Computational design of peptides that target transmembrane helices

Allosteric targeted drug delivery for enhanced blood-brain barrier penetration via mimicking transmembrane domain interactions

Current strategies for active targeting in the brain are entirely based on the effective interaction of the ligand with the orthosteric sites of specific receptors on the blood-brain barrier (BBB), which is highly susceptible to various pathophysiological factors and limits the efficacy of drug delivery. Here, we propose an allosteric targeted drug delivery strategy that targets classical BBB transmembrane receptors by designing peptide ligands that specifically bind to their transmembrane domains. This strategy prevents competitive interference from endogenous ligands and antibodies by using the insulin receptor and integrin αv as model targets, respectively, and can effectively overcome pseudotargets or target loss caused by shedding or mutating the extracellular domain of target receptors. Moreover, these ligands can be spontaneously embedded in the phospholipid layer of lipid carriers using a plug-and-play approach without chemical modification, with excellent tunability and immunocompatibility. Overall, this allosteric targeted drug delivery strategy can be applied to multiple receptor targets and drug carriers and offers promising therapeutic benefits in brain diseases.

Importance of integrin transmembrane helical interactions for antagonistic versus agonistic ligand behavior: Consequences for medical applications

Integrins are well-characterized receptors involved in cell adhesion and signaling. With six approved drugs, they are recognized as valuable therapeutic targets. Here, we explore potential activation mechanisms that may clarify the agonist versus antagonist behavior of integrin ligands. The reorganization of the transmembrane domain (TMD) in the integrin receptor, forming homooligomers within focal adhesions, could be key to the understanding of the agonistic properties of integrin ligands at substoichiometric concentrations. This has significant implications for medical applications. While we focus on the RGD peptide-recognizing integrin subfamily, we propose that these mechanistic insights may also apply to other integrin subtypes. For application of integrin ligands in medicine it is essential to consider this mechanism and its consequences for affinity and bioavailability.

Quest for New Generation Biocompatible Materials: Tailoring β-Peptide Structure and Interactions via Synergy of Experiments and Modelling

Peptide-based self-assembly has been used to produce a wide range of nanostructures. While most of these systems involve self-assembly of α-peptides, more recently β-peptides have also been shown to undergo supramolecular self-assembly, and have been used to produce materials for applications in tissue engineering, cell culture and drug delivery. In order to engineer new materials with specific structure and function, theoretical molecular modelling can provide significant insights into the collective balance of non-covalent interactions that drive the self-assembly and determine the structure of the resultant supramolecular materials under different conditions. However, this approach has only recently become feasible for peptide-based self-assembled nanomaterials, particularly those that incorporate non α-amino acids. This perspective provides an overview of the challenges associated with computational modelling of the self-assembly of β-peptides and the recent success using a combination of experimental and computational techniques to provide insights into the self-assembly mechanisms and fully atomistic models of these new biocompatible materials.

De novo-designed transmembrane proteins bind and regulate a cytokine receptor

Transmembrane (TM) domains as simple as a single span can perform complex biological functions using entirely lipid-embedded chemical features. Computational design has the potential to generate custom tool molecules directly targeting membrane proteins at their functional TM regions. Thus far, designed TM domain-targeting agents have been limited to mimicking the binding modes and motifs of natural TM interaction partners. Here, we demonstrate the design of de novo TM proteins targeting the erythropoietin receptor (EpoR) TM domain in a custom binding topology competitive with receptor homodimerization. The TM proteins expressed in mammalian cells complex with EpoR and inhibit erythropoietin-induced cell proliferation. In vitro, the synthetic TM domain complex outcompetes EpoR homodimerization. Structural characterization reveals that the complex involves the intended amino acids and agrees with our designed molecular model of antiparallel TM helices at 1:1 stoichiometry. Thus, membrane protein TM regions can now be targeted in custom-designed topologies.

De novo design of high-affinity binders of bioactive helical peptides

Many peptide hormones form an α-helix on binding their receptors1-4, and sensitive methods for their detection could contribute to better clinical management of disease5. De novo protein design can now generate binders with high affinity and specificity to structured proteins6,7. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion8 to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.

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.

Designed Transmembrane Proteins Inhibit the Erythropoietin Receptor in a Custom Binding Topology

Transmembrane (TM) domains as simple as a single span can perform complex biological functions using entirely lipid-embedded chemical features. Computational design has potential to generate custom tool molecules directly targeting membrane proteins at their functional TM regions. Thus far, designed TM domain-targeting agents have been limited to mimicking binding modes and motifs of natural TM interaction partners. Here, we demonstrate the design of de novo TM proteins targeting the erythropoietin receptor (EpoR) TM domain in a custom binding topology competitive with receptor homodimerization. The TM proteins expressed in mammalian cells complex with EpoR and inhibit erythropoietin-induced cell proliferation. In vitro, the synthetic TM domain complex outcompetes EpoR homodimerization. Structural characterization reveals that the complex involves the intended amino acids and agrees with our designed molecular model of antiparallel TM helices at 1:1 stoichiometry. Thus, membrane protein TM regions can now be targeted in custom designed topologies.

Proline C-H Bonds as Loci for Proline Assembly via C-H/O Interactions

Proline residues within proteins lack a traditional hydrogen bond donor. However, the hydrogens of the proline ring are all sterically accessible, with polarized C-H bonds at Hα and Hδ that exhibit greater partial positive character and can be utilized as alternative sites for molecular recognition. C-H/O interactions, between proline C-H bonds and oxygen lone pairs, have been previously identified as modes of recognition within protein structures and for higher-order assembly of protein structures. In order to better understand intermolecular recognition of proline residues, a series of proline derivatives was synthesized, including 4R-hydroxyproline nitrobenzoate methyl ester, acylated on the proline nitrogen with bromoacetyl and glycolyl groups, and Boc-4S-(4-iodophenyl)hydroxyproline methyl amide. All three derivatives exhibited multiple close intermolecular C-H/O interactions in the crystallographic state, with H⋅⋅⋅O distances as close as 2.3 Å. These observed distances are well below the 2.72 Å sum of the van der Waals radii of H and O, and suggest that these interactions are particularly favorable. In order to generalize these results, we further analyzed the role of C-H/O interactions in all previously crystallized derivatives of these amino acids, and found that all 26 structures exhibited close intermolecular C-H/O interactions. Finally, we analyzed all proline residues in the Cambridge Structural Database of small-molecule crystal structures. We found that the majority of these structures exhibited intermolecular C-H/O interactions at proline C-H bonds, suggesting that C-H/O interactions are an inherent and important mode for recognition of and higher-order assembly at proline residues. Due to steric accessibility and multiple polarized C-H bonds, proline residues are uniquely positioned as sites for binding and recognition via C-H/O interactions.

Predicting the Assembly of the Transmembrane Domains of Viral Channel Forming Proteins and Peptide Drug Screening Using a Docking Approach

A de novo assembly algorithm is provided to propose the assembly of bitopic transmembrane domains (TMDs) of membrane proteins. The algorithm is probed using, in particular, viral channel forming proteins (VCPs) such as M2 of influenza A virus, E protein of severe acute respiratory syndrome corona virus (SARS-CoV), 6K of Chikungunya virus (CHIKV), SH of human respiratory syncytial virus (hRSV), and Vpu of human immunodeficiency virus type 2 (HIV-2). The generation of the structures is based on screening a 7-dimensional space. Assembly of the TMDs can be achieved either by simultaneously docking the individual TMDs or via a sequential docking. Scoring based on estimated binding energies (EBEs) of the oligomeric structures is obtained by the tilt to decipher the handedness of the bundles. The bundles match especially well for all-atom models of M2 referring to an experimentally reported tetrameric bundle. Docking of helical poly-peptides to experimental structures of M2 and E protein identifies improving EBEs for positively charged (K,R,H) and aromatic amino acids (F,Y,W). Data are improved when using polypeptides for which the coordinates of the amino acids are adapted to the Cα coordinates of the respective experimentally derived structures of the TMDs of the target proteins.

Computationally designed GPCR quaternary structures bias signaling pathway activation

Communication across membranes controls critical cellular processes and is achieved by receptors translating extracellular signals into selective cytoplasmic responses. While receptor tertiary structures can be readily characterized, receptor associations into quaternary structures are challenging to study and their implications in signal transduction remain poorly understood. Here, we report a computational approach for predicting receptor self-associations, and designing receptor oligomers with various quaternary structures and signaling properties. Using this approach, we designed chemokine receptor CXCR4 dimers with reprogrammed binding interactions, conformations, and abilities to activate distinct intracellular signaling proteins. In agreement with our predictions, the designed CXCR4s dimerized through distinct conformations and displayed different quaternary structural changes upon activation. Consistent with the active state models, all engineered CXCR4 oligomers activated the G protein Gi, but only specific dimer structures also recruited β-arrestins. Overall, we demonstrate that quaternary structures represent an important unforeseen mechanism of receptor biased signaling and reveal the existence of a bias switch at the dimer interface of several G protein-coupled receptors including CXCR4, mu-Opioid and type-2 Vasopressin receptors that selectively control the activation of G proteins vs β-arrestin-mediated pathways. The approach should prove useful for predicting and designing receptor associations to uncover and reprogram selective cellular signaling functions.

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.

Engineered cells along with smart scaffolds: critical factors for improving tissue engineering approaches

In this review, gene delivery and its applications are discussed in tissue engineering (TE); also, new techniques such as the CRISPR-Cas9 system, synthetics biology and molecular dynamics simulation to improve the efficiency of the scaffolds have been studied. CRISPR-Cas9 is expected to make significant advances in TE in the future. The fundamentals of synthetic biology have developed powerful and flexible methods for programming cells via artificial genetic circuits. The combination of regenerative medicine and artificial biology allows the engineering of cells and organisms for use in TE, biomaterials, bioprocessing and scaffold development. The dynamics of protein adsorption at the scaffold surface at the atomic level can provide valuable guidelines for the future design of TE scaffolds /implants.

Dawn of a New Era for Membrane Protein Design

A major advancement has recently occurred in the ability to predict protein secondary structure from sequence using artificial neural networks. This new accessibility to high-quality predicted structures provides a big opportunity for the protein design community. It is particularly welcome for membrane protein design, where the scarcity of solved structures has been a major limitation of the field for decades. Here, we review the work done to date on the membrane protein design and set out established and emerging tools that can be used to most effectively exploit this new access to structures.

A novel role for endoplasmic reticulum protein 46 (ERp46) in platelet function and arterial thrombosis in mice

Although several members of protein disulfide isomerase (PDI) family support thrombosis, other PDI family members with the CXYC motif remain uninvestigated. ERp46 has 3 CGHC redox-active sites and a radically different molecular architecture than other PDIs. Expression of ERp46 on the platelet surface increased with thrombin stimulation. An anti-ERp46 antibody inhibited platelet aggregation, adenosine triphosphate (ATP) release, and αIIbβ3 activation. ERp46 protein potentiated αIIbβ3 activation, platelet aggregation, and ATP release, whereas inactive ERp46 inhibited these processes. ERp46 knockout mice had prolonged tail-bleeding times and decreased platelet accumulation in thrombosis models that was rescued by infusion of ERp46. ERp46-deficient platelets had decreased αIIbβ3 activation, platelet aggregation, ATP release, and P-selectin expression. The defects were reversed by wild-type ERp46 and partially reversed by ERp46 containing any of the 3 active sites. Platelet aggregation stimulated by an αIIbβ3-activating peptide was inhibited by the anti-ERp46 antibody and was decreased in ERp46-deficient platelets. ERp46 bound tightly to αIIbβ3 by surface plasmon resonance but poorly to platelets lacking αIIbβ3 and physically associated with αIIbβ3 upon platelet activation. ERp46 mediated clot retraction and platelet spreading. ERp46 more strongly reduced disulfide bonds in the β3 subunit than other PDIs and in contrast to PDI, generated thiols in β3 independently of fibrinogen. ERp46 cleaved the Cys473-Cys503 disulfide bond in β3, implicating a target for ERp46. Finally, ERp46-deficient platelets have decreased thiols in β3, implying that ERp46 cleaves disulfide bonds in platelets. In conclusion, ERp46 is critical for platelet function and thrombosis and facilitates αIIbβ3 activation by targeting disulfide bonds.

A sequence space search engine for computational protein design to modulate molecular functionality

De-novo protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence space search engine for effective convergence in computational protein design. We propose a greedy simulated annealing-based Monte-Carlo parallel search algorithm for better sequence-structure compatibility probing in protein design. The guidance provided by the evolutionary profile, the greedy approach, and the cooling schedule adopted in the Monte Carlo simulation ensures sufficient exploration and exploitation of the search space leading to faster convergence. On evaluating the proposed algorithm, we find that a dataset of 76 target scaffolds report an average root-mean-square-deviation (RMSD) of 1.07 Å and an average TM-Score of 0.93 with the modeled designed protein sequences. High sequence recapitulation of 48.7% (59.4%) observed in the design sequences for all (hydrophobic) solvent-inaccessible residues again establish the goodness of the proposed algorithm. A high (93.4%) intra-group recapitulation of hydrophobic residues in the solvent-inaccessible region indicates that the proposed protein design algorithm preserves the core residues in the protein and provides alternative residue combinations in the solvent-accessible regions of the target protein. Furthermore, a COFACTOR-based protein functional analysis shows that the design sequences exhibit altered molecular functionality and introduce new molecular functions compared to the target scaffolds.Communicated by Ramaswamy H. Sarma.

Engineered protein-small molecule conjugates empower selective enzyme inhibition

Potent, specific ligands drive precision medicine and fundamental biology. Proteins, peptides, and small molecules constitute effective ligand classes. Yet greater molecular diversity would aid the pursuit of ligands to elicit precise biological activity against challenging targets. We demonstrate a platform to discover protein-small molecule (PriSM) hybrids to combine unique pharmacophore activities and shapes with constrained, efficiently engineerable proteins. In this platform, a fibronectin protein library is displayed on yeast with a single cysteine coupled to acetazolamide via a maleimide-poly(ethylene glycol) linker. Magnetic and flow cytometric sorts enrich specific binders to carbonic anhydrase isoforms. Isolated PriSMs exhibit potent, specific inhibition of carbonic anhydrase isoforms with efficacy superior to that of acetazolamide or protein alone, including an 80-fold specificity increase and 9-fold potency gain. PriSMs are engineered with multiple linker lengths, protein conjugation sites, and sequences against two different isoforms, which reveal platform flexibility and impacts of molecular designs. PriSMs advance the molecular diversity of efficiently engineerable ligands.

Spiers Memorial Lecture: Analysis and de novo design of membrane-interactive peptides

Membrane-peptide interactions play critical roles in many cellular and organismic functions, including protection from infection, remodeling of membranes, signaling, and ion transport. Peptides interact with membranes in a variety of ways: some associate with membrane surfaces in either intrinsically disordered conformations or well-defined secondary structures. Peptides with sufficient hydrophobicity can also insert vertically as transmembrane monomers, and many associate further into membrane-spanning helical bundles. Indeed, some peptides progress through each of these stages in the process of forming oligomeric bundles. In each case, the structure of the peptide and the membrane represent a delicate balance between peptide-membrane and peptide-peptide interactions. We will review this literature from the perspective of several biologically important systems, including antimicrobial peptides and their mimics, α-synuclein, receptor tyrosine kinases, and ion channels. We also discuss the use of de novo design to construct models to test our understanding of the underlying principles and to provide useful leads for pharmaceutical intervention of diseases.

Rational Design of Anti-Angiogenic Peptides to Inhibit VEGF/VEGFR2 Interactions for Cancer Therapeutics

BACKGROUND

Angiogenesis is a critical physiological process that plays a key role in tumor progression, metastatic dissemination, and invasion. In the last two decades, the vascular endothelial growth factor (VEGF) signaling pathway has been the area of extensive researches. VEGF executes its special effects by binding to vascular endothelial growth factor receptors (VEGFRs), particularly VEGFR-2.

OBJECTIVE

The inhibition of VEGF/VEGFR2 interaction is known as an effective cancer therapy strategy. The current study pointed to design and model an anti-VEGF peptide based on VEGFR2 binding regions.

METHOD

The large-scale peptide mutation screening was used to achieve a potent peptide with high binding affinity to VEGF for possible application in inhibition of VEGF/VEGFR2 interaction. The AntiCP and Peptide Ranker servers were used to generate the possible peptides library with anticancer activities and prediction of peptides bioactivity. Then, the interaction of VEGF and all library peptides were analyzed using Hex 8.0.0 and ClusPro tools. A number of six peptides with favorable docking scores were achieved. All of the best docking scores of peptides in complexes with VEGF were evaluated to confirm their stability, using molecular dynamics simulation (MD) with the help of the GROMACS software package.

RESULTS

As a result, two antiangiogenic peptides with 13 residues of PepA (NGIDFNRDFFLGL) and PepC (NGIDFNRDKFLFL) were achieved and introduced to inhibit VEGF/VEGFR2 interactions.

CONCLUSIONS

In summary, this study provided new insights into peptide-based therapeutics development for targeting VEGF signaling pathway in tumor cells. PepA and PepC are recommended as potentially promising anticancer agents for further experimental evaluations.

Soy Isoflavones Inhibit Both GPIb-IX Signaling and αIIbβ3 Outside-In Signaling via 14-3-3ζ in Platelet

Soy diet is thought to help prevent cardiovascular diseases in humans. Isoflavone, which is abundant in soybean and other legumes, has been reported to possess antiplatelet activity and potential antithrombotic effect. Our study aims to elucidate the potential target of soy isoflavone in platelet. The anti-thrombosis formation effect of genistein and daidzein was evaluated in ex vivo perfusion chamber model under low (300 s-1) and high (1800 s-1) shear forces. The effect of genistein and daidzein on platelet aggregation and spreading was evaluated with platelets from both wildtype and GPIbα deficient mice. The interaction of these soy isoflavone with 14-3-3ζ was detected by surface plasmon resonance (SPR) and co-immunoprecipitation, and the effect of αIIbβ3-mediated outside-in signaling transduction was evaluated by western blot. We found both genistein and daidzein showed inhibitory effect on thrombosis formation in perfusion chamber, especially under high shear force (1800 s-1). These soy isoflavone interact with 14-3-3ζ and inhibited both GPIb-IX and αIIbβ3-mediated platelet aggregation, integrin-mediated platelet spreading and outside-in signaling transduction. Our findings indicate that 14-3-3ζ is a novel target of genistein and daidzein. 14-3-3ζ, an adaptor protein that regulates both GPIb-IX and αIIbβ3-mediated platelet activation is involved in soy isoflavone mediated platelet inhibition.

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.

A new class of sensing elements for sensors: Clamp peptides for Zika virus

The design of a new class of selective and high affinity antibody mimetics termed clamp peptide (CP) that incorporate three short peptides structurally and mechanically mimicking a clamp is proposed as sensing elements for a reliable detection sensor platform. The CPs consist of two short peptides functioning as arms that recognize two different epitopes in the target protein and are connected by a third short peptide that acts as a hinge between the peptide arms. For the construction of CPs, we employed a rational design combined with computational methods. To illustrate our approach, we designed a CP that binds selectively to the envelope protein of the Zika virus (ZIKV). The virtual docking cycles were run maximizing the discrimination between ZIKV and Dengue virus (DENV) envelope proteins. DENV was chosen among the flavivirus family because it has high structural similarity with ZIKV. When employed in a colorimetric binding assay or in label-free electrochemical impedance sensor format, the CP was selective for ZIKV vs DENV particles showing detection limit under 10⁴ copies/mL, comparable to anti-ZIKV antibodies. Apparent dissociation binding constants (Kd) confirmed a better performance of CPs than mono-arm peptides (Kd of best CP = 162 nM ± 23 nM; Kd of best mono-arm peptide = 11.15 ± 2.76 μM). The performance of the assays based on CPs was also verified in serum and urine (diluted 1:10 and 1:1 respectively). The detection limits of CPs decreased about one order of magnitude for ZIKV detection in serum or urine, with a distinct analytical signal starting from 10⁵ copies/mL of ZIKV.

Visualization of Platelet Integrins via Two-Photon Microscopy Using Anti-transmembrane Domain Peptides Containing a Blue Fluorescent Amino Acid

The fluorescent reporters commonly used to visualize proteins can perturb both protein structure and function. Recently, we found that 4-cyanotryptophan (4CN-Trp), a blue fluorescent amino acid, is suitable for one-photon imaging applications. Here, we demonstrate its utility in two-photon fluorescence microscopy by using it to image integrins on cell surfaces. Specifically, we used solid-phase peptide synthesis to generate CHAMP peptides labeled with 4-cyanoindole (4CNI) at their N-termini to image integrins on cell surfaces. CHAMP (computed helical anti-membrane protein) peptides spontaneously insert into membrane bilayers to target integrin transmembrane domains and cause integrin activation. We found that 4CNI labeling did not perturb the ability of CHAMP peptides to insert into membranes, bind to integrins, or cause integrin activation. We then used two-photon fluorescence microscopy to image 4CNI-containing integrins on the surface of platelets. Compared to a 4CNI-labeled scrambled peptide that uniformly decorated cell surfaces, 4CNI-labeled CHAMP peptides were present in discrete blue foci. To confirm that these foci represented CN peptide-containing integrins, we co-stained platelets with integrin-specific fluorescent monoclonal antibodies and found that CN peptide and antibody fluorescence coincided. Because 4CNI can readily be biosynthetically incorporated into proteins with little if any effect on protein structure and function, it provides a facile way to directly monitor protein behavior and protein-protein interactions in cellular environments. In addition, these results clearly demonstrate that the two-photon excitation cross section of 4CN-Trp is sufficiently large to make it a useful two-photon fluorescence reporter for biological applications.

Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

Protein-protein interactions (PPIs) mediate a large number of important regulatory pathways. Their modulation represents an important strategy for discovering novel therapeutic agents. However, the features of PPI binding surfaces make the use of structure-based drug discovery methods very challenging. Among the diverse approaches used in the literature to tackle the problem, linear peptides have demonstrated to be a suitable methodology to discover PPI disruptors. Unfortunately, the poor pharmacokinetic properties of linear peptides prevent their direct use as drugs. However, they can be used as models to design enzyme resistant analogs including, cyclic peptides, peptide surrogates or peptidomimetics. Small molecules have a narrower set of targets they can bind to, but the screening technology based on virtual docking is robust and well tested, adding to the computational tools used to disrupt PPI. We review computational approaches used to understand and modulate PPI and highlight applications in a few case studies involved in physiological processes such as cell growth, apoptosis and intercellular communication.

The 14-3-3ζ-c-Src-integrin-β3 complex is vital for platelet activation

Several adaptor molecules bind to cytoplasmic tails of β-integrins and facilitate bidirectional signaling, which is critical in thrombosis and hemostasis. Interfering with integrin-adaptor interactions spatially or temporally to inhibit thrombosis without affecting hemostasis is an attractive strategy for the development of safe antithrombotic drugs. We show for the first time that the 14-3-3ζ-c-Src-integrin-β3 complex is formed during platelet activation. 14-3-3ζ-c-Src interaction is mediated by the -PIRLGLALNFSVFYYE- fragment (PE16) on the 14-3-3ζ and SH2-domain on c-Src, whereas the 14-3-3ζ-integrin-β3 interaction is mediated by the -ESKVFYLKMKGDYYRYL- fragment (EL17) on the 14-3-3ζ and -KEATSTF- fragment (KF7) on the β3-integrin cytoplasmic tail. The EL17-motif inhibitor, or KF7 peptide, interferes with the formation of the 14-3-3ζ-c-Src-integrin-β3 complex and selectively inhibits β3 outside-in signaling without affecting the integrin-fibrinogen interaction, which suppresses thrombosis without causing significant bleeding. This study characterized a previously unidentified 14-3-3ζ-c-Src-integrin-β3 complex in platelets and provided a novel strategy for the development of safe and effective antithrombotic treatments.

Dissecting Role of Charged Residue from Transmembrane Domain 5 of Latent Membrane Protein 1 via In Silico Simulations and Wet-Lab Experiments

Charged residues are frequently found in the transmembrane segments of membrane proteins, which reside in the hydrophobic bilayer environment. Charged residues are critical for the function of membrane protein. However, studies of their role in protein oligomerization are limited. By taking the fifth transmembrane domain (TMD5) of latent membrane protein 1 from the Epstein-Barr virus as a prototype model, in silico simulations and wet-lab experiments were performed to investigate how the charged states affect transmembrane domain oligomerization. Molecular dynamics (MD) simulations showed that the D150-protonated TMD5 trimer was stable, whereas unprotonated D150 created bends in the helices which distort the trimeric structure. D150 was mutated to asparagine to mimic the protonated D150 in TMD5, and the MD simulations of different D150N TMD5 trimers supported that the protonation state of D150 was critical for the trimerization of TMD5. In silico mutations found that D150N TMD5 preferred to interact with TMD5 to form the heterotrimer (1 D150N TMD5:2 protonated TMD5s) rather than the heterotrimer (2 D150N TMD5s:1 protonated TMD5). D150R TMD5 interacted with TMD5 to form the heterotrimer (1 D150R TMD5:2 protonated TMD5). These in silico results imply that D150N TMD5 and D150R TMD5 peptides may be probes for disrupting TMD5 trimerization, which was supported by the dominant-negative ToxR assay in bacterial membranes. In all, this study elucidates the role of charged residues at the membrane milieu in membrane protein oligomerization and provides insight into the development of oligomerization-regulating peptides for modulating transmembrane domain lateral interactions.

Characteristics and therapeutic applications of antimicrobial peptides

The demand for novel antimicrobial compounds is rapidly growing due to the phenomenon of antibiotic resistance in bacteria. In response, numerous alternative approaches are being taken including use of polymers, metals, combinatorial approaches, and antimicrobial peptides (AMPs). AMPs are a naturally occurring part of the immune system of all higher organisms and display remarkable broad-spectrum activity and high selectivity for bacterial cells over host cells. However, despite good activity and safety profiles, AMPs have struggled to find success in the clinic. In this review, we outline the fundamental properties of AMPs that make them effective antimicrobials and extend this into three main approaches being used to help AMPs become viable clinical options. These three approaches are the incorporation of non-natural amino acids into the AMP sequence to impart better pharmacological properties, the incorporation of AMPs in hydrogels, and the chemical modification of surfaces with AMPs for device applications. These approaches are being developed to enhance the biocompatibility, stability, and/or bioavailability of AMPs as clinical options.

Using physical features of protein core packing to distinguish real proteins from decoys

The ability to consistently distinguish real protein structures from computationally generated model decoys is not yet a solved problem. One route to distinguish real protein structures from decoys is to delineate the important physical features that specify a real protein. For example, it has long been appreciated that the hydrophobic cores of proteins contribute significantly to their stability. We used two sources to obtain datasets of decoys to compare with real protein structures: submissions to the biennial Critical Assessment of protein Structure Prediction competition, in which researchers attempt to predict the structure of a protein only knowing its amino acid sequence, and also decoys generated by 3DRobot, which have user-specified global root-mean-squared deviations from experimentally determined structures. Our analysis revealed that both sets of decoys possess cores that do not recapitulate the key features that define real protein cores. In particular, the model structures appear more densely packed (because of energetically unfavorable atomic overlaps), contain too few residues in the core, and have improper distributions of hydrophobic residues throughout the structure. Based on these observations, we developed a feed-forward neural network, which incorporates key physical features of protein cores, to predict how well a computational model recapitulates the real protein structure without knowledge of the structure of the target sequence. By identifying the important features of protein structure, our method is able to rank decoy structures with similar accuracy to that obtained by state-of-the-art methods that incorporate many additional features. The small number of physical features makes our model interpretable, emphasizing the importance of protein packing and hydrophobicity in protein structure prediction.

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.

De novo protein design, a retrospective

Proteins are molecular machines whose function depends on their ability to achieve complex folds with precisely defined structural and dynamic properties. The rational design of proteins from first-principles, or de novo, was once considered to be impossible, but today proteins with a variety of folds and functions have been realized. We review the evolution of the field from its earliest days, placing particular emphasis on how this endeavor has illuminated our understanding of the principles underlying the folding and function of natural proteins, and is informing the design of macromolecules with unprecedented structures and properties. An initial set of milestones in de novo protein design focused on the construction of sequences that folded in water and membranes to adopt folded conformations. The first proteins were designed from first-principles using very simple physical models. As computers became more powerful, the use of the rotamer approximation allowed one to discover amino acid sequences that stabilize the desired fold. As the crystallographic database of protein structures expanded in subsequent years, it became possible to construct proteins by assembling short backbone fragments that frequently recur in Nature. The second set of milestones in de novo design involves the discovery of complex functions. Proteins have been designed to bind a variety of metals, porphyrins, and other cofactors. The design of proteins that catalyze hydrolysis and oxygen-dependent reactions has progressed significantly. However, de novo design of catalysts for energetically demanding reactions, or even proteins that bind with high affinity and specificity to highly functionalized complex polar molecules remains an importnant challenge that is now being achieved. Finally, the protein design contributed significantly to our understanding of membrane protein folding and transport of ions across membranes. The area of membrane protein design, or more generally of biomimetic polymers that function in mixed or non-aqueous environments, is now becoming increasingly possible.

ProDCoNN: Protein design using a convolutional neural network

Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this problem as predicting the residue type given the 3D structural environment around the C _α atom of a residue, which is repeated for each residue of a protein. We designed a nine-layer 3D deep convolutional neural network (CNN) that takes as input a gridded box with the atomic coordinates and types around a residue. Several CNN layers were designed to capture structure information at different scales, such as bond lengths, bond angles, torsion angles, and secondary structures. Trained on a very large number of protein structures, the method, called ProDCoNN (protein design with CNN), achieved state-of-the-art performance when tested on large numbers of test proteins and benchmark datasets.

Membrane receptor activation mechanisms and transmembrane peptide tools to elucidate them

Single-pass membrane receptors contain extracellular domains that respond to external stimuli and transmit information to intracellular domains through a single transmembrane (TM) α-helix. Because membrane receptors have various roles in homeostasis, signaling malfunctions of these receptors can cause disease. Despite their importance, there is still much to be understood mechanistically about how single-pass receptors are activated. In general, single-pass receptors respond to extracellular stimuli via alterations in their oligomeric state. The details of this process are still the focus of intense study, and several lines of evidence indicate that the TM domain (TMD) of the receptor plays a central role. We discuss three major mechanistic hypotheses for receptor activation: ligand-induced dimerization, ligand-induced rotation, and receptor clustering. Recent observations suggest that receptors can use a combination of these activation mechanisms and that technical limitations can bias interpretation. Short peptides derived from receptor TMDs, which can be identified by screening or rationally developed on the basis of the structure or sequence of their targets, have provided critical insights into receptor function. Here, we explore recent evidence that, depending on the target receptor, TMD peptides cannot only inhibit but also activate target receptors and can accommodate novel, bifunctional designs. Furthermore, we call for more sharing of negative results to inform the TMD peptide field, which is rapidly transforming into a suite of unique tools with the potential for future therapeutics.

PepBDB: a comprehensive structural database of biological peptide-protein interactions

Summary

A structural database of peptide-protein interactions is important for drug discovery targeting peptide-mediated interactions. Although some peptide databases, especially for special types of peptides, have been developed, a comprehensive database of cleaned peptide-protein complex structures is still not available. Such cleaned structures are valuable for docking and scoring studies in structure-based drug design. Here, we have developed PepBDB-a curated Peptide Binding DataBase of biological complex structures from the Protein Data Bank (PDB). PepBDB presents not only cleaned structures but also extensive information about biological peptide-protein interactions, and allows users to search the database with a variety of options and interactively visualize the search results.

Availability and implementation

PepBDB is available at http://huanglab.phys.hust.edu.cn/pepbdb/.

Packing of apolar side chains enables accurate design of highly stable membrane proteins

The features that stabilize the structures of membrane proteins remain poorly understood. Polar interactions contribute modestly, and the hydrophobic effect contributes little to the energetics of apolar side-chain packing in membranes. Disruption of steric packing can destabilize the native folds of membrane proteins, but is packing alone sufficient to drive folding in lipids? If so, then membrane proteins stabilized by this feature should be readily designed and structurally characterized-yet this has not been achieved. Through simulation of the natural protein phospholamban and redesign of variants, we define a steric packing code underlying its assembly. Synthetic membrane proteins designed using this code and stabilized entirely by apolar side chains conform to the intended fold. Although highly stable, the steric complementarity required for their folding is surprisingly stringent. Structural informatics shows that the designed packing motif recurs across the proteome, emphasizing a prominent role for precise apolar packing in membrane protein folding, stabilization, and evolution.

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.

Targeting trimeric transmembrane domain 5 of oncogenic latent membrane protein 1 using a computationally designed peptide

A peptide inhibitor was designed in silico and validated experimentally to disrupt homotrimeric transmembrane helix assembly.

Protein–protein interactions are involved in diverse biological processes. These interactions are therefore vital targets for drug development. However, the design of peptide modulators targeting membrane-based protein–protein interactions is a challenging goal owing to the lack of experimentally-determined structures and efficient protocols to probe their functions. Here we employed rational peptide design and molecular dynamics simulations to design a membrane-insertable peptide that disrupts the strong trimeric self-association of the fifth transmembrane domain (TMD5) of the oncogenic Epstein–Barr virus (EBV) latent membrane protein-1 (LMP-1). The designed anti-TMD5 peptide formed 1 : 2 heterotrimers with TMD5 in micelles and inhibited TMD5 oligomerization in bacterial membranes. Moreover, the designed peptide inhibited LMP-1 homotrimerization based on NF-κB activity in EVB positive lymphoma cells. The results indicated that the designed anti-TMD5 peptide may represent a promising starting point for elaboration of anti-EBV therapeutics via inhibition of LMP-1 oligomerization. To the best of our knowledge, this represents the first example of disrupting homotrimeric transmembrane helices using a designed peptide inhibitor.

Unique transmembrane domain interactions differentially modulate integrin αvβ3 and αIIbβ3 function

Lateral transmembrane (TM) helix-helix interactions between single-span membrane proteins play an important role in the assembly and signaling of many cell-surface receptors. Often, these helices contain two highly conserved yet distinct interaction motifs, arranged such that the motifs cannot be engaged simultaneously. However, there is sparse experimental evidence that dual-engagement mechanisms play a role in biological signaling. Here, we investigate the function of the two conserved interaction motifs in the TM domain of the integrin β3-subunit. The first motif uses reciprocating "large-large-small" amino acid packing to mediate the interaction of the β3 and αIIb TM domains and maintain the inactive resting conformation of the platelet integrin αIIbβ3. The second motif, S-x₃-A-x₃-I, is a variant of the classical "G-x₃-G" motif. Using site-directed mutagenesis, optical trap-based force spectroscopy, and molecular modeling, we show that S-x₃-A-x₃-I does not engage αIIb but rather mediates the interaction of the β3 TM domain with the TM domain of the αv-subunit of the integrin αvβ3. Like αIIbβ3, αvβ3 on circulating platelets is inactive, and in the absence of platelet stimulation is unable to interact with components of the subendothelial matrix. However, disrupting any residue in the β3 S-x₃-A-x₃-I motif by site-directed mutations is sufficient to induce αvβ3 binding to the αvβ3 ligand osteopontin and to the monoclonal antibody WOW-1. Thus, the β3-integrin TM domain is able to engage in two mutually exclusive interactions that produce alternate α-subunit pairing, creating two integrins with distinct biological functions.

Folding and Misfolding of Human Membrane Proteins in Health and Disease: From Single Molecules to Cellular Proteostasis

Advances over the past 25 years have revealed much about how the structural properties of membranes and associated proteins are linked to the thermodynamics and kinetics of membrane protein (MP) folding. At the same time biochemical progress has outlined how cellular proteostasis networks mediate MP folding and manage misfolding in the cell. When combined with results from genomic sequencing, these studies have established paradigms for how MP folding and misfolding are linked to the molecular etiologies of a variety of diseases. This emerging framework has paved the way for the development of a new class of small molecule "pharmacological chaperones" that bind to and stabilize misfolded MP variants, some of which are now in clinical use. In this review, we comprehensively outline current perspectives on the folding and misfolding of integral MPs as well as the mechanisms of cellular MP quality control. Based on these perspectives, we highlight new opportunities for innovations that bridge our molecular understanding of the energetics of MP folding with the nuanced complexity of biological systems. Given the many linkages between MP misfolding and human disease, we also examine some of the exciting opportunities to leverage these advances to address emerging challenges in the development of therapeutics and precision medicine.

Human LC3 and GABARAP subfamily members achieve functional specificity via specific structural modulations

Autophagy is a conserved adaptive cellular pathway essential to maintain a variety of physiological functions. Core components of this machinery are the six human Atg8 orthologs that initiate formation of appropriate protein complexes. While these proteins are routinely used as indicators of autophagic flux, it is presently not possible to discern their individual biological functions due to our inability to predict specific binding partners. In our attempts towards determining downstream effector functions, we developed a computational pipeline to define structural determinants of human Atg8 family members that dictate functional diversity. We found a clear evolutionary separation between human LC3 and GABARAP subfamilies and also defined a novel sequence motif responsible for their specificity. By analyzing known protein structures, we observed that functional modules or microclusters reveal a pattern of intramolecular network, including distinct hydrogen bonding of key residues (F52/Y49; a subset of HP2) that may directly modulate their interaction preferences. Multiple molecular dynamics simulations were performed to characterize how these proteins interact with a common protein binding partner, PLEKHM1. Our analysis showed remarkable differences in binding modes via intrinsic protein dynamics, with PLEKHM1-bound GABARAP complexes showing less fluctuations and higher number of contacts. We further mapped 373 genomic variations and demonstrated that distinct cancer-related mutations are likely to lead to significant structural changes. Our findings present a quantitative framework to establish factors underlying exquisite specificity of human Atg8 proteins, and thus facilitate the design of precise modulators.Abbreviations: Atg: autophagy-related; ECs: evolutionary constraints; GABARAP: GABA type A receptor-associated protein; HsAtg8: human Atg8; HP: hydrophobic pocket; KBTBD6: kelch repeat and BTB domain containing 6; LIR: LC3-interacting region; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MD: molecular dynamics; HIV-1 Nef: human immunodeficiency virus type 1 negative regulatory factor; PLEKHM1: pleckstrin homology and RUN domain containing M1; RMSD: root mean square deviation; SQSTM1/p62: sequestosome 1; WDFY3/ALFY: WD repeat and FYVE domain containing 3.

Peptide Nanomaterials Designed from Natural Supramolecular Systems

Natural supramolecular assemblies exhibit unique structural and functional properties that have been optimized over the course of evolution. Inspired by these natural systems, various bio-nanomaterials have been developed using peptides, proteins, and nucleic acids as components. Peptides are attractive building blocks because they enable the important domains of natural protein assemblies to be isolated and optimized while retaining the original structures and functions. Furthermore, the peptide subunits can be conjugated with exogenous molecules such as peptides, proteins, nucleic acids, and metal nanoparticles to generate advanced functions. In this personal account, we summarize recent progress in the construction of peptide-based nanomaterial designed from natural supramolecular systems, including (1) artificial viral capsids, (2) self-assembled nanofibers, and (3) protein-binding motifs. The peptides inspired by nature should provide new design principles for bio-nanomaterials.

Nach Is a Novel Subgroup at an Early Evolutionary Stage of the CNC-bZIP Subfamily Transcription Factors from the Marine Bacteria to Humans

Normal growth and development, as well as adaptive responses to various intracellular and environmental stresses, are tightly controlled by transcriptional networks. The evolutionarily conserved genomic sequences across species highlights the architecture of such certain regulatory elements. Among them, one of the most conserved transcription factors is the basic-region leucine zipper (bZIP) family. Herein, we have performed phylogenetic analysis of these bZIP proteins and found, to our surprise, that there exist a few homologous proteins of the family members Jun, Fos, ATF2, BATF, C/EBP and CNC (cap’n’collar) in either viruses or bacteria, albeit expansion and diversification of this bZIP superfamily have occurred in vertebrates from metazoan. Interestingly, a specific group of bZIP proteins is identified, designated Nach (Nrf and CNC homology), because of their strong conservation with all the known CNC and NF-E2 p45 subunit-related factors Nrf1 and Nrf2. Further experimental evidence has also been provided, revealing that Nach1 and Nach2 from the marine bacteria exert distinctive functions, when compared with human Nrf1 and Nrf2, in the transcriptional regulation of antioxidant response element (ARE)-battery genes. Collectively, further insights into these Nach/CNC-bZIP subfamily transcription factors provide a novel better understanding of distinct biological functions of these factors expressed in distinct species from the marine bacteria to humans.

Identifying the Coiled-Coil Triple Helix Structure of β-Peptide Nanofibers at Atomic Resolution

Peptide self-assembly represents a powerful bottom-up approach to the fabrication of nanomaterials. β³-Peptides are non-natural peptides composed entirely of β-amino acids, which have an extra methylene in the backbone, and we reported fibers derived from the self-assembly of β³-peptides that adopt 14-helical structures. β³-Peptide assemblies represent a class of stable nanomaterials that can be used to generate bio- and magneto-responsive materials with proteolytic stability. However, the three-dimensional structure of many of these materials remains unknown. To develop structure-based criteria for the design of β³-peptide-based biomaterials with tailored function, we investigated the structure of a tri-β³-peptide nanoassembly by molecular dynamics simulations and X-ray fiber diffraction analysis. Diffraction data was collected from aligned fibrils formed by Ac-β³[LIA] in water and used to inform and validate the model structure. Models with 3-fold radial symmetry resulted in stable fibers with a triple-helical coiled-coil motif and measurable helical pitch and periodicity. The fiber models revealed a hydrophobic core and twist along the fiber axis arising from a maximization of contacts between hydrophobic groups of adjacent tripeptides on the solvent-exposed fiber surface. These atomic structures of macroscale fibers derived from β³-peptide-based materials provide valuable insight into the effects of the geometric placement of the side chains and the influence of solvent on the core fiber structure which is perpetuated in the superstructure morphology.

Structure of the EmrE multidrug transporter and its use for inhibitor peptide design

Small multidrug resistance (SMR) pumps represent a minimal paradigm of proton-coupled membrane transport in bacteria, yet no high-resolution structure of an SMR protein is available. Here, atomic-resolution structures of the Escherichia coli efflux-multidrug resistance E (EmrE) multidrug transporter in ligand-bound form are refined using microsecond molecular dynamics simulations biased using low-resolution data from X-ray crystallography. The structures are compatible with existing mutagenesis data as well as NMR and biochemical experiments, including pKas of the catalytic glutamate residues and the dissociation constant ([Formula: see text]) of the tetraphenylphosphonium⁺ cation. The refined structures show the arrangement of residue side chains in the EmrE active site occupied by two different ligands and in the absence of a ligand, illustrating how EmrE can adopt structurally diverse active site configurations. The structures also show a stable, well-packed binding interface between the helices H4 of the two monomers, which is believed to be crucial for EmrE dimerization. Guided by the atomic details of this interface, we design proteolysis-resistant stapled peptides that bind to helix H4 of an EmrE monomer. The peptides are expected to interfere with the dimerization and thereby inhibit drug transport. Optimal positions of the peptide staple were determined using free-energy simulations of peptide binding to monomeric EmrE Three of the four top-scoring peptides selected for experimental testing resulted in significant inhibition of proton-driven ethidium efflux in live cells without nonspecific toxicity. The approach described here is expected to be of general use for the design of peptide therapeutics.

De novo designed transmembrane peptides activating the α5β1 integrin

Computationally designed transmembrane α-helical peptides (CHAMP) have been used to compete for helix-helix interactions within the membrane, enabling the ability to probe the activation of the integrins αIIbβ3 and αvβ3. Here, this method is extended towards the design of CHAMP peptides that inhibit the association of the α5β1 transmembrane (TM) domains, targeting the Ala-X3-Gly motif within α5. Our previous design algorithm was performed alongside a new workflow implemented within the widely used Rosetta molecular modeling suite. Peptides from each computational approach activated integrin α5β1 but not αVβ3 in human endothelial cells. Two CHAMP peptides were shown to directly associate with an α5 TM domain peptide in detergent micelles to a similar degree as a β1 TM peptide does. By solution-state nuclear magnetic resonance, one of these CHAMP peptides was shown to bind primarily the integrin β1 TM domain, which itself has a Gly-X3-Gly motif. The second peptide associated modestly with both α5 and β1 constructs, with slight preference for α5. Although the design goal was not fully realized, this work characterizes novel CHAMP peptides activating α5β1 that can serve as useful reagents for probing integrin biology.

Membrane-spanning α-helical barrels as tractable protein-design targets

The rational (de novo) design of membrane-spanning proteins lags behind that for water-soluble globular proteins. This is due to gaps in our knowledge of membrane-protein structure, and experimental difficulties in studying such proteins compared to water-soluble counterparts. One limiting factor is the small number of experimentally determined three-dimensional structures for transmembrane proteins. By contrast, many tens of thousands of globular protein structures provide a rich source of 'scaffolds' for protein design, and the means to garner sequence-to-structure relationships to guide the design process. The α-helical coiled coil is a protein-structure element found in both globular and membrane proteins, where it cements a variety of helix-helix interactions and helical bundles. Our deep understanding of coiled coils has enabled a large number of successful de novo designs. For one class, the α-helical barrels-that is, symmetric bundles of five or more helices with central accessible channels-there are both water-soluble and membrane-spanning examples. Recent computational designs of water-soluble α-helical barrels with five to seven helices have advanced the design field considerably. Here we identify and classify analogous and more complicated membrane-spanning α-helical barrels from the Protein Data Bank. These provide tantalizing but tractable targets for protein engineering and de novo protein design.This article is part of the themed issue 'Membrane pores: from structure and assembly, to medicine and technology'.

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'.

Computer-aided design of short peptide ligands targeting tumor necrosis factor-alpha for adsorbent applications

A peptide ligand (T1: Ac-RKEM-NH₂) designed by a computer-aided method can enhance TNF-α adsorption from the plasma of rats with sepsis to PVA.

Rational and Semirational Protein Design

This mini review gives an overview over different design approaches and methodologies applied in rational and semirational enzyme engineering. The underlying principles for engineering novel activities, enantioselectivity, substrate specificity, stability, and pH optimum are summarized.