. Krokhin; Analytical Chemistry 2008 80 (18), 70367042. Practical Implementation of 2D HPLC Scheme with Accurate Peptide Retention Prediction in Both Dimensions for HighThroughput BottomUp Proteomics.
Note
Cysteine is Carbamidomethylated.
Conditions: 300 um x 150mm PepMap100 (Dionex, 0.1% FA), packed with 5um Luna C18(2) (Phenomenex, Torrance, CA), pore size 100A, pH=2.0. Both eluents A (2% ACN in water) and B (98% ACN) contained 0.1% FA as ionpairing modifier. 0.33% ACN/min linear gradient (030% B).

pyteomics.achrom.
RCs_krokhin_100A_tfa
¶ A set of retention coefficients from R.C. Dwivedi, V. Spicer, M. Harder, M. Antonovici, W. Ens, K.G. Standing, J.A. Wilkins, and O.V. Krokhin; Analytical Chemistry 2008 80 (18), 70367042. Practical Implementation of 2D HPLC Scheme with Accurate Peptide Retention Prediction in Both Dimensions for HighThroughput BottomUp Proteomics.
Note
Cysteine is Carbamidomethylated.
Conditions: 300 um x 150mm PepMap100 (Dionex, 0.1% TFA), packed with 5um Luna C18(2) (Phenomenex, Torrance, CA), pore size 100 A, pH=2.0. Both eluents A (2% ACN in water) and B (98% ACN) contained 0.1% TFA as ionpairing modifier. 0.33% ACN/min linear gradient (030% B).

pyteomics.achrom.
RCs_meek_ph2_1
¶ A set of retention coefficients determined in Meek, J. L. Prediction of peptide retention times in highpressure liquid chromatography on the basis of amino acid composition. PNAS, 1980, 77 (3), 16321636.
Note
C stands for Cystine.
Conditions: BioRad “ODS” column, gradient (A = 0.1 M NaClO4, 0.1% phosphoric acid in water; B = 0.1 M NaClO4, 0.1% phosphoric acid in 60% aq. acetonitrile) at 1.25% B/min, room temperature.

pyteomics.achrom.
RCs_meek_ph7_4
¶ A set of retention coefficients determined in Meek, J. L. Prediction of peptide retention times in highpressure liquid chromatography on the basis of amino acid composition. PNAS, 1980, 77 (3), 16321636.
Note
C stands for Cystine.
Conditions: BioRad “ODS” column, gradient (A = 0.1 M NaClO4, 5 mM phosphate buffer in water; B = 0.1 M NaClO4, 5 mM phosphate buffer in 60% aq. acetonitrile) at 1.25% B/min, room temperature.

pyteomics.achrom.
RCs_palmblad
¶ A set of retention coefficients determined in Palmblad, M.; Ramstrom, M.; Markides, K. E.; Hakansson, P.; Bergquist, J. Prediction of Chromatographic Retention and Protein Identification in Liquid Chromatography/Mass Spectrometry. Analytical Chemistry, 2002, 74 (22), 58265830.
Conditions: a fused silica column (80100 x 0.200 mm I.D.) packed inhouse with C18 ODSAQ; solvent A = 0.5% aq. HAc, B = 0.5% HAc in acetonitrile.

pyteomics.achrom.
RCs_yoshida
¶ A set of retention coefficients determined in Yoshida, T. Calculation of peptide retention coefficients in normalphase liquid chromatography. Journal of Chromatography A, 1998, 808 (12), 105112.
Note
Cysteine is Carboxymethylated.
Conditions: TSK gel Amide80 column (250 x 4.6 mm I.D.), gradient (A = 0.1% TFA in ACNwater (90:10); B = 0.1% TFA in ACNwater (55:45)) at 0.6% water/min, flow rate 1.0 ml/min, 40 centigrades.

pyteomics.achrom.
RCs_yoshida_lc
¶ A set of retention coefficients from the lengthcorrected model of normalphase peptide chromatography. The dataset comes from Yoshida, T. Calculation of peptide retention coefficients in normalphase liquid chromatography. Journal of Chromatography A, 1998, 808 (12), 105112. The RCs were calculated in Moskovets, E.; Goloborodko A. A.; Gorshkov A. V.; Gorshkov M.V. Limitation of predictive 2D liquid chromatography in reducing the database search space in shotgun proteomics: In silico studies. Journal of Separation Science, 2012, 35 (14), 17711778.
Note
Cysteine is Carboxymethylated.
Conditions: TSK gel Amide80 column (250 x 4.6 mm I.D.), gradient (A = 0.1% TFA in ACNwater (90:10); B = 0.1% TFA in ACNwater (55:45)) at 0.6% water/min, flow rate 1.0 ml/min, 40 centigrades.

pyteomics.achrom.
RCs_zubarev
¶ A set of retention coefficients from the lengthcorrected model of reversedphase peptide chromatography. The dataset was taken from Goloborodko A. A.; Mayerhofer C.; Zubarev A. R.; Tarasova I. A.; Gorshkov A. V.; Zubarev, R. A.; Gorshkov, M. V. Empirical approach to false discovery rate estimation in shotgun proteomics. Rapid communications in mass spectrometry, 2010, 24(4), 45462.
Note
Cysteine is Carbamidomethylated.
Conditions: ReprosilPur C18AQ column (150 x 0.075 mm I.D.), gradient (A = 0.5% AA in water; B = 0.5% AA in ACNwater (90:10)) at 0.5% water/min, flow rate 200.0 nl/min, room temperature.

pyteomics.achrom.
calculate_RT
(peptide, RC_dict, raise_no_mod=True)[source]¶ Calculate the retention time of a peptide using a given set of retention coefficients.
Parameters:  peptide (str or dict) – A peptide sequence or amino acid composition.
 RC_dict (dict) – A set of retention coefficients, length correction parameter and a fixed retention time shift. Keys are: ‘aa’, ‘lcp’ and ‘const’.
 raise_no_mod (bool, optional) – If
True
then an exception is raised when a modified amino acid from peptides is not found in RC_dict. IfFalse
, then the retention coefficient for the nonmodified amino acid residue is used instead.True
by default.
Returns: RT – Calculated retention time.
Return type: Examples
>>> RT = calculate_RT('AA', {'aa': {'A': 1.1}, 'lcp':0.0, 'const': 0.1}) >>> abs(RT  2.3) < 1e6 # Float comparison True >>> RT = calculate_RT('AAA', {'aa': {'ntermA': 1.0, 'A': 1.1, 'ctermA': 1.2}, 'lcp': 0.0, 'const':0.1}) >>> abs(RT  3.4) < 1e6 # Float comparison True >>> RT = calculate_RT({'A': 3}, {'aa': {'ntermA': 1.0, 'A': 1.1, 'ctermA': 1.2}, 'lcp': 0.0, 'const':0.1}) >>> abs(RT  3.4) < 1e6 # Float comparison True

pyteomics.achrom.
get_RCs
(sequences, RTs, lcp=0.21, term_aa=False, **kwargs)[source]¶ Calculate the retention coefficients of amino acids using retention times of a peptide sample and a fixed value of length correction parameter.
Parameters:  sequences (list of str) – List of peptide sequences.
 RTs (list of float) – List of corresponding retention times.
 lcp (float, optional) – A multiplier before ln(L) term in the equation for the retention time of a peptide. Set to 0.21 by default.
 term_aa (bool, optional) – If
True
, terminal amino acids are treated as being modified with ‘ntermX’/’ctermX’ modifications.False
by default.  labels (list of str, optional) – List of all possible amino acids and terminal groups If not given, any modX labels are allowed.
Returns: RC_dict – Dictionary with the calculated retention coefficients.
 RC_dict[‘aa’] – amino acid retention coefficients.
 RC_dict[‘const’] – constant retention time shift.
 RC_dict[‘lcp’] – length correction parameter.
Return type: Examples
>>> RCs = get_RCs(['A','AA'], [1.0, 2.0], 0.0, labels=['A']) >>> abs(RCs['aa']['A']  1) < 1e6 and abs(RCs['const']) < 1e6 True >>> RCs = get_RCs(['A','AA','B'], [1.0, 2.0, 2.0], 0.0, labels=['A','B']) >>> abs(RCs['aa']['A']  1) + abs(RCs['aa']['B']  2) + abs(RCs['const']) < 1e6 True

pyteomics.achrom.
get_RCs_vary_lcp
(sequences, RTs, term_aa=False, lcp_range=(1.0, 1.0), **kwargs)[source]¶ Find the best combination of a length correction parameter and retention coefficients for a given peptide sample.
Parameters:  sequences (list of str) – List of peptide sequences.
 RTs (list of float) – List of corresponding retention times.
 term_aa (bool, optional) – If True, terminal amino acids are treated as being modified with ‘ntermX’/’ctermX’ modifications. False by default.
 lcp_range (2tuple of float, optional) – Range of possible values of the length correction parameter.
 labels (list of str, optional) – List of labels for all possible amino acids and terminal groups If not given, any modX labels are allowed.
 lcp_accuracy (float, optional) – The accuracy of the length correction parameter calculation.
Returns: RC_dict – Dictionary with the calculated retention coefficients.
 RC_dict[‘aa’] – amino acid retention coefficients.
 RC_dict[‘const’] – constant retention time shift.
 RC_dict[‘lcp’] – length correction parameter.
Return type: Examples
>>> RCs = get_RCs_vary_lcp(['A', 'AA', 'AAA'], [1.0, 2.0, 3.0], labels=['A']) >>> abs(RCs['aa']['A']  1) + abs(RCs['lcp']) + abs(RCs['const']) < 1e6 True