Template-free prediction of a new monotopic membrane protein fold and assembly by AlphaFold2

AlphaFold and what is next: bridging functional, systems and structural biology

INTRODUCTION

The DeepMind's AlphaFold (AF) has revolutionized biomedical and biocience research by providing both experts and non-experts with an invaluable tool for predicting protein structures. However, while AF is highly effective for predicting structures of rigid and globular proteins, it is not able to fully capture the dynamics, conformational variability, and interactions of proteins with ligands and other biomacromolecules.

AREAS COVERED

In this review, we present a comprehensive overview of the latest advancements in 3D model predictions for biomacromolecules using AF. We also provide a detailed analysis its of strengths and limitations, and explore more recent iterations, modifications, and practical applications of this strategy. Moreover, we map the path forward for expanding the landscape of AF toward predicting structures of every protein and peptide, and their interactions in the proteome in the most physiologically relevant form. This discussion is based on an extensive literature search performed using PubMed and Google Scholar.

EXPERT OPINION

While significant progress has been made to enhance AF's modeling capabilities, we argue that a combined approach integrating both various in silico and in vitro methods will be most beneficial for the future of structural biology, bridging the gaps between static and dynamic features of proteins and their functions.

Insights in caveolae protein structure arrangements and their local lipid environment

Caveolae are 50-80 nm sized plasma membrane invaginations found in adipocytes, endothelial cells or fibroblasts. They are involved in endocytosis, lipid uptake and the regulation of the cellular lipid metabolism as well as sensing and adapting to changes in plasma membrane tension. Caveolae are characterized by their unique lipid composition and their specific protein coat consisting of caveolin and cavin proteins. Recently, detailed structural information was obtained for the major caveolae protein caveolin1 showing the formation of a disc-like 11-mer protein complex. Furthermore, the importance of the cavin disordered regions in the generation of cavin trimers and caveolae at the plasma membrane were revealed. Thus, finally, structural insights about the assembly of the caveolar coat can be elucidated. Here, we review recent developments in caveolae structural biology with regard to caveolae coat formation and caveolae curvature generation. Secondly, we discuss the importance of specific lipid species necessary for caveolae curvature and formation. In the last years, it was shown that specifically sphingolipids, cholesterol and fatty acids can accumulate in caveolae invaginations and may drive caveolae endocytosis. Throughout, we summarize recent studies in the field and highlight future research directions.

Scaffolds and the scaffolding domain: an alternative paradigm for caveolin-1 signaling

Caveolin-1 (Cav1) is a 22 kDa intracellular protein that is the main protein constituent of bulb-shaped membrane invaginations known as caveolae. Cav1 can be also found in functional non-caveolar structures at the plasma membrane called scaffolds. Scaffolds were originally described as SDS-resistant oligomers composed of 10-15 Cav1 monomers observable as 8S complexes by sucrose velocity gradient centrifugation. Recently, cryoelectron microscopy (cryoEM) and super-resolution microscopy have shown that 8S complexes are interlocking structures composed of 11 Cav1 monomers each, which further assemble modularly to form higher-order scaffolds and caveolae. In addition, Cav1 can act as a critical signaling regulator capable of direct interactions with multiple client proteins, in particular, the endothelial nitric oxide (NO) synthase (eNOS), a role believed by many to be attributable to the highly conserved and versatile scaffolding domain (CSD). However, as the CSD is a hydrophobic domain located by cryoEM to the periphery of the 8S complex, it is predicted to be enmeshed in membrane lipids. This has led some to challenge its ability to interact directly with client proteins and argue that it impacts signaling only indirectly via local alteration of membrane lipids. Here, based on recent advances in our understanding of higher-order Cav1 structure formation, we discuss how the Cav1 CSD may function through both lipid and protein interaction and propose an alternate view in which structural modifications to Cav1 oligomers may impact exposure of the CSD to cytoplasmic client proteins, such as eNOS.

Computational drug development for membrane protein targets

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have limitations for development of drugs that target membrane proteins. Structural transitions of membrane proteins have a central role during transmembrane signaling and are often influenced by therapeutic compounds. Resolving the structural and functional basis of dynamic transmembrane signaling networks, especially within the native membrane or cellular environment, remains a central challenge for drug development. Tackling this challenge will require an interplay between experimental and computational tools, such as super-resolution optical microscopy for quantification of the molecular interactions of cellular signaling networks and their modulation by potential drugs, cryo-electron microscopy for determination of the structural transitions of proteins in native cell membranes and entire cells, and computational tools for data analysis and prediction of the structure and function of cellular signaling networks, as well as generation of promising drug candidates.

The building blocks of caveolae revealed: caveolins finally take center stage

The ability of cells to divide, migrate, relay signals, sense mechanical stimuli, and respond to stress all rely on nanoscale invaginations of the plasma membrane known as caveolae. The caveolins, a family of monotopic membrane proteins, form the inner layer of the caveolar coat. Caveolins have long been implicated in the generation of membrane curvature, in addition to serving as scaffolds for signaling proteins. Until recently, however, the molecular architecture of caveolins was unknown, making it impossible to understand how they operate at a mechanistic level. Over the past year, two independent lines of evidence - experimental and computational - have now converged to provide the first-ever glimpse into the structure of the oligomeric caveolin complexes that function as the building blocks of caveolae. Here, we summarize how these discoveries are transforming our understanding of this long-enigmatic protein family and their role in caveolae assembly and function. We present new models inspired by the structure for how caveolins oligomerize, remodel membranes, interact with their binding partners, and reorganize when mutated. Finally, we discuss emerging insights into structural differences among caveolin family members that enable them to support the proper functions of diverse tissues and organisms.