Directed evolution of prenylated FMN-dependent Fdc supports efficient in vivo isobutene production.

Isobutene is a high value gaseous alkene used as fuel additive and a chemical building block. As an alternative to fossil fuel derived isobutene, we here develop a modified mevalonate pathway for the production of isobutene from glucose in vivo. The final step in the pathway consists of the decarboxylation of 3-methylcrotonic acid, catalysed by an evolved ferulic acid decarboxylase (Fdc) enzyme. Fdc belongs to the prFMN-dependent UbiD enzyme family that catalyses reversible decarboxylation of (hetero)aromatic acids or acrylic acids with extended conjugation. Following a screen of an Fdc library for inherent 3-methylcrotonic acid decarboxylase activity, directed evolution yields variants with up to an 80-fold increase in activity. Crystal structures of the evolved variants reveal that changes in the substrate binding pocket are responsible for increased selectivity. Solution and computational studies suggest that isobutene cycloelimination is rate limiting and strictly dependent on presence of the 3-methyl group.

Production of unstable proteins through the formation of stable core complexes.

Purification of proteins that participate in large transient complexes is impeded by low amounts, heterogeneity, instability and poor solubility. To circumvent these difficulties we set up a methodology that enables the production of stable complexes for structural and functional studies. This procedure is benchmarked and applied to two challenging protein families: the human steroid nuclear receptors (SNR) and the HIV-1 pre-integration complex. In the context of transcriptional regulation studies, we produce and characterize the ligand-binding domains of the glucocorticoid nuclear receptor and the oestrogen receptor beta in complex with a TIF2 (transcriptional intermediary factor 2) domain containing the three SNR-binding motifs. In the context of retroviral integration, we demonstrate the stabilization of the HIV-1 integrase by formation of complexes with partner proteins and DNA. This procedure provides a powerful research tool for structural and functional studies of proteins participating in non-covalent macromolecular complexes.

HSPA8/HSC70 chaperone protein: structure, function, and chemical targeting.

HSPA8/HSC70 protein is a fascinating chaperone protein. It represents a constitutively expressed, cognate protein of the HSP70 family, which is central in many cellular processes. In particular, its regulatory role in autophagy is decisive. We focused this review on HSC70 structure-function considerations and based on this, we put a particular emphasis on HSC70 targeting by small molecules and peptides in order to develop intervention strategies that deviate some of HSC70 properties for therapeutic purposes. Generating active biomolecules regulating autophagy via its effect on HSC70 can effectively be designed only if we understand the fine relationships between HSC70 structure and functions.

Engineering of weak helper interactions for high-efficiency FRET probes.

Fluorescence resonance energy transfer (FRET)-based detection of protein interactions is limited by the very narrow range of FRET-permitting distances. We show two different strategies for the rational design of weak helper interactions that co-recruit donor and acceptor fluorophores for a more robust detection of bimolecular FRET: (i) in silico design of electrostatically driven encounter complexes and (ii) fusion of tunable domain-peptide interaction modules based on WW or SH3 domains. We tested each strategy for optimization of FRET between (m)Citrine and mCherry, which do not natively interact. Both approaches yielded comparable and large increases in FRET efficiencies with little or no background. Helper-interaction modules can be fused to any pair of fluorescent proteins and could, we found, enhance FRET between mTFP1 and mCherry as well as between mTurquoise2 and mCitrine. We applied enhanced helper-interaction FRET (hiFRET) probes to study the binding between full-length H-Ras and Raf1 as well as the drug-induced interaction between Raf1 and B-Raf.

E-cadherin destabilization accounts for the pathogenicity of missense mutations in hereditary diffuse gastric cancer.

E-cadherin is critical for the maintenance of tissue architecture due to its role in cell-cell adhesion. E-cadherin mutations are the genetic cause of Hereditary Diffuse Gastric Cancer (HDGC) and missense mutations represent a clinical burden, due to the uncertainty of their pathogenic role. In vitro and in vivo, most mutations lead to loss-of-function, although the causal factor is unknown for the majority. We hypothesized that destabilization could account for the pathogenicity of E-cadherin missense mutations in HDGC, and tested our hypothesis using in silico and in vitro tools. FoldX algorithm was used to calculate the impact of each mutation in E-cadherin native-state stability, and the analysis was complemented with evolutionary conservation, by SIFT. Interestingly, HDGC patients harbouring germline E-cadherin destabilizing mutants present a younger age at diagnosis or death, suggesting that the loss of native-state stability of E-cadherin accounts for the disease phenotype. To elucidate the biological relevance of E-cadherin destabilization in HDGC, we investigated a group of newly identified HDGC-associated mutations (E185V, S232C and L583R), of which L583R is predicted to be destabilizing. We show that this mutation is not functional in vitro, exhibits shorter half-life and is unable to mature, due to premature proteasome-dependent degradation, a phenotype reverted by stabilization with the artificial mutation L583I (structurally tolerated). Herein we report E-cadherin structural models suitable to predict the impact of the majority of cancer-associated missense mutations and we show that E-cadherin destabilization leads to loss-of-function in vitro and increased pathogenicity in vivo.

A graphical interface for the FoldX forcefield.

SUMMARY: A graphical user interface for the FoldX protein design program has been developed as a plugin for the YASARA molecular graphics suite. The most prominent FoldX commands such as free energy difference upon mutagenesis and interaction energy calculations can now be run entirely via a windowed menu system and the results are immediately shown on screen. AVAILABILITY AND IMPLEMENTATION: The plugin is written in Python and is freely available for download at http://foldxyasara.switchlab.org/ and supported on Linux, MacOSX and MS Windows.

Molecular basis of engineered meganuclease targeting of the endogenous human RAG1 locus.

Homing endonucleases recognize long target DNA sequences generating an accurate double-strand break that promotes gene targeting through homologous recombination. We have modified the homodimeric I-CreI endonuclease through protein engineering to target a specific DNA sequence within the human RAG1 gene. Mutations in RAG1 produce severe combined immunodeficiency (SCID), a monogenic disease leading to defective immune response in the individuals, leaving them vulnerable to infectious diseases. The structures of two engineered heterodimeric variants and one single-chain variant of I-CreI, in complex with a 24-bp oligonucleotide of the human RAG1 gene sequence, show how the DNA binding is achieved through interactions in the major groove. In addition, the introduction of the G19S mutation in the neighborhood of the catalytic site lowers the reaction energy barrier for DNA cleavage without compromising DNA recognition. Gene-targeting experiments in human cell lines show that the designed single-chain molecule preserves its in vivo activity with higher specificity, further enhanced by the G19S mutation. This is the first time that an engineered meganuclease variant targets the human RAG1 locus by stimulating homologous recombination in human cell lines up to 265 bp away from the cleavage site. Our analysis illustrates the key features for à la carte procedure in protein-DNA recognition design, opening new possibilities for SCID patients whose illness can be treated ex vivo.

BriX: a database of protein building blocks for structural analysis, modeling and design.

High-resolution structures of proteins remain the most valuable source for understanding their function in the cell and provide leads for drug design. Since the availability of sufficient protein structures to tackle complex problems such as modeling backbone moves or docking remains a problem, alternative approaches using small, recurrent protein fragments have been employed. Here we present two databases that provide a vast resource for implementing such fragment-based strategies. The BriX database contains fragments from over 7000 non-homologous proteins from the Astral collection, segmented in lengths from 4 to 14 residues and clustered according to structural similarity, summing up to a content of 2 million fragments per length. To overcome the lack of loops classified in BriX, we constructed the Loop BriX database of non-regular structure elements, clustered according to end-to-end distance between the regular residues flanking the loop. Both databases are available online (http://brix.crg.es) and can be accessed through a user-friendly web-interface. For high-throughput queries a web-based API is provided, as well as full database downloads. In addition, two exciting applications are provided as online services: (i) user-submitted structures can be covered on the fly with BriX classes, representing putative structural variation throughout the protein and (ii) gaps or low-confidence regions in these structures can be bridged with matching fragments.

Analysis of disease-linked rhodopsin mutations based on structure, function, and protein stability calculations.

Retinitis pigmentosa (RP) refers to a heterogeneous group of inherited diseases that result in progressive retinal degeneration, characterized by visual field constriction and night blindness. A total of 103 mutations in rhodopsin are linked to RP to date, and the phenotypes range from severe to asymptomatic. To study the relation between phenotype and rhodopsin stability in disease mutants, we used a structure-based approach. For 12 of the mutants located at the protein-lipid interphase, we used the von Heijne water-membrane transfer scale, and we find that 9 of the mutations could affect membrane insertion. For 91 mutants, we used the protein design algorithm FoldX. The 3 asymptomatic mutations had no significant reduced stability, 2 were unsuitable for FoldX analysis since the structure was incorrect in this region, 63 mutations had a significant change in protein stability (>1.6 kcal/mol), and 23 mutations had energy change values under the prediction error threshold (<1.6 kcal/mol). Out of these 23, the disease-causing effect could be explained by the involvement in other functions (e.g., glycosylation motifs, the interface with arrestin and transducin, and the cilia-binding motif) for 19 mutants. The remaining 4 mutants were probably incorrectly associated with RP or have functionalities not discovered yet. For destabilizing mutations where clinical data were available, we found a highly significant correlation between FoldX energy changes and the average age of night blindness and between FoldX energy changes and daytime vision loss onset. Our detailed structural, functional, and energetic analysis provides a complete picture of the rhodopsin mutations and can guide mutation-specific therapies.

Using protein design algorithms to understand the molecular basis of disease caused by protein-DNA interactions: the Pax6 example.

Quite often a single or a combination of protein mutations is linked to specific diseases. However, distinguishing from sequence information which mutations have real effects in the protein's function is not trivial. Protein design tools are commonly used to explain mutations that affect protein stability, or protein-protein interaction, but not for mutations that could affect protein-DNA binding. Here, we used the protein design algorithm FoldX to model all known missense mutations in the paired box domain of Pax6, a highly conserved transcription factor involved in eye development and in several diseases such as aniridia. The validity of FoldX to deal with protein-DNA interactions was demonstrated by showing that high levels of accuracy can be achieved for mutations affecting these interactions. Also we showed that protein-design algorithms can accurately reproduce experimental DNA-binding logos. We conclude that 88% of the Pax6 mutations can be linked to changes in intrinsic stability (77%) and/or to its capabilities to bind DNA (30%). Our study emphasizes the importance of structure-based analysis to understand the molecular basis of diseases and shows that protein-DNA interactions can be analyzed to the same level of accuracy as protein stability, or protein-protein interactions.

T-RMSD: a fine-grained, structure-based classification method and its application to the functional characterization of TNF receptors.

This study addresses the relation between structural and functional similarity in proteins. We introduce a novel method named tree based on root mean square deviation (T-RMSD), which uses distance RMSD (dRMSD) variations to build fine-grained structure-based classifications of proteins. The main improvement of the T-RMSD over similar methods, such as Dali, is its capacity to produce the equivalent of a bootstrap value for each cluster node. We validated our approach on two domain families studied extensively for their role in many biological and pathological pathways: the small GTPase RAS superfamily and the cysteine-rich domains (CRDs) associated with the tumor necrosis factor receptors (TNFRs) family. Our analysis showed that T-RMSD is able to automatically recover and refine existing classifications. In the case of the small GTPase ARF subfamily, T-RMSD can distinguish GTP- from GDP-bound states, while in the case of CRDs it can identify two new subgroups associated with well defined functional features (ligand binding and formation of ligand pre-assembly complex). We show how hidden Markov models (HMMs) can be built on these new groups and propose a methodology to use these models simultaneously in order to do fine-grained functional genomic annotation without known 3D structures. T-RMSD, an open source freeware incorporated in the T-Coffee package, is available online.

PepX: a structural database of non-redundant protein-peptide complexes.

Although protein-peptide interactions are estimated to constitute up to 40% of all protein interactions, relatively little information is available for the structural details of these interactions. Peptide-mediated interactions are a prime target for drug design because they are predominantly present in signaling and regulatory networks. A reliable data set of nonredundant protein-peptide complexes is indispensable as a basis for modeling and design, but current data sets for protein-peptide interactions are often biased towards specific types of interactions or are limited to interactions with small ligands. In PepX (http://pepx.switchlab.org), we have designed an unbiased and exhaustive data set of all protein-peptide complexes available in the Protein Data Bank with peptide lengths up to 35 residues. In addition, these complexes have been clustered based on their binding interfaces rather than sequence homology, providing a set of structurally diverse protein-peptide interactions. The final data set contains 505 unique protein-peptide interface clusters from 1431 complexes. Thorough annotation of each complex with both biological and structural information facilitates searching for and browsing through individual complexes and clusters. Moreover, we provide an additional source of data for peptide design by annotating peptides with naturally occurring backbone variations using fragment clusters from the BriX database.

Protein-peptide interactions adopt the same structural motifs as monomeric protein folds.

We compared the modes of interaction between protein-peptide interfaces and those observed within monomeric proteins and found surprisingly few differences. Over 65% of 731 protein-peptide interfaces could be reconstructed within 1 A RMSD using solely fragment interactions occurring in monomeric proteins. Interestingly, more than 80% of interacting fragments used in reconstructing a protein-peptide binding site were obtained from monomeric proteins of an entirely different structural classification, with an average sequence identity below 15%. Nevertheless, geometric properties perfectly match the interaction patterns observed within monomeric proteins. We show the usefulness of our approach by redesigning the interaction scaffold of nine protein-peptide complexes, for which five of the peptides can be modeled within 1 A RMSD of the original peptide position. These data suggest that the wealth of structural data on monomeric proteins could be harvested to model protein-peptide interactions and, more importantly, that sequence homology is no prerequisite.

Protein design in biological networks: from manipulating the input to modifying the output.

Protein engineering has been an invaluable tool for the deciphering of protein folding and function and in the understanding of biological signaling networks. From an applied point of view it has been of paramount importance in biotechnological and biopharmaceutical products and applications. Traditionally, the protein engineering tools of choice were 'classical' rational design, or directed evolution-based methods. In recent years, a third tool has matured: computational protein design (CPD). In this review, we summarize the underlying principles of CPD and discuss its application for understanding and modifying biological systems. Three main applications of the use of protein design will be highlighted and reviewed: artificially rewiring of signal transduction networks, prediction and generation of large-scale in silico interaction networks and using protein design to manipulate gene expression.

Molecular basis of xeroderma pigmentosum group C DNA recognition by engineered meganucleases.

Xeroderma pigmentosum is a monogenic disease characterized by hypersensitivity to ultraviolet light. The cells of xeroderma pigmentosum patients are defective in nucleotide excision repair, limiting their capacity to eliminate ultraviolet-induced DNA damage, and resulting in a strong predisposition to develop skin cancers. The use of rare cutting DNA endonucleases-such as homing endonucleases, also known as meganucleases-constitutes one possible strategy for repairing DNA lesions. Homing endonucleases have emerged as highly specific molecular scalpels that recognize and cleave DNA sites, promoting efficient homologous gene targeting through double-strand-break-induced homologous recombination. Here we describe two engineered heterodimeric derivatives of the homing endonuclease I-CreI, produced by a semi-rational approach. These two molecules-Amel3-Amel4 and Ini3-Ini4-cleave DNA from the human XPC gene (xeroderma pigmentosum group C), in vitro and in vivo. Crystal structures of the I-CreI variants complexed with intact and cleaved XPC target DNA suggest that the mechanism of DNA recognition and cleavage by the engineered homing endonucleases is similar to that of the wild-type I-CreI. Furthermore, these derivatives induced high levels of specific gene targeting in mammalian cells while displaying no obvious genotoxicity. Thus, homing endonucleases can be designed to recognize and cleave the DNA sequences of specific genes, opening up new possibilities for genome engineering and gene therapy in xeroderma pigmentosum patients whose illness can be treated ex vivo.

Quantifying information transfer by protein domains: analysis of the Fyn SH2 domain structure.

BACKGROUND: Efficient communication between distant sites within a protein is essential for cooperative biological response. Although often associated with large allosteric movements, more subtle changes in protein dynamics can also induce long-range correlations. However, an appropriate formalism that directly relates protein structural dynamics to information exchange between functional sites is still lacking. RESULTS: Here we introduce a method to analyze protein dynamics within the framework of information theory and show that signal transduction within proteins can be considered as a particular instance of communication over a noisy channel. In particular, we analyze the conformational correlations between protein residues and apply the concept of mutual information to quantify information exchange. Mapping out changes of mutual information on the protein structure then allows visualizing how distal communication is achieved. We illustrate the approach by analyzing information transfer by the SH2 domain of Fyn tyrosine kinase, obtained from Monte Carlo dynamics simulations. Our analysis reveals that the Fyn SH2 domain forms a noisy communication channel that couples residues located in the phosphopeptide and specificity binding sites and a number of residues at the other side of the domain near the linkers that connect the SH2 domain to the SH3 and kinase domains. We find that for this particular domain, communication is affected by a series of contiguous residues that connect distal sites by crossing the core of the SH2 domain. CONCLUSION: As a result, our method provides a means to directly map the exchange of biological information on the structure of protein domains, making it clear how binding triggers conformational changes in the protein structure. As such it provides a structural road, next to the existing attempts at sequence level, to predict long-range interactions within protein structures.

Combinatorial optimization of a CD4-mimetic miniprotein and cocrystal structures with HIV-1 gp120 envelope glycoprotein.

Miniproteins provide a bridge between proteins and small molecules. Here we adapt methods from combinatorial chemistry to optimize CD4M33, a synthetic miniprotein into which we had previously transplanted the HIV-1 gp120 binding surface of the CD4 receptor. Iterative deconvolution of generated libraries produced CD4M47, a derivative of CD4M33 that had been optimized at four positions. Surface plasmon resonance demonstrated fourfold to sixfold improvement in CD4M47 affinity for gp120 to a level about threefold tighter than that of CD4 itself. Assessment of the neutralization properties of CD4M47 against a diverse range of isolates spanning from HIV-1 to SIVcpz showed that CD4M47 retained the extraordinary breadth of the parent CD4M33, but yielded only limited improvements in neutralization potencies. Crystal structures of CD4M47 and a phenylalanine variant ([Phe23]M47) were determined at resolutions of 2.4 and 2.6 A, in ternary complexes with HIV-1 gp120 and the 17b antibody. Analysis of these structures revealed a correlation between mimetic affinity for gp120 and overall mimetic-gp120 interactive surface. A correlation was also observed between CD4- and mimetic-induced gp120 structural similarity and CD4- and mimetic-induced gp120 affinity for the CCR5 coreceptor. Despite mimetic substitutions, including a glycine-to-(d)-proline change, the gp120 conformation induced by CD4M47 was as close or closer to the conformation induced by CD4 as the one induced by the parent CD4M33. Our results demonstrate the ability of combinatorial chemistry to optimize a disulfide-containing miniprotein, and of structural biology to decipher the resultant interplay between binding affinity, neutralization breadth, molecular mimicry, and induced affinity for CCR5.

Reconstruction of protein backbones from the BriX collection of canonical protein fragments.

As modeling of changes in backbone conformation still lacks a computationally efficient solution, we developed a discretisation of the conformational states accessible to the protein backbone similar to the successful rotamer approach in side chains. The BriX fragment database, consisting of fragments from 4 to 14 residues long, was realized through identification of recurrent backbone fragments from a non-redundant set of high-resolution protein structures. BriX contains an alphabet of more than 1,000 frequently observed conformations per peptide length for 6 different variation levels. Analysis of the performance of BriX revealed an average structural coverage of protein structures of more than 99% within a root mean square distance (RMSD) of 1 Angstrom. Globally, we are able to reconstruct protein structures with an average accuracy of 0.48 Angstrom RMSD. As expected, regular structures are well covered, but, interestingly, many loop regions that appear irregular at first glance are also found to form a recurrent structural motif, albeit with lower frequency of occurrence than regular secondary structures. Larger loop regions could be completely reconstructed from smaller recurrent elements, between 4 and 8 residues long. Finally, we observed that a significant amount of short sequences tend to display strong structural ambiguity between alpha helix and extended conformations. When the sequence length increases, this so-called sequence plasticity is no longer observed, illustrating the context dependency of polypeptide structures.

How protein stability and new functions trade off.

Numerous studies have noted that the evolution of new enzymatic specificities is accompanied by loss of the protein's thermodynamic stability (DeltaDeltaG), thus suggesting a tradeoff between the acquisition of new enzymatic functions and stability. However, since most mutations are destabilizing (DeltaDeltaG>0), one should ask how destabilizing mutations that confer new or altered enzymatic functions relative to all other mutations are. We applied DeltaDeltaG computations by FoldX to analyze the effects of 548 mutations that arose from the directed evolution of 22 different enzymes. The stability effects, location, and type of function-altering mutations were compared to DeltaDeltaG changes arising from all possible point mutations in the same enzymes. We found that mutations that modulate enzymatic functions are mostly destabilizing (average DeltaDeltaG = +0.9 kcal/mol), and are almost as destabilizing as the "average" mutation in these enzymes (+1.3 kcal/mol). Although their stability effects are not as dramatic as in key catalytic residues, mutations that modify the substrate binding pockets, and thus mediate new enzymatic specificities, place a larger stability burden than surface mutations that underline neutral, non-adaptive evolutionary changes. How are the destabilizing effects of functional mutations balanced to enable adaptation? Our analysis also indicated that many mutations that appear in directed evolution variants with no obvious role in the new function exert stabilizing effects that may compensate for the destabilizing effects of the crucial function-altering mutations. Thus, the evolution of new enzymatic activities, both in nature and in the laboratory, is dependent on the compensatory, stabilizing effect of apparently "silent" mutations in regions of the protein that are irrelevant to its function.

Genome-wide prediction of SH2 domain targets using structural information and the FoldX algorithm.

Current experiments likely cover only a fraction of all protein-protein interactions. Here, we developed a method to predict SH2-mediated protein-protein interactions using the structure of SH2-phosphopeptide complexes and the FoldX algorithm. We show that our approach performs similarly to experimentally derived consensus sequences and substitution matrices at predicting known in vitro and in vivo targets of SH2 domains. We use our method to provide a set of high-confidence interactions for human SH2 domains with known structure filtered on secondary structure and phosphorylation state. We validated the predictions using literature-derived SH2 interactions and a probabilistic score obtained from a naive Bayes integration of information on coexpression, conservation of the interaction in other species, shared interaction partners, and functions. We show how our predictions lead to a new hypothesis for the role of SH2 domains in signaling.