De novo design of foldable proteins with smooth folding funnel: automated negative design and experimental verification

De novo sequence design of foldable proteins provides a way of investigating principles of protein architecture. We performed fully automated sequence design for a target structure having a three-helix bundle topology and synthesized the designed sequences. Our design principle is different from the conventional approach, in that instead of optimizing interactions within the target structure, we design the global shape of the protein folding funnel. This includes automated implementation of negative design by explicitly requiring higher free energy of the denatured state. The designed sequences do not have significant similarity to those of any natural proteins. The NMR and CD spectroscopic data indicated that one designed sequence has a well-defined three-dimensional structure as well as alpha-helical content consistent with the target.     

Protein design for non-aqueous solvents

Improving protein stability in unnatural and suboptimal environments is a promising application of protein engineering technology. Carefully designed amino acid alterations may lead to dramatic positive effects on the stability of proteins under highly perturbing conditions, such as in non-aqueous solvents. Applications of biocatalysts and proteins with specific binding capabilities in the chemical industry have been severely limited by constraints placed on the solvent environment. With the advent of convenient methods for altering the amino acid composition and even synthesizing entirely new protein molecules, it is worthwhile to consider engineering proteins for stability in non-aqueous solvents. In order to identify the features that a protein would need for stability in organic media, we have been studying the structure and properties of the hydrophobic protein crambin. Crambin is unique in that it is soluble and stable in very high concentrations of polar organic solvents. Crambin and its water-soluble homologs offer a powerful demonstration of protein engineering for non-aqueous solvents. This paper describes the structural features that contribute to crambin's special properties. Based on these observations and consideration of how non-aqueous solvents affect the interactions important in protein folding, a set of rules for designing non-aqueous solvent-stable proteins is proposed.     

Accounting for protein-solvent contacts facilitates design of nonaggregating lattice proteins

The folding specificity of proteins can be simulated using simplified structural models and knowledge-based pair-potentials. However, when the same models are used to simulate systems that contain many proteins, large aggregates tend to form. In other words, these models cannot account for the fact that folded, globular proteins are soluble. Here we show that knowledge-based pair-potentials, which include explicitly calculated energy terms between the solvent and each amino acid, enable the simulation of proteins that are much less aggregation-prone in the folded state. Our analysis clarifies why including a solvent term improves the foldability. The aggregation for potentials without water is due to the unrealistically attractive interactions between polar residues, causing artificial clustering. When a water-based potential is used instead, polar residues prefer to interact with water; this leads to designed protein surfaces rich in polar residues and well-defined hydrophobic cores, as observed in real protein structures. We developed a simple knowledge-based method to calculate interactions between the solvent and amino acids. The method provides a starting point for modeling the folding and aggregation of soluble proteins. Analysis of our simple model suggests that inclusion of these solvent terms may also improve off-lattice potentials for protein simulation, design, and structure prediction.     

Computational protein design with a generalized Born solvent model: application to Asparaginyl-tRNA synthetase

Computational Protein Design (CPD) is a promising method for high throughput protein and ligand mutagenesis. Recently, we developed a CPD method that used a polar-hydrogen energy function for protein interactions and a Coulomb/Accessible Surface Area (CASA) model for solvent effects. We applied this method to engineer aspartyl-adenylate (AspAMP) specificity into Asparaginyl-tRNA synthetase (AsnRS), whose substrate is asparaginyl-adenylate (AsnAMP). Here, we implement a more accurate function, with an all-atom energy for protein interactions and a residue-pairwise generalized Born model for solvent effects. As a first test, we compute aminoacid affinities for several point mutants of Aspartyl-tRNA synthetase (AspRS) and Tyrosyl-tRNA synthetase and stability changes for three helical peptides and compare with experiment. As a second test, we readdress the problem of AsnRS aminoacid engineering. We compare three design criteria, which optimize the folding free-energy, the absolute AspAMP affinity, and the relative (AspAMP-AsnAMP) affinity. The sequences and conformations are improved with respect to our previous, polar-hydrogen/CASA study: For several designed complexes, the AspAMP carboxylate forms three interactions with a conserved arginine and a designed lysine, as in the active site of the AspRS:AspAMP complex. The conformations and interactions are well maintained in molecular dynamics simulations and the sequences have an inverted specificity, favoring AspAMP over AsnAMP. The method is not fully successful, since experimental measurements with the seven most promising sequences show that they do not catalyze at a detectable level the adenylation of Asp (or Asn) with ATP. This may be due to weak AspAMP binding and/or disruption of transition-state stabilization.     

Computer-aided design of a PDZ domain to recognize new target sequences

PDZ domains are small globular domains that recognize the last 4-7 amino acids at the C-terminus of target proteins. The specificity of the PDZ-ligand recognition is due to side chain-side chain interactions, as well as the positioning of an alpha-helix involved in ligand binding. We have used computer-aided protein design to produce mutant versions of a Class I PDZ domain that bind to novel Class I and Class II target sequences both in vitro and in vivo, thus providing an alternative to primary antibodies in western blotting, affinity chromatography and pull-down experiments. Our results suggest that by combining different backbone templates with computer-aided protein design, PDZ domains could be engineered to specifically recognize a large number of proteins.     

A novel approach to decoy set generation: designing a physical energy function having local minima with native structure characteristics

We suggest a new approach to the generation of candidate structures (decoys) for ab initio prediction of protein structures. Our method is based on random sampling of conformation space and subsequent local energy minimization. At the core of this approach lies the design of a novel type of energy function. This energy function has local minima with native structure characteristics and wide basins of attraction. The current work presents our motivation for deriving such an energy function and also tests the derived energy function.Our approach is novel in that it takes advantage of the inherently rough energy landscape of proteins, which is generally considered a major obstacle for protein structure prediction. When local minima have wide basins of attraction, the protein's conformation space can be greatly reduced by the convergence of large regions of the space into single points, namely the local minima corresponding to these funnels. We have implemented this concept by an iterative process. The potential is first used to generate decoy sets and then we study these sets of decoys to guide further development of the potential. A key feature of our potential is the use of cooperative multi-body interactions that mimic the role of the entropic and solvent contributions to the free energy.The validity and value of our approach is demonstrated by applying it to 14 diverse, small proteins. We show that, for these proteins, the size of conformation space is considerably reduced by the new energy function. In fact, the reduction is so substantial as to allow efficient conformational sampling. As a result we are able to find a significant number of near-native conformations in random searches performed with limited computational resources.     

Exploring local and non-local interactions for protein stability by structural motif engineering

In order to probe the relative contribution of local and non-local interactions to the thermodynamic stability of proteins, we have devised an experimental approach based on a combination of motif engineering and sequence shuffling. Candidate chain segments in an immunoglobulin V(L) domain were identified whose conformation is proposed to be dominated by non-local interactions. Locally interacting structural motifs of a different conformation were then constructed as replacements, by introducing motif consensus sequences. We find that all nine replacements we constructed systematically reduce the folding cooperativity. By comparing this destabilising effect with the folding transitions of shuffled sequences for three of these motifs, we estimate the contribution of local, native interactions to the free energy of folding. Our results suggest that local and non-local interactions contribute to stability by an approximately equal amount, but that local interactions stabilise by increasing the resistance to denaturation while non-local interactions increase folding cooperativity. The systematic loss of stability by sequence shuffling in these host-guest experiments suggests that the designed interactions indeed are present in the native state, thus consensus sequence engineering may be a useful tool in structure design, but non-local interactions must be taken into account for global stability engineering. Statistical approaches are powerful tools for engineering protein structure and stability, but an analysis based on local sequence propensities alone does not adequately represent the balance of sequence and context in protein structures.     

Inter-residue and solvent-residue interactions in proteins: a statistical study on experimental structures

A large set of protein structures resolved by X-ray or NMR techniques has been extracted from the Protein Data Bank and analyzed using statistical methods. In particular, we investigate the interactions between side chains and the interactions between solvent and side chains, pointing out on the possibility of including the solvent as part of a knowledge-based potential. The solvent-residue contacts are accounted for on the basis of the Voronoi's polyhedron analysis. Our investigation confirms the importance of hydrophobic residues in determining the protein stability. We observe that in general hydrophobic-hydrophobic interactions and, more specifically, aromatic-aromatic contacts tend to be increasingly distally separated in the primary sequence of proteins, thus connecting distinct secondary structure elements. A simple relation expressing the dependence of the protein free energy by the number of residues is proposed. Such a relation includes both the residue-residue and the solvent-residue contributions. The former is dominant for large size proteins, whereas for small sizes (number of residues less than 100) the two terms are comparable. Gapless threading experiments show that the solvent-residue knowledge-based potential yields a significant contribution with respect to discriminating the native structure of proteins. Such contribution is important especially for proteins of small size and is similar to that given by the most favorable residue-residue knowledge-based potential referring to hydrophobic-hydrophobic interactions such as isoleucine-leucine. In general, the inclusion of the solvent-residue interaction produces a relevant increase of the free energy gap between the native structures and decoys.     

Mapping the folding pathway of an immunoglobulin domain: structural detail from Phi value analysis and movement of the transition state

BACKGROUND: Do proteins that have the same structure fold by the same pathway even when they are unrelated in sequence? To address this question, we are comparing the folding of a number of different immunoglobulin-like proteins. Here, we present a detailed protein engineering phi value analysis of the folding pathway of TI I27, an immunoglobulin domain from human cardiac titin. RESULTS: TI I27 folds rapidly via a kinetic intermediate that is destabilized by most mutations. The transition state for folding is remarkably native-like in terms of solvent accessibility. We use phi value analysis to map this transition state and show that it is highly structured; only a few residues close to the N-terminal region of the protein remain completely unfolded. Interestingly, most mutations cause the transition state to become less native-like. This anti-Hammond behavior can be used as a novel means of obtaining additional structural information about the transition state. CONCLUSIONS: The residues that are involved in nucleating the folding of TI I27 are structurally equivalent to the residues that form the folding nucleus in an evolutionary unrelated fibronectin type III protein. These residues form part of the common structural core of Ig-like domains. The data support the hypothesis that interactions essential for defining the structure of these beta sandwich proteins are also important in nucleation of folding.     

Designing enzymes for use in organic solvents.

Enzymes are routinely used in organic solvents where numerous reactions of interest to synthetic and polymer chemists can be performed with high selectivity. Recently, it has become apparent that the catalytic properties of an enzyme can be tailored to a specific catalytic requirement by the use of solvent and protein engineering. The former involves altering the polarity, hydrophobicity, water content, etc., of the organic milieu, while the later applies site-directed mutagenesis to alter the physicochemical properties of the biocatalyst. The dominant effects of organic solvents on enzyme structure and function, and the potential of solvent and protein engineering to design enzymes to function optimally in organic media, are the major foci of this review.     

Harnessing the Unique Structural Properties of Isolated α-Helices

The α-helix is a ubiquitous secondary structural element that is almost exclusively observed in proteins when stabilized by tertiary or quaternary interactions. However, beginning with the unexpected observations of α-helix formation in the isolated C-peptide in ribonuclease A, there is growing evidence that a significant percentage (0.2%) of all proteins contain isolated stable single α-helical domains (SAH). These SAH domains provide unique structural features essential for normal protein function. A subset of SAH domains contain a characteristic ER/K motif, composed of a repeating sequence of ∼4 consecutive glutamic acids followed by ∼4 consecutive basic arginine or lysine (R/K) residues. The ER/K α-helix, also termed the ER/K linker, has been extensively characterized in the context of the myosin family of molecular motors and is emerging as a versatile structural element for protein and cellular engineering applications. Here, we review the structure and function of SAH domains, as well as the tools to identify them in natural proteins. We conclude with a discussion of recent studies that have successfully used the modular ER/K linker for engineering chimeric myosin proteins with altered mechanical properties, as well as synthetic polypeptides that can be used to monitor and systematically modulate protein interactions within cells.     

Conformational study of silklike peptides modified by the addition of the calcium-binding sequence from the shell nacreous matrix protein MSI60 using 13C CP/MAS NMR spectroscopy

The calcium-binding site of the pearl oyster (Pinctada fucata) nacreous layer matrix protein MSI60 was introduced between different Ala-Gly repeating regions derived from the primary sequences of several silk fibroins. Several different organic solvents whose effect on the repetitive domains of silk peptides is well-understood were used to modify the secondary structure of the flanking Ala-Gly repeating regions. The local conformations of the flanking Ala-Gly repeating regions as well as the calcium-binding motif, MSI60, were determined by 13C CP/MAS NMR spectroscopy. The secondary structures of the polyalanine, poly(Ala), domains were modified by the solvent treatments in a predictable fashion, suggesting that only the solvent treatment and not the conformation of the MSI60 domain affected the conformation of poly(Ala) regions. Ala-Gly domains behaved differently, taking random coil conformation regardless of the choice of solvent, indicating that their secondary structure is affected by the central MSI60 domain. The conformation of the MSI60 domain is not altered by the solvent treatments, suggesting that it may retain its ability to bind calcium ions. This was confirmed using a calcium-binding assay. The assay further showed that the calcium-binding capability of MSI60 in the synthetic peptides was most effective when the flanking domain was in the beta-sheet structure.     

Calorimetric and Fourier transform infrared spectroscopic study of solid proteins immersed in low water organic solvents.

Calorimetric heat effects and structural rearrangements assessed by means of Fourier transform infrared (FTIR) amide I spectra were followed by immersing dry human serum albumin and bovine pancreatic alpha-chymotrypsin in low water organic solvents and in pure water at 298 K. Enthalpy changes upon immersion of the proteins in different media are in a good linear correlation with the corresponding IR absorbance changes. Based on calorimetric and FTIR data the solvents were divided into two groups. The first group includes carbon tetrachloride, benzene, nitromethane, acetonitrile, 1,4-dioxane, n-butanol, n-propanol and pyridine where no significant heat evolution and structural changes were found during protein immersion. Due to kinetic reasons no significant protein-solvent interactions are expected in such systems. The second group of solvents includes dimethyl sulfoxide, methanol, ethanol, and water. Immersion of proteins in these media results in protein swelling and involves significant exothermic heat evolution and structural changes in the protein. Dividing of different media in the two groups is in a qualitative correlation with the solvent hydrophilicity defined as partial excess molar Gibbs free energy of water at infinite dilution in a given solvent. The first group includes the solvents with hydrophilicity exceeding 2.7 kJ/mol. More hydrophilic second group solvents have this energy values less than 2.3 kJ/mol. The hydrogen bond donating ability of the solvents also assists in protein swelling. Hydrogen bonding between protein and solvent is assumed to be a main factor controlling the swelling of dry solid proteins in the studied solvents.     

Contemporary strategies for the stabilization of peptides in the alpha-helical conformation

Herein we review contemporary synthetic and protein design strategies to stabilize the alpha-helical motif in short peptides and miniature proteins. Advances in organometallic catalyst design, specifically for the olefin metathesis reaction, enable the use of hydrocarbon bridges to either crosslink side chains of specific residues or mimic intramolecular hydrogen bonds with carbon-carbon bonds. The resulting hydrocarbon-stapled and hydrogen bond surrogate alpha-helices provide unique synthetic ligands for targeting biomolecules. In the protein design realm, several classes of miniature proteins that display stable helical domains have been engineered and manipulated with powerful in vitro selection technologies to yield libraries of sequences that retain their helical folds. Rational re-design of these scaffolds provide distinctive reagents for the modulation of protein-protein interactions.     

PPI_SVM: Prediction of protein-protein interactions using machine learning,domain-domain affinities and frequency tables

Protein-protein interactions (PPI) control most of the biological processes in a living cell. In order to fully understand protein functions, a knowledge of protein-protein interactions is necessary. Prediction of PPI is challenging, especially when the three-dimensional structure of interacting partners is not known. Recently, a novel prediction method was proposed by exploiting physical interactions of constituent domains. We propose here a novel knowledge-based prediction method, namely PPI_SVM, which predicts interactions between two protein sequences by exploiting their domain information. We trained a two-class support vector machine on the benchmarking set of pairs of interacting proteins extracted from the Database of Interacting Proteins (DIP). The method considers all possible combinations of constituent domains between two protein sequences, unlike most of the existing approaches. Moreover, it deals with both single-domain proteins and multi domain proteins; therefore it can be applied to the whole proteome in high-throughput studies. Our machine learning classifier, following a brainstorming approach, achieves accuracy of 86%, with specificity of 95%, and sensitivity of 75%, which are better results than most previous methods that sacrifice recall values in order to boost the overall precision. Our method has on average better sensitivity combined with good selectivity on the benchmarking dataset. The PPI_SVM source code, train/test datasets and supplementary files are available freely in the public domain at: .     

A de novo peptide hexamer with a mutable channel

The design of new proteins that expand the repertoire of natural protein structures represents a formidable challenge. Success in this area would increase understanding of protein structure and present new scaffolds that could be exploited in biotechnology and synthetic biology. Here we describe the design, characterization and X-ray crystal structure of a new coiled-coil protein. The de novo sequence forms a stand-alone, parallel, six-helix bundle with a channel running through it. Although lined exclusively by hydrophobic leucine and isoleucine side chains, the 6-? channel is permeable to water. One layer of leucine residues within the channel is mutable, accepting polar aspartic acid and histidine side chains, which leads to subdivision and organization of solvent within the lumen. Moreover, these mutants can be combined to form a stable and unique (Asp-His)(3) heterohexamer. These new structures provide a basis for engineering de novo proteins with new functions.     

Predicting synthetic lethal genetic interactions in <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis> using short polypeptide clusters

Background

Protein synthetic lethal genetic interactions are useful to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions remains unclear.

Results

In this study we used the clusters of short polypeptide sequences, which are typically shorter than the classically defined protein domains, to characterize the functionalities of proteins. We developed a framework to identify significant short polypeptide clusters from yeast protein sequences, and then used these short polypeptide clusters as features to predict yeast synthetic lethal genetic interactions. The short polypeptide clusters based approach provides much higher coverage for predicting yeast synthetic lethal genetic interactions. Evaluation using experimental data sets showed that the short polypeptide clusters based approach is superior to the previous protein domain based one.

Conclusion

We were able to achieve higher performance in yeast synthetic lethal genetic interactions prediction using short polypeptide clusters as features. Our study suggests that the short polypeptide cluster may help better understand the functionalities of proteins.

     

Arginine/serine repeats are sufficient to constitute a splicing activation domain

SR proteins are essential pre-mRNA splicing factors that have been shown to bind a number of exonic splicing enhancers where they function to stimulate the splicing of adjacent introns. Members of the SR protein family contain one or two N-terminal RNA binding domains, as well as a C-terminal arginine–serine (RS) rich domain. The RS domains mediate protein–protein interactions with other RS domain containing proteins and are essential for many, but not all, SR protein functions. Hybrid proteins containing an RS domain fused to the bacteriophage MS2 coat protein are sufficient to activate enhancer-dependent splicing in HeLa cell nuclear extract when bound to the pre-mRNA. Here we report progress towards determining the protein sequence requirements for RS domain function. We show that the RS domains from non-SR proteins can also function as splicing activation domains when tethered to the pre-mRNA. Truncation experiments with the RS domain of the human SR protein 9G8 identified a 29 amino acid segment, containing 26 arginine or serine residues, that is sufficient to activate splicing when fused to MS2. We also show that synthetic domains composed solely of RS dipeptides are capable of activating splicing, although their potency is proportional to their size.     

Statistical analysis of domains in interacting protein pairs

MOTIVATION: Several methods have recently been developed to analyse large-scale sets of physical interactions between proteins in terms of physical contacts between the constituent domains, often with a view to predicting new pairwise interactions. Our aim is to combine genomic interaction data, in which domain-domain contacts are not explicitly reported, with the domain-level structure of individual proteins, in order to learn about the structure of interacting protein pairs. Our approach is driven by the need to assess the evidence for physical contacts between domains in a statistically rigorous way. RESULTS: We develop a statistical approach that assigns p-values to pairs of domain superfamilies, measuring the strength of evidence within a set of protein interactions that domains from these superfamilies form contacts. A set of p-values is calculated for SCOP superfamily pairs, based on a pooled data set of interactions from yeast. These p-values can be used to predict which domains come into contact in an interacting protein pair. This predictive scheme is tested against protein complexes in the Protein Quaternary Structure (PQS) database, and is used to predict domain-domain contacts within 705 interacting protein pairs taken from our pooled data set.     

RosettaSurf—A surface-centric computational design approach

Proteins are typically represented by discrete atomic coordinates providing an accessible framework to describe different conformations. However, in some fields proteins are more accurately represented as near-continuous surfaces, as these are imprinted with geometric (shape) and chemical (electrostatics) features of the underlying protein structure. Protein surfaces are dependent on their chemical composition and, ultimately determine protein function, acting as the interface that engages in interactions with other molecules. In the past, such representations were utilized to compare protein structures on global and local scales and have shed light on functional properties of proteins. Here we describe RosettaSurf, a surface-centric computational design protocol, that focuses on the molecular surface shape and electrostatic properties as means for protein engineering, offering a unique approach for the design of proteins and their functions. The RosettaSurf protocol combines the explicit optimization of molecular surface features with a global scoring function during the sequence design process, diverging from the typical design approaches that rely solely on an energy scoring function. With this computational approach, we attempt to address a fundamental problem in protein design related to the design of functional sites in proteins, even when structurally similar templates are absent in the characterized structural repertoire. Surface-centric design exploits the premise that molecular surfaces are, to a certain extent, independent of the underlying sequence and backbone configuration, meaning that different sequences in different proteins may present similar surfaces. We benchmarked RosettaSurf on various sequence recovery datasets and showcased its design capabilities by generating epitope mimics that were biochemically validated. Overall, our results indicate that the explicit optimization of surface features may lead to new routes for the design of functional proteins.