Determination and prediction of peptide mobilities by micellar electro-kinetic chromatography using adaptive neuro-fuzzy inference system as a feature selection method
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
View: 60
This Paper With 16 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_AMECJ-3-2_007
تاریخ نمایه سازی: 14 آذر 1402
Abstract:
Mobility of ۱۲۸ peptides composed of up to ۱۴ amino acids is
determined for sodium dodecyl sulfate (SDS) micellar systems using
micellar electrokinetic chromatography (MEKC). The mobilities of
these peptides are predicted using back propagation of error artificial
neural networks (BP-ANNs). Adaptive neuro-fuzzy inference system
(ANFIS) which can deal with linear and nonlinear phenomena is
used to select the inputs of BP-ANN. A ۳:۴:۱ BP-ANN model with
four variables of Kappa substituent constant, Kappa(H), number of
peptide bonds, (lnN), molar refractivity of C-terminal, MRC, and
steric effects at N-terminal, ES,N, which incorporate substituent,
steric and molar refractivity effects as its inputs was developed.
Comparison of Multiple Linear Regression (MLR) and ANN results
shows the nonlinear characteristic of the phenomena. The nonlinear
model was successful in predicting the mobilities of ۱۲۰ peptides
except for the ones (۸ peptides) with negatively charged amino acids.
It is shown that that most outlier peptides contain middle glutamic
acid (E) and aspartic acid (D) amino acids and their mobilities follow
a similar mechanism in MEKC.
Keywords:
Peptide mobilities , Micellar ElectroKinetic Chromatography , Artificial neural networks , Adaptive neuro-fuzzy inference system
Authors
Mostafa Hassanisadi
Nanotechnology Research Center, Research Institute of Petroleum Industry, Tehran, Iran
Morteza G.Khaledi
Department of Chemistry, Sharif University of Technology, P.O.Box۹۵۱۶-۱۱۳۶۵, Tehran, Iran
Mehdi Jalali-Heravi
Department of Chemistry, North Carolina State University, NC۸۲۰۴-۲۷۶۹۵, USA