Structural response to mutation at a protein-protein interface

Assessing the functional impact of protein binding site definition

Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data, this approach also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also shows that methods for protein binding interface predictions should perform above approximately F-score = 0.7 accuracy level to capture the biological function of a protein.

Assessing the functional impact of protein binding site definition

Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data this approach generates, it also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also provides guidance on the minimum expected accuracy of interface definition that is required to capture the biological function of a protein.

Rational Design of Constrained Peptides as Protein Interface Inhibitors

The lack of progress in developing targeted therapeutics directed at protein–protein complexes has been due to the absence of well-defined ligand-binding pockets and the extensive intermolecular contacts at the protein–protein interface. Our laboratory has developed approaches to dissect protein–protein complexes focusing on the superfamilies of erbB and tumor necrosis factor (TNF) receptors by the combined use of structural biology and computational biology to facilitate small molecule development. We present a perspective on the development and application of peptide inhibitors as well as immunoadhesins to cell surface receptors performed in our laboratory.

Rebuilding Ring-Type Assembly of Peroxiredoxin by Chemical Modification

Direct control of the protein quaternary structure (QS) is challenging owing to the complexity of the protein structure. As a protein with a characteristic QS, peroxiredoxin from Aeropyrum pernix K1 (ApPrx) forms a decamer, wherein five dimers associate to form a ring. Here, we disrupted and reconstituted ApPrx QS via amino acid mutations and chemical modifications targeting hot spots for protein assembly. The decameric QS of an ApPrx* mutant, wherein all cysteine residues in wild-type ApPrx were mutated to serine, was destructed to dimers via an F80C mutation. The dimeric ApPrx*F80C mutant was then modified with a small molecule and successfully assembled as a decamer. Structural analysis confirmed that an artificially installed chemical moiety potentially facilitates suitable protein-protein interactions to rebuild a native structure. Rebuilding of dodecamer was also achieved through an additional amino acid mutation. This study describes a facile method to regulate the protein assembly state.

Assessing the capability of in silico mutation protocols for predicting the finite temperature conformation of amino acids

Mutation protocols are a key tool in computational biophysics for modelling unknown side chain conformations. In particular, these protocols are used to generate the starting structures for molecular dynamics simulations. The accuracy of the initial side chain and backbone placement is crucial to obtain a stable and quickly converging simulation. In this work, we assessed the performance of several mutation protocols in predicting the most probable conformer observed in finite temperature molecular dynamics simulations for a set of protein-peptide crystals differing only by single-point mutations in the peptide sequence. Our results show that several programs which predict well the crystal conformations fail to predict the most probable finite temperature configuration. Methods relying on backbone-dependent rotamer libraries have, in general, a better performance, but even the best protocol fails in predicting approximately 30% of the mutations.

SnapDock-template-based docking by Geometric Hashing

Motivation

A highly efficient template-based protein–protein docking algorithm, nicknamed SnapDock, is presented. It employs a Geometric Hashing-based structural alignment scheme to align the target proteins to the interfaces of non-redundant protein–protein interface libraries. Docking of a pair of proteins utilizing the 22 600 interface PIFACE library is performed in < 2 min on the average. A flexible version of the algorithm allowing hinge motion in one of the proteins is presented as well.

Results

To evaluate the performance of the algorithm a blind re-modelling of 3547 PDB complexes, which have been uploaded after the PIFACE publication has been performed with success ratio of about 35%. Interestingly, a similar experiment with the template free PatchDock docking algorithm yielded a success rate of about 23% with roughly 1/3 of the solutions different from those of SnapDock. Consequently, the combination of the two methods gave a 42% success ratio.

Availability and implementation

A web server of the application is under development.

Small Molecules Engage Hot Spots through Cooperative Binding To Inhibit a Tight Protein-Protein Interaction

Protein-protein interactions drive every aspect of cell signaling, yet only a few small-molecule inhibitors of these interactions exist. Despite our ability to identify critical residues known as hot spots, little is known about how to effectively engage them to disrupt protein-protein interactions. Here, we take advantage of the ease of preparation and stability of pyrrolinone 1, a small-molecule inhibitor of the tight interaction between the urokinase receptor (uPAR) and its binding partner, the urokinase-type plasminogen activator uPA, to synthesize more than 40 derivatives and explore their effect on the protein-protein interaction. We report the crystal structure of uPAR bound to previously discovered pyrazole 3 and to pyrrolinone 12. While both 3 and 12 bind to uPAR and compete with a fluorescently labeled peptide probe, only 12 and its derivatives inhibit the full uPAR·uPA interaction. Compounds 3 and 12 mimic and engage different hot-spot residues on uPA and uPAR, respectively. Interestingly, 12 is involved in a π-cation interaction with Arg-53, which is not considered a hot spot. Explicit-solvent molecular dynamics simulations reveal that 3 and 12 exhibit dramatically different correlations of motion with residues on uPAR. Free energy calculations for the wild-type and mutant uPAR bound to uPA or 12 show that Arg-53 interacts with uPA or with 12 in a highly cooperative manner, thereby altering the contributions of hot spots to uPAR binding. The direct engagement of peripheral residues not considered hot spots through π-cation or salt-bridge interactions could provide new opportunities for enhanced small-molecule engagement of hot spots to disrupt challenging protein-protein interactions.

Accurate estimation of electrostatic binding energy with Poisson-Boltzmann equation solver DelPhi program

Poisson–Boltzmann (PB) model is a widely used implicit solvent approximation in biophysical modeling because of its ability to provide accurate and reliable PB electrostatic salvation free energies ([Formula: see text] as well as electrostatic binding free energy ([Formula: see text] estimations. However, a recent study has warned that the 0.5[Formula: see text]Å grid spacing which is normally adopted can produce unacceptable errors in [Formula: see text] estimation with the solvent excluded surface (SES) (Harris RC, Boschitsch AH and Fenley MO, Influence of grid spacing in Poisson–Boltzmann equation binding energy estimation, J Chem Theory Comput 19: 3677–3685, 2013). In this work, we investigate the grid dependence of the widely used PB solver DelPhi v6.2 with molecular surface (MS) for estimating both electrostatic solvation free energies and electrostatic binding free energies. Our results indicate that, for the molecular complex and components the absolute errors of [Formula: see text] are smaller than that of [Formula: see text], and grid spacing of 0.8[Formula: see text]Å with DelPhi program ensures the accuracy and reliability of [Formula: see text]; however, the accuracy of [Formula: see text] largely relies on the order of magnitude of [Formula: see text] itself rather than that of [Formula: see text] or [Formula: see text]. Our findings suggest that grid spacing of 0.5[Formula: see text]Å is enough to produce accurate [Formula: see text] for molecules whose [Formula: see text] are large, but finer grids are needed when [Formula: see text] is very small.

Binding of small molecules at interface of protein-protein complex - A newer approach to rational drug design

Protein–protein interaction is a vital process which drives many important physiological processes in the cell and has also been implicated in several diseases. Though the protein–protein interaction network is quite complex but understanding its interacting partners using both in silico as well as molecular biology techniques can provide better insights for targeting such interactions. Targeting protein–protein interaction with small molecules is a challenging task because of druggability issues. Nevertheless, several studies on the kinetics as well as thermodynamic properties of protein–protein interactions have immensely contributed toward better understanding of the affinity of these complexes. But, more recent studies on hot spots and interface residues have opened up new avenues in the drug discovery process. This approach has been used in the design of hot spot based modulators targeting protein–protein interaction with the objective of normalizing such interactions.

Computational method to identify druggable binding sites that target protein-protein interactions

Protein-protein interactions are implicated in the pathogenesis of many diseases and are therefore attractive but challenging targets for drug design. One of the challenges in development is the identification of potential druggable binding sites in protein interacting interfaces. Identification of interface surfaces can greatly aid rational drug design of small molecules inhibiting protein-protein interactions. In this work, starting from the structure of a free monomer, we have developed a ligand docking based method, called "FindBindSite" (FBS), to locate protein-protein interacting interface regions and potential druggable sites in this interface. FindBindSite utilizes the results from docking a small and diverse library of small molecules to the entire protein structure. By clustering regions with the highest docked ligand density from FBS, we have shown that these high ligand density regions strongly correlate with the known protein-protein interacting surfaces. We have further predicted potential druggable binding sites on the protein surface using FBS, with druggability being defined as the site with high density of ligands docked. FBS shows a hit rate of 71% with high confidence and 93% with lower confidence for the 41 proteins used for predicting druggable binding sites on the protein-protein interface. Mining the regions of lower ligand density that are contiguous with the high scoring high ligand density regions from FBS, we were able to map 70% of the protein-protein interacting surface in 24 out of 41 structures tested. We also observed that FBS has limited sensitivity to the size and nature of the small molecule library used for docking. The experimentally determined hotspot residues for each protein-protein complex cluster near the best scoring druggable binding sites identified by FBS. These results validate the ability of our technique to identify druggable sites within protein-protein interface regions that have the maximal possibility of interface disruption.

SKEMPI: a Structural Kinetic and Energetic database of Mutant Protein Interactions and its use in empirical models

MOTIVATION

Empirical models for the prediction of how changes in sequence alter protein-protein binding kinetics and thermodynamics can garner insights into many aspects of molecular biology. However, such models require empirical training data and proper validation before they can be widely applied. Previous databases contained few stabilizing mutations and no discussion of their inherent biases or how this impacts model construction or validation.

RESULTS

We present SKEMPI, a database of 3047 binding free energy changes upon mutation assembled from the scientific literature, for protein-protein heterodimeric complexes with experimentally determined structures. This represents over four times more data than previously collected. Changes in 713 association and dissociation rates and 127 enthalpies and entropies were also recorded. The existence of biases towards specific mutations, residues, interfaces, proteins and protein families is discussed in the context of how the data can be used to construct predictive models. Finally, a cross-validation scheme is presented which is capable of estimating the efficacy of derived models on future data in which these biases are not present.

AVAILABILITY

The database is available online at http://life.bsc.es/pid/mutation_database/.

Structural model of ligand-G protein-coupled receptor (GPCR) complex based on experimental double mutant cycle data: MT7 snake toxin bound to dimeric hM1 muscarinic receptor

The snake toxin MT7 is a potent and specific allosteric modulator of the human M1 muscarinic receptor (hM1). We previously characterized by mutagenesis experiments the functional determinants of the MT7-hM1 receptor interaction (Fruchart-Gaillard, C., Mourier, G., Marquer, C., Stura, E., Birdsall, N. J., and Servent, D. (2008) Mol. Pharmacol. 74, 1554-1563) and more recently collected evidence indicating that MT7 may bind to a dimeric form of hM1 (Marquer, C., Fruchart-Gaillard, C., Mourier, G., Grandjean, O., Girard, E., le Maire, M., Brown, S., and Servent, D. (2010) Biol. Cell 102, 409-420). To structurally characterize the MT7-hM1 complex, we adopted a strategy combining double mutant cycle experiments and molecular modeling calculations. First, thirty-three ligand-receptor proximities were identified from the analysis of sixty-one double mutant binding affinities. Several toxin residues that are more than 25 Å apart still contact the same residues on the receptor. As a consequence, attempts to satisfy all the restraints by docking the toxin onto a single receptor failed. The toxin was then positioned onto two receptors during five independent flexible docking simulations. The different possible ligand and receptor extracellular loop conformations were described by performing simulations in explicit solvent. All the docking calculations converged to the same conformation of the MT7-hM1 dimer complex, satisfying the experimental restraints and in which (i) the toxin interacts with the extracellular side of the receptor, (ii) the tips of MT7 loops II and III contact one hM1 protomer, whereas the tip of loop I binds to the other protomer, and (iii) the hM1 dimeric interface involves the transmembrane helices TM6 and TM7. These results structurally support the high affinity and selectivity of the MT7-hM1 interaction and highlight the atypical mode of interaction of this allosteric ligand on its G protein-coupled receptor target.

A structure-based benchmark for protein-protein binding affinity

We have assembled a nonredundant set of 144 protein-protein complexes that have high-resolution structures available for both the complexes and their unbound components, and for which dissociation constants have been measured by biophysical methods. The set is diverse in terms of the biological functions it represents, with complexes that involve G-proteins and receptor extracellular domains, as well as antigen/antibody, enzyme/inhibitor, and enzyme/substrate complexes. It is also diverse in terms of the partners' affinity for each other, with K(d) ranging between 10(-5) and 10(-14) M. Nine pairs of entries represent closely related complexes that have a similar structure, but a very different affinity, each pair comprising a cognate and a noncognate assembly. The unbound structures of the component proteins being available, conformation changes can be assessed. They are significant in most of the complexes, and large movements or disorder-to-order transitions are frequently observed. The set may be used to benchmark biophysical models aiming to relate affinity to structure in protein-protein interactions, taking into account the reactants and the conformation changes that accompany the association reaction, instead of just the final product.

Nicotinic receptor interloop proline anchors beta1-beta2 and Cys loops in coupling agonist binding to channel gating

Nicotinic acetylcholine receptors (AChRs) mediate rapid excitatory synaptic transmission throughout the peripheral and central nervous systems. They transduce binding of nerve-released ACh into opening of an intrinsic channel, yet the structural basis underlying transduction is not fully understood. Previous studies revealed a principal transduction pathway in which αArg 209 of the pre-M1 domain and αGlu 45 of the β1–β2 loop functionally link the two regions, positioning αVal 46 of the β1–β2 loop in a cavity formed by αPro 272 through αSer 269 of the M2–M3 loop. Here we investigate contributions of residues within and proximal to this pathway using single-channel kinetic analysis, site-directed mutagenesis, and thermodynamic mutant cycle analysis. We find that in contributing to channel gating, αVal 46 and αVal 132 of the signature Cys loop couple energetically to αPro 272. Furthermore, these residues are optimized in both their size and hydrophobicity to mediate rapid and efficient channel gating, suggesting naturally occurring substitutions at these positions enable a diverse range of gating rate constants among the Cys-loop receptor superfamily. The overall results indicate that αPro 272 functionally couples to flanking Val residues extending from the β1–β2 and Cys loops within the ACh binding to channel opening transduction pathway.

Volume-based solvation models out-perform area-based models in combined studies of wild-type and mutated protein-protein interfaces

BACKGROUND

Empirical binding models have previously been investigated for the energetics of protein complexation (DeltaG models) and for the influence of mutations on complexation (i.e. differences between wild-type and mutant complexes, DeltaDeltaG models). We construct binding models to directly compare these processes, which have generally been studied separately.

RESULTS

Although reasonable fit models were found for both DeltaG and DeltaDeltaG cases, they differ substantially. In a dataset curated for the absence of mainchain rearrangement upon binding, non-polar area burial is a major determinant of DeltaG models. However this DeltaG model does not fit well to the data for binding differences upon mutation. Burial of non-polar area is weighted down in fitting of DeltaDeltaG models. These calculations were made with no repacking of sidechains upon complexation, and only minimal packing upon mutation. We investigated the consequences of more extensive packing changes with a modified mean-field packing scheme. Rather than emphasising solvent exposure with relatively extended sidechains, rotamers are selected that exhibit maximal packing with protein. This provides solvent accessible areas for proteins that are much closer to those of experimental structures than the more extended sidechain regime. The new packing scheme increases changes in non-polar burial for mutants compared to wild-type proteins, but does not substantially improve agreement between DeltaG and DeltaDeltaG binding models.

CONCLUSION

We conclude that solvent accessible area, based on modelled mutant structures, is a poor correlate for DeltaDeltaG upon mutation. A simple volume-based, rather than solvent accessibility-based, model is constructed for DeltaG and DeltaDeltaG systems. This shows a more consistent behaviour. We discuss the efficacy of volume, as opposed to area, approaches to describe the energetic consequences of mutations at interfaces. This knowledge can be used to develop simple computational screens for binding in comparative modelled interfaces.

Crystal structural analysis of protein-protein interactions drastically destabilized by a single mutation

The complex of barnase (bn) and barstar (bs), which has been widely studied as a model for quantitative analysis of protein-protein interactions, is significantly destabilized by a single mutation, namely, bs Asp39 --> Ala, which corresponds to a change of 7.7 kcal x mol(-1) in the free energy of binding. However, there has been no structural information available to explain such a drastic destabilization. In the present study, we determined the structure of the mutant complex at 1.58 A resolution by X-ray crystallography. The complex was similar to the wild-type complex in terms of overall and interface structures; however, the hydrogen bond network mediated by water molecules at the interface was significantly different. Several water molecules filled the cavity created by the mutation and consequently caused rearrangement of the hydrated water molecules at the interface. The water molecules were redistributed into a channel-like structure that penetrated into the complex. Furthermore, molecular dynamics simulations showed that the mutation increased the mobility of water molecules at the interface. Since such a drastic change in hydration was not observed in other mutant complexes of bn and bs, the significant destabilization of the interaction may be due to this channel-like structure of hydrated water molecules.

Functionally important segments in proteins dissected using Gene Ontology and geometric clustering of peptide fragments

A geometric clustering algorithm has been developed to dissect protein fragments based on their relevance to function.

We have developed a geometric clustering algorithm using backbone φ,ψ angles to group conformationally similar peptide fragments of any length. By labeling each fragment in the cluster with the level-specific Gene Ontology 'molecular function' term of its protein, we are able to compute statistics for molecular function-propensity and p-value of individual fragments in the cluster. Clustering-cum-statistical analysis for peptide fragments 8 residues in length and with only trans peptide bonds shows that molecular function propensities ≥20 and p-values ≤0.05 can dissect fragments within a protein linked to the molecular function.

Molecular and cellular approaches for the detection of protein-protein interactions: latest techniques and current limitations

Homotypic and heterotypic protein interactions are crucial for all levels of cellular function, including architecture, regulation, metabolism, and signaling. Therefore, protein interaction maps represent essential components of post-genomic toolkits needed for understanding biological processes at a systems level. Over the past decade, a wide variety of methods have been developed to detect, analyze, and quantify protein interactions, including surface plasmon resonance spectroscopy, NMR, yeast two-hybrid screens, peptide tagging combined with mass spectrometry and fluorescence-based technologies. Fluorescence techniques range from co-localization of tags, which may be limited by the optical resolution of the microscope, to fluorescence resonance energy transfer-based methods that have molecular resolution and can also report on the dynamics and localization of the interactions within a cell. Proteins interact via highly evolved complementary surfaces with affinities that can vary over many orders of magnitude. Some of the techniques described in this review, such as surface plasmon resonance, provide detailed information on physical properties of these interactions, while others, such as two-hybrid techniques and mass spectrometry, are amenable to high-throughput analysis using robotics. In addition to providing an overview of these methods, this review emphasizes techniques that can be applied to determine interactions involving membrane proteins, including the split ubiquitin system and fluorescence-based technologies for characterizing hits obtained with high-throughput approaches. Mass spectrometry-based methods are covered by a review by Miernyk and Thelen (2008; this issue, pp. 597-609). In addition, we discuss the use of interaction data to construct interaction networks and as the basis for the exciting possibility of using to predict interaction surfaces.

Destabilization of human glycine N-methyltransferase by H176N mutation

In the presence of moderate (2-4 M) urea concentrations the tetrameric enzyme, glycine N-methyltransferase (GNMT), dissociates into compact monomers. Higher concentrations of urea (7-8 M) promote complete denaturation of the enzyme. We report here that the H176N mutation in this enzyme, found in humans with hypermethioninaemia, significantly decreases stability of the tetramer, although H176 is located far from the intersubunit contact areas. Dissociation of the tetramer to compact monomers and unfolding of compact monomers of the mutant protein were detected by circular dichroism, quenching of fluorescence emission, size-exclusion chromatography, and enzyme activity. The values of apparent free energy of dissociation of tetramer and of unfolding of compact monomers for the H176N mutant (27.7 and 4.2 kcal/mol, respectively) are lower than those of wild-type protein (37.5 and 6.2 kcal/mol). A 2.7 A resolution structure of the mutant protein revealed no significant difference in the conformation of the protein near the mutated residue.

Protein-protein interaction hotspots carved into sequences

Protein-protein interactions, a key to almost any biological process, are mediated by molecular mechanisms that are not entirely clear. The study of these mechanisms often focuses on all residues at protein-protein interfaces. However, only a small subset of all interface residues is actually essential for recognition or binding. Commonly referred to as "hotspots," these essential residues are defined as residues that impede protein-protein interactions if mutated. While no in silico tool identifies hotspots in unbound chains, numerous prediction methods were designed to identify all the residues in a protein that are likely to be a part of protein-protein interfaces. These methods typically identify successfully only a small fraction of all interface residues. Here, we analyzed the hypothesis that the two subsets correspond (i.e., that in silico methods may predict few residues because they preferentially predict hotspots). We demonstrate that this is indeed the case and that we can therefore predict directly from the sequence of a single protein which residues are interaction hotspots (without knowledge of the interaction partner). Our results suggested that most protein complexes are stabilized by similar basic principles. The ability to accurately and efficiently identify hotspots from sequence enables the annotation and analysis of protein-protein interaction hotspots in entire organisms and thus may benefit function prediction and drug development. The server for prediction is available at http://www.rostlab.org/services/isis.

In silico screening of mutational effects on enzyme-proteic inhibitor affinity: a docking-based approach

Background

Molecular recognition between enzymes and proteic inhibitors is crucial for normal functioning of many biological pathways. Mutations in either the enzyme or the inhibitor protein often lead to a modulation of the binding affinity with no major alterations in the 3D structure of the complex.

Results

In this study, a rigid body docking-based approach has been successfully probed in its ability to predict the effects of single and multiple point mutations on the binding energetics in three enzyme-proteic inhibitor systems. The only requirement of the approach is an accurate structural model of the complex between the wild type forms of the interacting proteins, with the assumption that the architecture of the mutated complexes is almost the same as that of the wild type and no major conformational changes occur upon binding. The method was applied to 23 variants of the ribonuclease inhibitor-angiogenin complex, to 15 variants of the barnase-barstar complex, and to 8 variants of the bovine pancreatic trypsin inhibitor-β Trypsin system, leading to thermodynamic and kinetic estimates consistent with in vitro data. Furthermore, simulations with and without explicit water molecules at the protein-protein interface suggested that they should be included in the simulations only when their positions are well defined both in the wild type and in the mutants and they result to be relevant for the modulation of mutational effects on the association process.

Conclusion

The correlative models built in this study allow for predictions of mutational effects on the thermodynamics and kinetics of association of three substantially different systems, and represent important extensions of our computational approach to cases in which it is not possible to estimate the absolute free energies. Moreover, this study is the first example in the literature of an extensive evaluation of the correlative weights of the single components of the ZDOCK score on the thermodynamics and kinetics of binding of protein mutants compared to the native state.

Finally, the results of this study corroborate and extend a previously developed quantitative model for in silico predictions of absolute protein-protein binding affinities spanning a wide range of values, i.e. from -10 up to -21 kcal/mol.

The computational approach is simple and fast and can be used for structure-based design of protein-protein complexes and for in silico screening of mutational effects on protein-protein recognition.

Hot spots-A review of the protein-protein interface determinant amino-acid residues

Proteins tendency to bind to one another in a highly specific manner forming stable complexes is fundamental to all biological processes. A better understanding of complex formation has many practical applications, which include the rational design of new therapeutic agents, and the analysis of metabolic and signal transduction networks. Alanine-scanning mutagenesis made possible the detection of the functional epitopes, and demonstrated that most of the protein-protein binding energy is related only to a group of few amino acids at intermolecular protein interfaces: the hot spots. The scope of this review is to summarize all the available information regarding hot spots for a better atomic understanding of their structure and function. The ultimate objective is to improve the rational design of complexes of high affinity and specificity as well as that of small molecules, which can mimic the functional epitopes of the proteic complexes.

Comparison of C40/82A and P27A C40/82A barstar mutants using 19F NMR

Barstar, an inhibitor of the enzyme barnase, contains two phenylalanine residues, three tryptophan residues, and two proline residues. After incorporating either 2-19F-Phe, 4-19F-Phe, or 6-19F-Trp, the structural, dynamic, and folding properties of two mutants (C40/82A, a double mutant, and P27A C40/82A, a triple mutant) were studied by 19F NMR. Experiments were performed as a function of temperature and urea with the two mutants. We show that the consequences of the P27A mutation are extensive. The effect of the mutation is transmitted to distant residues (Phe56 and Trp53) as well as to a residue deeply buried in the hydrophobic core (Phe74). By incorporating 2-19F-Phe, it is shown that Phe56 undergoes a slow ring flipping on the NMR time scale in the triple mutant that is not observed in the double mutant. On the other hand, incorporating 4-19F-Phe shows that the P27A mutation has little effect along the Cbeta-Cgamma axis of Phe56. Labeling with 4-19F-Phe shows, from line broadening, that Phe74 experiences more dynamic motion than does Phe56 in both the double and triple mutant. After incorporating 6-19F-Trp, it is found that, in the triple mutant, Trp53 shows conformational heterogeneity at low temperature while Trp44, which is close to the P27A mutation, does not. At 20 degrees C, residual native-like structure was detected around Trp53 at high concentrations of denaturant. Barstar is cold denatured in the presence of urea. For the double mutant at temperatures below 15 degrees C, and in the presence of 2.5-3.5 M urea, the resonance for Phe74 broadens, and two peaks are observed at 5 degrees C indicative of an exchange process. From line-shape analysis, assuming a two-site conformational exchange, the rate constants as a function of temperature can be extracted. An Eyring plot is linear at 0 M urea but deviates from linearity below 20 degrees C in the presence of 2.5 or 3.5 M urea. The data as a function of urea suggest sequential events in the unfolding process.

Functional analysis of the carboxy-terminal region of Bacillus subtilis TnrA, a MerR family protein

The Bacillus subtilis TnrA transcription factor belongs to the MerR family of proteins and regulates gene expression during nitrogen-limited growth. When B. subtilis cells are grown with excess nitrogen, feedback-inhibited glutamine synthetase forms a protein-protein complex with TnrA that prevents TnrA from binding to DNA. The C-terminal region of TnrA is required for the interaction with glutamine synthetase. Alanine scanning mutagenesis of the C-terminal region of TnrA identified three classes of mutants that altered the regulation by glutamine synthetase. While expression of the TnrA-regulated amtB gene was expressed constitutively in the class I (M96A, Q100A, and A103G) and class II (L97A, L101A, and F105A) mutants, the class II mutants were unable to grow on minimal medium unless a complex mixture of amino acids was present. The class III tnrA mutants (R93A, G99A, N102A, H104A, and Y107A mutants) were partially defective in the regulation of TnrA activity. In vitro experiments showed that feedback-inhibited glutamine synthetase had a significantly reduced ability to inhibit the DNA-binding activity of several class I and class II mutant TnrA proteins. A coiled-coil homology model of the C-terminal region of TnrA is used to explain the properties of the class I and II mutant proteins. The C-terminal region of TnrA corresponds to a dimerization domain in other MerR family proteins. Surprisingly, gel filtration and cross-linking analysis showed that a truncated TnrA protein which contained only the N-terminal DNA binding domain was dimeric. The implications of these results for the structure of TnrA are discussed.

Free energies of protein-protein association determined by electrospray ionization mass spectrometry correlate accurately with values obtained by solution methods

The advantages of electrospray ionization mass spectrometry (ESIMS) to measure relative solution-phase affinities of tightly bound protein-protein complexes are demonstrated with selected variants of the Bacillus amyloliquefaciens protein barstar (b*) and the RNAase barnase (bn), which form protein-protein complexes with a range of picomolar to nanomolar dissociation constants. A novel chemical annealing procedure rapidly establishes equilibrium in solutions containing competing b* variants with limiting bn. The relative ion abundances of the complexes and those of the competing unbound monomers are shown to reflect the relative solution-phase concentrations of those respective species. No measurable dissociation of the complexes occurs either during ESI or mass detection, nor is there any evidence for nonspecific binding at protein concentrations < 25 microM. Differences in DeltaDeltaG of dissociation between variants were determined with precisions < 0.1 kcal/mol. The DeltaDeltaG values obtained deviate on average by 0.26 kcal/mol from those measured with a solution-phase enzyme assay. It is demonstrated that information about the protein conformation and covalent modifications can be obtained from differences in mass and charge state distributions. This method serves as a rapid and precise means to interrogate protein-protein-binding surfaces for complexes that have affinities in the picomolar to nanomolar range.

Automated use of mutagenesis data in structure prediction

In the absence of experimental structural determination, numerous methods are available to indirectly predict or probe the structure of a target molecule. Genetic modification of a protein sequence is a powerful tool for identifying key residues involved in binding reactions or protein stability. Mutagenesis data is usually incorporated into the modeling process either through manual inspection of model compatibility with empirical data, or through the generation of geometric constraints linking sensitive residues to a binding interface. We present an approach derived from statistical studies of lattice models for introducing mutation information directly into the fitness score. The approach takes into account the phenotype of mutation (neutral or disruptive) and calculates the energy for a given structure over an ensemble of sequences. The structure prediction procedure searches for the optimal conformation where neutral sequences either have no impact or improve stability and disruptive sequences reduce stability relative to wild type. We examine three types of sequence ensembles: information from saturation mutagenesis, scanning mutagenesis, and homologous proteins. Incorporating multiple sequences into a statistical ensemble serves to energetically separate the native state and misfolded structures. As a result, the prediction of structure with a poor force field is sufficiently enhanced by mutational information to improve accuracy. Furthermore, by separating misfolded conformations from the target score, the ensemble energy serves to speed up conformational search algorithms such as Monte Carlo-based methods.

Interaction between a 1998 human influenza virus N2 neuraminidase and monoclonal antibody Mem5

Influenza virus constantly escapes antibody inhibition by introducing mutations that disrupt protein-protein interactions. Based on the structure of the complex between neuraminidase (NA) of influenza A/Memphis/31/98 (H3N2) and the Fab of a monoclonal antibody (Mem5) that binds and inhibits the Memphis/98 NA, we investigated the contribution made by individual amino acids of NA to the stability of the complex. We made mutations D147A, D147N, H150A, H197A, D198A, D198N, E199A, E199Q, K221R, A246K, D251N, and D251A. Binding of each mutant to NA was quantitated by NA inhibition assays and ELISA. Most of the mutant NAs were inhibited by Mem5 to the same extent as wild-type, but with lower affinity. The exceptions were E199A, E199Q, and K221R, in which binding was abrogated. The ELISA results confirmed a correlation between NA inhibition and binding. The Mem5 epitope is dominated by a few high-energy interactions as was found in the epitope on an avian subtype N9 NA that binds antibody NC41 and different to the more diffuse energy distribution in the NC10 epitope on N9 NA. Energetic dominance of a particular interaction, which is associated with potential for antibody escape mutations, may be associated with the absence of water molecules in the vicinity. Critical contacts in a dominant antigenic site are likely to mutate, allowing some predictions of antigenic drift.

How optimal are the binding energetics of barnase and barstar?

The extracellular ribonuclease barnase and its intracellular inhibitor barstar bind fast and with high affinity. Although extensive experimental and theoretical studies have been carried out on this system, it is unclear what the relative importance of different contributions to the high affinity is and whether binding can be improved through point mutations. In this work, we first applied Poisson-Boltzmann electrostatic calculations to 65 barnase-barstar complexes with mutations in both barnase and barstar. The continuum electrostatic calculations with a van der Waals surface dielectric boundary definition result in the electrostatic interaction free energy providing the dominant contribution favoring barnase-barstar binding. The results show that the computed electrostatic binding free energy can be improved through mutations at W44/barstar and E73/barnase. Furthermore, the determinants of binding affinity were quantified by applying COMparative BINding Energy (COMBINE) analysis to derive quantitative structure-activity relationships (QSARs) for the 65 complexes. The COMBINE QSAR model highlights approximately 20 interfacial residue pairs as responsible for most of the differences in binding affinity between the mutant complexes, mainly due to electrostatic interactions. Based on the COMBINE model, together with Brownian dynamics simulations to compute diffusional association rate constants, several mutants were designed to have higher binding affinities than the wild-type proteins.

Energy Functions for Protein Design: Adjustment with Protein–Protein Complex Affinities, Models for the Unfolded State, and Negative Design of Solubility and Specificity

The development of the EGAD program and energy function for protein design is described. In contrast to most protein design methods, which require several empirical parameters or heuristics such as patterning of residues or rotamers, EGAD has a minimalist philosophy; it uses very few empirical factors to account for inaccuracies resulting from the use of fixed backbones and discrete rotamers in protein design calculations, and describes the unfolded state, aggregates, and alternative conformers explicitly with physical models instead of fitted parameters. This approach unveils important issues in protein design that are often camouflaged by heuristic-emphasizing methods. Inter-atom energies are modeled with the OPLS-AA all-atom forcefield, electrostatics with the generalized Born continuum model, and the hydrophobic effect with a solvent-accessible surface area-dependent term. Experimental characterization of proteins designed with an unmodified version of the energy function revealed problems with under-packing, stability, aggregation, and structural specificity. Under-packing was addressed by modifying the van der Waals function. By optimizing only three parameters, the effects of >400 mutations on protein-protein complex formation were predicted to within 1.0 kcal mol(-1). As an independent test, this modified energy function was used to predict the stabilities of >1500 mutants to within 1.0 kcal mol(-1); this required a physical model of the unfolded state that includes more interactions than traditional tripeptide-based models. Solubility and structural specificity were addressed with simple physical approximations of aggregation and conformational equilibria. The complete energy function can design protein sequences that have high levels of identity with their natural counterparts, and have predicted structural properties more consistent with soluble and uniquely folded proteins than the initial designs.

Improving the tolerance of a protein a analogue to repeated alkaline exposures using a bypass mutagenesis approach

Staphylococcal protein A (SPA) is a cell surface protein expressed by Staphylococcus aureus. It consists of five repetitive domains. The five SPA-domains show individual interaction to the Fc-fragment as well as certain Fab-fragments of immunoglobulin G (IgG) from most mammalian species. Due to the high affinity and selectivity of SPA, it has a widespread use as an affinity ligand for capture and purification of antibodies. One of the problems with proteinaceous affinity ligands in large-scale purification is their sensitivity to alkaline conditions. SPA however, is considered relatively stable to alkaline treatment. Nevertheless, it is desirable to further improve the stability in order to enable an SPA-based affinity medium to withstand even longer exposure to the harsh conditions associated with cleaning-in-place (CIP) procedures. For this purpose, a protein engineering strategy, which was used earlier for stabilization and consists of replacing the asparagine residues, is employed. Since Z in its "nonengineered" form already has a significant tolerance to alkaline treatment, small changes in stability due to the mutations are difficult to assess. Hence, in order to enable detection of improvements regarding the alkaline resistance of the Z domain, we chose to use a bypass mutagenesis strategy using a mutated variant Z(F30A) as a surrogate framework. Z(F30A) has earlier been shown to possess an affinity to IgG that is similar to the wild-type but also demonstrates decreased structural stability. Since the contribution of the different asparagine residues to the deactivation rate of a ligand is dependent on the environment and also the structural flexibility of the particular region, it is important to consider all sensitive amino acids one by one. The parental Z-domain contains eight asparagine residues, each with a different impact on the alkaline stability of the domain. By exchanging asparagine 23 for a threonine, we were able to increase the stability of the Z(F30A) domain in alkaline conditions. Also, when grafting the N23T mutation to the Z scaffold, we were able to detect an increased tolerance to alkaline treatment compared to the native Z molecule.

Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RalGDS complexes

Absolute binding free energy calculations and free energy decompositions are presented for the protein-protein complexes H-Ras/C-Raf1 and H-Ras/RalGDS. Ras is a central switch in the regulation of cell proliferation and differentiation. In our study, we investigate the capability of the molecular mechanics (MM)-generalized Born surface area (GBSA) approach to estimate absolute binding free energies for the protein-protein complexes. Averaging gas-phase energies, solvation free energies, and entropic contributions over snapshots extracted from trajectories of the unbound proteins and the complexes, calculated binding free energies (Ras-Raf: -15.0(+/-6.3)kcal mol(-1); Ras-RalGDS: -19.5(+/-5.9)kcal mol(-1)) are in fair agreement with experimentally determined values (-9.6 kcal mol(-1); -8.4 kcal mol(-1)), if appropriate ionic strength is taken into account. Structural determinants of the binding affinity of Ras-Raf and Ras-RalGDS are identified by means of free energy decomposition. For the first time, computationally inexpensive generalized Born (GB) calculations are applied in this context to partition solvation free energies along with gas-phase energies between residues of both binding partners. For selected residues, in addition, entropic contributions are estimated by classical statistical mechanics. Comparison of the decomposition results with experimentally determined binding free energy differences for alanine mutants of interface residues yielded correlations with r(2)=0.55 and 0.46 for Ras-Raf and Ras-RalGDS, respectively. Extension of the decomposition reveals residues as far apart as 25A from the binding epitope that can contribute significantly to binding free energy. These "hotspots" are found to show large atomic fluctuations in the unbound proteins, indicating that they reside in structurally less stable regions. Furthermore, hotspot residues experience a significantly larger-than-average decrease in local fluctuations upon complex formation. Finally, by calculating a pair-wise decomposition of interactions, interaction pathways originating in the binding epitope of Raf are found that protrude through the protein structure towards the loop L1. This explains the finding of a conformational change in this region upon complex formation with Ras, and it may trigger a larger structural change in Raf, which is considered to be necessary for activation of the effector by Ras.

Structural and thermodynamic basis for the interaction of the Src SH2 domain with the activated form of the PDGF beta-receptor

Recruitment of the Src kinase to the activated form of the platelet-derived growth factor (PDGF) receptor involves recognition of a unique sequence motif in the juxtamembrane region of the receptor by the Src homology 2 (SH2) domain of the enzyme. This motif contains two phosphotyrosine residues separated by one residue (sequence pYIpYV where pY indicates a phosphotyrosine). Here, we provide the thermodynamic and structural basis for the binding of this motif by the Src SH2 domain. We show that the second phosphorylation event increases the free energy window for specific interaction and that the physiological target is exquisitely designed for the task of recruiting specifically an SH2 domain which otherwise demonstrates very little intrinsic ability to discriminate sequences C-terminal to the first phosphorylation event. Surprisingly, we show that water plays a role in the recognition process.

Beyond the rotamer library: genetic algorithm combined with the disturbing mutation process for upbuilding protein side-chains

The disturbing genetic algorithm, incorporating the disturbing mutation process into the genetic algorithm flow, has been developed to extend the searching space of side-chain conformations and to improve the quality of the rotamer library. Moreover, the growing generation amount idea, simulating the real situation of the natural evolution, is introduced to improve the searching speed. In the calculations using the pseudo energy scoring function of the root mean squared deviation, the disturbing genetic algorithm method has been shown to be highly efficient. With the real energy function based on AMBER force field, the program has been applied to rebuilding side-chain conformations of 25 high-quality crystallographic structures of single-protein and protein-protein complexes. The averaged root mean standard deviation of atom coordinates in side-chains and veracities of the torsion angles of chi(1) and chi(1) + chi(2) are 1.165 A, 88.2 and 72.9% for the buried residues, respectively, and 1.493 A, 79.2 and 64.7% for all residues, showing that the method has equal precision to the program SCWRL, whereas it performs better in the prediction of buried residues and protein-protein interfaces. This method has been successfully used in redesigning the interface of the Basnase-Barstar complex, indicating that it will have extensive application in protein design, protein sequence and structure relationship studies, and research on protein-protein interaction.

Binding free energy differences in a TCR-peptide-MHC complex induced by a peptide mutation: a simulation analysis

Recognition by the T-cell receptor (TCR) of immunogenic peptides presented by class I major histocompatibility complexes (MHCs) is the determining event in the specific cellular immune response against virus-infected cells or tumor cells. It is of great interest, therefore, to elucidate the molecular principles upon which the selectivity of a TCR is based. These principles can in turn be used to design therapeutic approaches, such as peptide-based immunotherapies of cancer. In this study, free energy simulation methods are used to analyze the binding free energy difference of a particular TCR (A6) for a wild-type peptide (Tax) and a mutant peptide (Tax P6A), both presented in HLA A2. The computed free energy difference is 2.9 kcal/mol, in good agreement with the experimental value. This makes possible the use of the simulation results for obtaining an understanding of the origin of the free energy difference which was not available from the experimental results. A free energy component analysis makes possible the decomposition of the free energy difference between the binding of the wild-type and mutant peptide into its components. Of particular interest is the fact that better solvation of the mutant peptide when bound to the MHC molecule is an important contribution to the greater affinity of the TCR for the latter. The results make possible identification of the residues of the TCR which are important for the selectivity. This provides an understanding of the molecular principles that govern the recognition. The possibility of using free energy simulations in designing peptide derivatives for cancer immunotherapy is briefly discussed.

Short constrained peptides that inhibit HIV-1 entry

Peptides corresponding to the C-terminal heptad repeat of HIV-1 gp41 (C-peptides) are potent inhibitors of HIV-1 entry into cells. Their mechanism of inhibition involves binding in a helical conformation to the central coiled coil of HIV-1 gp41 in a dominant-negative manner. Short C-peptides, however, have low binding affinity for gp41 and poor inhibitory activity, which creates an obstacle to the development of small drug-like C-peptides. To improve the inhibitory potency of short C-peptides that target the hydrophobic pocket region of gp41, we use two strategies to stabilize the C-peptide helix: chemical crosslinking and substitution with unnatural helix-favoring amino acids. In this study, the short linear peptide shows no significant inhibitory activity, but a constrained peptide (C14linkmid) inhibits cell-cell fusion at micromolar potency. Structural studies confirm that the constrained peptides bind to the gp41 hydrophobic pocket. Calorimetry reveals that, of the peptides analyzed, the most potent are those that best balance the changes in binding enthalpy and entropy, and surprisingly not those with the highest helical propensity as measured by circular dichroism spectroscopy. Our study reveals the thermodynamic basis of inhibition of an HIV C-peptide, demonstrates the utility of constraining methods for a short antiviral peptide inhibitor, and has implications for the future design of constrained peptides.

Protein-protein interactions: mechanisms and modification by drugs

Protein-protein interactions form the proteinaceous network, which plays a central role in numerous processes in the cell. This review highlights the main structures, properties of contact surfaces, and forces involved in protein-protein interactions. The properties of protein contact surfaces depend on their functions. The characteristics of contact surfaces of short-lived protein complexes share some similarities with the active sites of enzymes. The contact surfaces of permanent complexes resemble domain contacts or the protein core. It is reasonable to consider protein-protein complex formation as a continuation of protein folding. The contact surfaces of the protein complexes have unique structure and properties, so they represent prospective targets for a new generation of drugs. During the last decade, numerous investigations have been undertaken to find or design small molecules that block protein dimerization or protein(peptide)-receptor interaction, or on the other hand, induce protein dimerization.

Site-specific incorporation of (aminooxy)acetic acid into proteins

By employing a general biosynthetic method for the elaboration of proteins containing unnatural amino acid analogues, we incorporated (aminooxy)acetic acid into positions 10 and 27 of Escherichia coli dihydrofolate reductase. Introduction of the modified amino acid into DHFR was accomplished in an in vitro protein biosynthesizing system by readthrough of a nonsense (UAG) codon with a suppressor tRNA that had been activated with (aminooxy)acetic acid. Incorporation of the amino acid proceeded with reasonable efficiency at codon position 10 but less well at position 27. (Aminooxy)acetic acid was also incorporated into position 72 of DNA polymerase beta. Peptides containing (aminooxy)acetic acid have been shown to adopt a preferred conformation involving an eight-membered ring that resembles a gamma-turn. Accordingly, the present study may facilitate the elaboration of proteins containing conformationally biased peptidomimetic motifs at predetermined sites. The present results further extend the examples of ribosomally mediated formation of peptide bond analogues of altered connectivity and provide a conformationally biased linkage at a predetermined site. It has also been shown that the elaborated protein can be cleaved chemically at the site containing the modified amino acid.

Cyclosporin A as a model antigen: immunochemical and structural studies

The immunosuppressant drug cyclosporin (Cs) A is a cyclic undecapeptide which has been used as a model antigen because structural information and a large number of analogs, modified at each of its 11 positions, were available. This review summarizes immunochemical and crystallographic studies of the interaction between the Fab of monoclonal antibody R45-45-11 and Cs. Three points are discussed: (1) the different conformations of CsA and the question of its biologically active form; (2) the Fab-CsA recognition mechanism; and (3) the relationship between structure and binding properties of CsA analogs.

Identification of key amino acid residues in the assembly of enzymes into the pyruvate dehydrogenase complex of Bacillus stearothermophilus: a kinetic and thermodynamic analysis

Structural studies have shown that electrostatic interactions play a major part in the binding of dihydrolipoyl dehydrogenase (E3) to the peripheral subunit-binding domain (PSBD) of the dihydrolipoyl acyltransferase (E2) in the assembly of the pyruvate dehydrogenase multienzyme complex of Bacillus stearothermophilus. The binding is characterized by a small, unfavorable enthalpy change (deltaH degrees = +2.2 kcal/mol) and a large, positive entropy change (TdeltaS degrees = +14.8 kcal/mol). The contributions of individual surface residues of the PSBD of E2 to its interaction with E3 have been assessed by alanine-scanning mutagenesis, surface plasmon resonance detection, and isothermal titration calorimetry. The mutation R135A in the PSBD gave rise to a significant decrease (120-fold) in the binding affinity; two other mutations (R139A and R156A) were associated with smaller effects. The binding of the R135A mutant to E3 was accompanied by a favorable enthalpy (deltaH degrees = -2.6 kcal/mol) and a less positive entropy change (TdeltaS degrees = +7.2 kcal/mol). The midpoint melting temperature (T(m)) of E3-PSBD complexes was determined by differential scanning calorimetry. The R135A mutation caused a significant decrease (5 degrees C) in the T(m), compared with the wild-type complex. The results reveal the importance of Arg135 of the PSBD as a key residue in the molecular recognition of E3 by E2, and as a major participant in the overall entropy-driven binding process. Further, the effects of mutagenesis on the deltaCp of subunit association illustrate the difficulties in attributing changes in heat capacity to specific classes of interactions.

Manipulating monomer-dimer equilibrium of bovine Beta -lactoglobulin by amino acid substitution

Bovine beta-lactoglobulin, a major protein in cow's milk composed of nine beta-strands (betaA-betaI) and one alpha-helix, exists as a dimer at neutral pH while it dissociates to a native monomer below pH 3.0. It is assumed that the intermolecular beta-sheet formed between I-strands and salt bridges at AB-loops play important roles in dimer formation. Several site-directed mutants in which intermolecular interactions stabilizing the dimer would be removed were expressed in the methylotrophic yeast Pichia pastoris, and their monomer-dimer equilibria were studied by analytical ultracentrifugation. Various I-strand mutants showed decreases in K(a), suggesting that the intermolecular beta-sheet is essential for dimer formation. By substituting either Asp(33) or Arg(40) on the AB-loop to oppositely charged residues (i.e. R40D, R40E, and D33R), a large decrease in K(a) was observed probably because of the charge repulsion, which is consistent with the role of electrostatic attraction between Arg(40) on one monomer and Asp(33) on the other monomer in the wild-type dimer. However, when two of these mutants, R40D and D33R, were mixed, a heterodimer was formed by the electrostatic attraction between Arg(33) and Asp(40) of different molecules. These results suggested that protein-protein interactions of bovine beta-lactoglobulin can be manipulated by redesigning the residues on the interface without affecting global folding.

Design and synthesis of type-III mimetics of ShK toxin

ShK toxin is a structurally defined, 35-residue polypeptide which blocks the voltage-gated Kv1.3 potassium channel in T-lymphocytes and has been identified as a possible immunosuppressant. Our interest lies in the rational design and synthesis of type-III mimetics of protein and polypeptide structure and function. ShK toxin is a challenging target for mimetic design as its binding epitope consists of relatively weakly binding residues, some of which are discontinuous. We discuss here our investigations into the design and synthesis of 1st generation, small molecule mimetics of ShK toxin and highlight any principles relevant to the generic design of type-III mimetics of continuous and discontinuous binding epitopes. We complement our approach with attempted pharmacophore-based database mining.

Essential domain motions in barnase revealed by MD simulations

The wealth of data accumulated on the bacterial ribonuclease barnase is complemented by molecular dynamics trajectories starting from four different experimental structures and covering a total of >10 ns. Using principal component analysis, the simulations are interpreted in view of dynamic domains and hinges promoting relative motions of these domains. Two domains with residues 7-22 and 52-108 for the first domain and residues 25-51 for the second domain were consistently observed. Hinge regions consist primarily of Tyr24, Ser50, Ile51, and Gly52. Earlier mutation studies have demonstrated that the residues of the hinge regions play essential roles for the stability and activity of barnase. The domain motions are correlated to inter-domain interactions involving functionally important active site residues, such as Lys27 and Glu73. A model is presented that combines the observation of dynamic domains and their motions with the extensive mutation data from the literature. Enthalpic energy contributions originating from specific inter-domain interactions as well as entropic energy contributions due to the domain motions are discussed in the frame of this model and compared with destabilization energies measured for corresponding mutants.

Mutational analysis of the interaction between albumin-binding domain from streptococcal protein G and human serum albumin

Streptococcal protein G (SpG) is a bacterial cell surface receptor exhibiting affinity to both human immunoglobulin (IgG) and human serum albumin (HSA). Interestingly, the serum albumin and immunoglobulin-binding activities have been shown to reside at functionally and structurally separated receptor domains. The binding domain of the HSA-binding part has been shown to be a 46-residue triple alpha-helical structure, but the binding site to HSA has not yet been determined. Here, we have investigated the precise binding region of this bacterial receptor by protein engineering applying an alanine-scanning procedure followed by binding studies by surface plasmon resonance (SPR). The secondary structure as well as the HSA binding of the resulting albumin-binding domain (ABD) variants were analyzed using circular dichroism (CD) and affinity blotting. The analysis shows that the HSA binding involves residues mainly in the second alpha-helix.

Unraveling hot spots in binding interfaces: progress and challenges

Protein interface hot spots, as revealed by alanine scanning mutagenesis, continue to stimulate interest in the biophysical basis of molecular recognition. Although these regions apparently constitute fertile grounds for intermolecular interactions, no general algorithm has yet been developed that can predict hot spots based solely on their shape or composition. The discovery of structural plasticity in hot spot regions indicates that dynamic simulation techniques may be essential for achieving a predictive understanding of binding interface energetics. Future progress will depend as much on the application of new computational approaches for dissecting protein interfaces as on expanding our empirical databank of mutagenic substitutions and their effects. Despite our current theoretical shortcomings, recent methodological advances provide efficient experimental means of probing hot spots and enable immediate applications for hot spots in drug discovery.

Design and synthesis of type-III mimetics of omega-conotoxin GVIA

Our interest lies in the rational design and synthesis of type-III mimetics of protein and polypeptide structure and function. Our approach involves interactive design of conformationally defined molecular scaffolds that project certain functional groups in a way that mimics the projection of important binding residues as determined in the parent structure. These design principles are discussed and applied to the structurally defined polypeptide, omega-conotoxin GVIA, which blocks voltage-gated, neuronal N-type calcium channels. These ion channels represent therapeutic targets for the development of new analgesics that can treat chronic pain. It is shown how a discontinuous, 3-residue pharmacophore of GVIA can be mimicked by different molecular scaffolds. It is illustrated how such 1st generation leads must necessarily be weak and that optimisability must therefore be built-in during the design process.