Dual recognition and the role of specificity-determining residues in colicin E9 DNase-immunity protein interactions

ProBASS - a language model with sequence and structural features for predicting the effect of mutations on binding affinity

Protein-protein interactions (PPIs) govern virtually all cellular processes. Even a single mutation within PPI can significantly influence overall protein functionality and potentially lead to various types of diseases. To date, numerous approaches have emerged for predicting the change in free energy of binding (ΔΔGbind) resulting from mutations, yet the majority of these methods lack precision. In recent years, protein language models (PLMs) have been developed and shown powerful predictive capabilities by leveraging both sequence and structural data from protein-protein complexes. Yet, PLMs have not been optimized specifically for predicting ΔΔGbind. We developed an approach to predict effects of mutations on PPI binding affinity based on two most advanced protein language models ESM2 and ESM-IF1 that incorporate PPI sequence and structural features, respectively. We used the two models to generate embeddings for each PPI mutant and subsequently fine-tuned our model by training on a large dataset of experimental ΔΔGbind values. Our model, ProBASS (Protein Binding Affinity from Structure and Sequence) achieved a correlation with experimental ΔΔGbind values of 0.83 ± 0.05 for single mutations and 0.69 ± 0.04 for double mutations when model training and testing was done on the same PDB. Moreover, ProBASS exhibited very high correlation (0.81 ± 0.02) between prediction and experiment when training and testing was performed on a dataset containing 2325 single mutations in 132 PPIs. ProBASS surpasses the state-of-the-art methods in correlation with experimental data and could be further trained as more experimental data becomes available. Our results demonstrate that the integration of extensive datasets containing ΔΔGbind values across multiple PPIs to refine the pre-trained PLMs represents a successful approach for achieving a precise and broadly applicable model for ΔΔGbind prediction, greatly facilitating future protein engineering and design studies.

Alchemical Calculation of Relative Free Energies for Charge-Changing Mutations at Protein-Protein Interfaces Considering Fixed and Variable Protonation States

The calculation of relative free energies (ΔΔG) for charge-changing mutations at protein-protein interfaces through alchemical methods remains challenging due to variations in the system's net charge during charging steps, the possibility of mutated and contacting ionizable residues occurring in various protonation states, and undersampling issues. In this study, we present a set of strategies, collectively termed TIRST/TIRST-H+, to address some of these challenges. Our approaches combine thermodynamic integration (TI) with the prediction of pKa shifts to calculate ΔΔG values. Moreover, special sets of restraints are employed to keep the alchemically transformed molecules separated. The accuracy of the devised approaches was assessed on a large and diverse data set comprising 164 point mutations of charged residues (Asp, Glu, Lys, and Arg) to Ala at the protein-protein interfaces of complexes with known three-dimensional structures. Mean absolute and root-mean-square errors ranging from 1.38 to 1.66 and 1.89 to 2.44 kcal/mol, respectively, and Pearson correlation coefficients of ∼0.6 were obtained when testing the approaches on the selected data set using the GPU-TI module of Amber18 suite and the ff14SB force field. Furthermore, the inclusion of variable protonation states for the mutated acid residues improved the accuracy of the predicted ΔΔG values. Therefore, our results validate the use of TIRST/TIRST-H+ in prospective studies aimed at evaluating the impact of charge-changing mutations to Ala on the stability of protein-protein complexes.

Condensed-phase signaling can expand kinase specificity and respond to macromolecular crowding

Phase separation can concentrate biomolecules and accelerate reactions. However, the mechanisms and principles connecting this mesoscale organization to signaling dynamics are difficult to dissect because of the pleiotropic effects associated with disrupting endogenous condensates. To address this limitation, we engineered new phosphorylation reactions within synthetic condensates. We generally found increased activity and broadened kinase specificity. Phosphorylation dynamics within condensates were rapid and could drive cell-cycle-dependent localization changes. High client concentration within condensates was important but not the main factor for efficient phosphorylation. Rather, the availability of many excess client-binding sites together with a flexible scaffold was crucial. Phosphorylation within condensates was also modulated by changes in macromolecular crowding. Finally, the phosphorylation of the Alzheimer's-disease-associated protein Tau by cyclin-dependent kinase 2 was accelerated within condensates. Thus, condensates enable new signaling connections and can create sensors that respond to the biophysical properties of the cytoplasm.

Cold spots are universal in protein-protein interactions

Proteins interact with each other through binding interfaces that differ greatly in size and physico-chemical properties. Within the binding interface, a few residues called hot spots contribute the majority of the binding free energy and are hence irreplaceable. In contrast, cold spots are occupied by suboptimal amino acids, providing possibility for affinity enhancement through mutations. In this study, we identify cold spots due to cavities and unfavorable charge interactions in multiple protein-protein interactions (PPIs). For our cold spot analysis, we first use a small affinity database of PPIs with known structures and affinities and then expand our search to nearly 4000 homo- and heterodimers in the Protein Data Bank (PDB). We observe that cold spots due to cavities are present in nearly all PPIs unrelated to their binding affinity, while unfavorable charge interactions are relatively rare. We also find that most cold spots are located in the periphery of the binding interface, with high-affinity complexes showing fewer centrally located colds spots than low-affinity complexes. A larger number of cold spots is also found in non-cognate interactions compared to their cognate counterparts. Furthermore, our analysis reveals that cold spots are more frequent in homo-dimeric complexes compared to hetero-complexes, likely due to symmetry constraints imposed on sequences of homodimers. Finally, we find that glycines, glutamates, and arginines are the most frequent amino acids appearing at cold spot positions. Our analysis emphasizes the importance of cold spot positions to protein evolution and facilitates protein engineering studies directed at enhancing binding affinity and specificity in a wide range of applications.

Affinity and Valence Impact the Extent and Symmetry of Phase Separation of Multivalent Proteins

Biomolecular self-assembly spatially segregates proteins with a limited number of binding sites (valence) into condensates that coexist with a dilute phase. We develop a many-body lattice model for a three-component system of proteins with fixed valence in a solvent. We compare the predictions of the model to experimental phase diagrams that we measure in vivo, which allows us to vary specifically a binding site's affinity and valency. We find that the extent of phase separation varies exponentially with affinity and increases with valency. Valency alone determines the symmetry of the phase diagram.

Synthetic condensate size correlates with yeast replicative cell age

Yeast divides asymmetrically, with an aging mother cell and a 'rejuvenated' daughter cell, and serves as a model organism for studying aging. At the same time, determining the age of yeast cells is technically challenging, requiring complex experimental setups or genetic strategies. We developed a synthetic system composed of two interacting oligomers, which forms condensates in living yeast cells. Here, we report that these synthetic condensates' size correlates with yeast replicative age, making these condensates age reporters for this model organism.

Structural design principles for specific ultra-high affinity interactions between colicins/pyocins and immunity proteins

The interactions of the antibiotic proteins colicins/pyocins with immunity proteins is a seminal model system for studying protein–protein interactions and specificity. Yet, a precise and quantitative determination of which structural elements and residues determine their binding affinity and specificity is still lacking. Here, we used comparative structure-based energy calculations to map residues that substantially contribute to interactions across native and engineered complexes of colicins/pyocins and immunity proteins. We show that the immunity protein α1–α2 motif is a unique structurally-dissimilar element that restricts interaction specificity towards all colicins/pyocins, in both engineered and native complexes. This motif combines with a diverse and extensive array of electrostatic/polar interactions that enable the exquisite specificity that characterizes these interactions while achieving ultra-high affinity. Surprisingly, the divergence of these contributing colicin residues is reciprocal to residue conservation in immunity proteins. The structurally-dissimilar immunity protein α1–α2 motif is recognized by divergent colicins similarly, while the conserved immunity protein α3 helix interacts with diverse colicin residues. Electrostatics thus plays a key role in setting interaction specificity across all colicins and immunity proteins. Our analysis and resulting residue-level maps illuminate the molecular basis for these protein–protein interactions, with implications for drug development and rational engineering of these interfaces.

Droplet printing reveals the importance of micron-scale structure for bacterial ecology

Bacteria often live in diverse communities where the spatial arrangement of strains and species is considered critical for their ecology. However, a test of this hypothesis requires manipulation at the fine scales at which spatial structure naturally occurs. Here we develop a droplet-based printing method to arrange bacterial genotypes across a sub-millimetre array. We print strains of the gut bacterium Escherichia coli that naturally compete with one another using protein toxins. Our experiments reveal that toxin-producing strains largely eliminate susceptible non-producers when genotypes are well-mixed. However, printing strains side-by-side creates an ecological refuge where susceptible strains can persist in large numbers. Moving to competitions between toxin producers reveals that spatial structure can make the difference between one strain winning and mutual destruction. Finally, we print different potential barriers between competing strains to understand how ecological refuges form, which shows that cells closest to a toxin producer mop up the toxin and protect their clonemates. Our work provides a method to generate customised bacterial communities with defined spatial distributions, and reveals that micron-scale changes in these distributions can drive major shifts in ecology.

The spatial arrangement of bacterial strains and species within microbial communities is considered crucial for their ecology. Here, Krishna Kumar et al. use a droplet-based printing method to arrange different bacterial genotypes across a sub-millimetre array, and show that micron-scale changes in spatial distributions can drive major shifts in ecology.

Assessment of software methods for estimating protein-protein relative binding affinities

A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83-98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.

Using collections of structural models to predict changes of binding affinity caused by mutations in protein-protein interactions

Protein-protein interactions (PPIs) in all the molecular aspects that take place both inside and outside cells. However, determining experimentally the structure and affinity of PPIs is expensive and time consuming. Therefore, the development of computational tools, as a complement to experimental methods, is fundamental. Here, we present a computational suite: MODPIN, to model and predict the changes of binding affinity of PPIs. In this approach we use homology modeling to derive the structures of PPIs and score them using state-of-the-art scoring functions. We explore the conformational space of PPIs by generating not a single structural model but a collection of structural models with different conformations based on several templates. We apply the approach to predict the changes in free energy upon mutations and splicing variants of large datasets of PPIs to statistically quantify the quality and accuracy of the predictions. As an example, we use MODPIN to study the effect of mutations in the interaction between colicin endonuclease 9 and colicin endonuclease 2 immune protein from Escherichia coli. Finally, we have compared our results with other state-of-art methods.

Designer protein assemblies with tunable phase diagrams in living cells

Protein self-organization is a hallmark of biological systems. Although the physicochemical principles governing protein-protein interactions have long been known, the principles by which such nanoscale interactions generate diverse phenotypes of mesoscale assemblies, including phase-separated compartments, remain challenging to characterize. To illuminate such principles, we create a system of two proteins designed to interact and form mesh-like assemblies. We devise a new strategy to map high-resolution phase diagrams in living cells, which provide self-assembly signatures of this system. The structural modularity of the two protein components allows straightforward modification of their molecular properties, enabling us to characterize how interaction affinity impacts the phase diagram and material state of the assemblies in vivo. The phase diagrams and their dependence on interaction affinity were captured by theory and simulations, including out-of-equilibrium effects seen in growing cells. Finally, we find that cotranslational protein binding suffices to recruit a messenger RNA to the designed micron-scale structures.

Molecular basis of ALK1-mediated signalling by BMP9/BMP10 and their prodomain-bound forms

Activin receptor-like kinase 1 (ALK1)-mediated endothelial cell signalling in response to bone morphogenetic protein 9 (BMP9) and BMP10 is of significant importance in cardiovascular disease and cancer. However, detailed molecular mechanisms of ALK1-mediated signalling remain unclear. Here, we report crystal structures of the BMP10:ALK1 complex at 2.3 Å and the prodomain-bound BMP9:ALK1 complex at 3.3 Å. Structural analyses reveal a tripartite recognition mechanism that defines BMP9 and BMP10 specificity for ALK1, and predict that crossveinless 2 is not an inhibitor of BMP9, which is confirmed by experimental evidence. Introduction of BMP10-specific residues into BMP9 yields BMP10-like ligands with diminished signalling activity in C2C12 cells, validating the tripartite mechanism. The loss of osteogenic signalling in C2C12 does not translate into non-osteogenic activity in vivo and BMP10 also induces bone-formation. Collectively, these data provide insight into ALK1-mediated BMP9 and BMP10 signalling, facilitating therapeutic targeting of this important pathway.

Computational studies of protein-protein dissociation by statistical potential and coarse-grained simulations: a case study on interactions between colicin E9 endonuclease and immunity proteins

Proteins carry out their diverse functions in cells by forming interactions with each other. The dynamics of these interactions are quantified by the measurement of association and dissociation rate constants. Relative to the efforts made to model the association of biomolecules, little has been studied to understand the principles of protein complex dissociation. Using the interaction between colicin E9 endonucleases and immunity proteins as a test system, here we develop a coarse-grained simulation method to explore the dissociation mechanisms of protein complexes. The interactions between proteins in the complex are described by the knowledge-based potential that was constructed by the statistics from available protein complexes in the structural database. Our study provides the supportive evidences to the dual recognition mechanism for the specificity of binding between E9 DNase and immunity proteins, in which the conserved residues of helix III of Im2 and Im9 proteins act as the anchor for binding, while the sequence variations in helix II make positive or negative contributions to specificity. Beyond that, we further suggest that this binding specificity is rooted in the process of complex dissociation instead of association. While we increased the flexibility of protein complexes, we further found that they are less prone to dissociation, suggesting that conformational fluctuations of protein complexes play important functional roles in regulating their binding and dissociation. Our studies therefore bring new insights to the molecule mechanisms of protein-protein interactions, while the method can serve as a new addition to a suite of existing computational tools for the simulations of protein complexes.

Cold Spots in Protein Binding

Understanding the energetics and architecture of protein-binding interfaces is important for basic research and could potentially facilitate the design of novel binding domains for biotechnological applications. It is well accepted that a few key residues at binding interfaces (binding hot spots) are responsible for contributing most to the free energy of binding. In this opinion article, we introduce a new concept of 'binding cold spots', or interface positions occupied by suboptimal amino acids. Such positions exhibit a potential for affinity enhancement through various mutations. We give several examples of cold spots from different protein-engineering studies and argue that identification of such positions is crucial for studies of protein evolution and protein design.

Diversification of β-Augmentation Interactions between CDI Toxin/Immunity Proteins

Contact-dependent growth inhibition (CDI) is a widespread mechanism of inter-bacterial competition mediated by the CdiB/CdiA family of two-partner secretion proteins. CdiA effectors carry diverse C-terminal toxin domains (CdiA-CT), which are delivered into neighboring target cells to inhibit growth. CDI(+) bacteria also produce CdiI immunity proteins that bind specifically to cognate CdiA-CT toxins and protect the cell from auto-inhibition. Here, we compare the structures of homologous CdiA-CT/CdiI complexes from Escherichia coli EC869 and Yersinia pseudotuberculosis YPIII to explore the evolution of CDI toxin/immunity protein interactions. Both complexes share an unusual β-augmentation interaction, in which the toxin domain extends a β-hairpin into the immunity protein to complete a six-stranded anti-parallel sheet. However, the specific contacts differ substantially between the two complexes. The EC869 β-hairpin interacts mainly through direct H-bond and ion-pair interactions, whereas the YPIII β-hairpin pocket contains more hydrophobic contacts and a network of bridging water molecules. In accord with these differences, we find that each CdiI protein only protects target bacteria from its cognate CdiA-CT toxin. The compact β-hairpin binding pocket within the immunity protein represents a tractable system for the rationale design of small molecules to block CdiA-CT/CdiI complex formation. We synthesized a macrocyclic peptide mimic of the β-hairpin from EC869 toxin and solved its structure in complex with cognate immunity protein. These latter studies suggest that small molecules could potentially be used to disrupt CDI toxin/immunity complexes.

Structures of the Ultra-High-Affinity Protein-Protein Complexes of Pyocins S2 and AP41 and Their Cognate Immunity Proteins from Pseudomonas aeruginosa

How ultra-high-affinity protein-protein interactions retain high specificity is still poorly understood. The interaction between colicin DNase domains and their inhibitory immunity (Im) proteins is an ultra-high-affinity interaction that is essential for the neutralisation of endogenous DNase catalytic activity and for protection against exogenous DNase bacteriocins. The colicin DNase-Im interaction is a model system for the study of high-affinity protein-protein interactions. However, despite the fact that closely related colicin-like bacteriocins are widely produced by Gram-negative bacteria, this interaction has only been studied using colicins from Escherichia coli. In this work, we present the first crystal structures of two pyocin DNase-Im complexes from Pseudomonas aeruginosa, pyocin S2 DNase-ImS2 and pyocin AP41 DNase-ImAP41. These structures represent divergent DNase-Im subfamilies and are important in extending our understanding of protein-protein interactions for this important class of high-affinity protein complex. A key finding of this work is that mutations within the immunity protein binding energy hotspot, helix III, are tolerated by complementary substitutions at the DNase-Immunity protein binding interface. Im helix III is strictly conserved in colicins where an Asp forms polar interactions with the DNase backbone. ImAP41 contains an Asp-to-Gly substitution in helix III and our structures show the role of a co-evolved substitution where Pro in DNase loop 4 occupies the volume vacated and removes the unfulfilled hydrogen bond. We observe the co-evolved mutations in other DNase-Immunity pairs that appear to underpin the split of this family into two distinct groups.

Crucial roles of single residues in binding affinity, specificity, and promiscuity in the cellulosomal cohesin-dockerin interface

Interactions between cohesin and dockerin modules play a crucial role in the assembly of multienzyme cellulosome complexes. Although intraspecies cohesin and dockerin modules bind in general with high affinity but indiscriminately, cross-species binding is rare. Here, we combined ELISA-based experiments with Rosetta-based computational design to evaluate the contribution of distinct residues at the Clostridium thermocellum cohesin-dockerin interface to binding affinity, specificity, and promiscuity. We found that single mutations can show distinct and significant effects on binding affinity and specificity. In particular, mutations at cohesin position Asn(37) show dramatic variability in their effect on dockerin binding affinity and specificity: the N37A mutant binds promiscuously both to cognate (C. thermocellum) as well as to non-cognate Clostridium cellulolyticum dockerin. N37L in turn switches binding specificity: compared with the wild-type C. thermocellum cohesin, this mutant shows significantly increased preference for C. cellulolyticum dockerin combined with strongly reduced binding to its cognate C. thermocellum dockerin. The observation that a single mutation can overcome the naturally observed specificity barrier provides insights into the evolutionary dynamics of this system that allows rapid modulation of binding specificity within a high affinity background.

Extraction of accurate biomolecular parameters from single-molecule force spectroscopy experiments

The atomic force microscope (AFM) is able to manipulate biomolecules and their complexes with exquisite force sensitivity and distance resolution. This capability, complemented by theoretical models, has greatly improved our understanding of the determinants of mechanical strength in proteins and revealed the diverse effects of directional forces on the energy landscape of biomolecules. In unbinding experiments, the interacting partners are usually immobilized on their respective substrates via extensible linkers. These linkers affect both the force and contour length (Lc) of the complex at rupture. Surprisingly, while the former effect is well understood, the latter is largely neglected, leading to incorrect estimations of Lc, a parameter that is often used as evidence for the detection of specific interactions and remodeling events and for the inference of interaction regions. To address this problem, a model that predicts contour length measurements from single-molecule forced-dissociation experiments is presented that considers attachment position on the AFM tip, geometric effects, and polymer dynamics of the linkers. Modeled data are compared with measured contour length distributions from several different experimental systems, revealing that current methods underestimate contour lengths. The model enables nonspecific interactions to be identified unequivocally, allows accurate determination of Lc, and, by comparing experimental and modeled distributions, enables partial unfolding events before rupture to be identified unequivocally.

How structure defines affinity in protein-protein interactions

Protein-protein interactions (PPI) in nature are conveyed by a multitude of binding modes involving various surfaces, secondary structure elements and intermolecular interactions. This diversity results in PPI binding affinities that span more than nine orders of magnitude. Several early studies attempted to correlate PPI binding affinities to various structure-derived features with limited success. The growing number of high-resolution structures, the appearance of more precise methods for measuring binding affinities and the development of new computational algorithms enable more thorough investigations in this direction. Here, we use a large dataset of PPI structures with the documented binding affinities to calculate a number of structure-based features that could potentially define binding energetics. We explore how well each calculated biophysical feature alone correlates with binding affinity and determine the features that could be used to distinguish between high-, medium- and low- affinity PPIs. Furthermore, we test how various combinations of features could be applied to predict binding affinity and observe a slow improvement in correlation as more features are incorporated into the equation. In addition, we observe a considerable improvement in predictions if we exclude from our analysis low-resolution and NMR structures, revealing the importance of capturing exact intermolecular interactions in our calculations. Our analysis should facilitate prediction of new interactions on the genome scale, better characterization of signaling networks and design of novel binding partners for various target proteins.

Structure of the ultra-high-affinity colicin E2 DNase--Im2 complex

How proteins achieve high-affinity binding to a specific protein partner while simultaneously excluding all others is a major biological problem that has important implications for protein design. We report the crystal structure of the ultra-high-affinity protein-protein complex between the endonuclease domain of colicin E2 and its cognate immunity (Im) protein, Im2 (K(d)∼10(-)(15) M), which, by comparison to previous structural and biophysical data, provides unprecedented insight into how high affinity and selectivity are achieved in this model family of protein complexes. Our study pinpoints the role of structured water molecules in conjoining hotspot residues that govern stability with residues that control selectivity. A key finding is that a single residue, which in a noncognate context massively destabilizes the complex through frustration, does not participate in specificity directly but rather acts as an organizing center for a multitude of specificity interactions across the interface, many of which are water mediated.

Nuclease colicins and their immunity proteins

It is more than 80 years since Gratia first described 'a remarkable antagonism between two strains of Escherichia coli'. Shown subsequently to be due to the action of proteins (or peptides) produced by one bacterium to kill closely related species with which it might be cohabiting, such bacteriocins have since been shown to be commonplace in the internecine warfare between bacteria. Bacteriocins have been studied primarily from the twin perspectives of how they shape microbial communities and how they penetrate bacteria to kill them. Here, we review the modes of action of a family of bacteriocins that cleave nucleic acid substrates in E. coli, known collectively as nuclease colicins, and the specific immunity (inhibitor) proteins that colicin-producing organisms make in order to avoid committing suicide. In a process akin to targeting in mitochondria, nuclease colicins engage in a variety of cellular associations in order to translocate their cytotoxic domains through the cell envelope to the cytoplasm. As well as informing on the process itself, the study of nuclease colicin import has also illuminated functional aspects of the host proteins they parasitize. We also review recent studies where nuclease colicins and their immunity proteins have been used as model systems for addressing fundamental problems in protein folding and protein-protein interactions, areas of biophysics that are intimately linked to the role of colicins in bacterial competition and to the import process itself.

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.

Strengths and weaknesses of data-driven docking in critical assessment of prediction of interactions

The recent CAPRI rounds have introduced new docking challenges in the form of protein-RNA complexes, multiple alternative interfaces, and an unprecedented number of targets for which homology modeling was required. We present here the performance of HADDOCK and its web server in the CAPRI experiment and discuss the strengths and weaknesses of data-driven docking. HADDOCK was successful for 6 out of 9 complexes (6 out of 11 targets) and accurately predicted the individual interfaces for two more complexes. The HADDOCK server, which is the first allowing the simultaneous docking of generic multi-body complexes, was successful in 4 out of 7 complexes for which it participated. In the scoring experiment, we predicted the highest number of targets of any group. The main weakness of data-driven docking revealed from these last CAPRI results is its vulnerability for incorrect experimental data related to the interface or the stoichiometry of the complex. At the same time, the use of experimental and/or predicted information is also the strength of our approach as evidenced for those targets for which accurate experimental information was available (e.g., the 10 three-stars predictions for T40!). Even when the models show a wrong orientation, the individual interfaces are generally well predicted with an average coverage of 60% ± 26% over all targets. This makes data-driven docking particularly valuable in a biological context to guide experimental studies like, for example, targeted mutagenesis.

Selection of near-native poses in CAPRI rounds 13-19

In CAPRI rounds 13-19, we submitted models that are of acceptable or higher quality for 6 of the total of 13 targets. This success builds on our record in previous CAPRI rounds. The docking problem can be divided into two steps. In the first, translational/rotational and conformational space is searched to generate a pool of docked poses; the success of this search step is measured by whether near-native poses are included in the pool. In the second step, the pool is selected for near-native poses. In our previous assessment of CAPRI results, we suggested that the search problem is largely solved; a remaining problem is to select near-native poses. Our work in these new rounds of CAPRI was guided by this assessment. To solve the selection problem, we used an assortment of criteria on the interfaces of candidate poses. In one extreme, represented by T29, with very little known interface information, our criterion for top models was based on interface prediction. Poses in which the predicted interface residues occurred in interfaces were selected. Our model 1 for T29 was of medium quality. In the other extreme, represented by T40, with reliably known interface information, our selection was solely based on such information. Nine of the ten models submitted for T40 were of high (3 models), medium (4 models), and acceptable (2 models) quality. Our strategy of mixing predicted and known interface information appears to be widely applicable for the selection of near-native poses.

Optimization of pyDock for the new CAPRI challenges: Docking of homology-based models, domain-domain assembly and protein-RNA binding

We describe here our results in the last CAPRI edition. We have participated in all targets, both as predictors and as scorers, using our pyDock docking methodology. The new challenges (homology-based modeling of the interacting subunits, domain-domain assembling, and protein-RNA interactions) have pushed our computer tools to the limits and have encouraged us to devise new docking approaches. Overall, the results have been quite successful, in line with previous editions, especially considering the high difficulty of some of the targets. Our docking approaches succeeded in five targets as predictors or as scorers (T29, T34, T35, T41, and T42). Moreover, with the inclusion of available information on the residues expected to be involved in the interaction, our protocol would have also succeeded in two additional cases (T32 and T40). In the remaining targets (except T37), results were equally poor for most of the groups. We submitted the best model (in ligand RMSD) among scorers for the unbound-bound target T29, the second best model among scorers for the protein-RNA target T34, and the only correct model among predictors for the domain assembly target T35. In summary, our excellent results for the new proposed challenges in this CAPRI edition showed the limitations and applicability of our approaches and encouraged us to continue developing methodologies for automated biomolecular docking.

Performance of ZDOCK and ZRANK in CAPRI rounds 13-19

We report the performance of the ZDOCK and ZRANK algorithms in CAPRI rounds 13-19 and introduce a novel measure atom contact frequency (ACF). To compute ACF, we identify the residues that most often make contact with the binding partner in the complete set of ZDOCK predictions for each target. We used ACF to predict the interface of the proteins, which, in combination with the biological data available in the literature, is a valuable addition to our docking pipeline. Furthermore, we incorporated a straightforward and efficient clustering algorithm with two purposes: (1) to determine clusters of similar docking poses (corresponding to energy funnels) and (2) to remove redundancies from the final set of predictions. With these new developments, we achieved at least one acceptable prediction for targets 29 and 36, at least one medium-quality prediction for targets 41 and 42, and at least one high-quality prediction for targets 37 and 40; thus, we succeeded for six out of a total of 12 targets.

The structural and energetic basis for high selectivity in a high-affinity protein-protein interaction

High-affinity, high-selectivity protein-protein interactions that are critical for cell survival present an evolutionary paradox: How does selectivity evolve when acquired mutations risk a lethal loss of high-affinity binding? A detailed understanding of selectivity in such complexes requires structural information on weak, noncognate complexes which can be difficult to obtain due to their transient and dynamic nature. Using NMR-based docking as a guide, we deployed a disulfide-trapping strategy on a noncognate complex between the colicin E9 endonuclease (E9 DNase) and immunity protein 2 (Im2), which is seven orders of magnitude weaker binding than the cognate femtomolar E9 DNase-Im9 interaction. The 1.77 A crystal structure of the E9 DNase-Im2 complex reveals an entirely noncovalent interface where the intersubunit disulfide merely supports the crystal lattice. In combination with computational alanine scanning of interfacial residues, the structure reveals that the driving force for binding is so strong that a severely unfavorable specificity contact is tolerated at the interface and as a result the complex becomes weakened through "frustration." As well as rationalizing past mutational and thermodynamic data, comparing our noncognate structure with previous cognate complexes highlights the importance of loop regions in developing selectivity and accentuates the multiple roles of buried water molecules that stabilize, ameliorate, or aggravate interfacial contacts. The study provides direct support for dual-recognition in colicin DNase-Im protein complexes and shows that weakened noncognate complexes are primed for high-affinity binding, which can be achieved by economical mutation of a limited number of residues at the interface.

Energy-dependent immunity protein release during tol-dependent nuclease colicin translocation

Nuclease colicins bind their target receptor in the outer membrane of sensitive cells in the form of a high affinity complex with their cognate immunity proteins. Upon cell entry the immunity protein is lost from the complex by means that are poorly understood. We have developed a sensitive fluorescence assay that has enabled us to study the molecular requirements for immunity protein release. Nuclease colicins use members of the tol operon for their translocation across the outer membrane. We have demonstrated that the amino-terminal 80 residues of the colicin E9 molecule, which is the region that interacts with TolB, are essential for immunity protein release. Using tol deletion strains we analyzed the cellular components necessary for immunity protein release and found that in addition to a requirement for tolB, the tolA deletion strain was most affected. Complementation studies showed that the mutation H22A, within the transmembrane segment of TolA, abolishes immunity protein release. Investigation of the energy requirements demonstrated that the proton motive force of the cytoplasmic membrane is critical. Taken together these results demonstrate for the first time a clear energy requirement for the uptake of a nuclease colicin complex and suggest that energy transduced from the cytoplasmic membrane to the outer membrane by TolA could be the driving force for immunity protein release and concomitant translocation of the nuclease domain.

Experimental and computational analyses of the energetic basis for dual recognition of immunity proteins by colicin endonucleases

Colicin endonucleases (DNases) are bound and inactivated by immunity (Im) proteins. Im proteins are broadly cross-reactive yet specific inhibitors binding cognate and non-cognate DNases with K(d) values that vary between 10(-4) and 10(-14) M, characteristics that are explained by a 'dual-recognition' mechanism. In this work, we addressed for the first time the energetics of Im protein recognition by colicin DNases through a combination of E9 DNase alanine scanning and double-mutant cycles (DMCs) coupled with kinetic and calorimetric analyses of cognate Im9 and non-cognate Im2 binding, as well as computational analysis of alanine scanning and DMC data. We show that differential DeltaDeltaGs observed for four E9 DNase residues cumulatively distinguish cognate Im9 association from non-cognate Im2 association. E9 DNase Phe86 is the primary specificity hotspot residue in the centre of the interface, which is coordinated by conserved and variable hotspot residues of the cognate Im protein. Experimental DMC analysis reveals that only modest coupling energies to Im9 residues are observed, in agreement with calculated DMCs using the program ROSETTA and consistent with the largely hydrophobic nature of E9 DNase-Im9 specificity contacts. Computed values for the 12 E9 DNase alanine mutants showed reasonable agreement with experimental DeltaDeltaG data, particularly for interactions not mediated by interfacial water molecules. DeltaDeltaG predictions for residues that contact buried water molecules calculated using solvated rotamer models met with mixed success; however, we were able to predict with a high degree of accuracy the location and energetic contribution of one such contact. Our study highlights how colicin DNases are able to utilise both conserved and variable amino acids to distinguish cognate from non-cognate Im proteins, with the energetic contributions of the conserved residues modulated by neighbouring specificity sites.

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.

Colicin biology

Colicins are proteins produced by and toxic for some strains of Escherichia coli. They are produced by strains of E. coli carrying a colicinogenic plasmid that bears the genetic determinants for colicin synthesis, immunity, and release. Insights gained into each fundamental aspect of their biology are presented: their synthesis, which is under SOS regulation; their release into the extracellular medium, which involves the colicin lysis protein; and their uptake mechanisms and modes of action. Colicins are organized into three domains, each one involved in a different step of the process of killing sensitive bacteria. The structures of some colicins are known at the atomic level and are discussed. Colicins exert their lethal action by first binding to specific receptors, which are outer membrane proteins used for the entry of specific nutrients. They are then translocated through the outer membrane and transit through the periplasm by either the Tol or the TonB system. The components of each system are known, and their implication in the functioning of the system is described. Colicins then reach their lethal target and act either by forming a voltage-dependent channel into the inner membrane or by using their endonuclease activity on DNA, rRNA, or tRNA. The mechanisms of inhibition by specific and cognate immunity proteins are presented. Finally, the use of colicins as laboratory or biotechnological tools and their mode of evolution are discussed.

Computational Design of a New Hydrogen Bond Network and at Least a 300-fold Specificity Switch at a Protein−Protein Interface

The redesign of protein-protein interactions is a stringent test of our understanding of molecular recognition and specificity. Previously we engineered a modest specificity switch into the colicin E7 DNase-Im7 immunity protein complex by identifying mutations that are disruptive in the native complex, but can be compensated by mutations on the interacting partner. Here we extend the approach by systematically sampling alternate rigid body orientations to optimize the interactions in a binding mode specific manner. Using this protocol we designed a de novo hydrogen bond network at the DNase-immunity protein interface and confirmed the design with X-ray crystallographic analysis. Subsequent design of the second shell of interactions guided by insights from the crystal structure on tightly bound water molecules, conformational strain, and packing defects yielded new binding partners that exhibited specificities of at least 300-fold between the cognate and the non-cognate complexes. This multi-step approach should be applicable to the design of polar protein-protein interactions and contribute to the re-engineering of regulatory networks mediated by protein-protein interactions.

A modular interface of IL-4 allows for scalable affinity without affecting specificity for the IL-4 receptor

BACKGROUND

Interleukin 4 (IL-4) is a key regulator of the immune system and an important factor in the development of allergic hypersensitivity. Together with interleukin 13 (IL-13), IL-4 plays an important role in exacerbating allergic and asthmatic symptoms. For signal transduction, both cytokines can utilise the same receptor, consisting of the IL-4Ralpha and the IL-13Ralpha1 chain, offering an explanation for their overlapping biological functions. Since both cytokine ligands share only moderate similarity on the amino acid sequence level, molecular recognition of the ligands by both receptor subunits is of great interest. IL-4 and IL-13 are interesting targets for allergy and asthma therapies. Knowledge of the binding mechanism will be important for the generation of either IL-4 or IL-13 specific drugs.

RESULTS

We present a structure/function analysis of the IL-4 ligand-receptor interaction. Structural determination of a number of IL-4 variants together with in vitro binding studies show that IL-4 and its high-affinity receptor subunit IL-4Ralpha interact via a modular protein-protein interface consisting of three independently-acting interaction clusters. For high-affinity binding of wild-type IL-4 to its receptor IL-4Ralpha, only two of these clusters (i.e. cluster 1 centered around Glu9 and cluster 2 around Arg88) contribute significantly to the free binding energy. Mutating residues Thr13 or Phe82 located in cluster 3 to aspartate results in super-agonistic IL-4 variants. All three clusters are fully engaged in these variants, generating a three-fold higher binding affinity for IL-4Ralpha. Mutagenesis studies reveal that IL-13 utilizes the same main binding determinants, i.e. Glu11 (cluster 1) and Arg64 (cluster 2), suggesting that IL-13 also uses this modular protein interface architecture.

CONCLUSION

The modular architecture of the IL-4-IL-4Ralpha interface suggests a possible mechanism by which proteins might be able to generate binding affinity and specificity independently. So far, affinity and specificity are often considered to co-vary, i.e. high specificity requires high affinity and vice versa. Although the binding affinities of IL-4 and IL-13 to IL-4Ralpha differ by a factor of more than 1000, the specificity remains high because the receptor subunit IL-4Ralpha binds exclusively to IL-4 and IL-13. An interface formed by several interaction clusters/binding hot-spots allows for a broad range of affinities by selecting how many of these interaction clusters will contribute to the overall binding free energy. Understanding how proteins generate affinity and specificity is essential as more and more growth factor receptor families show promiscuous binding to their respective ligands. This limited specificity is, however, not accompanied by low binding affinities.

Interactions of TolB with the translocation domain of colicin E9 require an extended TolB box

The mechanism by which enzymatic E colicins such as colicin E3 (ColE3) and ColE9 cross the outer membrane, periplasm, and cytoplasmic membrane to reach the cytoplasm and thus kill Escherichia coli cells is unique in prokaryotic biology but is poorly understood. This requires an interaction between TolB in the periplasm and three essential residues, D35, S37, and W39, of a pentapeptide sequence called the TolB box located in the N-terminal translocation domain of the enzymatic E colicins. Here we used site-directed mutagenesis to demonstrate that the TolB box sequence in ColE9 is actually larger than the pentapeptide and extends from residues 34 to 46. The affinity of the TolB box mutants for TolB was determined by surface plasmon resonance to confirm that the loss of biological activity in all except one (N44A) of the extended TolB box mutants correlates with a reduced affinity of binding to TolB. We used a PCR mutagenesis protocol to isolate residues that restored activity to the inactive ColE9 D35A, S37A, and W39A mutants. A serine residue at position 35, a threonine residue at position 37, and phenylalanine or tyrosine residues at position 39 restored biological activity of the mutant ColE9. The average area predicted to be buried upon folding (AABUF) was correlated with the activity of the variants at positions 35, 37, and 39 of the TolB box. All active variants had AABUF profiles that were similar to the wild-type residues at those positions and provided information on the size, stereochemistry, and potential folding pattern of the residues of the TolB Box.

The Kinetic Basis for Dual Recognition in Colicin Endonuclease–Immunity Protein Complexes

The antibacterial activity of E colicin endonucleases (DNases) is counteracted by the binding of immunity proteins; the affinities of cognate and non-cognate complexes differing by up to ten orders of magnitude. Here, we address the mechanism of complex formation using a combination of protein engineering, pre-steady-state kinetics and isothermal titration calorimetry, in order to understand the underlying basis for specificity. Contrary to previous work, we show that a pre-equilibrium mechanism does not explain the binding kinetics. Instead, the data are best explained by a modified induced-fit mechanism where cognate and non-cognate complexes alike form a non-specific, conformationally dynamic encounter complex, most likely centred on conserved interactions at the interface. The dynamics appear to be an intrinsic property of the encounter complex where the proteins move relative to one another, thereby sampling different conformations rather than being "induced" by binding. This allows optimal alignment of interface specificity sites, without producing energetically costly conformational changes, essential for high-affinity binding. Importantly, specificity is achieved without slowing the rate of association, an important requirement for rapid inhibition of the colicin in the producing bacterial cell. A rigid-body rotation model is also consistent with the observation that specificity contacts in colicin-immunity protein complexes can involve different regions of the interface. Such a kinetic discrimination mechanism explains the ability of DNase-specific immunity proteins to display dual recognition specificity, wherein they are broadly cross-reactive yet are highly specific, achieving femtomolar binding affinities in complexes with their cognate DNases.

Directed Evolution of Protein Inhibitors of DNA-nucleases by in Vitro Compartmentalization (IVC) and Nano-droplet Delivery

In vitro compartmentalization (IVC) uses water-in-oil emulsions to create artificial cell-like compartments in which genes can be individually transcribed and translated. Here, we present a new application of IVC for the selection of DNA-nuclease inhibitors. We developed a nano-droplets delivery system that allows the transport of various solutes, including metal ions, into the emulsion droplets. This transport mechanism was used to regulate the activity of colicin nucleases that were co-compartmentalized with the genes, so that the nucleases were activated by nickel or cobalt ions only after the potential inhibitor genes have been translated. Thus, genes encoding nuclease inhibitors survived the digestion and were subsequently amplified and isolated. Selection is therefore directly for inhibition, and not for binding of the nuclease. The stringency of selection can be easily modulated to give high enrichments (100-500-fold) and recoveries. We demonstrated its utility by selecting libraries of the gene encoding the cognate inhibitor of colicin E9 (immunity protein 9, or Im9) for inhibition of another colicin (ColE7). The in vitro evolved inhibitors show significant inhibition of ColE7 both in vitro and in vivo. These Im9 variants carry mutations into residues that determine the selectivity of the natural counterpart (Im7) while completely retaining the residues that are conserved throughout the family of immunity protein inhibitors. The in vitro evolution process confirms earlier hypotheses regarding the "dual recognition" binding mechanism and the way in which new colicin-immunity pairs diverged from existing ones.

Highly Discriminating Protein–Protein Interaction Specificities in the Context of a Conserved Binding Energy Hotspot

We explore the thermodynamic basis for high affinity binding and specificity in conserved protein complexes using colicin endonuclease-immunity protein complexes as our model system. We investigated the ability of each colicin-specific immunity protein (Im2, Im7, Im8 and Im9) to bind the endonuclease (DNase) domains of colicins E2, E7 and E8 in vitro and compared these to the previously studied colicin E9. We find that high affinity binding (Kd < or = 10(-14) M) is a common feature of cognate colicin DNase-Im protein complexes as are non-cognate protein-protein associations, which are generally 10(6)-10(8)-fold weaker. Comparative alanine scanning of Im2 and Im9 residues involved in binding the E2 DNase revealed similar behaviour to that of the two proteins binding the E9 DNase; helix III forms a conserved binding energy hotspot with specificity residues from helix II only contributing favourably in a cognate interaction, a combination we have termed as "dual recognition". Significant differences are seen, however, in the number and side-chain chemistries of specificity sites that contribute to cognate binding. In Im2, Asp33 from helix II dominates colicin E2 specificity, whereas in Im9 several hydrophobic residues, including position 33 (leucine), help define its colicin specificity. A similar distribution of specificity sites was seen using phage display where, with Im2 as the template, a library of randomised sequences was generated in helix II and the library panned against either the E2 or E9 DNase. Position 33 was the dominant specificity site recovered in all E2 DNase-selected clones, whereas a number of Im9 specificity sites were recovered in E9 DNase-selected clones, including position 33. In order to probe the relationship between biological specificity and in vitro binding affinity we compared the degree of protection afforded to bacteria against colicin E9 toxicity by a set of immunity proteins whose affinities for the E9 DNase differed by up to ten orders of magnitude. This analysis indicated that the Kd required for complete biological protection is <10(-10)M and that the "affinity window" over which the selection of novel immunity protein specificities likely evolves is 10(-6)-10(-10)M. This comprehensive survey of colicin DNase-immunity protein complexes illustrates how high affinity protein-protein interactions can be very discriminating even though binding is dominated by a conserved hotspot, with single or multiple specificity sites modulating the overall binding free energy. We discuss these results in the context of other conserved protein complexes and suggest that they point to a generic specificity mechanism in divergently evolved protein-protein interactions.

Protein-protein interactions: structurally conserved residues distinguish between binding sites and exposed protein surfaces

Polar residue hot spots have been observed at protein-protein binding sites. Here we show that hot spots occur predominantly at the interfaces of macromolecular complexes, distinguishing binding sites from the remainder of the surface. Consequently, hot spots can be used to define binding epitopes. We further show a correspondence between energy hot spots and structurally conserved residues. The number of structurally conserved residues, particularly of high ranking energy hot spots, increases with the binding site contact size. This finding may suggest that effectively dispersing hot spots within a large contact area, rather than compactly clustering them, may be a strategy to sustain essential key interactions while still allowing certain protein flexibility at the interface. Thus, most conserved polar residues at the binding interfaces confer rigidity to minimize the entropic cost on binding, whereas surrounding residues form a flexible cushion. Furthermore, our finding that similar residue hot spots occur across different protein families suggests that affinity and specificity are not necessarily coupled: higher affinity does not directly imply greater specificity. Conservation of Trp on the protein surface indicates a highly likely binding site. To a lesser extent, conservation of Phe and Met also imply a binding site. For all three residues, there is a significant conservation in binding sites, whereas there is no conservation on the exposed surface. A hybrid strategy, mapping sequence alignment onto a single structure illustrates the possibility of binding site identification around these three residues.

Structural analysis of the rate-limiting transition states in the folding of Im7 and Im9: similarities and differences in the folding of homologous proteins

The bacterial immunity proteins Im7 and Im9 fold with mechanisms of different kinetic complexity. Whilst Im9 folds in a two-state transition at pH 7.0 and 10 degrees C, Im7 populates an on-pathway intermediate under these conditions. In order to assess the role of sequence versus topology in the folding of these proteins, and to analyse the effect of populating an intermediate on the landscape for folding, we have determined the conformational properties of the rate-limiting transition state for Im9 folding/unfolding using Phi(F)-value analysis and have compared the results with similar data obtained previously for Im7. The data show that the rate-limiting transition states for Im9 and Im7 folding/unfolding are similar: both are compact (beta(T)=0.94 and 0.89, respectively) and contain three of the four native helices docked around a specific hydrophobic core. Significant differences are observed, however, in the magnitude of the Phi(F)-values obtained for the two proteins. Of the 20 residues studied in both proteins, ten have Phi(F)-values in Im7 that exceed those in Im9 by more than 0.2, and of these five differ by more than 0.4. The data suggest that the population of an intermediate in Im7 results in folding via a transition state ensemble that is conformationally restricted relative to that of Im9. The data are consistent with the view that topology is an important determinant of folding. Importantly, however, they also demonstrate that while the folding transition state may be conserved in homologous proteins that fold with two and three-state kinetics, the population of an intermediate can have a significant effect on the breadth of the transition state ensemble.

Principles of docking: An overview of search algorithms and a guide to scoring functions

The docking field has come of age. The time is ripe to present the principles of docking, reviewing the current state of the field. Two reasons are largely responsible for the maturity of the computational docking area. First, the early optimism that the very presence of the "correct" native conformation within the list of predicted docked conformations signals a near solution to the docking problem, has been replaced by the stark realization of the extreme difficulty of the next scoring/ranking step. Second, in the last couple of years more realistic approaches to handling molecular flexibility in docking schemes have emerged. As in folding, these derive from concepts abstracted from statistical mechanics, namely, populations. Docking and folding are interrelated. From the purely physical standpoint, binding and folding are analogous processes, with similar underlying principles. Computationally, the tools developed for docking will be tremendously useful for folding. For large, multidomain proteins, domain docking is probably the only rational way, mimicking the hierarchical nature of protein folding. The complexity of the problem is huge. Here we divide the computational docking problem into its two separate components. As in folding, solving the docking problem involves efficient search (and matching) algorithms, which cover the relevant conformational space, and selective scoring functions, which are both efficient and effectively discriminate between native and non-native solutions. It is universally recognized that docking of drugs is immensely important. However, protein-protein docking is equally so, relating to recognition, cellular pathways, and macromolecular assemblies. Proteins function when they are bound to other molecules. Consequently, we present the review from both the computational and the biological points of view. Although large, it covers only partially the extensive body of literature, relating to small (drug) and to large protein-protein molecule docking, to rigid and to flexible. Unfortunately, when reviewing these, a major difficulty in assessing the results is the non-uniformity in the formats in which they are presented in the literature. Consequently, we further propose a way to rectify it here.

Structural aspects of the inhibition of DNase and rRNase colicins by their immunity proteins

Nuclease E colicins that exert their cytotoxic activity through either non-specific DNase or specific rRNase action are inhibited by immunity proteins in a high affinity interaction that gives complete protection to the producing host cell from the deleterious effects of the toxin. Previous X-ray crystallographic analysis of these systems has revealed that in both cases, the immunity protein inhibitor forms its highly stable complex with the enzyme by binding as an exosite inhibitor-adjacent to, but not obscuring, the enzyme active site. The structures of the free E9 DNase domain and its complex with an ssDNA substrate now show that inhibition is achieved without deformation of the enzyme and by occlusion of a limited number of residues of the enzyme critical in recognition and binding of the substrate that are 3' to the cleaved scissile phosphodiester. No sequence or structural similarity is evident between the two classes of cytotoxic domain, and the heterodimer interfaces are also dissimilar. Thus, whilst these structures suggest the basis for specificity in each case, they give few indications as to the basis for the remarkably strong binding that is observed. Structural analyses of complexes bearing single site mutations in the immunity protein at the heterodimer interface reveal further differences. For the DNases, a largely plastic interface is suggested, where optimal binding may be achieved in part by rigid body adjustment in the relative positions of inhibitor and enzyme. For the rRNases, a large solvent-filled cavity is found at the immunity-enzyme interface, suggesting that other considerations, such as that arising from the entropy contribution from bound water molecules, may have greater significance in the determination of rRNase complex affinity than for the DNases.

Translocation of a functional protein by a voltage-dependent ion channel

The voltage-dependent gating of the colicin channel involves a substantial structural rearrangement that results in the transfer of about 35% of the 200 residues in its pore-forming domain across the membrane. This transfer appears to represent an unusual type of protein translocation that does not depend on a large, multimeric, protein pore. To investigate the ability of this system to transport arbitrary proteins, we made use of a pair of strongly interacting proteins, either of which could serve as a translocated cargo or as a probe to detect the other. Here we show that both an 86-residue and a 134-residue hydrophilic protein inserted into the translocated segment of colicin A are themselves translocated and are functional on the trans side of the bilayer. The disparate features of these proteins suggest that the colicin channel has a general protein translocation mechanism.

Immunity proteins: enzyme inhibitors that avoid the active site

Immunity proteins are high affinity inhibitors of colicins--SOS-induced toxins released by bacteria during times of stress. Recent work has shown that nuclease-specific immunity proteins are exosite inhibitors, binding adjacent to the enzyme active site and inhibiting colicin activity indirectly. Unusually, their binding sites comprise a near contiguous sequence that lies N-terminal to active site sequences, raising the possibility that immunity proteins bind colicins co-translationally. Exosite binding accounts for the extensive sequence diversity seen at the interfaces of colicin-immunity protein complexes, which is not only a selective advantage to colicin-producing bacteria, but also represents a powerful model system for studying specificity in protein-protein recognition.

Using chimeric immunity proteins to explore the energy landscape for alpha-helical protein folding

To address the role of sequence in the folding of homologous proteins, the folding and unfolding kinetics of the all-helical bacterial immunity proteins Im2 and Im9 were characterised, together with six chimeric derivatives of these proteins. We show that both Im2 and Im9 fold rapidly (k(UN)(H(2)O)) approximately 2000 s(-1) at pH 7.0, 25 degrees C) in apparent two-state transitions, through rate-limiting transition states that are highly compact (beta(TS)0.93 and 0.96, respectively). Whilst the folding and unfolding properties of three of the chimeras (Im2 (1-44)(Im9), Im2 (1-64)(Im9 )and Im2 (25-44)(Im9)) are similar to their parental counterparts, in other chimeric proteins the introduced sequence variation results in altered kinetic behaviour. At low urea concentrations, Im2 (1-29)(Im9) and Im2 (56-64)(Im9) fold in two-state transitions via transition states that are significantly less compact (beta(TS) approximately 0.7) than those characterised for the other immunity proteins presented here. At higher urea concentrations, however, the rate-limiting transition state for these two chimeras switches or moves to a more compact species (beta(TS) approximately 0.9). Surprisingly, Im2 (30-64)(Im9) populates a highly collapsed species (beta(I)=0.87) in the dead-time (2.5 ms) of stopped flow measurements. These data indicate that whilst topology may place significant constraints on the folding process, specific inter-residue interactions, revealed here through multiple sequence changes, can modulate the ruggedness of the folding energy landscape.

Inhibition of a ribosome-inactivating ribonuclease: the crystal structure of the cytotoxic domain of colicin E3 in complex with its immunity protein

BACKGROUND

The cytotoxicity of most ribonuclease E colicins towards Escherichia coli arises from their ability to specifically cleave between bases 1493 and 1494 of 16S ribosomal RNA. This activity is carried by the C-terminal domain of the colicin, an activity which if left unneutralised would lead to destruction of the producing cell. To combat this the host E. coli cell produces an inhibitor protein, the immunity protein, which forms a complex with the ribonuclease domain effectively suppressing its activity.

RESULTS

We have solved the crystal structure of the cytotoxic domain of the ribonuclease colicin E3 in complex with its immunity protein, Im3. The structure of the ribonuclease domain, the first of its class, reveals a highly twisted central beta-sheet elaborated with a short N-terminal helix, the residues of which form a well-packed interface with the immunity protein.

CONCLUSIONS

The structure of the ribonuclease domain of colicin E3 is novel and forms an interface with its inhibitor which is significantly different in character to that reported for the DNase colicin complexes with their immunity proteins. The structure also gives insight into the mode of action of this class of enzymatic colicins by allowing the identification of potentially catalytic residues. This in turn reveals that the inhibitor does not bind at the active site but rather at an adjacent site, leaving the catalytic centre exposed in a fashion similar to that observed for the DNase colicins. Thus, E. coli appears to have evolved similar methods for ensuring efficient inhibition of the potentially destructive effects of the two classes of enzymatic colicins.

NMR investigation of the interaction of the inhibitor protein Im9 with its partner DNase

The bacterial toxin colicin E9 is secreted by producing Escherichia coli cells with its 9.5 kDa inhibitor protein Im9 bound tightly to its 14.5 kDa C-terminal DNase domain. Double- and triple-resonance NMR spectra of the 24 kDa complex of uniformly 13C and 15N labeled Im9 bound to the unlabeled DNase domain have provided sufficient constraints for the solution structure of the bound Im9 to be determined. For the final ensemble of 20 structures, pairwise RMSDs for residues 3-84 were 0.76 +/- 0.14 A for the backbone atoms and 1.36 +/- 0.15 A for the heavy atoms. Representative solution structures of the free and bound Im9 are highly similar, with backbone and heavy atom RMSDs of 1.63 and 2.44 A, respectively, for residues 4-83, suggesting that binding does not cause a major conformational change in Im9. The NMR studies have also allowed the DNase contact surface on Im9 to be investigated through changes in backbone chemical shifts and NOEs between the two proteins determined from comparisons of 1H-1H-13C NOESY-HSQC spectra with and without 13C decoupling. The NMR-defined interface agrees well with that determined in a recent X-ray structure analysis with the major difference being that a surface loop of Im9, which is at the interface, has a different conformation in the solution and crystal structures. Tyr54, a key residue on the interface, is shown to exhibit NMR characteristics indicative of slow rotational flipping. A mechanistic description of the influence binding of Im9 has on the dynamic behavior of E9 DNase, which is known to exist in two slowly interchanging conformers in solution, is proposed.

Specificity in protein-protein interactions: the structural basis for dual recognition in endonuclease colicin-immunity protein complexes

Bacteria producing endonuclease colicins are protected against their cytotoxic activity by virtue of a small immunity protein that binds with high affinity and specificity to inactivate the endonuclease. DNase binding by the immunity protein occurs through a "dual recognition" mechanism in which conserved residues from helix III act as the binding-site anchor, while variable residues from helix II define specificity. We now report the 1.7 A crystal structure of the 24.5 kDa complex formed between the endonuclease domain of colicin E9 and its cognate immunity protein Im9, which provides a molecular rationale for this mechanism. Conserved residues of Im9 form a binding-energy hotspot through a combination of backbone hydrogen bonds to the endonuclease, many via buried solvent molecules, and hydrophobic interactions at the core of the interface, while the specificity-determining residues interact with corresponding specificity side-chains on the enzyme. Comparison between the present structure and that reported recently for the colicin E7 endonuclease domain in complex with Im7 highlights how specificity is achieved by very different interactions in the two complexes, predominantly hydrophobic in nature in the E9-Im9 complex but charged in the E7-Im7 complex. A key feature of both complexes is the contact between a conserved tyrosine residue from the immunity proteins (Im9 Tyr54) with a specificity residue on the endonuclease directing it toward the specificity sites of the immunity protein. Remarkably, this tyrosine residue and its neighbour (Im9 Tyr55) are the pivots of a 19 degrees rigid-body rotation that relates the positions of Im7 and Im9 in the two complexes. This rotation does not affect conserved immunity protein interactions with the endonuclease but results in different regions of the specificity helix being presented to the enzyme.