Probing designability via a generalized model of helical bundle geometry

The myosin II coiled-coil domain atomic structure in its native environment

The atomic structure of the complete myosin tail within thick filaments isolated from Lethocerus indicus flight muscle is described and compared to crystal structures of recombinant, human cardiac myosin tail segments. Overall, the agreement is good with three exceptions: the proximal S2, in which the filament has heads attached but the crystal structure doesn't, and skip regions 2 and 4. At the head-tail junction, the tail α-helices are asymmetrically structured encompassing well-defined unfolding of 12 residues for one myosin tail, ∼4 residues of the other, and different degrees of α-helix unwinding for both tail α-helices, thereby providing an atomic resolution description of coiled-coil "uncoiling" at the head-tail junction. Asymmetry is observed in the nonhelical C termini; one C-terminal segment is intercalated between ribbons of myosin tails, the other apparently terminating at Skip 4 of another myosin tail. Between skip residues, crystal and filament structures agree well. Skips 1 and 3 also agree well and show the expected α-helix unwinding and coiled-coil untwisting in response to skip residue insertion. Skips 2 and 4 are different. Skip 2 is accommodated in an unusual manner through an increase in α-helix radius and corresponding reduction in rise/residue. Skip 4 remains helical in one chain, with the other chain unfolded, apparently influenced by the acidic myosin C terminus. The atomic model may shed some light on thick filament mechanosensing and is a step in understanding the complex roles that thick filaments of all species undergo during muscle contraction.

A library of coiled-coil domains: from regular bundles to peculiar twists

MOTIVATION

Coiled coils are widespread protein domains involved in diverse processes ranging from providing structural rigidity to the transduction of conformational changes. They comprise two or more α-helices that are wound around each other to form a regular supercoiled bundle. Owing to this regularity, coiled-coil structures can be described with parametric equations, thus enabling the numerical representation of their properties, such as the degree and handedness of supercoiling, rotational state of the helices, and the offset between them. These descriptors are invaluable in understanding the function of coiled coils and designing new structures of this type. The existing tools for such calculations require manual preparation of input and are therefore not suitable for the high-throughput analyses.

RESULTS

To address this problem, we developed SamCC-Turbo, a software for fully automated, per-residue measurement of coiled coils. By surveying Protein Data Bank with SamCC-Turbo, we generated a comprehensive atlas of ∼50 000 coiled-coil regions. This machine learning-ready dataset features precise measurements as well as decomposes coiled-coil structures into fragments characterized by various degrees of supercoiling. The potential applications of SamCC-Turbo are exemplified by analyses in which we reveal general structural features of coiled coils involved in functions requiring conformational plasticity. Finally, we discuss further directions in the prediction and modeling of coiled coils.

AVAILABILITY AND IMPLEMENTATION

SamCC-Turbo is available as a web server (https://lbs.cent.uw.edu.pl/samcc_turbo) and as a Python library (https://github.com/labstructbioinf/samcc_turbo), whereas the results of the Protein Data Bank scan can be browsed and downloaded at https://lbs.cent.uw.edu.pl/ccdb.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Acyl Transfer Catalytic Activity in De Novo Designed Protein with N-Terminus of α-Helix As Oxyanion-Binding Site

The design of catalytic proteins with functional sites capable of specific chemistry is gaining momentum and a number of artificial enzymes have recently been reported, including hydrolases, oxidoreductases, retro-aldolases, and others. Our goal is to develop a peptide ligase for robust catalysis of amide bond formation that possesses no stringent restrictions to the amino acid composition at the ligation junction. We report here the successful completion of the first step in this long-term project by building a completely de novo protein with predefined acyl transfer catalytic activity. We applied a minimalist approach to rationally design an oxyanion hole within a small cavity that contains an adjacent thiol nucleophile. The N-terminus of the α-helix with unpaired hydrogen-bond donors was exploited as a structural motif to stabilize negatively charged tetrahedral intermediates in nucleophilic addition-elimination reactions at the acyl group. Cysteine acting as a principal catalytic residue was introduced at the second residue position of the α-helix N-terminus in a designed three-α-helix protein based on structural informatics prediction. We showed that this minimal set of functional elements is sufficient for the emergence of catalytic activity in a de novo protein. Using peptide-αthioesters as acyl-donors, we demonstrated their catalyzed amidation concomitant with hydrolysis and proved that the environment at the catalytic site critically influences the reaction outcome. These results represent a promising starting point for the development of efficient catalysts for protein labeling, conjugation, and peptide ligation.

Structural resolution of switchable states of a de novo peptide assembly

De novo protein design is advancing rapidly. However, most designs are for single states. Here we report a de novo designed peptide that forms multiple α-helical-bundle states that are accessible and interconvertible under the same conditions. Usually in such designs amphipathic α helices associate to form compact structures with consolidated hydrophobic cores. However, recent rational and computational designs have delivered open α-helical barrels with functionalisable cavities. By placing glycine judiciously in the helical interfaces of an α-helical barrel, we obtain both open and compact states in a single protein crystal. Molecular dynamics simulations indicate a free-energy landscape with multiple and interconverting states. Together, these findings suggest a frustrated system in which steric interactions that maintain the open barrel and the hydrophobic effect that drives complete collapse are traded-off. Indeed, addition of a hydrophobic co-solvent that can bind within the barrel affects the switch between the states both in silico and experimentally.

So far most of the de novo designed proteins are for single states only. Here, the authors present the de novo design and crystal structure determination of a coiled-coil peptide that assembles into multiple, distinct conformational states under the same conditions and further characterise its properties with biophysical experiments, NMR and MD simulations.

Structural characterization of the self-association domain of swallow

Swallow, a 62 kDa multidomain protein, is required for the proper localization of several mRNAs involved in the development of Drosophila oocytes. The dimerization of Swallow depends on a 71-residue self-association domain in the center of the protein sequence, and is significantly stabilized by a binding interaction with dynein light chain (LC8). Here, we detail the use of solution-state nuclear magnetic resonance spectroscopy to characterize the structure of this self-association domain, thereby establishing that this domain forms a parallel coiled-coil and providing insight into how the stability of the dimerization interaction is regulated.

Large-Amplitude Conformational Changes in Self-Assembled Multi-Stranded Aromatic Sheets

The orchestration of ever larger conformational changes is made possible by the development of increasingly complex foldamers. Aromatic sheets, a rare motif in synthetic foldamer structures, have been designed so as to form discrete stacks of intercalated aromatic strands through the self‐assembly of two identical subunits. Ion‐mobility ESI‐MS confirms the formation of compact dimers. X‐ray crystallography reveals the existence of two distinct conformational dimeric states that require large changes to interconvert. Molecular dynamics simulation validates the stability of the two conformations and the possibility of their interconversion.

Allosteric cooperation in a de novo-designed two-domain protein

We describe the de novo design of an allosterically regulated protein, which comprises two tightly coupled domains. One domain is based on the DF (Due Ferri in Italian or two-iron in English) family of de novo proteins, which have a diiron cofactor that catalyzes a phenol oxidase reaction, while the second domain is based on PS1 (Porphyrin-binding Sequence), which binds a synthetic Zn-porphyrin (ZnP). The binding of ZnP to the original PS1 protein induces changes in structure and dynamics, which we expected to influence the catalytic rate of a fused DF domain when appropriately coupled. Both DF and PS1 are four-helix bundles, but they have distinct bundle architectures. To achieve tight coupling between the domains, they were connected by four helical linkers using a computational method to discover the most designable connections capable of spanning the two architectures. The resulting protein, DFP1 (Due Ferri Porphyrin), bound the two cofactors in the expected manner. The crystal structure of fully reconstituted DFP1 was also in excellent agreement with the design, and it showed the ZnP cofactor bound over 12 Å from the dimetal center. Next, a substrate-binding cleft leading to the diiron center was introduced into DFP1. The resulting protein acts as an allosterically modulated phenol oxidase. Its Michaelis-Menten parameters were strongly affected by the binding of ZnP, resulting in a fourfold tighter Km and a 7-fold decrease in kcat These studies establish the feasibility of designing allosterically regulated catalytic proteins, entirely from scratch.

Toward complete rational control over protein structure and function through computational design

The grand challenge of protein design is a general method for producing a polypeptide with arbitrary functionality, conformation, and biochemical properties. To that end, a wide variety of methods have been developed for the improvement of native proteins, the design of ideal proteins de novo, and the redesign of suboptimal proteins with better-performing substructures. These methods employ informatic comparisons of function-structure-sequence relationships as well as knowledge-based evaluation of protein properties to narrow the immense protein sequence search space down to an enumerable and often manually evaluable set of structures that meet specified criteria. While arbitrary manipulation of protein-protein interfaces and molecular catalysis remains an unsolved problem, and no protein shape or behavior manipulation algorithm is universally applicable, the promising results thus far are a strong indicator that a general approach to the arbitrary manipulation of polypeptides is within reach.

Structural intermediates in the low pH-induced transition of influenza hemagglutinin

The hemagglutinin (HA) glycoproteins of influenza viruses play a key role in binding host cell receptors and in mediating virus-host cell membrane fusion during virus infection. Upon virus entry, HA is triggered by low pH and undergoes large structural rearrangements from a prefusion state to a postfusion state. While structures of prefusion state and postfusion state of HA have been reported, the intermediate structures remain elusive. Here, we report two distinct low pH intermediate conformations of the influenza virus HA using cryo-electron microscopy (cryo-EM). Our results show that a decrease in pH from 7.8 to 5.2 triggers the release of fusion peptides from the binding pockets and then causes a dramatic conformational change in the central helices, in which the membrane-proximal ends of the central helices unwind to an extended form. Accompanying the conformational changes of the central helices, the stem region of the HA undergoes an anticlockwise rotation of 9.5 degrees and a shift of 15 Å. The HA head, after being stabilized by an antibody, remains unchanged compared to the neutral pH state. Thus, the conformational change of the HA stem region observed in our research is likely to be independent of the HA head. These results provide new insights into the structural transition of HA during virus entry.

RamaNet: Computational de novo helical protein backbone design using a long short-term memory generative neural network

The ability to perform de novo protein design will allow researchers to expand the variety of available proteins. By designing synthetic structures computationally, they can utilise more structures than those available in the Protein Data Bank, design structures that are not found in nature, or direct the design of proteins to acquire a specific desired structure. While some researchers attempt to design proteins from first physical and thermodynamic principals, we decided to attempt to test whether it is possible to perform de novo helical protein design of just the backbone statistically using machine learning by building a model that uses a long short-term memory (LSTM) architecture. The LSTM model used only the φ and ψ angles of each residue from an augmented dataset of only helical protein structures. Though the network’s generated backbone structures were not perfect, they were idealised and evaluated post generation where the non-ideal structures were filtered out and the adequate structures kept. The results were successful in developing a logical, rigid, compact, helical protein backbone topology. This paper is a proof of concept that shows it is possible to generate a novel helical backbone topology using an LSTM neural network architecture using only the φ and ψ angles as features. The next step is to attempt to use these backbone topologies and sequence design them to form complete protein structures.

An enumerative algorithm for de novo design of proteins with diverse pocket structures

To create new enzymes and biosensors from scratch, precise control over the structure of small-molecule binding sites is of paramount importance, but systematically designing arbitrary protein pocket shapes and sizes remains an outstanding challenge. Using the NTF2-like structural superfamily as a model system, we developed an enumerative algorithm for creating a virtually unlimited number of de novo proteins supporting diverse pocket structures. The enumerative algorithm was tested and refined through feedback from two rounds of large-scale experimental testing, involving in total the assembly of synthetic genes encoding 7,896 designs and assessment of their stability on yeast cell surface, detailed biophysical characterization of 64 designs, and crystal structures of 5 designs. The refined algorithm generates proteins that remain folded at high temperatures and exhibit more pocket diversity than naturally occurring NTF2-like proteins. We expect this approach to transform the design of small-molecule sensors and enzymes by enabling the creation of binding and active site geometries much more optimal for specific design challenges than is accessible by repurposing the limited number of naturally occurring NTF2-like proteins.

A defined structural unit enables de novo design of small-molecule-binding proteins

The de novo design of proteins that bind highly functionalized small molecules represents a great challenge. To enable computational design of binders, we developed a unit of protein structure-a van der Mer (vdM)-that maps the backbone of each amino acid to statistically preferred positions of interacting chemical groups. Using vdMs, we designed six de novo proteins to bind the drug apixaban; two bound with low and submicromolar affinity. X-ray crystallography and mutagenesis confirmed a structure with a precisely designed cavity that forms favorable interactions in the drug-protein complex. vdMs may enable design of functional proteins for applications in sensing, medicine, and catalysis.

Computational design of transmembrane pores

Protein pores play key roles in fundamental biological processes¹ and biotechnological applications such as DNA nanopore sequencing^2–4, and hence the design of pore-containing proteins is of considerable scientific and biotechnological interest. Synthetic amphiphilic peptides have been found to form ion channels^5,6, and there have been recent advances in de novo membrane protein design^7,8 and in redesigning naturally occurring channel-containing proteins^9,10. However, the de novo design of stable, well-defined transmembrane protein pores capable of conducting ions selectively or large enough to allow passage of small-molecule fluorophores remains an outstanding challenge^11,12. Here, we report the computational design of protein pores formed by two concentric rings of ɑ-helices that are stable and mono-disperse in both water-soluble and transmembrane forms. Crystal structures of the water-soluble forms of a 12 helical and a 16 helical pore are close to the computational design models. Patch-clamp electrophysiology experiments show that the transmembrane form of the 12-helix pore expressed in insect cells allows passage of ions across the membrane with high selectivity for potassium over sodium, which is blocked by specific chemical modification at the pore entrance. The transmembrane form of the 16-helix pore, but not the 12-helix pore, allows passage of biotinylated Alexa Fluor 488 when incorporated into liposomes using in vitro protein synthesis. A cryo-EM structure of the 16-helix transmembrane pore closely matches the design model. The ability to produce structurally and functionally well-defined transmembrane pores opens the door to the creation of designer pores for a wide variety of applications.

Pair Potentials as Machine Learning Features

Atom pairwise potential functions make up an essential part of many scoring functions for protein decoy detection. With the development of machine learning (ML) tools, there are multiple ways to combine potential functions to create novel ML models and methods. Potential function parameters can be easily extracted; however, it is usually hard to directly obtain the calculated atom pairwise energies from scoring functions. Amber, as one of the most popular suites of modeling programs, has an extensive history and library of force field potential functions. In this work, we directly used the force field parameters in ff94 and ff14SB from Amber and encoded them to calculate atom pairwise energies for different interactions. Two sets of structures (single amino acid set and a dipeptide set) were used to evaluate the performance of our encoded Amber potentials. From the comparison results between energy terms obtained from our encoding and Amber, we find energy difference within ±0.06 kcal/mol for all tested structures. Previously we have shown that the Random Forest (RF) model can help to emphasize more important atom pairwise interactions and ignore insignificant ones [Pei, J.; Zheng, Z.; Merz, K. M. J. Chem. Inf. Model. 2019, 59, 1919-1929]. Here, as an example of combining ML methods with traditional potential functions, we followed the same work flow to combine the RF models with force field potential functions from Amber. To determine the performance of our RF models with force field potential functions, 224 different protein native-decoy systems were used as our training and testing sets We find that the RF models with ff94 and ff14SB force field parameters outperformed all other scoring functions (RF models with KECSA2, RWplus, DFIRE, dDFIRE, and GOAP) considered in this work for native structure detection, and they performed similarly in detecting the best decoy. Through inclusion of best decoy to decoy comparisons in building our RF models, we were able to generate models that outperformed the score functions tested herein both on accuracy and best decoy detection, again showing the performance and flexibility of our RF models to tackle this problem. Finally, the importance of the RF algorithm and force field parameters were also tested and the comparison results suggest that both the RF algorithm and force field potentials are important with the ML scoring function achieving its best performance only by combining them together. All code and data used in this work are available at https://github.com/JunPei000/FFENCODER_for_Protein_Folding_Pose_Selection.

Molecular assemblies built with the artificial protein Pizza

Recently an artificial protein named Pizza6 was reported, which possesses six identical tandem repeats and adopts a monomeric β -propeller fold with sixfold structural symmetry. Pizza2, a truncated form that consists of a double tandem repeat, self-assembles into a trimer reconstructing the same propeller architecture as Pizza6. The ability of pizza proteins to self-assemble to form complete propellers makes them interesting building blocks to engineer larger symmetrical protein complexes such as symmetric nanoparticles. Here we have explored the self-assembly of Pizza2 fused to homo-oligomerizing peptides. In total, we engineered five different fusion proteins, of which three appeared to assemble successfully into larger complexes. Further characterization of these proteins showed one monodisperse designer protein with a structure close to the intended design. This protein was further fused to eGFP to investigate functionalization of the nanoparticle. The fusion protein was stable and could be expressed in high yield, showing that Pizza-based nanoparticles may be further decorated with functional domains.

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.

Parallel Homochiral and Anti-Parallel Heterochiral Hydrogen-Bonding Interfaces in Multi-Helical Abiotic Foldamers

A hydrogen-bonding interface between helical aromatic oligoamide foldamers has been designed to promote the folding of a helix-turn-helix motif with a head-to-tail arrangement of two helices of opposite handedness. This design complements an earlier helix-turn-helix motif with a head-to-head arrangement of two helices of identical handedness interface. The two motifs were shown to have comparable stability and were combined in a unimolecular tetra-helix fold constituting the largest abiotic tertiary structure to date.

Bent Into Shape: Folded Peptides to Mimic Protein Structure and Modulate Protein Function

Protein secondary and tertiary structure mimics have served as model systems to probe biophysical parameters that guide protein folding and as attractive reagents to modulate protein interactions. Here we review contemporary methods to reproduce loop, helix, sheet and coiled-coil conformations in short peptides.

De novo design of tunable, pH-driven conformational changes

The ability of naturally occurring proteins to change conformation in response to environmental changes is critical to biological function. Although there have been advances in the de novo design of stable proteins with a single, deep free-energy minimum, the design of conformational switches remains challenging. We present a general strategy to design pH-responsive protein conformational changes by precisely preorganizing histidine residues in buried hydrogen-bond networks. We design homotrimers and heterodimers that are stable above pH 6.5 but undergo cooperative, large-scale conformational changes when the pH is lowered and electrostatic and steric repulsion builds up as the network histidine residues become protonated. The transition pH and cooperativity can be controlled through the number of histidine-containing networks and the strength of the surrounding hydrophobic interactions. Upon disassembly, the designed proteins disrupt lipid membranes both in vitro and after being endocytosed in mammalian cells. Our results demonstrate that environmentally triggered conformational changes can now be programmed by de novo protein design.

Applying graph theory to protein structures: an Atlas of coiled coils

Motivation

To understand protein structure, folding and function fully and to design proteins de novo reliably, we must learn from natural protein structures that have been characterized experimentally. The number of protein structures available is large and growing exponentially, which makes this task challenging. Indeed, computational resources are becoming increasingly important for classifying and analyzing this resource. Here, we use tools from graph theory to define an Atlas classification scheme for automatically categorizing certain protein substructures.

Results

Focusing on the α-helical coiled coils, which are ubiquitous protein-structure and protein-protein interaction motifs, we present a suite of computational resources designed for analyzing these assemblies. iSOCKET enables interactive analysis of side-chain packing within proteins to identify coiled coils automatically and with considerable user control. Applying a graph theory-based Atlas classification scheme to structures identified by iSOCKET gives the Atlas of Coiled Coils, a fully automated, updated overview of extant coiled coils. The utility of this approach is illustrated with the first formal classification of an emerging subclass of coiled coils called α-helical barrels. Furthermore, in the Atlas, the known coiled-coil universe is presented alongside a partial enumeration of the 'dark matter' of coiled-coil structures; i.e. those coiled-coil architectures that are theoretically possible but have not been observed to date, and thus present defined targets for protein design.

Availability and implementation

iSOCKET is available as part of the open-source GitHub repository associated with this work (https://github.com/woolfson-group/isocket). This repository also contains all the data generated when classifying the protein graphs. The Atlas of Coiled Coils is available at: http://coiledcoils.chm.bris.ac.uk/atlas/app.

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.

De novo design of bioactive protein switches

Allosteric regulation of protein function is widespread in biology, but is challenging for de novo protein design as it requires the explicit design of multiple states with comparable free energies. Here we explore the possibility of designing switchable protein systems de novo, through the modulation of competing inter- and intramolecular interactions. We design a static, five-helix 'cage' with a single interface that can interact either intramolecularly with a terminal 'latch' helix or intermolecularly with a peptide 'key'. Encoded on the latch are functional motifs for binding, degradation or nuclear export that function only when the key displaces the latch from the cage. We describe orthogonal cage-key systems that function in vitro, in yeast and in mammalian cells with up to 40-fold activation of function by key. The ability to design switchable protein functions that are controlled by induced conformational change is a milestone for de novo protein design, and opens up new avenues for synthetic biology and cell engineering.

Navigating the Structural Landscape of De Novo α-Helical Bundles

The association of amphipathic α helices in water leads to α-helical-bundle protein structures. However, the driving force for this-the hydrophobic effect-is not specific and does not define the number or the orientation of helices in the associated state. Rather, this is achieved through deeper sequence-to-structure relationships, which are increasingly being discerned. For example, for one structurally extreme but nevertheless ubiquitous class of bundle-the α-helical coiled coils-relationships have been established that discriminate between all-parallel dimers, trimers, and tetramers. Association states above this are known, as are antiparallel and mixed arrangements of the helices. However, these alternative states are less well understood. Here, we describe a synthetic-peptide system that switches between parallel hexamers and various up-down-up-down tetramers in response to single-amino-acid changes and solution conditions. The main accessible states of each peptide variant are characterized fully in solution and, in most cases, to high resolution with X-ray crystal structures. Analysis and inspection of these structures helps rationalize the different states formed. This navigation of the structural landscape of α-helical coiled coils above the dimers and trimers that dominate in nature has allowed us to design rationally a well-defined and hyperstable antiparallel coiled-coil tetramer (apCC-Tet). This robust de novo protein provides another scaffold for further structural and functional designs in protein engineering and synthetic biology.

A Conserved Basic Patch and Central Kink in the Nipah Virus Phosphoprotein Multimerization Domain Are Essential for Polymerase Function

Nipah virus is a highly lethal zoonotic pathogen found in Southeast Asia that has caused human encephalitis outbreaks with 40%-70% mortality. NiV encodes its own RNA-dependent RNA polymerase within the large protein, L. Efficient polymerase activity requires the phosphoprotein, P, which tethers L to its template, the viral nucleocapsid. P is a multifunctional protein with modular domains. The central P multimerization domain is composed of a long, tetrameric coiled coil. We investigated the importance of structural features found in this domain for polymerase function using a newly constructed NiV bicistronic minigenome assay. We identified a conserved basic patch and central kink in the coiled coil that are important for polymerase function, with R555 being absolutely essential. This basic patch and central kink are conserved in the related human pathogens measles and mumps viruses, suggesting that this mechanism may be conserved.

A Hendecad Motif Is Preferred for Heterochiral Coiled-Coil Formation

The structural principles that govern interactions between l- and d-peptides are not well understood. Among natural proteins, coiled-coil assemblies formed between or among α-helices are the most regular feature of tertiary and quaternary structures. We recently reported the first high-resolution structures for heterochiral coiled-coil dimers, which represent a starting point for understanding associations of l- and d-polypeptides. These structures were an unexpected outcome from crystallization of a racemic peptide corresponding to the transmembrane domain of the influenza A M2 protein (M2-TM). The reported structures raised the possibility that heterochiral coiled-coil dimers prefer an 11-residue (hendecad) sequence repeat, in contrast to the 7-residue (heptad) sequence repeat that is dominant among natural coiled coils. To gain insight on sequence repeat preferences of heterochiral coiled-coils, we have examined three M2-TM variants containing substitutions intended to minimize steric clashes between side chains at the coiled-coil interface. In each of the three new crystal structures, we observed heterochiral coiled-coil associations that closely match a hendecad sequence motif, which strengthens the conclusion that this motif is intrinsic to the pairing of α-helices with opposite handedness. In each case, the presence of a hendecad motif was established by comparing the observed helical frequency to that of an ideal hendecad. This comparison revealed that decreasing the size of the amino acid side chain at positions that project toward the superhelical axis produces tighter packing, as determined by the size of the coiled-coil radius. These results provide a basis for future design of heterochiral coiled-coil pairings.

DeepCoil—a fast and accurate prediction of coiled-coil domains in protein sequences

Motivation

Coiled coils are protein structural domains that mediate a plethora of biological interactions, and thus their reliable annotation is crucial for studies of protein structure and function.

Results

Here, we report DeepCoil, a new neural network-based tool for the detection of coiled-coil domains in protein sequences. In our benchmarks, DeepCoil significantly outperformed current state-of-the-art tools, such as PCOILS and Marcoil, both in the prediction of canonical and non-canonical coiled coils. Furthermore, in a scan of the human genome with DeepCoil, we detected many coiled-coil domains that remained undetected by other methods. This higher sensitivity of DeepCoil should make it a method of choice for accurate genome-wide detection of coiled-coil domains.

Availability and implementation

DeepCoil is written in Python and utilizes the Keras machine learning library. A web server is freely available at https://toolkit.tuebingen.mpg.de/#/tools/deepcoil and a standalone version can be downloaded at https://github.com/labstructbioinf/DeepCoil.

Supplementary information

Supplementary data are available at Bioinformatics online.

Programmable design of orthogonal protein heterodimers

Specificity of interactions between two DNA strands, or between protein and DNA, is often achieved by varying bases or side chains coming off the DNA or protein backbone-for example, the bases participating in Watson-Crick pairing in the double helix, or the side chains contacting DNA in TALEN-DNA complexes. By contrast, specificity of protein-protein interactions usually involves backbone shape complementarity¹, which is less modular and hence harder to generalize. Coiled-coil heterodimers are an exception, but the restricted geometry of interactions across the heterodimer interface (primarily at the heptad a and d positions²) limits the number of orthogonal pairs that can be created simply by varying side-chain interactions^3,4. Here we show that protein-protein interaction specificity can be achieved using extensive and modular side-chain hydrogen-bond networks. We used the Crick generating equations⁵ to produce millions of four-helix backbones with varying degrees of supercoiling around a central axis, identified those accommodating extensive hydrogen-bond networks, and used Rosetta to connect pairs of helices with short loops and to optimize the remainder of the sequence. Of 97 such designs expressed in Escherichia coli, 65 formed constitutive heterodimers, and the crystal structures of four designs were in close agreement with the computational models and confirmed the designed hydrogen-bond networks. In cells, six heterodimers were fully orthogonal, and in vitro-following mixing of 32 chains from 16 heterodimer designs, denaturation in 5 M guanidine hydrochloride and reannealing-almost all of the interactions observed by native mass spectrometry were between the designed cognate pairs. The ability to design orthogonal protein heterodimers should enable sophisticated protein-based control logic for synthetic biology, and illustrates that nature has not fully explored the possibilities for programmable biomolecular interaction modalities.

Maintaining and breaking symmetry in homomeric coiled-coil assemblies

In coiled-coil (CC) protein structures α-helices wrap around one another to form rope-like assemblies. Most natural and designed CCs have two–four helices and cyclic (C_n) or dihedral (D_n) symmetry. Increasingly, CCs with five or more helices are being reported. A subset of these higher-order CCs is of interest as they have accessible central channels that can be functionalised; they are α-helical barrels. These extended cavities are surprising given the drive to maximise buried hydrophobic surfaces during protein folding and assembly in water. Here, we show that α-helical barrels can be maintained by the strategic placement of β-branched aliphatic residues lining the lumen. Otherwise, the structures collapse or adjust to give more-complex multi-helix assemblies without C_n or D_n symmetry. Nonetheless, the structural hallmark of CCs—namely, knobs-into-holes packing of side chains between helices—is maintained leading to classes of CCs hitherto unobserved in nature or accessed by design.

Higher order coiled coils with five or more helices can form α-helical barrels. Here the authors show that placing β-branched aliphatic residues along the lumen yields stable and open α-helical barrels, which is of interest for the rational design of functional proteins; whereas, the absence of β-branched side chains leads to unusual low-symmetry α-helical bundles.

Spectroscopic and metal binding properties of a de novo metalloprotein binding a tetrazinc cluster

De novo design provides an attractive approach, which allows one to test and refine the principles guiding metalloproteins in defining the geometry and reactivity of their metal ion cofactors. Although impressive progress has been made in designing proteins that bind transition metal ions including iron-sulfur clusters, the design of tetranuclear clusters with oxygen-rich environments remains in its infancy. In previous work, we described the design of homotetrameric four-helix bundles that bind tetra-Zn2+ clusters. The crystal structures of the helical proteins were in good agreement with the overall design, and the metal-binding and conformational properties of the helical bundles in solution were consistent with the crystal structures. However, the corresponding apo-proteins were not fully folded in solution. In this work, we design three peptides, based on the crystal structure of the original bundles. One of the peptides forms tetramers in aqueous solution in the absence of metal ions as assessed by CD and NMR. It also binds Zn2+ in the intended stoichiometry. These studies strongly suggest that the desired structure has been achieved in the apo state, providing evidence that the peptide is able to actively impart the designed geometry to the metal cluster.

De Novo-Designed α-Helical Barrels as Receptors for Small Molecules

We describe de novo-designed α-helical barrels (αHBs) that bind and discriminate between lipophilic biologically active molecules. αHBs have five or more α-helices arranged around central hydrophobic channels the diameters of which scale with oligomer state. We show that pentameric, hexameric, and heptameric αHBs bind the environmentally sensitive dye 1,6-diphenylhexatriene (DPH) in the micromolar range and fluoresce. Displacement of the dye is used to report the binding of nonfluorescent molecules: palmitic acid and retinol bind to all three αHBs with submicromolar inhibitor constants; farnesol binds the hexamer and heptamer; but β-carotene binds only the heptamer. A co-crystal structure of the hexamer with farnesol reveals oriented binding in the center of the hydrophobic channel. Charged side chains engineered into the lumen of the heptamer facilitate binding of polar ligands: a glutamate variant binds a cationic variant of DPH, and introducing lysine allows binding of the biosynthetically important farnesol diphosphate.

Self-assembly and soluble aggregate behavior of computationally designed coiled-coil peptide bundles

Coiled-coil peptides have proven useful in a range of materials applications ranging from the formation of well-defined fibrils to responsive hydrogels. The ability to design from first principles their oligomerization and subsequent higher order assembly offers their expanded use in producing new materials. Toward these ends, homo-tetrameric, antiparallel, coiled-coil, peptide bundles have been designed computationally, synthesized via solid-phase methods, and their solution behavior characterized. Two different bundle-forming peptides were designed and examined. Within the targeted coiled coil structure, both bundles contained the same hydrophobic core residues. However, different exterior residues on the two different designs yielded sequences with different distributions of charged residues and two different expected isoelectric points of pI 4.4 and pI 10.5. Both coiled-coil bundles were extremely stable with respect to temperature (Tm > 80 C) and remained soluble in solution even at high (millimolar) peptide concentrations. The coiled-coil tetramer was confirmed to be the dominant species in solution by analytical sedimentation studies and by small-angle neutron scattering, where the scattering form factor is well represented by a cylinder model with the dimensions of the targeted coiled coil. At high concentrations (5-15 mM), evidence of interbundle structure was observed via neutron scattering. At these concentrations, the synthetic bundles form soluble aggregates, and interbundle distances can be determined via a structure factor fit to scattering data. The data support the successful design of robust coiled-coil bundles. Despite their different sequences, each sequence forms loosely associated but soluble aggregates of the bundles, suggesting similar dissociated states for each. The behavior of the dispersed bundles is similar to that observed for natural proteins.

ISAMBARD: an open-source computational environment for biomolecular analysis, modelling and design

Motivation

The rational design of biomolecules is becoming a reality. However, further computational tools are needed to facilitate and accelerate this, and to make it accessible to more users.

Results

Here we introduce ISAMBARD, a tool for structural analysis, model building and rational design of biomolecules. ISAMBARD is open-source, modular, computationally scalable and intuitive to use. These features allow non-experts to explore biomolecular design in silico. ISAMBARD addresses a standing issue in protein design, namely, how to introduce backbone variability in a controlled manner. This is achieved through the generalization of tools for parametric modelling, describing the overall shape of proteins geometrically, and without input from experimentally determined structures. This will allow backbone conformations for entire folds and assemblies not observed in nature to be generated de novo, that is, to access the ‘dark matter of protein-fold space’. We anticipate that ISAMBARD will find broad applications in biomolecular design, biotechnology and synthetic biology.

Availability and implementation

A current stable build can be downloaded from the python package index (https://pypi.python.org/pypi/isambard/) with development builds available on GitHub (https://github.com/woolfson-group/) along with documentation, tutorial material and all the scripts used to generate the data described in this paper.

Supplementary information

Supplementary data are available at Bioinformatics online.

Creation of artificial protein-protein interactions using α-helices as interfaces

Designing novel protein-protein interactions (PPIs) with high affinity is a challenging task. Directed evolution, a combination of randomization of the gene for the protein of interest and selection using a display technique, is one of the most powerful tools for producing a protein binder. However, the selected proteins often bind to the target protein at an undesired surface. More problematically, some selected proteins bind to their targets even though they are unfolded. Current state-of-the-art computational design methods have successfully created novel protein binders. These computational methods have optimized the non-covalent interactions at interfaces and thus produced artificial protein complexes. However, to date there are only a limited number of successful examples of computationally designed de novo PPIs. De novo design of coiled-coil proteins has been extensively performed and, therefore, a large amount of knowledge of the sequence-structure relationship of coiled-coil proteins has been accumulated. Taking advantage of this knowledge, de novo design of inter-helical interactions has been used to produce artificial PPIs. Here, we review recent progress in the in silico design and rational design of de novo PPIs and the use of α-helices as interfaces.

De novo synthetic biliprotein design, assembly and excitation energy transfer

Bilins are linear tetrapyrrole chromophores with a wide range of visible and near-visible light absorption and emission properties. These properties are tuned upon binding to natural proteins and exploited in photosynthetic light-harvesting and non-photosynthetic light-sensitive signalling. These pigmented proteins are now being manipulated to develop fluorescent experimental tools. To engineer the optical properties of bound bilins for specific applications more flexibly, we have used first principles of protein folding to design novel, stable and highly adaptable bilin-binding four-α-helix bundle protein frames, called maquettes, and explored the minimal requirements underlying covalent bilin ligation and conformational restriction responsible for the strong and variable absorption, fluorescence and excitation energy transfer of these proteins. Biliverdin, phycocyanobilin and phycoerythrobilin bind covalently to maquette Cys in vitro A blue-shifted tripyrrole formed from maquette-bound phycocyanobilin displays a quantum yield of 26%. Although unrelated in fold and sequence to natural phycobiliproteins, bilin lyases nevertheless interact with maquettes during co-expression in Escherichia coli to improve the efficiency of bilin binding and influence bilin structure. Bilins bind in vitro and in vivo to Cys residues placed in loops, towards the amino end or in the middle of helices but bind poorly at the carboxyl end of helices. Bilin-binding efficiency and fluorescence yield are improved by Arg and Asp residues adjacent to the ligating Cys on the same helix and by His residues on adjacent helices.

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'.

TetraBASE: A Side Chain-Independent Statistical Energy for Designing Realistically Packed Protein Backbones

To construct backbone structures of high designability is a primary aspect of computational protein design. We report here a side chain-independent statistical energy that aims at realistic modeling of through-space packing of polypeptide backbones. To mitigate the lack of explicit amino acid side chains, the model treats the interbackbone site packing as being dependent on peptide local conformation. In addition, new variables suitable for statistical analysis, one for relative orientation and another for distance, have been introduced to represent the intersite geometry based on the asymmetrical tetrahedron organization of distinct chemical groups surrounding the Cα-carbon atoms. The resulting tetrahedron-based backbone statistical energy (tetraBASE) model has been used to optimize the tertiary organizations of secondary structure elements (SSEs) of designated types with Monte Caro simulated annealing, starting from artificial initial configurations. The tetraBASE minimum energy structures can reproduce SSE packing frequently observed in native proteins with atomic root-mean-square deviations of 1-2 Å. The model has also been tested by examining the stability of native SSE arrangements under tetraBASE. The results suggest that tetraBASE model can be used to effectively represent interbackbone packing when designing backbone structures without explicitly knowing side chain types.

De Novo Design of Tetranuclear Transition Metal Clusters Stabilized by Hydrogen-Bonded Networks in Helical Bundles

De novo design provides an attractive approach to test the mechanism by which metalloproteins define the geometry and reactivity of their metal ion cofactors. While there has been considerable progress in designing proteins that bind transition metal ions including iron-sulfur clusters, the design of tetranuclear clusters with oxygen-rich environments has not been accomplished. Here, we describe the design of tetranuclear clusters, consisting of four Zn2+ and four carboxylate oxygens situated at the vertices of a distorted cube-like structure. The tetra-Zn2+ clusters are bound at a buried site within a four-helix bundle, with each helix donating a single carboxylate (Glu or Asp) and imidazole (His) ligand, as well as second- and third-shell ligands. Overall, the designed site consists of four Zn2+ and 16 polar side chains in a fully connected hydrogen-bonded network. The designed proteins have apolar cores at the top and bottom of the bundle, which drive the assembly of the liganding residues near the center of the bundle. The steric bulk of the apolar residues surrounding the binding site was varied to determine how subtle changes in helix-helix packing affect the binding site. The crystal structures of two of four proteins synthesized were in good agreement with the overall design; both formed a distorted cuboidal site stabilized by flanking second- and third-shell interactions that stabilize the primary ligands. A third structure bound a single Zn2+ in an unanticipated geometry, and the fourth bound multiple Zn2+ at multiple sites at partial occupancy. The metal-binding and conformational properties of the helical bundles in solution, probed by circular dichroism spectroscopy, analytical ultracentrifugation, and NMR, were consistent with the crystal structures.

Hierarchical design of artificial proteins and complexes toward synthetic structural biology

In multiscale structural biology, synthetic approaches are important to demonstrate biophysical principles and mechanisms underlying the structure, function, and action of bio-nanomachines. A central goal of "synthetic structural biology" is the design and construction of artificial proteins and protein complexes as desired. In this paper, I review recent remarkable progress of an array of approaches for hierarchical design of artificial proteins and complexes that signpost the path forward toward synthetic structural biology as an emerging interdisciplinary field. Topics covered include combinatorial and protein-engineering approaches for directed evolution of artificial binding proteins and membrane proteins, binary code strategy for structural and functional de novo proteins, protein nanobuilding block strategy for constructing nano-architectures, protein-metal-organic frameworks for 3D protein complex crystals, and rational and computational approaches for design/creation of artificial proteins and complexes, novel protein folds, ideal/optimized protein structures, novel binding proteins for targeted therapeutics, and self-assembling nanomaterials. Protein designers and engineers look toward a bright future in synthetic structural biology for the next generation of biophysics and biotechnology.