Experimental and computational approaches for membrane protein insertion and topology determination

• Published in: Methods (San Diego, Calif.) Calif.), 2024-06, Vol.226, p.102-119
• Main Authors: Duart, Gerard, Graña-Montes, Ricardo, Pastor-Cantizano, Noelia, Mingarro, Ismael
• Format: Article
• Language: English
• Subjects: Computational Biology - methods; Computational prediction; Experimental approaches; Helical membrane protein; Humans; Membrane insertion; Membrane Proteins - chemistry; Membrane Proteins - genetics; Models, Molecular; Topology; Translocon
• ISSN: 1046-2023; 1095-9130
• DOI: 10.1016/j.ymeth.2024.03.012

•The attainment of the native structure of membrane proteins within biological membranes has been revealed as a dynamic and intricate process.•Foundational concepts like hydrophobicity and the positive inside rule offer a framework for comprehending insertion dynamics and determining topology.•Various techniques, including reporter fusions and biophysical assays, can be employed to experimentally ascertain the insertion properties and topology of membrane proteins.•The integration of topology prediction with deep learning 3D structure prediction models proves highly complementary, expanding our understanding of the membrane protein universe. Membrane proteins play pivotal roles in a wide array of cellular processes and constitute approximately a quarter of the protein-coding genes across all organisms. Despite their ubiquity and biological significance, our understanding of these proteins remains notably less comprehensive compared to their soluble counterparts. This disparity in knowledge can be attributed, in part, to the inherent challenges associated with employing specialized techniques for the investigation of membrane protein insertion and topology. This review will center on a discussion of molecular biology methodologies and computational prediction tools designed to elucidate the insertion and topology of helical membrane proteins.