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Updated: Jun 17, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
Published on: January 26, 2024
Prediction of lipid-interacting amino acid residues from sequence features
Liangjiang Wang1, Stephanie J Irausquin, Jack Y Yang
1Department of Genetics and Biochemistry, Clemson University, Clemson, South Carolina 29634, USA. liangjw@clemson.edu
Abstract:
Proteins and lipids are integral components of cell membranes, and play important roles in cell signalling. Alterations of normal protein-lipid recognition may cause various diseases. However, molecular mechanisms underlying protein-lipid recognition are still poorly understood. In this study, we have developed a support vector machine-based approach for predicting lipid-interacting residues from amino acid sequence features. To the best of our knowledge, this is the first study that applies machine learning to sequence-based prediction of lipid-interacting residues in proteins. Our study provides useful information for understanding protein-lipid interactions, and may lead to advances in drug discovery.
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