Intramolecular cooperativity in a protein binding site assessed by combinatorial shotgun scanning mutagenesis

Systematic substitutions at BLIP position 50 result in changes in binding specificity for class A β-lactamases

Background

The production of β-lactamases by bacteria is the most common mechanism of resistance to the widely prescribed β-lactam antibiotics. β-lactamase inhibitory protein (BLIP) competitively inhibits class A β-lactamases via two binding loops that occlude the active site. It has been shown that BLIP Tyr50 is a specificity determinant in that substitutions at this position result in large differential changes in the relative affinity of BLIP for class A β-lactamases.

Results

In this study, the effect of systematic substitutions at BLIP position 50 on binding to class A β-lactamases was examined to further explore the role of BLIP Tyr50 in modulating specificity. The results indicate the sequence requirements at position 50 are widely different depending on the target β-lactamase. Stringent sequence requirements were observed at Tyr50 for binding Bacillus anthracis Bla1 while moderate requirements for binding TEM-1 and relaxed requirements for binding KPC-2 β-lactamase were seen. These findings cannot be easily rationalized based on the β-lactamase residues in direct contact with BLIP Tyr50 since they are identical for Bla1 and KPC-2 suggesting that differences in the BLIP-β-lactamase interface outside the local environment of Tyr50 influence the effect of substitutions.

Conclusions

Results from this study and previous studies suggest that substitutions at BLIP Tyr50 may induce changes at the interface outside its local environment and point to the complexity of predicting the impact of substitutions at a protein-protein interaction interface.

MASP-3 is the exclusive pro-factor D activator in resting blood: the lectin and the alternative complement pathways are fundamentally linked

MASP-3 was discovered 15 years ago as the third mannan-binding lectin (MBL)-associated serine protease of the complement lectin pathway. Lacking any verified substrate its role remained ambiguous. MASP-3 was shown to compete with a key lectin pathway enzyme MASP-2 for MBL binding, and was therefore considered to be a negative complement regulator. Later, knock-out mice experiments suggested that MASP-1 and/or MASP-3 play important roles in complement pro-factor D (pro-FD) maturation. However, studies on a MASP-1/MASP-3-deficient human patient produced contradicting results. In normal resting blood unperturbed by ongoing coagulation or complement activation, factor D is present predominantly in its active form, suggesting that resting blood contains at least one pro-FD activating proteinase that is not a direct initiator of coagulation or complement activation. We have recently showed that all three MASPs can activate pro-FD in vitro. In resting blood, however, using our previously evolved MASP-1 and MASP-2 inhibitors we proved that neither MASP-1 nor MASP-2 activates pro-FD. Other plasma proteinases, particularly MASP-3, remained candidates for that function. For this study we evolved a specific MASP-3 inhibitor and unambiguously proved that activated MASP-3 is the exclusive pro-FD activator in resting blood, which demonstrates a fundamental link between the lectin and alternative pathways.

Structural determinants governing S100A4-induced isoform-selective disassembly of nonmuscle myosin II filaments

The Ca(2+) -binding protein S100A4 interacts with the C terminus of nonmuscle myosin IIA (NMIIA) causing filament disassembly, which is correlated with an increased metastatic potential of tumor cells. Despite high sequence similarity of the three NMII isoforms, S100A4 discriminates against binding to NMIIB. We searched for structural determinants of this selectivity. Based on paralog scanning using phage display, we identified a single position as major determinant of isoform selectivity. Reciprocal single amino acid replacements showed that at position 1907 (NMIIA numbering), the NMIIA/NMIIC-specific alanine provides about 60-fold higher affinity than the NMIIB-specific asparagine. The structural background of this can be explained in part by a communication between the two consecutive α-helical binding segments. This communication is completely abolished by the Ala-to-Asn substitution. Mutual swapping of the disordered tailpieces only slightly affects the affinity of the NMII chimeras. Interestingly, we found that the tailpiece and position 1907 act in a nonadditive fashion. Finally, we also found that the higher stability of the C-terminal coiled-coil region of NMIIB also discriminates against interaction with S100A4. Our results clearly show that the isoform-selective binding of S100A4 is determined at multiple levels in the structure of the three NMII isoforms and the corresponding functional elements of NMII act synergistically with one another resulting in a complex interaction network. The experimental and in silico results suggest two divergent evolutionary pathways: NMIIA and NMIIB evolved to possess S100A4-dependent and -independent regulations, respectively.

Insights into cytokine-receptor interactions from cytokine engineering

Cytokines exert a vast array of immunoregulatory actions critical to human biology and disease. However, the desired immunotherapeutic effects of native cytokines are often mitigated by toxicity or lack of efficacy, either of which results from cytokine receptor pleiotropy and/or undesired activation of off-target cells. As our understanding of the structural principles of cytokine-receptor interactions has advanced, mechanism-based manipulation of cytokine signaling through protein engineering has become an increasingly feasible and powerful approach. Modified cytokines, both agonists and antagonists, have been engineered with narrowed target cell specificities, and they have also yielded important mechanistic insights into cytokine biology and signaling. Here we review the theory and practice of cytokine engineering and rationalize the mechanisms of several engineered cytokines in the context of structure. We discuss specific examples of how structure-based cytokine engineering has opened new opportunities for cytokines as drugs, with a focus on the immunotherapeutic cytokines interferon, interleukin-2, and interleukin-4.

Mapping of the binding landscape for a picomolar protein-protein complex through computation and experiment

Our understanding of protein evolution would greatly benefit from mapping of binding landscapes, i.e., changes in protein-protein binding affinity due to all single mutations. However, experimental generation of such landscapes is a tedious task due to a large number of possible mutations. Here, we use a simple computational protocol to map the binding landscape for two homologous high-affinity complexes, involving a snake toxin fasciculin and acetylcholinesterase from two different species. To verify our computational predictions, we experimentally measure binding between 25 Fas mutants and the 2 enzymes. Both computational and experimental results demonstrate that the Fas sequence is close to the optimum when interacting with its targets, yet a few mutations could further improve Kd, kon, and koff. Our computational predictions agree well with experimental results and generate distributions similar to those observed in other high-affinity PPIs, demonstrating the potential of simple computational protocols in capturing realistic binding landscapes.

Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization

Predicting the effects of mutations on the kinetic rate constants of protein-protein interactions is central to both the modeling of complex diseases and the design of effective peptide drug inhibitors. However, while most studies have concentrated on the determination of association rate constants, dissociation rates have received less attention. In this work we take a novel approach by relating the changes in dissociation rates upon mutation to the energetics and architecture of hotspots and hotregions, by performing alanine scans pre- and post-mutation. From these scans, we design a set of descriptors that capture the change in hotspot energy and distribution. The method is benchmarked on 713 kinetically characterized mutations from the SKEMPI database. Our investigations show that, with the use of hotspot descriptors, energies from single-point alanine mutations may be used for the estimation of off-rate mutations to any residue type and also multi-point mutations. A number of machine learning models are built from a combination of molecular and hotspot descriptors, with the best models achieving a Pearson's Correlation Coefficient of 0.79 with experimental off-rates and a Matthew's Correlation Coefficient of 0.6 in the detection of rare stabilizing mutations. Using specialized feature selection models we identify descriptors that are highly specific and, conversely, broadly important to predicting the effects of different classes of mutations, interface regions and complexes. Our results also indicate that the distribution of the critical stability regions across protein-protein interfaces is a function of complex size more strongly than interface area. In addition, mutations at the rim are critical for the stability of small complexes, but consistently harder to characterize. The relationship between hotregion size and the dissociation rate is also investigated and, using hotspot descriptors which model cooperative effects within hotregions, we show how the contribution of hotregions of different sizes, changes under different cooperative effects.

Synthetic shuffling and in vitro selection reveal the rugged adaptive fitness landscape of a kinase ribozyme

The relationship between genotype and phenotype is often described as an adaptive fitness landscape. In this study, we used a combination of recombination, in vitro selection, and comparative sequence analysis to characterize the fitness landscape of a previously isolated kinase ribozyme. Point mutations present in improved variants of this ribozyme were recombined in vitro in more than 10(14) different arrangements using synthetic shuffling, and active variants were isolated by in vitro selection. Mutual information analysis of 65 recombinant ribozymes isolated in the selection revealed a rugged fitness landscape in which approximately one-third of the 91 pairs of positions analyzed showed evidence of correlation. Pairs of correlated positions overlapped to form densely connected networks, and groups of maximally connected nucleotides occurred significantly more often in these networks than they did in randomized control networks with the same number of links. The activity of the most efficient recombinant ribozyme isolated from the synthetically shuffled pool was 30-fold greater than that of any of the ribozymes used to build it, which indicates that synthetic shuffling can be a rich source of ribozyme variants with improved properties.

Monospecific inhibitors show that both mannan-binding lectin-associated serine protease-1 (MASP-1) and -2 Are essential for lectin pathway activation and reveal structural plasticity of MASP-2

The lectin pathway is an antibody-independent activation route of the complement system. It provides immediate defense against pathogens and altered self-cells, but it also causes severe tissue damage after stroke, heart attack, and other ischemia reperfusion injuries. The pathway is triggered by target binding of pattern recognition molecules leading to the activation of zymogen mannan-binding lectin-associated serine proteases (MASPs). MASP-2 is considered as the autonomous pathway-activator, while MASP-1 is considered as an auxiliary component. We evolved a pair of monospecific MASP inhibitors. In accordance with the key role of MASP-2, the MASP-2 inhibitor completely blocks the lectin pathway activation. Importantly, the MASP-1 inhibitor does the same, demonstrating that MASP-1 is not an auxiliary but an essential pathway component. We report the first Michaelis-like complex structures of MASP-1 and MASP-2 formed with substrate-like inhibitors. The 1.28 Å resolution MASP-2 structure reveals significant plasticity of the protease, suggesting that either an induced fit or a conformational selection mechanism should contribute to the extreme specificity of the enzyme.

Directed evolution reveals the binding motif preference of the LC8/DYNLL hub protein and predicts large numbers of novel binders in the human proteome

LC8 dynein light chain (DYNLL) is a eukaryotic hub protein that is thought to function as a dimerization engine. Its interacting partners are involved in a wide range of cellular functions. In its dozens of hitherto identified binding partners DYNLL binds to a linear peptide segment. The known segments define a loosely characterized binding motif: [D/S]_-4K_-3X_-2[T/V/I]_-1Q₀[T/V]₁[D/E]₂. The motifs are localized in disordered segments of the DYNLL-binding proteins and are often flanked by coiled coil or other potential dimerization domains. Based on a directed evolution approach, here we provide the first quantitative characterization of the binding preference of the DYNLL binding site. We displayed on M13 phage a naïve peptide library with seven fully randomized positions around a fixed, naturally conserved glutamine. The peptides were presented in a bivalent manner fused to a leucine zipper mimicking the natural dimer to dimer binding stoichiometry of DYNLL-partner complexes. The phage-selected consensus sequence V_-5S_-4R_-3G_-2T_-1Q₀T₁E₂ resembles the natural one, but is extended by an additional N-terminal valine, which increases the affinity of the monomeric peptide twentyfold. Leu-zipper dimerization increases the affinity into the subnanomolar range. By comparing crystal structures of an SRGTQTE-DYNLL and a dimeric VSRGTQTE-DYNLL complex we find that the affinity enhancing valine is accommodated in a binding pocket on DYNLL. Based on the in vitro evolved sequence pattern we predict a large number of novel DYNLL binding partners in the human proteome. Among these EML3, a microtubule-binding protein involved in mitosis contains an exact match of the phage-evolved consensus and binds to DYNLL with nanomolar affinity. These results significantly widen the scope of the human interactome around DYNLL and will certainly shed more light on the biological functions and organizing role of DYNLL in the human and other eukaryotic interactomes.

Triathlon for energy functions: who is the winner for design of protein-protein interactions?

Computational prediction of stabilizing mutations into monomeric proteins has become an almost ordinary task. Yet, computational stabilization of protein–protein complexes remains a challenge. Design of protein–protein interactions (PPIs) is impeded by the absence of an energy function that could reliably reproduce all favorable interactions between the binding partners. In this work, we present three energy functions: one function that was trained on monomeric proteins, while the other two were optimized by different techniques to predict side-chain conformations in a dataset of PPIs. The performances of these energy functions are evaluated in three different tasks related to design of PPIs: predicting side-chain conformations in PPIs, recovering native binding-interface sequences, and predicting changes in free energy of binding due to mutations. Our findings show that both functions optimized on side-chain repacking in PPIs are more suitable for PPI design compared to the function trained on monomeric proteins. Yet, no function performs best at all three tasks. Comparison of the three energy functions and their performances revealed that (1) burial of polar atoms should not be penalized significantly in PPI design as in single-protein design and (2) contribution of electrostatic interactions should be increased several-fold when switching from single-protein to PPI design. In addition, the use of a softer van der Waals potential is beneficial in cases when backbone flexibility is important. All things considered, we define an energy function that captures most of the nuances of the binding energetics and hence, should be used in future for design of PPIs.

Dissecting protein-protein interactions using directed evolution

Protein-protein interactions are essential for life. They are responsible for most cellular functions and when they go awry often lead to disease. Proteins are inherently complex. They are flexible macromolecules whose constituent amino acid components act in combinatorial and networked ways when they engage one another in binding interactions. It is just this complexity that allows them to conduct such a broad array of biological functions. Despite decades of intense study of the molecular basis of protein-protein interactions, key gaps in our understanding remain, hindering our ability to accurately predict the specificities and affinities of their interactions. Until recently, most protein-protein investigations have been probed experimentally at the single-amino acid level, making them, by definition, incapable of capturing the combinatorial nature of, and networked communications between, the numerous residues within and outside of the protein-protein interface. This aspect of protein-protein interactions, however, is emerging as a major driving force for protein affinity and specificity. Understanding a combinatorial process necessarily requires a combinatorial experimental tool. Much like the organisms in which they reside, proteins naturally evolve over time, through a combinatorial process of mutagenesis and selection, to functionally associate. Elucidating the process by which proteins have evolved may be one of the keys to deciphering the molecular rules that govern their interactions with one another. Directed evolution is a technique performed in the laboratory that mimics natural evolution on a tractable time scale that has been utilized widely to engineer proteins with novel capabilities, including altered binding properties. In this review, we discuss directed evolution as an emerging tool for dissecting protein-protein interactions.

Prediction of protein-protein interface sequence diversity using flexible backbone computational protein design

A major challenge in computational protein design is to identify functional sequences as top predictions. One reason for design failures is conformational plasticity, as proteins frequently change their conformation in response to mutations. To advance protein design, here we describe a method employing flexible backbone ensembles to predict sequences tolerated for a protein-protein interface. We show that the predictions are enriched in functional proteins when compared to a phage display screen quantitatively mapping the energy landscape for the interaction between human growth hormone and its receptor. Our model for structural plasticity is inspired by coupled side chain-backbone "backrub" motions observed in high-resolution protein crystal structures. Although the modeled structural changes are subtle, our results on predicting sequence plasticity suggest that backrub sampling may capture a sizable fraction of localized conformational changes that occur in proteins. The described method has implications for predicting sequence libraries to enable challenging protein engineering problems.

Exploring and designing protein function with restricted diversity

Combinatorial libraries with restricted diversity can be used to rapidly map binding energetics across protein interfaces. Shotgun scanning strategies have been used for alanine scanning and for alternative mutagenesis schemes that provide high-resolution functional views of binding interfaces. In addition, synthetic antibodies have been derived from naïve libraries restricted to a binary code to explore the minimal requirements for molecular recognition. These studies shed light on the underlying principles governing molecular recognition, and provide rapid yet quantitative alternatives to conventional biophysical methods for exploring protein structure and function.

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.

Hot Spot Occlusion from Bulk Water: a Comprehensive Study of the Complex between the Lysozyme HEL and the Antibody FVD1.3

Alanine scanning of protein-protein interfaces has shown that there are some residues in the protein-protein interfaces, responsible for most of the binding free energy, which are called hot spots. Hot spots tend to exist in densely packed central clusters, and a hypothesis has been proposed that considers that inaccessibility to the solvent must be a necessary condition to define a residue as a binding hot spot. This O-ring hypothesis is mainly based on the analysis of the accessible surface area (ASA) of 23 static, crystallographic structures of protein complexes. It is known, however, that protein flexibility allows for temporary exposures of buried interfacial groups, and even though the ASA provides a general trend of the propensity for hydration, protein/solvent-specific interactions or hydrogen bonding cannot be considered here. Therefore, a microscopic level, atomistic picture of hot spot solvation is needed to support the O-ring hypothesis. In this study, we began by applying a computational alanine-scanning mutagenesis technique, which reproduces the experimental results and allows for decomposing the binding free energy difference in its different energetic factors. Subsequently, we calculated the radial distribution function and residence times of the water molecules near the hot/warm spots to study the importance of the water environment around those energetically important amino acid residues. This study shows that within a flexible, dynamic protein framework, the warm/hot spot residues are, indeed, kept sheltered from the bulk solvent during the whole simulation, which allows a better interacting microenvironment.

The molecular architecture of protein-protein binding sites

The formation of specific protein interactions plays a crucial role in most, if not all, biological processes, including signal transduction, cell regulation, the immune response and others. Recent advances in our understanding of the molecular architecture of protein-protein binding sites, which facilitates such diversity in binding affinity and specificity, are enabling us to address key questions. What is the amino acid composition of binding sites? What are interface hotspots? How are binding sites organized? What are the differences between tight and weak interacting complexes? How does water contribute to binding? Can the knowledge gained be translated into protein design? And does a universal code for binding exist, or is it the architecture and chemistry of the interface that enable diverse but specific binding solutions?

Comprehensive and quantitative mapping of energy landscapes for protein-protein interactions by rapid combinatorial scanning

A novel, quantitative saturation (QS) scanning strategy was developed to obtain a comprehensive data base of the structural and functional effects of all possible mutations across a large protein-protein interface. The QS scan approach was applied to the high affinity site of human growth hormone (hGH) for binding to its receptor (hGHR). Although the published structure-function data base describing this system is probably the most extensive for any large protein-protein interface, it is nonetheless too sparse to accurately describe the nature of the energetics governing the interaction. Our comprehensive data base affords a complete view of the binding site and provides important new insights into the general principles underlying protein-protein interactions. The hGH binding interface is highly adaptable to mutations, but the nature of the tolerated mutations challenges generally accepted views about the evolutionary and biophysical pressures governing protein-protein interactions. Many substitutions that would be considered chemically conservative are not tolerated, while conversely, many non-conservative substitutions can be accommodated. Furthermore, conservation across species is a poor predictor of the chemical character of tolerated substitutions across the interface. Numerous deviations from generally accepted expectations indicate that mutational tolerance is highly context dependent and, furthermore, cannot be predicted by our current knowledge base. The type of data produced by the comprehensive QS scan can fill the gaps in the structure-function matrix. The compilation of analogous data bases from studies of other protein-protein interactions should greatly aid the development of computational methods for explaining and designing molecular recognition.

Structural basis of affinity maturation and intramolecular cooperativity in a protein-protein interaction

Although protein-protein interactions are involved in nearly all cellular processes, general rules for describing affinity and selectivity in protein-protein complexes are lacking, primarily because correlations between changes in protein structure and binding energetics have not been well determined. Here, we establish the structural basis of affinity maturation for a protein-protein interaction system that we had previously characterized energetically. This model system exhibits a 1500-fold affinity increase. Also, its affinity maturation is restricted by negative intramolecular cooperativity. With three complex and six unliganded variant X-ray crystal structures, we provide molecular snapshots of protein interface remodeling events that span the breadth of the affinity maturation process and present a comprehensive structural view of affinity maturation. Correlating crystallographically observed structural changes with measured energetic changes reveals molecular bases for affinity maturation, intramolecular cooperativity, and context-dependent binding.

Alternative views of functional protein binding epitopes obtained by combinatorial shotgun scanning mutagenesis

Combinatorial shotgun scanning mutagenesis was used to analyze two large, related protein binding sites to assess the specificity and importance of individual side chain contributions to binding affinity. The strategy allowed for cost-effective generation of a plethora of functional data. The ease of the technology promoted comprehensive investigations, in which the classic alanine-scanning approach was expanded with two additional strategies, serine- and homolog-scanning. Binding of human growth hormone (hGH) to the hGH receptor served as the model system. The entire high affinity receptor-binding sites (site 1) of wild-type hGH (hGHwt) and of an affinity-improved variant (hGHv) were investigated and the results were compared. The contributions that 35 residue positions make to binding were assessed on each hormone molecule by both serine- and homolog-scanning. The hormone molecules were displayed on the surfaces of bacteriophage, and the 35 positions were randomized simultaneously to allow equal starting frequencies of the wild-type residue and either serine or a homologous mutation in separate libraries. Functional selections for binding to the hGH receptor shifted the relative wild-type/mutant frequencies at each position to an extent characteristic of the functional importance of the side chain. Functional epitope maps were created and compared to previous maps obtained by alanine-scanning. Comparisons between the different scans provide insights into the affinity maturation process that produced hGHv. The serine and homolog-scanning results expand upon and complement the alanine-scanning results and provide additional data on the robustness of the high affinity receptor-binding site of hGH.

Survey of the year 2005 commercial optical biosensor literature

We identified 1113 articles (103 reviews, 1010 primary research articles) published in 2005 that describe experiments performed using commercially available optical biosensors. While this number of publications is impressive, we find that the quality of the biosensor work in these articles is often pretty poor. It is a little disappointing that there appears to be only a small set of researchers who know how to properly perform, analyze, and present biosensor data. To help focus the field, we spotlight work published by 10 research groups that exemplify the quality of data one should expect to see from a biosensor experiment. Also, in an effort to raise awareness of the common problems in the biosensor field, we provide side-by-side examples of good and bad data sets from the 2005 literature.