Enhancing Structure Prediction and Design of Soluble and Membrane Proteins with Explicit Solvent-Protein Interactions

Abstract

Summary Solvent molecules interact intimately with proteins and can profoundly regulate their structure and function. However, accurately and efficiently modeling protein solvation effects at the molecular level has been challenging. Here, we present a method that improves the atomic-level modeling of soluble and membrane protein structures and binding by efficiently predicting de novo protein-solvent molecule interactions. The method predicted with unprecedented accuracy buried water molecule positions, solvated protein conformations, and challenging mutational effects on protein binding. When applied to homology modeling, solvent-bound membrane protein structures, pockets, and cavities were recapitulated with near-atomic precision even from distant homologs. Blindly refined atomic-level structures of evolutionary distant G protein-coupled receptors imply strikingly different functional roles of buried solvent between receptor classes. The method should prove useful for refining low-resolution protein structures, accurately modeling drug binding sites in structurally-uncharacterized receptors, and designing solvent-mediated protein catalysis, recognition, ligand binding, and membrane protein signaling.

Protein structure prediction and design in a biologically-realistic implicit membrane

“…The membrane also bends and curves to accommodate the hydrophobic surface of proteins (65). A further challenge is accounting for local properties such as specific protein interactions with lipids and cholesterol, which may be captured by a hybrid implicit-explicit approach such as SPadES (66) or HMMM (67). An open question is how to account for mechanical properties such as lateral pressure and strain due to local curvature.…”

A lipophilicity-based energy function for membrane-protein modelling and design

“…An accurate energy function is a prerequisite for automated modelling and design, and solvation makes a critical contribution to protein structure and function. The recent dsTβL apparent energies of insertion into the plasma membrane 15 currently not treated 8,26 and warrant further research. The benchmark reported here provides a basis on which improvements in the energy function can be verified.…”

“…In summary, the actual contribution from solvation of an amino acid is a function of its exposure to the membrane and depends on the amino acid's lipophilicity according to the dsTβL apparent energy and the position's location relative to the membrane midplane. Note that this energy term averages lipophilicity contributions in the plasma membrane and does not express atomic contributions to solvation that are likely to be important in calculating membrane-protein energetics in different types of biological membranes 9,25 , in non-helical membrane-exposed segments, or surrounding water-filled cavities 26 .…”

Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation

“…These methods have been used to identify ligand binding sites and build pharmacophores for G-protein coupled receptors (GPCRs) (5)(6)(7), but the lack of diverse GPCR crystal structures presents serious challenges to using docking methods for identification of ligand binding sites. Moreover, homology models usually cannot be used to identify ligand binding sites or for docking without extensive optimization (4,8). An underappreciated feature that can be used to predict ligand binding sites is surface or sequence conservation.…”