Prediction of peptides retention behavior in reversed‐phase liquid chromatography based on their hydrophobicity. Issue 2 (14th November 2022)

• Record Type: Journal Article
• Authors: Al Musaimi, Othman; Valenzo, Oscar M. Mercado; Williams, Daryl R.
• Is Part Of: Journal of separation science. Volume 46:Issue 2(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-11-14
• Subjects: hydrophobicity -- machine learning -- peptides -- retention behavior; Separation (Technology) -- Periodicals; Chromatographic analysis -- Periodicals; 543.089
• DOI: 10.1002/jssc.202200743
• Languages: English
• ISSNs: 1615-9306

Abstract

Abstract : Hydrophobicity is an important physicochemical property of peptides and proteins. It is responsible for their conformational changes, stability, as well as various chemical intramolecular and intermolecular interactions. Enormous efforts have been invested to study the extent of hydrophobicity and how it could influence various biological processes, in addition to its crucial role in the separation and purification endeavor as well. Here, we have reviewed various studies that were carried out to determine the hydrophobicity starting from (i) simple amino acids solubility behavior, (ii) experimental approach that was undertaken in the reversed‐phase liquid chromatography mode, and ending with (iii) some examples of more advanced computational and machine learning models.