Toward high-resolution computational design of the structure and function of helical membrane proteins

Computational design of de novo bioenergetic membrane proteins

The major energy-producing reactions of biochemistry occur at biological membranes. Computational protein design now provides the opportunity to elucidate the underlying principles of these processes and to construct bioenergetic pathways on our own terms. Here, we review recent achievements in this endeavour of 'synthetic bioenergetics', with a particular focus on new enabling tools that facilitate the computational design of biocompatible de novo integral membrane proteins. We use recent examples to showcase some of the key computational approaches in current use and highlight that the overall philosophy of 'surface-swapping' - the replacement of solvent-facing residues with amino acids bearing lipid-soluble hydrophobic sidechains - is a promising avenue in membrane protein design. We conclude by highlighting outstanding design challenges and the emerging role of AI in sequence design and structure ideation.

AggreProt: a web server for predicting and engineering aggregation prone regions in proteins

Recombinant proteins play pivotal roles in numerous applications including industrial biocatalysts or therapeutics. Despite the recent progress in computational protein structure prediction, protein solubility and reduced aggregation propensity remain challenging attributes to design. Identification of aggregation-prone regions is essential for understanding misfolding diseases or designing efficient protein-based technologies, and as such has a great socio-economic impact. Here, we introduce AggreProt, a user-friendly webserver that automatically exploits an ensemble of deep neural networks to predict aggregation-prone regions (APRs) in protein sequences. Trained on experimentally evaluated hexapeptides, AggreProt compares to or outperforms state-of-the-art algorithms on two independent benchmark datasets. The server provides per-residue aggregation profiles along with information on solvent accessibility and transmembrane propensity within an intuitive interface with interactive sequence and structure viewers for comprehensive analysis. We demonstrate AggreProt efficacy in predicting differential aggregation behaviours in proteins on several use cases, which emphasize its potential for guiding protein engineering strategies towards decreased aggregation propensity and improved solubility. The webserver is freely available and accessible at https://loschmidt.chemi.muni.cz/aggreprot/.

One-shot design elevates functional expression levels of a voltage-gated potassium channel

Membrane proteins play critical physiological roles as receptors, channels, pumps, and transporters. Despite their importance, however, low expression levels often hamper the experimental characterization of membrane proteins. We present an automated and web-accessible design algorithm called mPROSS (https://mPROSS.weizmann.ac.il), which uses phylogenetic analysis and an atomistic potential, including an empirical lipophilicity scale, to improve native-state energy. As a stringent test, we apply mPROSS to the Kv1.2-Kv2.1 paddle chimera voltage-gated potassium channel. Four designs, encoding 9-26 mutations relative to the parental channel, were functional and maintained potassium-selective permeation and voltage dependence in Xenopus oocytes with up to 14-fold increase in whole-cell current densities. Additionally, single-channel recordings reveal no significant change in the channel-opening probability nor in unitary conductance, indicating that functional expression levels increase without impacting the activity profile of individual channels. Our results suggest that the expression levels of other dynamic channels and receptors may be enhanced through one-shot design calculations.

Synergy and anti-cooperativity in allostery: Molecular dynamics study of WT and oncogenic KRAS-RGL1

This study focuses on investigating the effects of an oncogenic mutation (G12V) on the stability and interactions within the KRAS-RGL1 protein complex. The KRAS-RGL1 complex is of particular interest due to its relevance to KRAS-associated cancers and the potential for developing targeted drugs against the KRAS system. The stability of the complex and the allosteric effects of specific residues are examined to understand their roles as modulators of complex stability and function. Using molecular dynamics simulations, we calculate the mutual information, MI, between two neighboring residues at the interface of the KRAS-RGL1 complex, and employ the concept of interaction information, II, to measure the contribution of a third residue to the interaction between interface residue pairs. Negative II indicates synergy, where the presence of the third residue strengthens the interaction, while positive II suggests anti-cooperativity. Our findings reveal that MI serves as a dominant factor in determining the results, with the G12V mutation increasing the MI between interface residues, indicating enhanced correlations due to the formation of a more compact structure in the complex. Interestingly, although II plays a role in understanding three-body interactions and the impact of distant residues, it is not significant enough to outweigh the influence of MI in determining the overall stability of the complex. Nevertheless, II may nonetheless be a relevant factor to consider in future drug design efforts. This study provides valuable insights into the mechanisms of complex stability and function, highlighting the significance of three-body interactions and the impact of distant residues on the binding stability of the complex. Additionally, our findings demonstrate that constraining the fluctuations of a third residue consistently increases the stability of the G12V variant, making it challenging to weaken complex formation of the mutated species through allosteric manipulation. The novel perspective offered by this approach on protein dynamics, function, and allostery has potential implications for understanding and targeting other protein complexes involved in vital cellular processes. The results contribute to our understanding of the effects of oncogenic mutations on protein-protein interactions and provide a foundation for future therapeutic interventions in the context of KRAS-associated cancers and beyond.

Structural basis of γ chain family receptor sharing at the membrane level

Common γ chain (γc) cytokine receptors, including interleukin-2 (IL-2), IL-4, IL-7, IL-9, IL-15, and IL-21 receptors, are activated upon engagement with a common γc receptor (CD132) by concomitant binding of their ectodomains to an interleukin. In this work, we find that direct interactions between the transmembrane domains (TMDs) of both the γc and the interleukin receptors (ILRs) are also required for receptor activation. Moreover, the same γc TMD can specifically recognize multiple ILR TMDs of diverse sequences within the family. Heterodimer structures of γc TMD bound to IL-7 and IL-9 receptor TMDs-determined in a lipid bilayer-like environment by nuclear magnetic resonance spectroscopy-reveal a conserved knob-into-hole mechanism of recognition that mediates receptor sharing within the membrane. Thus, signaling in the γc receptor family requires specific heterotypic interactions of the TMDs.

Structural basis of γ -chain family receptor sharing at the membrane level

The common γ-chain (γc) family of cytokine receptors, including interleukin (IL)-2, IL-4, IL-7, IL-9, IL-15, and IL-21 receptors, are activated upon engagement with the common γc receptor in ligand dependent manner. Sharing of γc by the IL receptors (ILRs) is thought to be achieved by concomitant binding of γc and ILR ectodomains to a cytokine. Here, we found that direct interactions between the transmembrane domain (TMD) of γc and those of the ILRs are also required for receptor activation, and remarkably, the same γc TMD can specifically recognize multiple ILR TMDs of diverse sequences. Heterodimer structures of γc TMD bound to the TMDs of IL-7R and IL-9R, determined in near lipid bilayer environment, reveal a conserved knob-into-hole mechanism of recognition that mediates receptor sharing within the membrane. Functional mutagenesis data indicate the requirement of the heterotypic interactions of TMDs in signaling, which could explain disease mutations within the receptor TMDs.

One-Sentence Summary

The transmembrane anchors of interleukin receptors of the gamma-chain family are critical for receptor sharing and activation.

Protein Design: From the Aspect of Water Solubility and Stability

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

De novo-designed transmembrane domains tune engineered receptor functions

De novo-designed receptor transmembrane domains (TMDs) present opportunities for precise control of cellular receptor functions. We developed a de novo design strategy for generating programmed membrane proteins (proMPs): single-pass α-helical TMDs that self-assemble through computationally defined and crystallographically validated interfaces. We used these proMPs to program specific oligomeric interactions into a chimeric antigen receptor (CAR) that we expressed in mouse primary T cells and found that both in vitro CAR T cell cytokine release and in vivo antitumor activity scaled linearly with the oligomeric state encoded by the receptor TMD, from monomers up to tetramers. All programmed CARs stimulated substantially lower T cell cytokine release relative to the commonly used CD28 TMD, which we show elevated cytokine release through lateral recruitment of the endogenous T cell costimulatory receptor CD28. Precise design using orthogonal and modular TMDs thus provides a new way to program receptor structure and predictably tune activity for basic or applied synthetic biology.

Principles and Methods in Computational Membrane Protein Design

After decades of progress in computational protein design, the design of proteins folding and functioning in lipid membranes appears today as the next frontier. Some notable successes in the de novo design of simplified model membrane protein systems have helped articulate fundamental principles of protein folding, architecture and interaction in the hydrophobic lipid environment. These principles are reviewed here, together with the computational methods and approaches that were used to identify them. We provide an overview of the methodological innovations in the generation of new protein structures and functions and in the development of membrane-specific energy functions. We highlight the opportunities offered by new machine learning approaches applied to protein design, and by new experimental characterization techniques applied to membrane proteins. Although membrane protein design is in its infancy, it appears more reachable than previously thought.

Computational structure prediction provides a plausible mechanism for electron transfer by the outer membrane protein Cyc2 from Acidithiobacillus ferrooxidans

Cyc2 is the key protein in the outer membrane of Acidithiobacillus ferrooxidans that mediates electron transfer between extracellular inorganic iron and the intracellular central metabolism. This cytochrome c is specific for iron and interacts with periplasmic proteins to complete a reversible electron transport chain. A structure of Cyc2 has not yet been characterized experimentally. Here we describe a structural model of Cyc2, and associated proteins, to highlight a plausible mechanism for the ferrous iron electron transfer chain. A comparative modeling protocol specific for trans membrane beta barrel (TMBB) proteins in acidophilic conditions (pH ~ 2) was applied to the primary sequence of Cyc2. The proposed structure has three main regimes: Extracellular loops exposed to low-pH conditions, a TMBB, and an N-terminal cytochrome-like region within the periplasmic space. The Cyc2 model was further refined by identifying likely iron and heme docking sites. This represents the first computational model of Cyc2 that accounts for the membrane microenvironment and the acidity in the extracellular matrix. This approach can be used to model other TMBBs which can be critical for chemolithotrophic microbial growth.

Membrane Protein Engineering with Rosetta

Protein engineering can yield new molecular tools for nanotechnology and therapeutic applications through modulating physiochemical and biological properties. Engineering membrane proteins is especially attractive because they perform key cellular processes including transport, nutrient uptake, removal of toxins, respiration, motility, and signaling. In this chapter, we describe two protocols for membrane protein engineering with the Rosetta software: (1) ΔΔG calculations for single point mutations and (2) sequence optimization in different membrane lipid compositions. These modular protocols are easily adaptable for more complex problems and serve as a foundation for efficient membrane protein engineering calculations.

Small-residue packing motifs modulate the structure and function of a minimal de novo membrane protein

Alpha-helical integral membrane proteins contain conserved sequence motifs that are known to be important in helix packing. These motifs are a promising starting point for the construction of artificial proteins, but their potential has not yet been fully explored. Here, we study the impact of introducing a common natural helix packing motif to the transmembrane domain of a genetically-encoded and structurally dynamic de novo membrane protein. The resulting construct is an artificial four-helix bundle with lipophilic regions that are defined only by the amino acids L, G, S, A and W. This minimal proto-protein could be recombinantly expressed by diverse prokaryotic and eukaryotic hosts and was found to co-sediment with cellular membranes. The protein could be extracted and purified in surfactant micelles and was monodisperse and stable in vitro, with sufficient structural definition to support the rapid binding of a heme cofactor. The reduction in conformational diversity imposed by this design also enhances the nascent peroxidase activity of the protein-heme complex. Unexpectedly, strains of Escherichia coli expressing this artificial protein specifically accumulated zinc protoporphyrin IX, a rare cofactor that is not used by natural metalloenzymes. Our results demonstrate that simple sequence motifs can rigidify elementary membrane proteins, and that orthogonal artificial membrane proteins can influence the cofactor repertoire of a living cell. These findings have implications for rational protein design and synthetic biology.

Common mechanism of thermostability in small α- and β-proteins studied by molecular dynamics

Protein thermostability is important to evolution, diseases, and industrial applications. Proteins use diverse molecular strategies to achieve stability at high temperature, yet reducing the entropy of unfolding seems required. We investigated five small α-proteins and five β-proteins with known, distinct structures and thermostability (T_m ) using multi-seed molecular dynamics simulations at 300, 350, and 400 K. The proteins displayed diverse changes in hydrogen bonding, solvent exposure, and secondary structure with no simple relationship to T_m . Our dynamics were in good agreement with experimental B-factors at 300 K and insensitive to force-field choice. Despite the very distinct structures, the native-state (300 + 350 K) free-energy landscapes (FELs) were significantly broader for the two most thermostable proteins and smallest for the three least stable proteins in both the α- and β-group and with both force fields studied independently (tailed t-test, 95% confidence level). Our results suggest that entropic ensembles stabilize proteins at high temperature due to reduced entropy of unfolding, viz., ΔG = ΔH - TΔS. Supporting this mechanism, the most thermostable proteins were also the least kinetically stable, consistent with broader FELs, typified by villin headpiece and confirmed by specific comparison to a mesophilic ortholog of Thermus thermophilus apo-pyrophosphate phosphohydrolase. We propose that molecular strategies of protein thermostabilization, although diverse, tend to converge toward highest possible entropy in the native state consistent with the functional requirements. We speculate that this tendency may explain why many proteins are not optimally structured and why molten-globule states resemble native proteins so much.

Helical polymers for biological and medical applications

Helices are the most prevalent secondary structure in biomolecules and play vital roles in their activity. Chemists have been fascinated with mimicking this molecular conformation with synthetic materials. Research has now been devoted to the synthesis and characterization of helical materials, and to understand the design principles behind this molecular architecture. In parallel, work has been done to develop synthetic polymers for biological and medical applications. We now have access to materials with controlled size, molecular conformation, multivalency or functionality. As a result, synthetic polymers are being investigated in areas such as drug and gene delivery, tissue engineering, imaging and sensing, or as polymer therapeutics. Here, we provide a critical view of where these two fields, helical polymers and polymers for biological and medical applications, overlap. We have selected relevant polymer families and examples to illustrate the range of applications that can be targeted and the impact of the helical conformation on the performance. For each family of polymers, we briefly describe how they can be prepared, what helical conformations are observed and what parameters control helicity. We close this Review with an outlook of the challenges ahead, including the characterization of helicity through the process and the identification of biocompatibility.

The First 3D Model of the Full-Length KIT Cytoplasmic Domain Reveals a New Look for an Old Receptor

Receptor tyrosine kinases (RTKs) are key regulators of normal cellular processes and have a critical role in the development and progression of many diseases. RTK ligand-induced stimulation leads to activation of the cytoplasmic kinase domain that controls the intracellular signalling. Although the kinase domain of RTKs has been extensively studied using X-ray analysis, the kinase insert domain (KID) and the C-terminal are partially or fully missing in all reported structures. We communicate the first structural model of the full-length RTK KIT cytoplasmic domain, a crucial target for cancer therapy. This model was achieved by integration of ab initio KID and C-terminal probe models into an X-ray structure, and by their further exploration through molecular dynamics (MD) simulation. An extended (2-µs) MD simulation of the proper model provided insight into the structure and conformational dynamics of the full-length cytoplasmic domain of KIT, which can be exploited in the description of the KIT transduction processes.

Protein Structure Prediction and Design in a Biologically Realistic Implicit Membrane

Protein design is a powerful tool for elucidating mechanisms of function and engineering new therapeutics and nanotechnologies. Although soluble protein design has advanced, membrane protein design remains challenging because of difficulties in modeling the lipid bilayer. In this work, we developed an implicit approach that captures the anisotropic structure, shape of water-filled pores, and nanoscale dimensions of membranes with different lipid compositions. The model improves performance in computational benchmarks against experimental targets, including prediction of protein orientations in the bilayer, ΔΔG calculations, native structure discrimination, and native sequence recovery. When applied to de novo protein design, this approach designs sequences with an amino acid distribution near the native amino acid distribution in membrane proteins, overcoming a critical flaw in previous membrane models that were prone to generating leucine-rich designs. Furthermore, the proteins designed in the new membrane model exhibit native-like features including interfacial aromatic side chains, hydrophobic lengths compatible with bilayer thickness, and polar pores. Our method advances high-resolution membrane protein structure prediction and design toward tackling key biological questions and engineering challenges.

Designing minimalist membrane proteins

The construction of artificial membrane proteins from first principles is of fundamental interest and holds considerable promise for new biotechnologies. This review considers the potential advantages of adopting a strictly minimalist approach to the process of membrane protein design. As well as the practical benefits of miniaturisation and simplicity for understanding sequence-structure-function relationships, minimalism should also support the abstract conceptualisation of membrane proteins as modular components for synthetic biology. These ideas are illustrated with selected examples that focus upon α-helical membrane proteins, and which demonstrate how such minimalist membrane proteins might be integrated into living biosystems.

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

Membrane-protein design is an exciting and increasingly successful research area which has led to landmarks including the design of stable and accurate membrane-integral proteins based on coiled-coil motifs. Design of topologically more complex proteins, such as most receptors, channels, and transporters, however, demands an energy function that balances contributions from intra-protein contacts and protein-membrane interactions. Recent advances in water-soluble all-atom energy functions have increased the accuracy in structure-prediction benchmarks. The plasma membrane, however, imposes different physical constraints on protein solvation. To understand these constraints, we recently developed a high-throughput experimental screen, called dsTβL, and inferred apparent insertion energies for each amino acid at dozens of positions across the bacterial plasma membrane. Here, we express these profiles as lipophilicity energy terms in Rosetta and demonstrate that the new energy function outperforms previous ones in modelling and design benchmarks. Rosetta ab initio simulations starting from an extended chain recapitulate two-thirds of the experimentally determined structures of membrane-spanning homo-oligomers with <2.5Å root-mean-square deviation within the top-predicted five models (available online: http://tmhop.weizmann.ac.il). Furthermore, in two sequence-design benchmarks, the energy function improves discrimination of stabilizing point mutations and recapitulates natural membrane-protein sequences of known structure, thereby recommending this new energy function for membrane-protein modelling and design.

The de novo design of a biocompatible and functional integral membrane protein using minimal sequence complexity

The de novo design of integral membrane proteins remains a major challenge in protein chemistry. Here, we describe the bottom-up design of a genetically-encoded synthetic membrane protein comprising only four amino acids (L, S, G and W) in the transmembrane domains. This artificial sequence, which we call REAMP for recombinantly expressed artificial membrane protein, is a single chain of 133 residues arranged into four antiparallel membrane-spanning α-helices. REAMP was overexpressed in Escherichia coli and localized to the cytoplasmic membrane with the intended transmembrane topology. Recombinant REAMP could be extracted from the cell membrane in detergent micelles and was robust and stable in vitro, containing helical secondary structure consistent with the original design. Engineered mono- and bis-histidine residues in the membrane domain of REAMP were able to coordinate heme in vitro, in a manner reminiscent of natural b-type cytochromes. This binding shifted the electrochemical potential of the cofactor, producing a synthetic hemoprotein capable of nascent redox catalysis. These results show that a highly reduced set of amino acids is sufficient to mimic some key properties of natural proteins, and that cellular biosynthesis is a viable route for the production of minimal de novo membrane sequences.

Reprogramming G protein coupled receptor structure and function

The prominence of G protein-coupled receptors (GPCRs) in human physiology and disease has resulted in their intense study in various fields of research ranging from neuroscience to structural biology. With over 800 members in the human genome and their involvement in a myriad of diseases, GPCRs are the single largest family of drug targets, and an ever-present interest exists in further drug discovery and structural characterization efforts. However, low GPCR expression and stability outside the natural lipid environments have challenged these efforts. In vivo functional studies of GPCR signaling are complicated not only by the need for specific spatiotemporal activation, but also by downstream effector promiscuity. In this review, we summarize the present and emerging GPCR engineering methods that have been employed to overcome the challenges involved in receptor characterization, and to better understand the functional role of these receptors.

Recent advances in automated protein design and its future challenges

INTRODUCTION

Protein function is determined by protein structure which is in turn determined by the corresponding protein sequence. If the rules that cause a protein to adopt a particular structure are understood, it should be possible to refine or even redefine the function of a protein by working backwards from the desired structure to the sequence. Automated protein design attempts to calculate the effects of mutations computationally with the goal of more radical or complex transformations than are accessible by experimental techniques. Areas covered: The authors give a brief overview of the recent methodological advances in computer-aided protein design, showing how methodological choices affect final design and how automated protein design can be used to address problems considered beyond traditional protein engineering, including the creation of novel protein scaffolds for drug development. Also, the authors address specifically the future challenges in the development of automated protein design. Expert opinion: Automated protein design holds potential as a protein engineering technique, particularly in cases where screening by combinatorial mutagenesis is problematic. Considering solubility and immunogenicity issues, automated protein design is initially more likely to make an impact as a research tool for exploring basic biology in drug discovery than in the design of protein biologics.

Design of self-assembling transmembrane helical bundles to elucidate principles required for membrane protein folding and ion transport

Ion transporters and channels are able to identify and act on specific substrates among myriads of ions and molecules critical to cellular processes, such as homeostasis, cell signalling, nutrient influx and drug efflux. Recently, we designed Rocker, a minimalist model for Zn²⁺/H⁺ co-transport. The success of this effort suggests that de novo membrane protein design has now come of age so as to serve a key approach towards probing the determinants of membrane protein folding, assembly and function. Here, we review general principles that can be used to design membrane proteins, with particular reference to helical assemblies with transport function. We also provide new functional and NMR data that probe the dynamic mechanism of conduction through Rocker.This article is part of the themed issue 'Membrane pores: from structure and assembly, to medicine and technology'.

Cyclic oligomer design with de novo αβ-proteins

We have previously shown that monomeric globular αβ-proteins can be designed de novo with considerable control over topology, size, and shape. In this paper, we investigate the design of cyclic homo-oligomers from these starting points. We experimented with both keeping the original monomer backbones fixed during the cyclic docking and design process, and allowing the backbone of the monomer to conform to that of adjacent subunits in the homo-oligomer. The latter flexible backbone protocol generated designs with shape complementarity approaching that of native homo-oligomers, but experimental characterization showed that the fixed backbone designs were more stable and less aggregation prone. Designed C2 oligomers with β-strand backbone interactions were structurally confirmed through x-ray crystallography and small-angle X-ray scattering (SAXS). In contrast, C3-C5 designed homo-oligomers with primarily nonpolar residues at interfaces all formed a range of oligomeric states. Taken together, our results suggest that for homo-oligomers formed from globular building blocks, improved structural specificity will be better achieved using monomers with increased shape complementarity and with more polar interfaces.

Reprogramming cellular functions with engineered membrane proteins

Taking inspiration from Nature, synthetic biology utilizes and modifies biological components to expand the range of biological functions for engineering new practical devices and therapeutics. While early breakthroughs mainly concerned the design of gene circuits, recent efforts have focused on engineering signaling pathways to reprogram cellular functions. Since signal transduction across cell membranes initiates and controls intracellular signaling, membrane receptors have been targeted by diverse protein engineering approaches despite limited mechanistic understanding of their function. The modular architecture of several receptor families has enabled the empirical construction of chimeric receptors combining domains from distinct native receptors which have found successful immunotherapeutic applications. Meanwhile, progress in membrane protein structure determination, computational modeling and rational design promise to foster the engineering of a broader range of membrane receptor functions. Marrying empirical and rational membrane protein engineering approaches should enable the reprogramming of cells with widely diverse fine-tuned functions.

Computational protein design with backbone plasticity

The computational algorithms used in the design of artificial proteins have become increasingly sophisticated in recent years, producing a series of remarkable successes. The most dramatic of these is the de novo design of artificial enzymes. The majority of these designs have reused naturally occurring protein structures as ‘scaffolds’ onto which novel functionality can be grafted without having to redesign the backbone structure. The incorporation of backbone flexibility into protein design is a much more computationally challenging problem due to the greatly increased search space, but promises to remove the limitations of reusing natural protein scaffolds. In this review, we outline the principles of computational protein design methods and discuss recent efforts to consider backbone plasticity in the design process.

Therapeutic design of peptide modulators of protein-protein interactions in membranes

Membrane proteins play the central roles in a variety of cellular processes, ranging from nutrient uptake and signalling, to cell-cell communication. Their biological functions are directly related to how they fold and assemble; defects often lead to disease. Protein-protein interactions (PPIs) within the membrane are therefore of great interest as therapeutic targets. Here we review the progress in the application of membrane-insertable peptides for the disruption or stabilization of membrane-based PPIs. We describe the design and preparation of transmembrane peptide mimics; and of several categories of peptidomimetics used for study, including d-enantiomers, non-natural amino acids, peptoids, and β-peptides. Further aspects of the review describe modifications to membrane-insertable peptides, including lipidation and cyclization via hydrocarbon stapling. These approaches provide a pathway toward the development of metabolically stable, non-toxic, and efficacious peptide modulators of membrane-based PPIs. This article is part of a Special Issue entitled: Lipid order/lipid defects and lipid-control of protein activity edited by Dirk Schneider.