Internal motion in protein crystal structures

The binding states of the substrates and the environment have significant influence on protein motion. We present the analysis of such motion derived from anisotropic atomic displacement parameters (ADPs) in a set of atomic resolution protein structures. Local structural motion caused by ligand binding as well as functional loops showing cooperative patterns of motion could be inferred. The results are in line with proposed protonation states, hydrogen bonding patterns and the location of distinctly flexible regions: we could locate the mobile active site loop in a virus integrase, distinguish the subdomains in RNAse A and hydroxynitrile lyase, and reconstruct the molecular architecture in a xylanase. We demonstrate that the ADP‐based motion analysis provides information at high level of detail and that the structural changes needed for substrate attachment or release may be derived from single X‐ray structures.     

Structures of in vitro evolved binding sites on neocarzinostatin scaffold reveal unanticipated evolutionary pathways

We have recently applied in vitro evolution methods to create in Neocarzinostatin a new binding site for a target molecule unrelated to its natural ligand. The main objective of this work was to solve the structure of some of the selected binders in complex with the target molecule: testosterone. Three proteins (1a.15, 3.24 and 4.1) were chosen as representative members of sequence families that came out of the selection process within different randomization schemes. In order to evaluate ligand-induced conformational adaptation, we also determined the structure of one of the proteins (3.24) in the free and complexed forms. Surprisingly, all these mutants bind not one but two molecules of testosterone in two very different ways. The 3.24 structure revealed that the protein spontaneously evolved in the system to bind two ligand molecules in one single binding crevice. These two binding sites are formed by substituted as well as by non-variable side-chains. The comparison with the free structure shows that only limited structural changes are observed upon ligand binding. The X-ray structures of the complex formed by 1a.15 and 4.1 Neocarzinostatin mutants revealed that the two variants form very similar dimers. These dimers were observed neither for the uncomplexed variants nor for wild-type Neocarzinostatin but were shown here to be induced by ligand binding. Comparison of the three complexed forms clearly suggests that these unanticipated structural responses resulted from the molecular arrangement used for the selection experiments.     

Anchored design of protein-protein interfaces

Background

Few existing protein-protein interface design methods allow for extensive backbone rearrangements during the design process. There is also a dichotomy between redesign methods, which take advantage of the native interface, and de novo methods, which produce novel binders.

Methodology

Here, we propose a new method for designing novel protein reagents that combines advantages of redesign and de novo methods and allows for extensive backbone motion. This method requires a bound structure of a target and one of its natural binding partners. A key interaction in this interface, the anchor, is computationally grafted out of the partner and into a surface loop on the design scaffold. The design scaffold''s surface is then redesigned with backbone flexibility to create a new binding partner for the target. Careful choice of a scaffold will bring experimentally desirable characteristics into the new complex. The use of an anchor both expedites the design process and ensures that binding proceeds against a known location on the target. The use of surface loops on the scaffold allows for flexible-backbone redesign to properly search conformational space.

Conclusions and Significance

This protocol was implemented within the Rosetta3 software suite. To demonstrate and evaluate this protocol, we have developed a benchmarking set of structures from the PDB with loop-mediated interfaces. This protocol can recover the correct loop-mediated interface in 15 out of 16 tested structures, using only a single residue as an anchor.     

NMR solution structure of the inserted domain of human leukocyte function associated antigen-1

The interaction between the leukocyte function-associated antigen-1 (LFA-1) and the intercellular adhesion molecule is thought to be mediated primarily via the inserted domain (I-domain) in the alpha-subunit. The activation of LFA-1 is an early step in triggering the adhesion of leukocytes to target cells decorated with intercellular adhesion molecules. There is some disagreement in the literature over the respective roles of conformational changes in the I-domain and of divalent cations (Mg(2+), Mn(2+)) in the activation of LFA-1 for intercellular adhesion molecule binding. X-ray crystallographic structures of the I-domains of LFA-1 and Mac-1 in the presence and absence of cations show structural differences in the C-terminal alpha-helix; this change was proposed to represent the active and inactive conformations of the I-domain. However, more recent X-ray results have called this proposal into question. The solution structure of the Mg(2+) complex of the I-domain of LFA-1 has been determined by NMR methods, using a model-based approach to nuclear Overhauser enhancement spectroscopy peak assignment. The protein adopts the same structure in solution as that of the published I-domain X-ray structures, but the C-terminal region, where the X-ray structures are most different from each other, is different again in the solution structures. The secondary structure of this helix is well formed, but NMR relaxation data indicate that there is considerable flexibility present, probably consisting of breathing or segmental motion of the helix. The conformational diversity seen in the various X-ray structures could be explained as a result of the inherent flexibility of this C-terminal region and as a result of crystal contacts. Our NMR data are consistent with a model where the C-terminal helix has the potential flexibility to take up alternative conformations, for example, in the presence and absence of the intercellular adhesion molecule ligand. The role of divalent cations appears from our results not to be as a direct mediator of a conformational change that alters affinity for the ligand. Rather, the presence of the cation appears to be involved in some other way in ligand binding, perhaps by acting as a bridge to the ligand and by modulation of the charge of the binding surface.     

Errata

Abstract

Mass spectrometry (MS)-based proteomics is an unrivaled tool for studying complex biological systems and diseases in the post-genomic era. In recent years, MS has emerged as a powerful structural biological tool to characterize protein conformation and conformational dynamics. The advantages of MS in structural studies are most evident for membrane proteins such as GPCRs (G protein-coupled receptors), where other well-established structural methods such as X-ray crystallography and NMR remain challenging. For proteins with available high-resolution structures, MS-based structural strategies can provide valuable, previously inaccessible information on protein conformational changes and dynamics, protein motion/flexibility, ligand–protein binding, and protein–protein interfaces. In the past several years, we have developed and adapted a number of MS-based structural approaches, such as CDSiL-MS (Conformational changes and Dynamics using Stable-isotope Labeling and MS), CXMS (Crosslinking/MS) and HDXMS (Hydrogen-Deuterium Exchange MS), to study protein structures and conformational dynamics in human β2-adrenegic receptor (β2AR) signaling. In this mini-review, we will highlight several examples demonstrating the power of MS in structural analysis to better elucidate the structural basis of GPCR signaling, particularly through the β-arrestin-mediated GPCR signaling pathway.     

Is a Malleable Protein Necessarily Highly Dynamic? The Hydrophobic Core of the Nuclear Coactivator Binding Domain Is Well Ordered

The nuclear coactivator binding domain of CREB binding protein folds into remarkably different structures in complex with different ligands. To understand the mechanism of the structural adaptability in the nuclear coactivator binding domain (NCBD), we have compared the dynamics of the hydrophobic core of NCBD in the ligand-free state and in a well-folded complex with the ligand activator for thyroid hormone and retinoid receptors using multiple NMR methods including methyl chemical shifts, coupling constants, and methyl order parameters. From all NMR measures, the aliphatic side chains in the hydrophobic core are slightly more dynamic in the free protein than in the complex, but have mobility comparable to the hydrophobic cores of average folded proteins. Urea titration monitored by NMR reveals that all parts of the protein, including the side-chain packing in the hydrophobic core, denatures in a single cooperative process. The molten globule characteristics of NCBD are thus restricted to a slowly fluctuating tertiary structure. Consequently, the conformational plasticity of the protein is most likely related to its low overall stability rather than an intrinsically flexible protein structure. The well-defined structure supports a model of molecular recognition dominated by conformational selection, whereas only minor structural adjustments are necessary after the association.     

Global and local dynamics of the U1A polyadenylation inhibition element (PIE) RNA and PIE RNA-U1A complexes

The structure and dynamics of the polyadenylation inhibition element (PIE) RNA, free and bound to the U1A protein, have been examined using time-resolved FRET and 2-aminopurine (2AP) fluorescence. This regulatory RNA, located at the 3' end of the U1A pre-mRNA, adopts a U-shaped structure, with binding sites for a single U1A protein at each bend (box 1 and box 2). The distance between the termini of the arms of the RNA is sensitive to its three-dimensional structure. Using Cy3/Cy5 FRET efficiency to monitor binding of Mg(2+), we show that the PIE RNA binds two Mg(2+) ions, which results in a restriction of its distance distribution of conformations. Local RNA structure probing using 2AP fluorescence shows that the structure of box 2 changes in response to Mg(2+) binding, thus tentatively locating the ion binding sites. Steady-state FRET data show that the distance R between the termini of the PIE RNA stems decreases from 66 A in the free RNA, to 58 A when N-terminal RNA binding domains (RBD1) of U1A are bound, and to 53 A when U1A proteins bind. However, anisotropy measurements indicate that both Cy3 and Cy5 stack on the ends of the RNA. To examine the consequences of the restricted motion of the fluorophores, FRET data are analyzed using two different models of motion and then compared to analogous data from the Cy3/fluorescein FRET pair. We conclude that the error introduced into distance calculations by stacking of the dyes is within the error of our measurements. Distance distributions of the RNA structures show that the intramolecular distance between the arms of the PIE RNA varies on the time scale of the fluorescence measurements; the mean distance is dependent on protein binding, but the breadth of the distributions indicates that the RNA retains structural heterogeneity.     

Concerted folding and binding of a flexible colicin domain to its periplasmic receptor TolA

Compared with folded structures, natively unfolded protein domains are over-represented in protein-protein and protein-DNA interactions. Such domains are common features of all colicins and are required for their translocation across the outer membrane of the target Escherichia coli cell. All of these domains bind to at least one periplasmic protein of the Tol or Ton family. Similar domains are found in Ton-dependent outer membrane transporters, indicating they may interact in a related manner. In this article we have studied binding of the colicin N translocation domain to its periplasmic receptor TolA, by fluorescence resonance energy transfer (FRET) using fluorescent probes attached to engineered cysteine residues and NMR techniques. The domain exhibits a random coil circular dichroism spectrum. However, FRET revealed that guanidinium hydrochloride denaturation caused increases in all measured intramolecular distances showing that, although natively unfolded, the domain is not extended. Furthermore NMR reported a compact hydrodynamic radius of 18 A. Nevertheless the FRET-derived distances changed upon binding to TolA indicating a significant structural rearrangement. Using 1H-15N NMR we show that, when bound, the peptide switches from a disordered state to an ordered state. The kinetics of binding and the associated structural change were measured by stopped-flow methods, and both events appear to occur simultaneously. The data therefore suggest that this molecular recognition involves the concerted binding and folding of a flexible but collapsed state.     

Structure of human Ki67 FHA domain and its binding to a phosphoprotein fragment from hNIFK reveal unique recognition sites and new views to the structural basis of FHA domain functions

Recent studies by use of short phosphopeptides showed that forkhead-associated (FHA) domains recognize pTXX(D/I/L) motifs. Solution structures and crystal structures of several different FHA domains and their complexes with short phosphopeptides have been reported by several groups. We now report the solution structure of the FHA domain of human Ki67, a large nuclear protein associated with the cell-cycle. Using fragments of its binding partner hNIFK, we show that Ki67-hNIFK binding involves ca 44 residues without a pTXX(D/I/L) motif. The pThr site of hNIFK recognized by Ki67 FHA is pThr234-Pro235, a motif also recognized by the proline isomerase Pin1. Heteronuclear single quantum coherence (HSQC) NMR was then used to map out the binding surface, and structural analyses were used to identify key binding residues of Ki67 FHA. The results represent the first structural characterization of the complex of an FHA domain with a biologically relevant target protein fragment. Detailed analyses of the results led us to propose that three major factors control the interaction of FHA with its target protein: the pT residue, +1 to +3 residues, and an extended binding surface, and that variation in the three factors is the likely cause of the great diversity in the function and specificity of FHA domains from different sources.     

DynaBiS: A hierarchical sampling algorithm to identify flexible binding sites for large ligands and peptides

Knowing the ligand or peptide binding site in proteins is highly important to guide drug discovery, but experimental elucidation of the binding site is difficult. Therefore, various computational approaches have been developed to identify potential binding sites in protein structures. However, protein and ligand flexibility are often neglected in these methods due to efficiency considerations despite the recognition that protein–ligand interactions can be strongly affected by mutual structural adaptations. This is particularly true if the binding site is unknown, as the screening will typically be performed based on an unbound protein structure. Herein we present DynaBiS, a hierarchical sampling algorithm to identify flexible binding sites for a target ligand with explicit consideration of protein and ligand flexibility, inspired by our previously presented flexible docking algorithm DynaDock. DynaBiS applies soft-core potentials between the ligand and the protein, thereby allowing a certain protein–ligand overlap resulting in efficient sampling of conformational adaptation effects. We evaluated DynaBiS and other commonly used binding site identification algorithms against a diverse evaluation set consisting of 26 proteins featuring peptide as well as small ligand binding sites. We show that DynaBiS outperforms the other evaluated methods for the identification of protein binding sites for large and highly flexible ligands such as peptides, both with a holo or apo structure used as input.     

Vorolign--fast structural alignment using Voronoi contacts

Vorolign, a fast and flexible structural alignment method for two or more protein structures is introduced. The method aligns protein structures using double dynamic programming and measures the similarity of two residues based on the evolutionary conservation of their corresponding Voronoi-contacts in the protein structure. This similarity function allows aligning protein structures even in cases where structural flexibilities exist. Multiple structural alignments are generated from a set of pairwise alignments using a consistency-based, progressive multiple alignment strategy. RESULTS: The performance of Vorolign is evaluated for different applications of protein structure comparison, including automatic family detection as well as pairwise and multiple structure alignment. Vorolign accurately detects the correct family, superfamily or fold of a protein with respect to the SCOP classification on a set of difficult target structures. A scan against a database of >4000 proteins takes on average 1 min per target. The performance of Vorolign in calculating pairwise and multiple alignments is found to be comparable with other pairwise and multiple protein structure alignment methods. AVAILABILITY: Vorolign is freely available for academic users as a web server at http://www.bio.ifi.lmu.de/Vorolign     

Structural Basis of the Action of Glucosyltransferase Lgt1 from Legionella pneumophila

The glucosyltransferase Lgt1 is one of three glucosylating toxins of Legionella pneumophila, the causative agent of Legionnaires disease. It acts through specific glucosylation of a serine residue (S53) in the eukaryotic elongation factor 1A and belongs to type A glycosyltransferases. High-resolution crystal structures of Lgt1 show an elongated shape of the protein, with the binding site for uridine disphosphate glucose at the bottom of a deep cleft. Lgt1 shows only a low sequence identity with other type A glycosyltransferases, and structural conservation is limited to a central folding core that is usually observed within this family of proteins. Domains and protrusions added to the core motif represent determinants for the specific recognition and binding of the target. Manual docking experiments based on the crystal structures of toxin and target protein suggest an obvious mode of binding to the target that allows for efficient transfer of a glucose moiety.     

Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking

One approach to incorporate protein flexibility in molecular docking is the use of an ensemble consisting of multiple protein structures. Sequentially docking each ligand into a large number of protein structures is computationally too expensive to allow large-scale database screening. It is challenging to achieve a good balance between docking accuracy and computational efficiency. In this work, we have developed a fast, novel docking algorithm utilizing multiple protein structures, referred to as ensemble docking, to account for protein structural variations. The algorithm can simultaneously dock a ligand into an ensemble of protein structures and automatically select an optimal protein structure that best fits the ligand by optimizing both ligand coordinates and the conformational variable m, where m represents the m-th structure in the protein ensemble. The docking algorithm was validated on 10 protein ensembles containing 105 crystal structures and 87 ligands in terms of binding mode and energy score predictions. A success rate of 93% was obtained with the criterion of root-mean-square deviation <2.5 A if the top five orientations for each ligand were considered, comparable to that of sequential docking in which scores for individual docking are merged into one list by re-ranking, and significantly better than that of single rigid-receptor docking (75% on average). Similar trends were also observed in binding score predictions and enrichment tests of virtual database screening. The ensemble docking algorithm is computationally efficient, with a computational time comparable to that for docking a ligand into a single protein structure. In contrast, the computational time for the sequential docking method increases linearly with the number of protein structures in the ensemble. The algorithm was further evaluated using a more realistic ensemble in which the corresponding bound protein structures of inhibitors were excluded. The results show that ensemble docking successfully predicts the binding modes of the inhibitors, and discriminates the inhibitors from a set of noninhibitors with similar chemical properties. Although multiple experimental structures were used in the present work, our algorithm can be easily applied to multiple protein conformations generated by computational methods, and helps improve the efficiency of other existing multiple protein structure(MPS)-based methods to accommodate protein flexibility.     

Ligand-induced conformational changes: improved predictions of ligand binding conformations and affinities

A computational docking strategy using multiple conformations of the target protein is discussed and evaluated. A series of low molecular weight, competitive, nonpeptide protein tyrosine phosphatase inhibitors are considered for which the x-ray crystallographic structures in complex with protein tyrosine phosphatase 1B (PTP1B) are known. To obtain a quantitative measure of the impact of conformational changes induced by the inhibitors, these were docked to the active site region of various structures of PTP1B using the docking program FlexX. Firstly, the inhibitors were docked to a PTP1B crystal structure cocrystallized with a hexapeptide. The estimated binding energies for various docking modes as well as the RMS differences between the docked compounds and the crystallographic structure were calculated. In this scenario the estimated binding energies were not predictive inasmuch as docking modes with low estimated binding energies corresponded to relatively large RMS differences when aligned with the corresponding crystal structure. Secondly, the inhibitors were docked to their parent protein structures in which they were cocrystallized. In this case, there was a good correlation between low predicted binding energy and a correct docking mode. Thirdly, to improve the predictability of the docking procedure in the general case, where only a single target protein structure is known, we evaluate an approach which takes possible protein side-chain conformational changes into account. Here, side chains exposed to the active site were considered in their allowed rotamer conformations and protein models containing all possible combinations of side-chain rotamers were generated. To evaluate which of these modeled active sites is the most likely binding site conformation for a certain inhibitor, the inhibitors were docked against all active site models. The receptor rotamer model corresponding to the lowest estimated binding energy is taken as the top candidate. Using this protocol, correct inhibitor binding modes could successfully be discriminated from proposed incorrect binding modes. Moreover, the ranking of the estimated ligand binding energies was in good agreement with experimentally observed binding affinities.     

Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM

Prediction of protein-protein interactions at the structural level on the proteome scale is important because it allows prediction of protein function, helps drug discovery and takes steps toward genome-wide structural systems biology. We provide a protocol (termed PRISM, protein interactions by structural matching) for large-scale prediction of protein-protein interactions and assembly of protein complex structures. The method consists of two components: rigid-body structural comparisons of target proteins to known template protein-protein interfaces and flexible refinement using a docking energy function. The PRISM rationale follows our observation that globally different protein structures can interact via similar architectural motifs. PRISM predicts binding residues by using structural similarity and evolutionary conservation of putative binding residue 'hot spots'. Ultimately, PRISM could help to construct cellular pathways and functional, proteome-scale annotation. PRISM is implemented in Python and runs in a UNIX environment. The program accepts Protein Data Bank-formatted protein structures and is available at http://prism.ccbb.ku.edu.tr/prism_protocol/.     

Structural and functional analysis of Saccharomyces cerevisiae Mob1

The Mob proteins function as activator subunits for the Dbf2/Dbf20 family of protein kinases. Human and Xenopus Mob1 protein structures corresponding to the most conserved C-terminal core, but lacking the variable N-terminal region, have been reported and provide a framework for understanding the mechanism of Dbf2/Dbf20 regulation. Here, we report the 2.0 A X-ray crystal structure of Saccharomyces cerevisiae Mob1 containing both the conserved C-terminal core and the variable N-terminal region. Within the N-terminal region, three novel structural elements are observed; namely, an alpha-helix denoted H0, a strand-like element denoted S0 and a short beta strand denoted S-1. Helix H0 associates in an intermolecular manner with a second Mob1 molecule to form a Mob1 homodimer. Strand S0 binds to the core domain in an intramolecular manner across a putative Dbf2 binding site mapped by Mob1 temperature-sensitive alleles and NMR binding experiments. In vivo functional analysis demonstrates that Mob1 mutants that target helix H0 or its reciprocal binding site are biologically compromised. The N-terminal region of Mob1 thus contains structural elements that are functionally important.     

Quantitative theory of hydrophobic effect as a driving force of protein structure

Various studies suggest that the hydrophobic effect plays a major role in driving the folding of proteins. In the past, however, it has been challenging to translate this understanding into a predictive, quantitative theory of how the full pattern of sequence hydrophobicity in a protein shapes functionally important features of its tertiary structure. Here, we extend and apply such a phenomenological theory of the sequence‐structure relationship in globular protein domains, which had previously been applied to the study of allosteric motion. In an effort to optimize parameters for the model, we first analyze the patterns of backbone burial found in single‐domain crystal structures, and discover that classic hydrophobicity scales derived from bulk physicochemical properties of amino acids are already nearly optimal for prediction of burial using the model. Subsequently, we apply the model to studying structural fluctuations in proteins and establish a means of identifying ligand‐binding and protein–protein interaction sites using this approach.     

Comparative analysis of nanobody sequence and structure data

Nanobodies are a class of antigen‐binding protein derived from camelids that achieve comparable binding affinities and specificities to classical antibodies, despite comprising only a single 15 kDa variable domain. Their reduced size makes them an exciting target molecule with which we can explore the molecular code that underpins binding specificity—how is such high specificity achieved? Here, we use a novel dataset of 90 nonredundant, protein‐binding nanobodies with antigen‐bound crystal structures to address this question. To provide a baseline for comparison we construct an analogous set of classical antibodies, allowing us to probe how nanobodies achieve high specificity binding with a dramatically reduced sequence space. Our analysis reveals that nanobodies do not diversify their framework region to compensate for the loss of the VL domain. In addition to the previously reported increase in H3 loop length, we find that nanobodies create diversity by drawing their paratope regions from a significantly larger set of aligned sequence positions, and by exhibiting greater structural variation in their H1 and H2 loops.