Understanding p300-transcription factor interactions using sequence variation and hybridization.

The hypoxic response is central to cell function and plays a significant role in the growth and survival of solid tumours. HIF-1 regulates the hypoxic response by activating over 100 genes responsible for adaptation to hypoxia, making it a potential target for anticancer drug discovery. Although there is significant structural and mechanistic understanding of the interaction between HIF-1α and p300 alongside negative regulators of HIF-1α such as CITED2, there remains a need to further understand the sequence determinants of binding. In this work we use a combination of protein expression, chemical synthesis, fluorescence anisotropy and isothermal titration calorimetry for HIF-1α sequence variants and a HIF-1α-CITED hybrid sequence which we term CITIF. We show the HIF-1α sequence is highly tolerant to sequence variation through reduced enthalpic and less unfavourable entropic contributions, These data imply backbone as opposed to side chain interactions and ligand folding control the binding interaction and that sequence variations are tolerated as a result of adopting a more disordered bound interaction or "fuzzy" complex.

Query-guided protein-protein interaction inhibitor discovery.

Protein-protein interactions (PPIs) are central to biological mechanisms, and can serve as compelling targets for drug discovery. Yet, the discovery of small molecule inhibitors of PPIs remains challenging given the large and typically shallow topography of the interacting protein surfaces. Here, we describe a general approach to the discovery of orthosteric PPI inhibitors that mimic specific secondary protein structures. Initially, hot residues at protein-protein interfaces are identified in silico or from experimental data, and incorporated into secondary structure-based queries. Virtual libraries of small molecules are then shape-matched against the queries, and promising ligands docked to target proteins. The approach is exemplified experimentally using two unrelated PPIs that are mediated by an α-helix (p53/hDM2) and a ß-strand (GKAP/SHANK1-PDZ). In each case, selective PPI inhibitors are discovered with low µM activity as determined by a combination of fluorescence anisotropy and 1H-15N HSQC experiments. In addition, hit expansion yields a series of PPI inhibitors with defined structure-activity relationships. It is envisaged that the generality of the approach will enable discovery of inhibitors of a wide range of unrelated secondary structure-mediated PPIs.

BAlaS: fast, interactive and accessible computational alanine-scanning using BudeAlaScan.

MOTIVATION: In experimental protein engineering, alanine-scanning mutagenesis involves the replacement of selected residues with alanine to determine the energetic contribution of each side chain to forming an interaction. For example, it is often used to study protein-protein interactions. However, such experiments can be time-consuming and costly, which has led to the development of programmes for performing computational alanine-scanning mutagenesis (CASM) to guide experiments. While programmes are available for this, there is a need for a real-time web application that is accessible to non-expert users. RESULTS: Here, we present BAlaS, an interactive web application for performing CASM via BudeAlaScan and visualizing its results. BAlaS is interactive and intuitive to use. Results are displayed directly in the browser for the structure being interrogated enabling their rapid inspection. BAlaS has broad applications in areas, such as drug discovery and protein-interface design. AVAILABILITY AND IMPLEMENTATION: BAlaS works on all modern browsers and is available through the following website: https://balas.app. The project is open source, distributed using an MIT license and is available on GitHub (https://github.com/wells-wood-research/balas).

Predicting and Experimentally Validating Hot-Spot Residues at Protein-Protein Interfaces.

Protein-protein interactions (PPIs) are vital to all biological processes. These interactions are often dynamic, sometimes transient, typically occur over large topographically shallow protein surfaces, and can exhibit a broad range of affinities. Considerable progress has been made in determining PPI structures. However, given the above properties, understanding the key determinants of their thermodynamic stability remains a challenge in chemical biology. An improved ability to identify and engineer PPIs would advance understanding of biological mechanisms and mutant phenotypes and also provide a firmer foundation for inhibitor design. In silico prediction of PPI hot-spot amino acids using computational alanine scanning (CAS) offers a rapid approach for predicting key residues that drive protein-protein association. This can be applied to all known PPI structures; however there is a trade-off between throughput and accuracy. Here we describe a comparative analysis of multiple CAS methods, which highlights effective approaches to improve the accuracy of predicting hot-spot residues. Alongside this, we introduce a new method, BUDE Alanine Scanning, which can be applied to single structures from crystallography and to structural ensembles from NMR or molecular dynamics data. The comparative analyses facilitate accurate prediction of hot-spots that we validate experimentally with three diverse targets: NOXA-B/MCL-1 (an α-helix-mediated PPI), SIMS/SUMO, and GKAP/SHANK-PDZ (both ß-strand-mediated interactions). Finally, the approach is applied to the accurate prediction of hot-spot residues at a topographically novel Affimer/BCL-xL protein-protein interface.

De novo coiled-coil peptides as scaffolds for disrupting protein-protein interactions.

Protein-protein interactions (PPIs) play pivotal roles in the majority of biological processes. Therefore, improved approaches to target and disrupt PPIs would provide tools for chemical biology and leads for therapeutic development. PPIs with α-helical components are appealing targets given that the secondary structure is well understood and can be mimicked or stabilised to render small-molecule and constrained-peptide-based inhibitors. Here we present a strategy to target α-helix-mediated PPIs that exploits de novo coiled-coil assemblies and test this using the MCL-1/NOXA-B PPI. First, computational alanine scanning is used to identify key α-helical residues from NOXA-B that contribute to the interface. Next, these residues are grafted onto the exposed surfaces of de novo designed homodimeric or heterodimeric coiled-coil peptides. The resulting synthetic peptides selectively inhibit a cognate MCL-1/BID complex in the mid-nM range. Furthermore, the heterodimeric system affords control as inhibition occurs only when both the grafted peptide and its designed partner are present. This establishes proof of concept for exploiting peptides stabilised in de novo coiled coils as inhibitors of PPIs. This dependence on supramolecular assembly introduces new possibilities for regulation and control.

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 ß-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.

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.

Conformational Dynamics of Asparagine at Coiled-Coil Interfaces.

Coiled coils (CCs) are among the best-understood protein folds. Nonetheless, there are gaps in our knowledge of CCs. Notably, CCs are likely to be structurally more dynamic than often considered. Here, we explore this in an abundant class of CCs, parallel dimers, focusing on polar asparagine (Asn) residues in the hydrophobic interface. It is well documented that such inclusions discriminate between different CC oligomers, which has been rationalized in terms of whether the Asn can make side-chain hydrogen bonds. Analysis of parallel CC dimers in the Protein Data Bank reveals a variety of Asn side-chain conformations, but not all of these make the expected inter-side-chain hydrogen bond. We probe the structure and dynamics of a de novo-designed coiled-coil homodimer, CC-Di, by multidimensional nuclear magnetic resonance spectroscopy, including model-free dynamical analysis and relaxation-dispersion experiments. We find dynamic exchange on the millisecond time scale between Asn conformers with the side chains pointing into and out of the core. We perform molecular dynamics simulations that are consistent with this, revealing that the side chains are highly dynamic, exchanging between hydrogen-bonded-paired conformations in picoseconds to nanoseconds. Combined, our data present a more dynamic view for Asn at CC interfaces. Although inter-side-chain hydrogen bonding states are the most abundant, Asn is not always buried or engaged in such interactions. Because interfacial Asn residues are key design features for modulating CC stability and recognition, these further insights into how they are accommodated within CC structures will aid their predictive modeling, engineering, and design.

Toward a Soluble Model System for the Amyloid State.

The formation and deposition of amyloids is associated with many diseases. ß-Sheet secondary structure is a common feature of amyloids, but the packing of sheets against one another is distinctive relative to soluble proteins. Standard methods that rely on perturbing a polypeptide's sequence and evaluating impact on folding can be problematic for amyloid aggregates because a single sequence can adopt multiple conformations and diverse packing arrangements. We describe initial steps toward a minimum-sized, soluble model system for the amyloid state that supports comparisons among sequence variants. Critical to this goal is development of a new linking strategy to enable intersheet association mediated by side chain interactions, which is characteristic of the amyloid state. The linker design we identified should ultimately support exploration of relationships between sequence and amyloid state stability for specific strand-association modes.

Miniprotein Design: Past, Present, and Prospects.

The design and study of miniproteins, that is, polypeptide chains <40 amino acids in length that adopt defined and stable 3D structures, is resurgent. Miniproteins offer possibilities for reducing the complexity of larger proteins and so present new routes to studying sequence-to-structure and sequence-to-stability relationships in proteins generally. They also provide modules for protein design by pieces and, with this, prospects for building more-complex or even entirely new protein structures. In addition, miniproteins are useful scaffolds for templating functional domains, for example, those involved in protein-protein interactions, catalysis, and biomolecular binding, leading to potential applications in biotechnology and medicine. Here we select examples from almost four decades of miniprotein design, development, and dissection. Simply because of the word limit for this Account, we focus on miniproteins that are cooperatively folded monomers in solution and not stabilized by cross-linking or metal binding. In these cases, the optimization of noncovalent interactions is even more critical for the maintenance of the folded states than in larger proteins. Our chronology and catalogue highlights themes in miniproteins, which we explore further and begin to put on a firmer footing through an analysis of the miniprotein structures that have been deposited in the Protein Data Bank (PDB) thus far. Specifically, and compared with larger proteins, miniproteins generally have a lower proportion of residues in regular secondary structure elements (α helices, ß strands, and polyproline-II helices) and, concomitantly, more residues in well-structured loops. This allows distortions of the backbone enabling mini-hydrophobic cores to be made. This also contrasts with larger proteins, which can achieve hydrophobic cores through tertiary contacts between distant regions of sequence. On average, miniproteins have a higher proportion of aromatic residues than larger proteins, and specifically electron-rich Trp and Tyr, which are often found in combination with Pro and Arg to render networks of CH-π or cation-π interactions. Miniproteins also have a higher proportion of the long-chain charged amino acids (Arg, Glu, and Lys), which presumably reflects salt-bridge formation and their greater surface area-to-volume ratio. Together, these amino-acid preferences appear to support greater densities of noncovalent interactions in miniproteins compared with larger proteins. We anticipate that with recent developments such as parametric protein design, it will become increasingly routine to use computation to generate and evaluate models for miniproteins in silico ahead of experimental studies. This could include accessing new structures comprising secondary structure elements linked in previously unseen configurations. The improved understanding of the noncovalent interactions that stabilize the folded states of such miniproteins that we are witnessing through both in-depth bioinformatics analyses and experimental testing will feed these computational protein designs. With this in mind, we can expect a new and exciting era for miniprotein design, study, and application.

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. CONTACT: d.n.woolfson@bristol.ac.uk or chris.wood@bristol.ac.uk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Engineering protein stability with atomic precision in a monomeric miniprotein.

Miniproteins simplify the protein-folding problem, allowing the dissection of forces that stabilize protein structures. Here we describe PPα-Tyr, a designed peptide comprising an α-helix buttressed by a polyproline II helix. PPα-Tyr is water soluble and monomeric, and it unfolds cooperatively with a midpoint unfolding temperature (TM) of 39 °C. NMR structures of PPα-Tyr reveal proline residues docked between tyrosine side chains, as designed. The stability of PPα is sensitive to modifications in the aromatic residues: replacing tyrosine with phenylalanine, i.e., changing three solvent-exposed hydroxyl groups to protons, reduces the TM to 20 °C. We attribute this result to the loss of CH-π interactions between the aromatic and proline rings, which we probe by substituting the aromatic residues with nonproteinogenic side chains. In analyses of natural protein structures, we find a preference for proline-tyrosine interactions over other proline-containing pairs, and observe abundant CH-π interactions in biologically important complexes between proline-rich ligands and SH3 and similar domains.

Characterization of long and stable de novo single alpha-helix domains provides novel insight into their stability.

Naturally-occurring single α-helices (SAHs), are rich in Arg (R), Glu (E) and Lys (K) residues, and stabilized by multiple salt bridges. Understanding how salt bridges promote their stability is challenging as SAHs are long and their sequences highly variable. Thus, we designed and tested simple de novo 98-residue polypeptides containing 7-residue repeats (AEEEXXX, where X is K or R) expected to promote salt-bridge formation between Glu and Lys/Arg. Lys-rich sequences (EK3 (AEEEKKK) and EK2R1 (AEEEKRK)) both form SAHs, of which EK2R1 is more helical and thermo-stable suggesting Arg increases stability. Substituting Lys with Arg (or vice versa) in the naturally-occurring myosin-6 SAH similarly increased (or decreased) its stability. However, Arg-rich de novo sequences (ER3 (AEEERRR) and EK1R2 (AEEEKRR)) aggregated. Combining a PDB analysis with molecular modelling provides a rational explanation, demonstrating that Glu and Arg form salt bridges more commonly, utilize a wider range of rotamer conformations, and are more dynamic than Glu-Lys. This promiscuous nature of Arg helps explain the increased propensity of de novo Arg-rich SAHs to aggregate. Importantly, the specific K:R ratio is likely to be important in determining helical stability in de novo and naturally-occurring polypeptides, giving new insight into how single α-helices are stabilized.

N@a and N@d: Oligomer and Partner Specification by Asparagine in Coiled-Coil Interfaces.

The α-helical coiled coil is one of the best-studied protein-protein interaction motifs. As a result, sequence-to-structure relationships are available for the prediction of natural coiled-coil sequences and the de novo design of new ones. However, coiled coils adopt a wide range of oligomeric states and topologies, and our understanding of the specification of these and the discrimination between them remains incomplete. Gaps in our knowledge assume more importance as coiled coils are used increasingly to construct biomimetic systems of higher complexity; for this, coiled-coil components need to be robust, orthogonal, and transferable between contexts. Here, we explore how the polar side chain asparagine (Asn, N) is tolerated within otherwise hydrophobic helix-helix interfaces of coiled coils. The long-held view is that Asn placed at certain sites of the coiled-coil sequence repeat selects one oligomer state over others, which is rationalized by the ability of the side chain to make hydrogen bonds, or interactions with chelated ions within the coiled-coil interior of the favored state. We test this with experiments on de novo peptide sequences traditionally considered as directing parallel dimers and trimers, and more widely through bioinformatics analysis of natural coiled-coil sequences and structures. We find that when located centrally, rather than near the termini of such coiled-coil sequences, Asn does exert the anticipated oligomer-specifying influence. However, outside of these bounds, Asn is observed less frequently in the natural sequences, and the synthetic peptides are hyperthermostable and lose oligomer-state specificity. These findings highlight that not all regions of coiled-coil repeat sequences are equivalent, and that care is needed when designing coiled-coil interfaces.

On the satisfaction of backbone-carbonyl lone pairs of electrons in protein structures.

Protein structures are stabilized by a variety of noncovalent interactions (NCIs), including the hydrophobic effect, hydrogen bonds, electrostatic forces and van der Waals' interactions. Our knowledge of the contributions of NCIs, and the interplay between them remains incomplete. This has implications for computational modeling of NCIs, and our ability to understand and predict protein structure, stability, and function. One consideration is the satisfaction of the full potential for NCIs made by backbone atoms. Most commonly, backbone-carbonyl oxygen atoms located within α-helices and ß-sheets are depicted as making a single hydrogen bond. However, there are two lone pairs of electrons to be satisfied for each of these atoms. To explore this, we used operational geometric definitions to generate an inventory of NCIs for backbone-carbonyl oxygen atoms from a set of high-resolution protein structures and associated molecular-dynamics simulations in water. We included more-recently appreciated, but weaker NCIs in our analysis, such as n→π* interactions, Cα-H bonds and methyl-H bonds. The data demonstrate balanced, dynamic systems for all proteins, with most backbone-carbonyl oxygen atoms being satisfied by two NCIs most of the time. Combinations of NCIs made may correlate with secondary structure type, though in subtly different ways from traditional models of α- and ß-structure. In addition, we find examples of under- and over-satisfied carbonyl-oxygen atoms, and we identify both sequence-dependent and sequence-independent secondary-structural motifs in which these reside. Our analysis provides a more-detailed understanding of these contributors to protein structure and stability, which will be of use in protein modeling, engineering and design.

Carbohydrate-Aromatic Interactions in Proteins.

Protein-carbohydrate interactions play pivotal roles in health and disease. However, defining and manipulating these interactions has been hindered by an incomplete understanding of the underlying fundamental forces. To elucidate common and discriminating features in carbohydrate recognition, we have analyzed quantitatively X-ray crystal structures of proteins with noncovalently bound carbohydrates. Within the carbohydrate-binding pockets, aliphatic hydrophobic residues are disfavored, whereas aromatic side chains are enriched. The greatest preference is for tryptophan with an increased prevalence of 9-fold. Variations in the spatial orientation of amino acids around different monosaccharides indicate specific carbohydrate C-H bonds interact preferentially with aromatic residues. These preferences are consistent with the electronic properties of both the carbohydrate C-H bonds and the aromatic residues. Those carbohydrates that present patches of electropositive saccharide C-H bonds engage more often in CH-π interactions involving electron-rich aromatic partners. These electronic effects are also manifested when carbohydrate-aromatic interactions are monitored in solution: NMR analysis indicates that indole favorably binds to electron-poor C-H bonds of model carbohydrates, and a clear linear free energy relationships with substituted indoles supports the importance of complementary electronic effects in driving protein-carbohydrate interactions. Together, our data indicate that electrostatic and electronic complementarity between carbohydrates and aromatic residues play key roles in driving protein-carbohydrate complexation. Moreover, these weak noncovalent interactions influence which saccharide residues bind to proteins, and how they are positioned within carbohydrate-binding sites.

De novo protein design: how do we expand into the universe of possible protein structures?

Protein scientists are paving the way to a new phase in protein design and engineering. Approaches and methods are being developed that could allow the design of proteins beyond the confines of natural protein structures. This possibility of designing entirely new proteins opens new questions: What do we build? How do we build into protein-structure space where there are few, if any, natural structures to guide us? To what uses can the resulting proteins be put? And, what, if anything, does this pursuit tell us about how natural proteins fold, function and evolve? We describe the origins of this emerging area of fully de novo protein design, how it could be developed, where it might lead, and what challenges lie ahead.

Local and macroscopic electrostatic interactions in single α-helices.

The noncovalent forces that stabilize protein structures are not fully understood. One way to address this is to study equilibria between unfolded states and α-helices in peptides. Electrostatic forces-which include interactions between side chains, the backbone and side chains, and side chains and the helix macrodipole-are believed to contribute to these equilibria. Here we probe these interactions experimentally using designed peptides. We find that both terminal backbone-side chain and certain side chain-side chain interactions (which include both local effects between proximal charges and interatomic contacts) contribute much more to helix stability than side chain-helix macrodipole electrostatics, which are believed to operate at larger distances. This has implications for current descriptions of helix stability, the understanding of protein folding and the refinement of force fields for biomolecular modeling and simulations. In addition, this study sheds light on the stability of rod-like structures formed by single α-helices, which are common in natural proteins such as non-muscle myosins.