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Updated: Jul 10, 2026

Quantification of Metal Leaching in Immobilized Metal Affinity Chromatography
Published on: January 17, 2020
Using Support Vector Machine Regression to Model the Retention of Peptides in Immobilized Metal-affinity
B G Kermani1, I Kozlov, P Melnyk
1Illumina, Inc. 9885 Towne Centre Drive, San Diego, CA 92122.
Abstract:
Retention of histidine-containing peptides in immobilized metal-affinity chromatography (IMAC) has been studied using several hundred model peptides. Retention in a Nickel column is primarily driven by the number of histidine residues; however, the amino acid composition of the peptide also plays a significant role. A regression model based on support vector machines was used to learn and subsequently predict the relationship between the amino acid composition and the retention time on a Nickel column. The model was predominantly governed by the count of the histidine residues, and the isoelectric point of the peptide.
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