Membrane contact probability: An essential and predictive character for the structural and functional studies of membrane proteins

Abstract

One of the unique traits of membrane proteins is that a significant fraction of their hydrophobic amino acids is exposed to the hydrophobic core of lipid bilayers rather than being embedded in the protein interior, which is often not explicitly considered in the protein structure and function predictions. Here, we propose a characteristic and predictive quantity, the membrane contact probability (MCP), to describe the likelihood of the amino acids of a given sequence being in direct contact with the acyl chains of lipid molecules. We show that MCP is complementary to solvent accessibility in characterizing the outer surface of membrane proteins, and it can be predicted for any given sequence with a machine learning-based method by utilizing a training dataset extracted from MemProtMD, a database generated from molecular dynamics simulations for the membrane proteins with a known structure. As the first of many potential applications, we demonstrate that MCP can be used to systematically improve the prediction precision of the protein contact maps and structures.

ProtRAP: Predicting Lipid Accessibility Together with Solvent Accessibility of Proteins in One Run

“…To generate the data set for training purposes, as shown in Figure A, we extracted 1362 nonredundant membrane protein structures and 7740 nonredundant soluble protein structures from the Protein Data Bank (PDB) and used FreeSASA to calculate the RASA of each residue . We then used MCP, as obtained from the MemProtMD database that was generated by massive coarse-grained (CG) molecular dynamics (MD) simulations, , to determine the RLA, RSA, and relative buried surface area (termed “RBSA”) of each residue with the following equations: RLA = MCP × RASA RSA = ( 1 − MCP ) × RASA RBSA = 1 − RASA = 1 − RLA − RSA Such a definition not only generates a quantity, RLA, which has the same dimension and physical meaning as RSA and RASA, but also accounts for the more complex nature of lipid molecules than water molecules in accessing the surface residues of proteins.…”

“…A residue is considered to be in direct contact with the hydrophobic core of membranes if its C α atom is within 6 Å of the lipid acyl chain atoms. In our recent study, we showed that 6 Å was indeed an appropriate cutoff value . The multichain proteins were split into single-chain sequences.…”

“…Similar model architectures were adopted in earlier studies for the prediction of protein properties and achieved very good performance. 11,16,25 To deal with long-range dependencies, attention layers were inserted between recurrent layers to improve the performance.…”

“…In our recent study, we showed that 6 Å was indeed an appropriate cutoff value. 16 The multichain proteins were split into single-chain sequences. To reduce the redundancy of protein sequences and avoid overfitting, we calculated the identity of every two single-chain sequences by BlastP (version 2.9.0+) 38 and filtered the chains with over 40% identity.…”

“…Recently, we proposed the use of membrane contact probability (MCP) to predict the likelihood of protein residues in direct contact with membranes. 16 Although showing great potential, MCP does not have the same dimension as SA and is inherently incompatible with SA. Therefore, we sought to study lipid accessibility (LA), a quantity defined in a similar manner as SA, to characterize the surface residues of membrane proteins that are accessible to lipid molecules.…”