Design of a 20-amino acid, three-stranded beta-sheet protein

Degradation of Di (2-ethylhexyl) phthalic acid plasticizer in baijiu by a foam titanium flow reactor attached with hairpin-like structured peptide enzyme mimics

Because of the significant environmental and health hazards imposed by di(2-ethylhexyl) phthalate (DEHP), a common plasticizer, developing safe and green techniques to degrade DEHP plasticizer is of huge scientific significance. It has been observed that environmental contamination of DEHP may also induce serious food safety problems because crops raised in plasticizers contaminated soils would transfer the plasticizer into foods, such as Baijiu. Additionally, when plastic packaging or vessels are used during Baijiu fermentation and processing, plasticizer compounds frequently migrate and contaminate the product. In this study, hairpin-like structured peptides with catalytically active sites containing serine, histidine and aspartic acid were found to degrade DEHP. Furthermore, after incorporating caffeic acid molecules at the N-terminus, the peptides could be attached onto foam titanium (Ti) surfaces via enediol-metal interactions to create an enzyme-mimicking flow reactor for the degradation of DEHP in Baijiu. The structure and catalytic activity of peptides, their interaction with DEHP substrate and the hydrolysis mechanism of DEHP were discussed in this work. The stability and reusability of the peptide-modified foam Ti flow reactor were also investigated. This approach provides an effective technique for the degradation of plasticizer compounds.

Rational design of antibody-like peptides for targeting the human complement fragment protein C5a

Human complement fragment 5a (C5a) is one of the most potent glycoproteins generated downstream of C3a and C4a during late-stage activation of the complement signaling cascade. C5a recruits receptors like C5aR1 and C5aR2 and is established to play a critical role in complement-mediated inflammation. Thus, excessive C5a in the plasma due to aberrant activation of the complement contributes to the pathophysiology of several chronic inflammatory diseases. Therefore, restricting the excessive interaction of C5a with its receptors by neutralizing C5a has been one of the most effective therapeutic strategies for the management of inflammatory diseases. Indeed, antibodies targeting C5 (Eculizumab), the precursor of C5a, and C5a (Vilobelimab) have already been approved by the FDA. Still, small designer peptides that work like antibodies and can target and stop C5a from interacting with its receptors seem to be a possible therapeutic alternative to antibodies because they are smaller, cheaper to make, more specific to their target, and can get through membrane barriers. As a proof-of-principle, the current study describes the computational design and evaluation of a pair of peptides that are able to form stable high-affinity complexes with the epitope regions of C5a that are important for the recruitment of C5aR1 and C5aR2. The computational data further supports the potential of designer peptides for mimicking the function of antibodies targeting C5a. However, further experimental studies will be required to establish the structure-function relationship of the designer peptides and also to establish the hypothesis of antibody-like peptides targeting C5a.

Dissecting the Conformational Stability of a Glycan Hairpin

Systematic structural studies of model oligopeptides revealed important aspects of protein folding and offered design principles to access non-natural materials. In the same way, the rules that regulate glycan folding could be established by studying synthetic oligosaccharide models. However, their analysis is often limited due to the synthetic and analytical complexity. By utilizing a glycan capable of spontaneously folding into a hairpin conformation as a model system, we investigated the factors that contribute to its conformational stability in aqueous solution. The modular design of the hairpin model featured a trisaccharide turn unit and two β-1,4-oligoglucoside stacking strands that allowed for systematic chemical modifications of the glycan sequence, including the introduction of NMR labels and staples. Nuclear magnetic resonance assisted by molecular dynamics simulations revealed that stereoelectronic effects and multiple glycan-glycan interactions are the major determinants of folding stabilization. Chemical modifications in the glycan primary sequence (e.g., strand elongation) can be employed to fine-tune the rigidity of structural motifs distant from the modification sites. These results could inspire the design of other glycan architectures, with implications in glycobiology and material sciences.

A three-state mechanism for trifluoroethanol denaturation of an intrinsically disordered protein (IDP)

Relating the amino acid composition and sequence to chain folding and binding preferences of intrinsically disordered proteins (IDPs) has emerged as a huge challenge. While globular proteins have respective 3D structures that are unique to their individual functions, IDPs violate this structure-function paradigm because rather than having a well-defined structure an ensemble of rapidly interconverting disordered structures characterize an IDP. This work measures 2,2,2-trifluoroethanol (TFE)-induced equilibrium transitions of an IDP called AtPP16-1 (Arabidopsis thaliana phloem protein type 16-1) by using fluorescence, circular dichroism, infrared and nuclear magnetic resonance (NMR) methods at pH 4, 298 K. Low TFE reversibly removes the tertiary structure to produce an ensemble of obligate intermediate ($\mathrm{I}$) retaining the native-state ($\mathrm{N}$) secondary structure. The intermediate $\mathrm{I}$ is preceded by a non-obligate tryptophan-specific intermediate ${\mathrm{I}}_{\mathrm{w}}$ whose population is detectable for AtPP16-1 specifically. Accumulation of such non-obligate intermediates is discriminated according to the sequence composition of the protein. In all cases, however, a tertiary structure-unfolded general obligate intermediate $\mathrm{I}$ is indispensable. The $\mathrm{I}$ ensemble has higher helical propensity conducive to the acquisition of an exceedingly large level of α-helices by a reversible denaturation transition of $\mathrm{I}$ to the denatured state $\mathrm{D}$ as the TFE level is increased. Strikingly, it is the same $\mathrm{N}\rightleftharpoons \mathrm{I}\rightleftharpoons \mathrm{D}$ scheme typifying the TFE transitions of globular proteins. The high-energy state $\mathrm{I}$ characterized by increased helical propensity is called a universal intermediate encountered in both genera of globular and disordered proteins. Neither $\mathrm{I}$ nor $\mathrm{D}$ strictly show molten globule (MG)-like properties, dismissing the belief that TFE promotes MGs.

Synthesis of a glycan hairpin

The primary sequence of a biopolymer encodes the essential information for folding, permitting to carry out sophisticated functions. Inspired by natural biopolymers, peptide and nucleic acid sequences have been designed to adopt particular three-dimensional (3D) shapes and programmed to exert specific functions. In contrast, synthetic glycans capable of autonomously folding into defined 3D conformations have so far not been explored owing to their structural complexity and lack of design rules. Here we generate a glycan that adopts a stable secondary structure not present in nature, a glycan hairpin, by combining natural glycan motifs, stabilized by a non-conventional hydrogen bond and hydrophobic interactions. Automated glycan assembly enabled rapid access to synthetic analogues, including site-specific 13C-labelled ones, for nuclear magnetic resonance conformational analysis. Long-range inter-residue nuclear Overhauser effects unequivocally confirmed the folded conformation of the synthetic glycan hairpin. The capacity to control the 3D shape across the pool of available monosaccharides has the potential to afford more foldamer scaffolds with programmable properties and functions.

A surprisingly simple three-state generic process for reversible protein denaturation by trifluoroethanol

Despite the rich knowledge of the influence of 2,2,2-trifluoroethanol (TFE) on the structure and conformation of peptides and proteins, the mode(s) of TFE-protein interactions and the mechanism by which TFE reversibly denatures a globular protein remain elusive. This study systematically examines TFE-induced equilibrium transition curves for six paradigmatic globular proteins by using basic fluorescence and circular dichroism measurements under neutral pH conditions. The results are remarkably simple. Low TFE invariably unfolds the tertiary structure of all proteins to produce the obligate intermediate (I) which retains nearly all of native-state secondary structure, but enables the formation of extra α-helices as the level of TFE is raised higher. Inspection of the transitions at once reveals that the tertiary structure unfolding is always a distinct process, necessitating the inclusion of at least one obligate intermediate in the TFE-induced protein denaturation. It appears that the intermediate in the minimal unfolding mechanism N⇌I⇌D somehow acquires higher α-helical propensity to generate α-helices in excess of that in the native state to produce the denatured state (D), also called the TFE state. The low TFE-populated intermediate I may be called a universal intermediate by virtue of its α-helical propensity. Contrary to many earlier suggestions, this study dismisses molten globule (MG)-like attribute of I or D.

Miniproteins in medicinal chemistry

Miniproteins exhibit great potential as scaffolds for drug candidates because of their well-defined structure and good synthetic availability. Because of recently described methodologies for their de novo design, the field of miniproteins is emerging and can provide molecules that effectively bind to problematic targets, i.e., those that have been previously considered to be undruggable. This review describes methodologies for the development of miniprotein scaffolds and for the construction of biologically active miniproteins.

De novo protein design by an energy function based on series expansion in distance and orientation dependence

MOTIVATION

Despite many successes, de novo protein design is not yet a solved problem as its success rate remains low. The low success rate is largely because we do not yet have an accurate energy function for describing the solvent-mediated interaction between amino acid residues in a protein chain. Previous studies showed that an energy function based on series expansions with its parameters optimized for side-chain and loop conformations can lead to one of the most accurate methods for side chain (OSCAR) and loop prediction (LEAP). Following the same strategy, we developed an energy function based on series expansions with the parameters optimized in four separate stages (recovering single-residue types without and with orientation dependence, selecting loop decoys and maintaining the composition of amino acids). We tested the energy function for de novo design by using Monte Carlo simulated annealing.

RESULTS

The method for protein design (OSCAR-Design) is found to be as accurate as OSCAR and LEAP for side-chain and loop prediction, respectively. In de novo design, it can recover native residue types ranging from 38% to 43% depending on test sets, conserve hydrophobic/hydrophilic residues at ∼75%, and yield the overall similarity in amino acid compositions at more than 90%. These performance measures are all statistically significantly better than several protein design programs compared. Moreover, the largest hydrophobic patch areas in designed proteins are near or smaller than those in native proteins. Thus, an energy function based on series expansion can be made useful for protein design.

AVAILABILITY AND IMPLEMENTATION

The Linux executable version is freely available for academic users at http://zhouyq-lab.szbl.ac.cn/resources/.

A Brief History of De Novo Protein Design: Minimal, Rational, and Computational

Protein design has come of age, but how will it mature? In the 1980s and the 1990s, the primary motivation for de novo protein design was to test our understanding of the informational aspect of the protein-folding problem; i.e., how does protein sequence determine protein structure and function? This necessitated minimal and rational design approaches whereby the placement of each residue in a design was reasoned using chemical principles and/or biochemical knowledge. At that time, though with some notable exceptions, the use of computers to aid design was not widespread. Over the past two decades, the tables have turned and computational protein design is firmly established. Here, I illustrate this progress through a timeline of de novo protein structures that have been solved to atomic resolution and deposited in the Protein Data Bank. From this, it is clear that the impact of rational and computational design has been considerable: More-complex and more-sophisticated designs are being targeted with many being resolved to atomic resolution. Furthermore, our ability to generate and manipulate synthetic proteins has advanced to a point where they are providing realistic alternatives to natural protein functions for applications both in vitro and in cells. Also, and increasingly, computational protein design is becoming accessible to non-specialists. This all begs the questions: Is there still a place for minimal and rational design approaches? And, what challenges lie ahead for the burgeoning field of de novo protein design as a whole?

A theoretical study of polymorphism in VQIVYK fibrils

The VQIVYK fragment from the Tau protein, also known as PHF6, is essential for aggregation of Tau into neurofibrillary lesions associated with neurodegenerative diseases. VQIVYK itself forms amyloid fibrils composed of paired β-sheets. Therefore, the full Tau protein and VQIVYK fibrils have been intensively investigated. A central issue in these studies is polymorphism, the ability of a protein to fold into more than one structure. Using all-atom molecular simulations, we generate five stable polymorphs of VQIVYK fibrils, establish their relative free energy with umbrella sampling methods, and identify the side chain interactions that provide stability. The two most stable polymorphs, which have nearly equal free energy, are formed by interdigitation of the mostly hydrophobic VIY "face" sides of the β-sheets. Another stable polymorph is formed by interdigitation of the QVK "back" sides. When we turn to examine structures from cryo-electron microscopy experiments on Tau filaments taken from diseased patients or generated in vitro, we find that the pattern of side chain interactions found in the two most stable face-to-face as well as the back-to-back polymorphs are recapitulated in amyloid structures of the full protein. Thus, our studies suggest that the interactions stabilizing PHF6 fibrils explain the amyloidogenicity of the VQIVYK motif within the full Tau protein and provide justification for the use of VQIVYK fibrils as a test bed for the design of molecules that identify or inhibit amyloid structures.

De Novo-Designed β-Sheet Heme Proteins

The field of de novo protein design has met with considerable success over the past few decades. Heme, a cofactor, has often been introduced to impart a diverse array of functions to a protein, ranging from electron transport to respiration. In nature, heme is found to occur predominantly in α-helical structures over β-sheets, which has resulted in significant designs of heme proteins utilizing coiled-coil helices. By contrast, there are only a few known β-sheet proteins that bind heme and designs of β-sheets frequently result in amyloid-like aggregates. This review reflects on our success in designing a series of multistranded β-sheet heme binding peptides that are well folded in both aqueous and membrane-like environments. Initially, we designed a β-hairpin peptide that self-assembles to bind heme and performs peroxidase activity in membrane. The β-hairpin was optimized further to accommodate a heme binding pocket within multistranded β-sheets for catalysis and electron transfer in membranes. Furthermore, we de novo designed and characterized β-sheet peptides and miniproteins that are soluble in an aqueous environment capable of binding single and multiple hemes with high affinity and stability. Collectively, these studies highlight the substantial progress made toward the design of functional β-sheets.

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.

B-SIDER: Computational Algorithm for the Design of Complementary β-Sheet Sequences

The β-sheet is an element of protein secondary structure, and intra-/intermolecular β-sheet interactions play pivotal roles in biological regulatory processes including scaffolding, transporting, and oligomerization. In nature, a β-sheet formation is tightly regulated because dysregulated β-stacking often leads to severe diseases such as Alzheimer's, Parkinson's, systemic amyloidosis, or diabetes. Thus, the identification of intrinsic β-sheet-forming propensities can provide valuable insight into protein designs for the development of novel therapeutics. However, structure-based design methods may not be generally applicable to such amyloidogenic peptides mainly owing to high structural plasticity and complexity. Therefore, an alternative design strategy based on complementary sequence information is of significant importance. Herein, we developed a database search method called β-Stacking Interaction DEsign for Reciprocity (B-SIDER) for the design of complementary β-strands. This method makes use of the structural database information and generates target-specific score matrices. The discriminatory power of the B-SIDER score function was tested on representative amyloidogenic peptide substructures against a sequence-based score matrix (PASTA 2.0) and two popular ab initio protein design score functions (Rosetta and FoldX). B-SIDER is able to distinguish wild-type amyloidogenic β-strands as favored interactions in a more consistent manner than other methods. B-SIDER was prospectively applied to the design of complementary β-strands for a splitGFP scaffold. Three variants were identified to have stronger interactions than the original sequence selected through a directed evolution, emitting higher fluorescence intensities. Our results indicate that B-SIDER can be applicable to the design of other β-strands, assisting in the development of therapeutics against disease-related amyloidogenic peptides.

Peptide-/Drug-Directed Self-Assembly of Hybrid Polyurethane Hydrogels for Wound Healing

Drug-loading hydrogels are promising candidates in the bioengineering research field; nevertheless, hydrophobic drug loading into a hydrophilic carrier system remains unsolved and is full of challenges. In this work, following the potential dual interactions between peptides and aromatic drugs, we developed a potent hybrid hydrogel formation method, namely, "peptide-/drug-directed self-assembly". The hybrid hydrogels were synthesized using polyethylene glycol (PEG)-based Fmoc-FF peptide hybrid polyurethane, in which curcumin could be encapsulated through self-assembly with Fmoc-FF peptide via π-π stacking. On the basis of this, curcumin loading capacity could be improved to as high as 3.3 wt % with sustained release. In addition, the curcumin loading enhanced the hydrogel mechanical properties from 4 kPa to over 10 kPa, similar to that of natural soft tissues. Furthermore, the hydrogels were injectable with self-healing properties since the Fmoc-FF peptide/curcumin coassembly was noncovalent and reversible. Spectroscopy results confirmed the existence of the coassembly of Fmoc-FF peptide/curcumin. Further in vivo experiments effectively demonstrated that the hydrogels could improve the cutaneous wound healing in a full-thickness skin defected model. This peptide-/drug-directed self-assembly of hybrid polyurethane hydrogel could be used as a promising platform for tissue-engineering scaffold and biomedical application.

Formation of Secondary and Supersecondary Structure of Proteins as a Result of Coupling Between Local and Backbone-Electrostatic Interactions: A View Through Cluster-Cumulant Scope

The secondary structure of proteins results from both local and long-range interactions, the latter being primarily backbone hydrogen bonding. In this chapter, based on our recent work, we suggest that the striking regularity of secondary structure can be described, in a semi-analytical manner, in terms of Kubo cluster cumulants (corresponding to the expansion of the protein's potential of mean force) that originate from the coupling between the backbone-local and backbone-electrostatic interactions. This finding is illustrated by the analysis of the Protein Data Bank statistics. Examples demonstrating the importance of the coupling terms in coarse-grained treatment of proteins are also presented.

Aromatic interactions in β-hairpin scaffold stability: A historical perspective

Non-covalent interactions between naturally occurring aromatic residues have been widely exploited as scaffold stabilizing agents in de novo designed peptides and in Nature - inspired structures. Our understanding of the factors driving aromatic interactions and their observed interaction geometries have advanced remarkably with improvements in conventional structural studies, availability of novel molecular methods and in silico studies, which have together provided atomistic information on aromatic interactions and interaction strengths. This review attempts to recapitulate the early advances in our understanding of aromatic interactions as stabilizing agents of peptide β-hairpins.

De novo design of a non-local β-sheet protein with high stability and accuracy

β-sheet proteins carry out critical functions in biology, and hence are attractive scaffolds for computational protein design. Despite this potential, de novo design of all-β-sheet proteins from first principles lags far behind the design of all-α or mixed-αβ domains owing to their non-local nature and the tendency of exposed β-strand edges to aggregate. Through study of loops connecting unpaired β-strands (β-arches), we have identified a series of structural relationships between loop geometry, side chain directionality and β-strand length that arise from hydrogen bonding and packing constraints on regular β-sheet structures. We use these rules to de novo design jellyroll structures with double-stranded β-helices formed by eight antiparallel β-strands. The nuclear magnetic resonance structure of a hyperthermostable design closely matched the computational model, demonstrating accurate control over the β-sheet structure and loop geometry. Our results open the door to the design of a broad range of non-local β-sheet protein structures.

Effective formation of stable and versatile double-stranded β-sheets templated by a hydrogen-bonded duplex

An effective approach to construct stable and versatile double-stranded β-sheets composed of tetra- and penta-peptides through a hydrogen-bonded duplex template has been explored.

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, β 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.

Protein β-sheet prediction using an efficient dynamic programming algorithm

Predicting the β-sheet structure of a protein is one of the most important intermediate steps towards the identification of its tertiary structure. However, it is regarded as the primary bottleneck due to the presence of non-local interactions between several discontinuous regions in β-sheets. To achieve reliable long-range interactions, a promising approach is to enumerate and rank all β-sheet conformations for a given protein and find the one with the highest score. The problem with this solution is that the search space of the problem grows exponentially with respect to the number of β-strands. Additionally, brute-force calculation in this conformational space leads to dealing with a combinatorial explosion problem with intractable computational complexity. The main contribution of this paper is to generate and search the space of the problem efficiently to reduce the time complexity of the problem. To achieve this, two tree structures, called sheet-tree and grouping-tree, are proposed. They model the search space by breaking it into sub-problems. Then, an advanced dynamic programming is proposed that stores the intermediate results, avoids repetitive calculation by repeatedly uses them efficiently in successive steps and reduces the space of the problem by removing those intermediate results that will no longer be required in later steps. As a consequence, the following contributions have been made. Firstly, more accurate β-sheet structures are found by searching all possible conformations, and secondly, the time complexity of the problem is reduced by searching the space of the problem efficiently which makes the proposed method applicable to predict β-sheet structures with high number of β-strands. Experimental results on the BetaSheet916 dataset showed significant improvements of the proposed method in both execution time and the prediction accuracy in comparison with the state-of-the-art β-sheet structure prediction methods Moreover, we investigate the effect of different contact map predictors on the performance of the proposed method using BetaSheet1452 dataset. The source code is available at http://www.conceptsgate.com/BetaTop.rar.

Designed Heme-Cage β-Sheet Miniproteins

The structure and function of naturally occurring proteins are governed by a large number of amino acids (≥100). The design of miniature proteins with desired structures and functions not only substantiates our knowledge about proteins but can also contribute to the development of novel applications. Excellent progress has been made towards the design of helical proteins with diverse functions. However, the development of functional β-sheet proteins remains challenging. Herein, we describe the construction and characterization of four-stranded β-sheet miniproteins made up of about 19 amino acids that bind heme inside a hydrophobic binding pocket or "heme cage" by bis-histidine coordination in an aqueous environment. The designed miniproteins bound to heme with high affinity comparable to that of native heme proteins. Atomic-resolution structures confirmed the presence of a four-stranded β-sheet fold. The heme-protein complexes also exhibited high stability against thermal and chaotrope-induced unfolding.

Efficient dynamic programming algorithm with prior knowledge for protein β-strand alignment

One of the main tasks towards the prediction of protein β-sheet structure is to predict the native alignment of β-strands. The alignment of two β-strands defines similar regions that may reflect functional, structural, or evolutionary relationships between them. Therefore, any improvement in β-strands alignment not only reduces the computational search space but also improves β-sheet structure prediction accuracy. To define the alignment scores, previous studies utilized predicted residue-residue contacts (contact maps). However, there are two serious problems using them. First, the precision of contact map prediction techniques, especially for long-range contacts (i.e., β-residues), is still not satisfactory. Second, the residue-residue contact predictors usually utilize general properties of amino acids and disregard the structural features of β-residues. In this paper, we consider β-structure information, which is estimated from protein β-sheet data sets, as alignment scores. However, the predicted contact maps are used as a prior knowledge about residues. They are used for strengthening or weakening the alignment scores in our algorithm. Thus, we can utilize both β-residues and β-structure information in alignment of β-strands. The structure of dynamic programming of the alignment algorithm is changed in order to work with our prior knowledge. Moreover, the Four Russians method is applied to the proposed alignment algorithm in order to reduce the time complexity of the problem. For evaluating the proposed method, we applied it to the state-of-the-art β-sheet structure prediction methods. The experimental results on the BetaSheet916 data set showed significant improvements in the execution time, the accuracy of β-strands' alignment and consequently β-sheet structure prediction accuracy. The results are available at http://conceptsgate.com/BetaSheet.

Achievements and Challenges in Computational Protein Design

Computational protein design (CPD), a yet evolving field, includes computer-aided engineering for partial or full de novo designs of proteins of interest. Designs are defined by a requested structure, function, or working environment. This chapter describes the birth and maturation of the field by presenting 101 CPD examples in a chronological order emphasizing achievements and pending challenges. Integrating these aspects presents the plethora of CPD approaches with the hope of providing a "CPD 101". These reflect on the broader structural bioinformatics and computational biophysics field and include: (1) integration of knowledge-based and energy-based methods, (2) hierarchical designated approach towards local, regional, and global motifs and the integration of high- and low-resolution design schemes that fit each such region, (3) systematic differential approaches towards different protein regions, (4) identification of key hot-spot residues and the relative effect of remote regions, (5) assessment of shape-complementarity, electrostatics and solvation effects, (6) integration of thermal plasticity and functional dynamics, (7) negative design, (8) systematic integration of experimental approaches, (9) objective cross-assessment of methods, and (10) successful ranking of potential designs. Future challenges also include dissemination of CPD software to the general use of life-sciences researchers and the emphasis of success within an in vivo milieu. CPD increases our understanding of protein structure and function and the relationships between the two along with the application of such know-how for the benefit of mankind. Applied aspects range from biological drugs, via healthier and tastier food products to nanotechnology and environmentally friendly enzymes replacing toxic chemicals utilized in the industry.

Automated protein design: Landmarks and operational principles

Protein design has an eventful history spanning over three decades, with handful of success stories reported, and numerous failures not reported. Design practices have benefited tremendously from improvements in computer hardware and advances in scientific algorithms. Though protein folding problem still remains unsolved, the possibility of having multiple sequence solutions for a single fold makes protein design a more tractable problem than protein folding. One of the most significant advancement in this area is the implementation of automated design algorithms on pre-defined templates or completely new folds, optimized through deterministic and heuristic search algorithms. This progress report provides a succinct presentation of important landmarks in automated design attempts, followed by brief account of operational principles in automated design methods.

Toward a Rational Design of Highly Folded Peptide Cation Conformations. 3D Gas-Phase Ion Structures and Ion Mobility Characterization

Heptapeptide ions containing combinations of polar Lys, Arg, and Asp residues with non-polar Leu, Pro, Ala, and Gly residues were designed to study polar effects on gas-phase ion conformations. Doubly and triply charged ions were studied by ion mobility mass spectrometry and electron structure theory using correlated ab initio and density functional theory methods and found to exhibit tightly folded 3D structures in the gas phase. Manipulation of the basic residue positions in LKGPADR, LRGPADK, KLGPADR, and RLGPADK resulted in only minor changes in the ion collision cross sections in helium. Replacement of the Pro residue with Leu resulted in only marginally larger collision cross sections for the doubly and triply charged ions. Disruption of zwitterionic interactions in doubly charged ions was performed by converting the C-terminal and Asp carboxyl groups to methyl esters. This resulted in very minor changes in the collision cross sections of doubly charged ions and even slightly diminished collision cross sections in most triply charged ions. The experimental collision cross sections were related to those calculated for structures of lowest free energy ion conformers that were obtained by extensive search of the conformational space and fully optimized by density functional theory calculations. The predominant factors that affected ion structures and collision cross sections were due to attractive hydrogen bonding interactions and internal solvation of the charged groups that overcompensated their Coulomb repulsion. Structure features typically assigned to the Pro residue and zwitterionic COO-charged group interactions were only secondary in affecting the structures and collision cross sections of these gas-phase peptide ions. Graphical Abstract ᅟ.

Synthetic beta-solenoid proteins with the fragment-free computational design of a beta-hairpin extension

The ability to design and construct structures with atomic level precision is one of the key goals of nanotechnology. Proteins offer an attractive target for atomic design because they can be synthesized chemically or biologically and can self-assemble. However, the generalized protein folding and design problem is unsolved. One approach to simplifying the problem is to use a repetitive protein as a scaffold. Repeat proteins are intrinsically modular, and their folding and structures are better understood than large globular domains. Here, we have developed a class of synthetic repeat proteins based on the pentapeptide repeat family of beta-solenoid proteins. We have constructed length variants of the basic scaffold and computationally designed de novo loops projecting from the scaffold core. The experimentally solved 3.56-Å resolution crystal structure of one designed loop matches closely the designed hairpin structure, showing the computational design of a backbone extension onto a synthetic protein core without the use of backbone fragments from known structures. Two other loop designs were not clearly resolved in the crystal structures, and one loop appeared to be in an incorrect conformation. We have also shown that the repeat unit can accommodate whole-domain insertions by inserting a domain into one of the designed loops.

The centriolar protein CPAP G-box: an amyloid fibril in a single domain

Centrioles are evolutionarily conserved cylindrical cell organelles with characteristic radial symmetry. Despite their considerable size (400 nm × 200 nm, in humans), genetic studies suggest that relatively few protein components are involved in their assembly. We recently characterized the molecular architecture of the centrosomal P4.1-associated protein (CPAP), which is crucial for controlling the centriolar cylinder length. Here, we review the remarkable architecture of the C-terminal domain of CPAP, termed the G-box, which comprises a single, entirely solvent exposed, antiparallel β-sheet. Molecular dynamics simulations support the stability of the G-box domain even in the face of truncations or amino acid substitutions. The similarity of the G-box domain to amyloids (or amyloid precursors) is strengthened by its oligomeric arrangement to form continuous fibrils. G-box fibrils were observed in crystals as well as in solution and are also supported by simulations. We conclude that the G-box domain may well represent the best analogue currently available for studies of exposed β-sheets, unencumbered by additional structural elements or severe aggregations problems.

Designed multi-stranded heme binding β-sheet peptides in membrane

Designed peptides demonstrating well-defined structures and functioning in membrane environment are of significant interest in developing novel proteins for membrane active biological processes including enzymes, electron transfer, ion channels and energy conversion. Heme proteins' ability to carry out multiple functions in nature has inspired the design of several helical heme binding peptides and proteins soluble in water and also recently in membrane. Naturally occurring β-sheet proteins are both water and membrane soluble, and are known to bind heme, however, designed heme binding β-sheet proteins are yet to be reported, plausibly because of the complex folding and difficulty in introducing heme binding sites in the β-sheet structures. Here, we describe the design, NMR structures and biochemical functional characterization of four stranded and six stranded membrane soluble β-sheet peptides that bind heme and di-heme, respectively. The designed peptides contain either DP-G or DP-DA residues for the nucleation of β-turns intended to stabilize multi-stranded β-sheet topologies and ligate heme with bis-His coordination between adjacent antiparallel β-strands. Furthermore, we have optimized a high affinity heme binding pocket, Kd ∼ nM range, in the adjacent β-strands by utilizing a series of four stranded β-sheet peptides employing β- and ω-amino acids. We find that there is a progressive increase in cofactor binding affinity in the designed peptides with the alkyl chain length of ω-amino acids. Notably, the six stranded β-sheet peptide binds two molecules of heme in a cooperative fashion. The designed peptides perform peroxidase activity with varying ability and efficiently carried out electron transfer with membrane associated protein cytochrome c. The current study demonstrates the designing of functional β-sheet proteins in a membrane environment and expands the repertoire of heme protein design.

A Miniature Protein Stabilized by a Cation-π Interaction Network

The design of folded miniature proteins is predicated on establishing noncovalent interactions that direct the self-assembly of discrete thermostable tertiary structures. In this work, we describe how a network of cation-π interactions present in proteins containing "WSXWS motifs" can be emulated to stabilize the core of a miniature protein. This 19-residue protein sequence recapitulates a set of interdigitated arginine and tryptophan residues that stabilize a distinctive β-strand:loop:PPII-helix topology. Validation of the compact fold determined by NMR was carried out by mutagenesis of the cation-π network and by comparison to the corresponding disulfide-bridged structure. These results support the involvement of a coordinated set of cation-π interactions that stabilize the tertiary structure.

Foldameric probes for membrane interactions by induced β-sheet folding

Design strategies were devised for α/β-peptide foldameric analogues of the antiangiogenic anginex with the goal of mimicking the diverse structural features from the unordered conformation to a folded β-sheet in response to membrane interactions. Structure-activity relationships were investigated in the light of different β-sheet folding levels.

Towards the computational design of protein post-translational regulation

Protein post-translational modifications (PTMs) are a fast and versatility mechanism used by the cell to regulate the function of proteins in response to changing conditions. PTMs can alter the activity of proteins by allosteric regulation or by controlling protein interactions, localization and abundance. Recent advances in proteomics have revealed the extent of regulation by PTMs and the different mechanisms used in nature to exert control over protein function via PTMs. These developments can serve as the foundation for the rational design of protein regulation. Here we review the advances in methods to determine the function of PTMs, protein allosteric control and examples of rational design of PTM regulation. These advances create an opportunity to move synthetic biology forward by making use of a level of regulation that is of yet unexplored.

Induced folding of protein-sized foldameric β-sandwich models with core β-amino acid residues

The mimicry of protein-sized β-sheet structures with unnatural peptidic sequences (foldamers) is a considerable challenge. In this work, the de novo designed betabellin-14 β-sheet has been used as a template, and α→β residue mutations were carried out in the hydrophobic core (positions 12 and 19). β-Residues with diverse structural properties were utilized: Homologous β(3) -amino acids, (1R,2S)-2-aminocyclopentanecarboxylic acid (ACPC), (1R,2S)-2-aminocyclohexanecarboxylic acid (ACHC), (1R,2S)-2-aminocyclohex-3-enecarboxylic acid (ACEC), and (1S,2S,3R,5S)-2-amino-6,6-dimethylbicyclo[3.1.1]heptane-3-carboxylic acid (ABHC). Six α/β-peptidic chains were constructed in both monomeric and disulfide-linked dimeric forms. Structural studies based on circular dichroism spectroscopy, the analysis of NMR chemical shifts, and molecular dynamics simulations revealed that dimerization induced β-sheet formation in the 64-residue foldameric systems. Core replacement with (1R,2S)-ACHC was found to be unique among the β-amino acid building blocks studied because it was simultaneously able to maintain the interstrand hydrogen-bonding network and to fit sterically into the hydrophobic interior of the β-sandwich. The novel β-sandwich model containing 25 % unnatural building blocks afforded protein-like thermal denaturation behavior.

A compact native 24-residue supersecondary structure derived from the villin headpiece subdomain

Many small proteins fold highly cooperatively in an all-or-none fashion and thus their native states are well protected from thermal fluctuations by an extensive network of interactions across the folded structure. Because protein structures are stabilized by local and nonlocal interactions among distal residues, dissecting individual substructures from the context of folded proteins results in large destabilization and loss of unique three-dimensional structure. Thus, mini-protein substructures can only rarely be derived from natural templates. Here, we describe a compact native 24-residues-long supersecondary structure derived from the hyperstable villin headpiece subdomain consisting of helices 2 and 3 (HP24). Using a combination of experimental techniques, including NMR and small-angle x-ray scattering, as well as all-atom replica exchange molecular-dynamics simulations, we show that a variant with stabilizing substitutions (HP24stab) forms a densely packed and compact conformation. In HP24stab, interactions between helices 2 and 3 are similar to those observed in native folded HP35, and the two helices cooperatively stabilize each other by completing the hydrophobic core lining the central part of HP35. Interestingly, even though the HP24wt fragment shows a more expanded and less structured conformation, NMR and simulations demonstrate a preference for a native-like topology. Thus, the two stabilizing residues in HP24stab shift the energy balance toward the native state, leading to a minimal folding motif.

bbcontacts: prediction of β-strand pairing from direct coupling patterns

MOTIVATION

It has recently become possible to build reliable de novo models of proteins if a multiple sequence alignment (MSA) of at least 1000 homologous sequences can be built. Methods of global statistical network analysis can explain the observed correlations between columns in the MSA by a small set of directly coupled pairs of columns. Strong couplings are indicative of residue-residue contacts, and from the predicted contacts a structure can be computed. Here, we exploit the structural regularity of paired β-strands that leads to characteristic patterns in the noisy matrices of couplings. The β-β contacts should be detected more reliably than single contacts, reducing the required number of sequences in the MSAs.

RESULTS

bbcontacts predicts β-β contacts by detecting these characteristic patterns in the 2D map of coupling scores using two hidden Markov models (HMMs), one for parallel and one for antiparallel contacts. β-bulges are modelled as indel states. In contrast to existing methods, bbcontacts uses predicted instead of true secondary structure. On a standard set of 916 test proteins, 34% of which have MSAs with < 1000 sequences, bbcontacts achieves 50% precision for contacting β-β residue pairs at 50% recall using predicted secondary structure and 64% precision at 64% recall using true secondary structure, while existing tools achieve around 45% precision at 45% recall using true secondary structure.

AVAILABILITY AND IMPLEMENTATION

bbcontacts is open source software (GNU Affero GPL v3) available at https://bitbucket.org/soedinglab/bbcontacts .

Direct prediction of profiles of sequences compatible with a protein structure by neural networks with fragment-based local and energy-based nonlocal profiles

Locating sequences compatible with a protein structural fold is the well-known inverse protein-folding problem. While significant progress has been made, the success rate of protein design remains low. As a result, a library of designed sequences or profile of sequences is currently employed for guiding experimental screening or directed evolution. Sequence profiles can be computationally predicted by iterative mutations of a random sequence to produce energy-optimized sequences, or by combining sequences of structurally similar fragments in a template library. The latter approach is computationally more efficient but yields less accurate profiles than the former because of lacking tertiary structural information. Here we present a method called SPIN that predicts Sequence Profiles by Integrated Neural network based on fragment-derived sequence profiles and structure-derived energy profiles. SPIN improves over the fragment-derived profile by 6.7% (from 23.6 to 30.3%) in sequence identity between predicted and wild-type sequences. The method also reduces the number of residues in low complex regions by 15.7% and has a significantly better balance of hydrophilic and hydrophobic residues at protein surface. The accuracy of sequence profiles obtained is comparable to those generated from the protein design program RosettaDesign 3.5. This highly efficient method for predicting sequence profiles from structures will be useful as a single-body scoring term for improving scoring functions used in protein design and fold recognition. It also complements protein design programs in guiding experimental design of the sequence library for screening and directed evolution of designed sequences. The SPIN server is available at http://sparks-lab.org.

Design of monomeric water-soluble β-hairpin and β-sheet peptides

Since the first report in 1993 (JACS 115, 5887-5888) of a peptide able to form a monomeric β-hairpin structure in aqueous solution, the design of peptides forming either β-hairpins (two-stranded antiparallel β-sheets) or three-stranded antiparallel β-sheets has become a field of growing interest and activity. These studies have yielded great insights into the principles governing the stability and folding of β-hairpins and antiparallel β-sheets. This chapter provides an overview of the reported β-hairpin/β-sheet peptides focussed on the applied design criteria, reviews briefly the factors contributing to β-hairpin/β-sheet stability, and describes a protocol for the de novo design of β-sheet-forming peptides based on them. Guidelines to select appropriate turn and strand residues and to avoid self-association are provided. The methods employed to check the success of new designed peptides are also summarized. Since NMR is the best technique to that end, NOEs and chemical shifts characteristic of β-hairpins and three-stranded antiparallel β-sheets are given.

Foldameric α/β-peptide analogs of the β-sheet-forming antiangiogenic anginex: structure and bioactivity

The principles of β-sheet folding and design for α-peptidic sequences are well established, while those for sheet mimetics containing homologated amino acid building blocks are still under investigation. To reveal the structure-function relations of β-amino-acid-containing foldamers, we followed a top-down approach to study a series of α/β-peptidic analogs of anginex, a β-sheet-forming antiangiogenic peptide. Eight anginex analogs were developed by systematic α → β(3) substitutions and analyzed by using NMR and CD spectroscopy. The foldamers retained the β-sheet tendency, though with a decreased folding propensity. β-Sheet formation could be induced by a micellar environment, similarly to that of the parent peptide. The destructuring effect was higher when the α → β(3) exchange was located in the β-sheet core. Analysis of the β-sheet stability versus substitution pattern and the local conformational bias of the bulky β(3)V and β(3)I residues revealed that a mismatch between the H-bonding preferences of the α- and β-residues played a minor role in the structure-breaking effect. Temperature-dependent CD and NMR measurements showed that the hydrophobic stabilization was scaled-down for the α/β-peptides. Analysis of the biological activity of the foldamer peptides showed that four anginex derivatives dose-dependently inhibited the proliferation of a mouse endothelial cell line. The α → β(3) substitution strategy applied in this work can be a useful approach to the construction of bioactive β-sheet mimetics with a reduced aggregation tendency and improved pharmacokinetic properties.

Energy functions in de novo protein design: current challenges and future prospects

In the past decade, a concerted effort to successfully capture specific tertiary packing interactions produced specific three-dimensional structures for many de novo designed proteins that are validated by nuclear magnetic resonance and/or X-ray crystallographic techniques. However, the success rate of computational design remains low. In this review, we provide an overview of experimentally validated, de novo designed proteins and compare four available programs, RosettaDesign, EGAD, Liang-Grishin, and RosettaDesign-SR, by assessing designed sequences computationally. Computational assessment includes the recovery of native sequences, the calculation of sizes of hydrophobic patches and total solvent-accessible surface area, and the prediction of structural properties such as intrinsic disorder, secondary structures, and three-dimensional structures. This computational assessment, together with a recent community-wide experiment in assessing scoring functions for interface design, suggests that the next-generation protein-design scoring function will come from the right balance of complementary interaction terms. Such balance may be found when more negative experimental data become available as part of a training set.

Statistical Analysis of Terminal Extensions of Protein β-Strand Pairs

The long-range interactions, required to the accurate predictions of tertiary structures of β-sheet-containing proteins, are still difficult to simulate. To remedy this problem and to facilitate β-sheet structure predictions, many efforts have been made by computational methods. However, known efforts on β-sheets mainly focus on interresidue contacts or amino acid partners. In this study, to go one step further, we studied β-sheets on the strand level, in which a statistical analysis was made on the terminal extensions of paired β-strands. In most cases, the two paired β-strands have different lengths, and terminal extensions exist. The terminal extensions are the extended part of the paired strands besides the common paired part. However, we found that the best pairing required a terminal alignment, and β-strands tend to pair to make bigger common parts. As a result, 96.97%  of β-strand pairs have a ratio of 25% of the paired common part to the whole length. Also 94.26% and 95.98%  of β-strand pairs have a ratio of 40% of the paired common part to the length of the two β-strands, respectively. Interstrand register predictions by searching interacting β-strands from several alternative offsets should comply with this rule to reduce the computational searching space to improve the performances of algorithms.

Predicting protein β-sheet contacts using a maximum entropy-based correlated mutation measure

MOTIVATION

The problem of ab initio protein folding is one of the most difficult in modern computational biology. The prediction of residue contacts within a protein provides a more tractable immediate step. Recently introduced maximum entropy-based correlated mutation measures (CMMs), such as direct information, have been successful in predicting residue contacts. However, most correlated mutation studies focus on proteins that have large good-quality multiple sequence alignments (MSA) because the power of correlated mutation analysis falls as the size of the MSA decreases. However, even with small autogenerated MSAs, maximum entropy-based CMMs contain information. To make use of this information, in this article, we focus not on general residue contacts but contacts between residues in β-sheets. The strong constraints and prior knowledge associated with β-contacts are ideally suited for prediction using a method that incorporates an often noisy CMM.

RESULTS

Using contrastive divergence, a statistical machine learning technique, we have calculated a maximum entropy-based CMM. We have integrated this measure with a new probabilistic model for β-contact prediction, which is used to predict both residue- and strand-level contacts. Using our model on a standard non-redundant dataset, we significantly outperform a 2D recurrent neural network architecture, achieving a 5% improvement in true positives at the 5% false-positive rate at the residue level. At the strand level, our approach is competitive with the state-of-the-art single methods achieving precision of 61.0% and recall of 55.4%, while not requiring residue solvent accessibility as an input.

AVAILABILITY

http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/