alexa Prediction of lipid-interacting amino acid residues from sequence features.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Glycomics & Lipidomics

Author(s): Wang L, Irausquin SJ, Yang JY

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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.
This article was published in Int J Comput Biol Drug Des and referenced in Journal of Glycomics & Lipidomics

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