An ultra‐high affinity protein–protein interface displaying sequence‐robustness

Protein–protein interactions are crucial in biology and play roles in for example, the immune system, signaling pathways, and enzyme regulation. Ultra‐high affinity interactions (K _d <0.1 nM) occur in these systems, however, structures and energetics behind stability of ultra‐high affinity protein–protein complexes are not well understood. Regulation of the starch debranching barley limit dextrinase (LD) and its endogenous cereal type inhibitor (LDI) exemplifies an ultra‐high affinity complex (K _d of 42 pM). In this study the LD–LDI complex is investigated to unveil how robust the ultra‐high affinity is to LDI sequence variation at the protein–protein interface and whether alternative sequences can retain the ultra‐high binding affinity. The interface of LD–LDI was engineered using computational protein redesign aiming at identifying LDI variants predicted to retain ultra‐high binding affinity. These variants present a very diverse set of mutations going beyond conservative and alanine substitutions typically used to probe interfaces. Surface plasmon resonance analysis of the LDI variants revealed that high affinity of LD–LDI requires interactions of several residues at the rim of the protein interface, unlike the classical hotspot arrangement where key residues are found at the center of the interface. Notably, substitution of interface residues in LDI, including amino acids with functional groups different from the wild‐type, could occur without loss of affinity. This demonstrates that ultra‐high binding affinity can be conferred without hotspot residues, thus making complexes more robust to mutational drift in evolution. The present mutational analysis also demonstrates how energetic coupling can emerge between residues at large distances at the interface.     

Amino acid–base interactions: a three-dimensional analysis of protein–DNA interactions at an atomic level

To assess whether there are universal rules that govern amino acid–base recognition, we investigate hydrogen bonds, van der Waals contacts and water-mediated bonds in 129 protein–DNA complex structures. DNA–backbone interactions are the most numerous, providing stability rather than specificity. For base interactions, there are significant base–amino acid type correlations, which can be rationalised by considering the stereochemistry of protein side chains and the base edges exposed in the DNA structure. Nearly two-thirds of the direct read-out of DNA sequences involves complex networks of hydrogen bonds, which enhance specificity. Two-thirds of all protein–DNA interactions comprise van der Waals contacts, compared to about one-sixth each of hydrogen and water-mediated bonds. This highlights the central importance of these contacts for complex formation, which have previously been relegated to a secondary role. Although common, water-mediated bonds are usually non-specific, acting as space-fillers at the protein–DNA interface. In conclusion, the majority of amino acid–base interactions observed follow general principles that apply across all protein–DNA complexes, although there are individual exceptions. Therefore, we distinguish between interactions whose specificities are ‘universal’ and ‘context-dependent’. An interactive Web-based atlas of side chain–base contacts provides access to the collected data, including analyses and visualisation of the three-dimensional geometry of the interactions.     

High-resolution profiling of homing endonuclease binding and catalytic specificity using yeast surface display

Experimental analysis and manipulation of protein–DNA interactions pose unique biophysical challenges arising from the structural and chemical homogeneity of DNA polymers. We report the use of yeast surface display for analytical and selection-based applications for the interaction between a LAGLIDADG homing endonuclease and its DNA target. Quantitative flow cytometry using oligonucleotide substrates facilitated a complete profiling of specificity, both for DNA-binding and catalysis, with single base pair resolution. These analyses revealed a comprehensive segregation of binding specificity and affinity to one half of the pseudo-dimeric interaction, while the entire interface contributed specificity at the level of catalysis. A single round of targeted mutagenesis with tandem affinity and catalytic selection steps provided mechanistic insights to the origins of binding and catalytic specificity. These methods represent a dynamic new approach for interrogating specificity in protein–DNA interactions.     

Determination of protein-DNA binding constants and specificities from statistical analyses of single molecules: MutS-DNA interactions

Atomic force microscopy (AFM) is a powerful technique for examining the conformations of protein–DNA complexes and determining the stoichiometries and affinities of protein–protein complexes. We extend the capabilities of AFM to the determination of protein–DNA binding constants and specificities. The distribution of positions of the protein on the DNA fragments provides a direct measure of specificity and requires no knowledge of the absolute binding constants. The fractional occupancies of the protein at a given position in conjunction with the protein and DNA concentrations permit the determination of the absolute binding constants. We present the theoretical basis for this analysis and demonstrate its utility by characterizing the interaction of MutS with DNA fragments containing either no mismatch or a single mismatch. We show that MutS has significantly higher specificities for mismatches than was previously suggested from bulk studies and that the apparent low specificities are the result of high affinity binding to DNA ends. These results resolve the puzzle of the apparent low binding specificity of MutS with the expected high repair specificities. In conclusion, from a single set of AFM experiments, it is possible to determine the binding affinity, specificity and stoichiometry, as well as the conformational properties of the protein–DNA complexes.     

Protein-RNA interactions: a structural analysis

A detailed computational analysis of 32 protein–RNA complexes is presented. A number of physical and chemical properties of the intermolecular interfaces are calculated and compared with those observed in protein–double-stranded DNA and protein–single-stranded DNA complexes. The interface properties of the protein–RNA complexes reveal the diverse nature of the binding sites. van der Waals contacts played a more prevalent role than hydrogen bond contacts, and preferential binding to guanine and uracil was observed. The positively charged residue, arginine, and the single aromatic residues, phenylalanine and tyrosine, all played key roles in the RNA binding sites. A comparison between protein–RNA and protein–DNA complexes showed that whilst base and backbone contacts (both hydrogen bonding and van der Waals) were observed with equal frequency in the protein–RNA complexes, backbone contacts were more dominant in the protein–DNA complexes. Although similar modes of secondary structure interactions have been observed in RNA and DNA binding proteins, the current analysis emphasises the differences that exist between the two types of nucleic acid binding protein at the atomic contact level.     

A new hydrogen-bonding potential for the design of protein-RNA interactions predicts specific contacts and discriminates decoys

RNA-binding proteins play many essential roles in the regulation of gene expression in the cell. Despite the significant increase in the number of structures for RNA–protein complexes in the last few years, the molecular basis of specificity remains unclear even for the best-studied protein families. We have developed a distance and orientation-dependent hydrogen-bonding potential based on the statistical analysis of hydrogen-bonding geometries that are observed in high-resolution crystal structures of protein–DNA and protein–RNA complexes. We observe very strong geometrical preferences that reflect significant energetic constraints on the relative placement of hydrogen-bonding atom pairs at protein–nucleic acid interfaces. A scoring function based on the hydrogen-bonding potential discriminates native protein–RNA structures from incorrectly docked decoys with remarkable predictive power. By incorporating the new hydrogen-bonding potential into a physical model of protein–RNA interfaces with full atom representation, we were able to recover native amino acids at protein–RNA interfaces.     

Discarding functional residues from the substitution table improves predictions of active sites within three-dimensional structures

Substitutions of individual amino acids in proteins may be under very different evolutionary restraints depending on their structural and functional roles. The Environment Specific Substitution Table (ESST) describes the pattern of substitutions in terms of amino acid location within elements of secondary structure, solvent accessibility, and the existence of hydrogen bonds between side chains and neighbouring amino acid residues. Clearly amino acids that have very different local environments in their functional state compared to those in the protein analysed will give rise to inconsistencies in the calculation of amino acid substitution tables. Here, we describe how the calculation of ESSTs can be improved by discarding the functional residues from the calculation of substitution tables. Four categories of functions are examined in this study: protein–protein interactions, protein–nucleic acid interactions, protein–ligand interactions, and catalytic activity of enzymes. Their contributions to residue conservation are measured and investigated. We test our new ESSTs using the program CRESCENDO, designed to predict functional residues by exploiting knowledge of amino acid substitutions, and compare the benchmark results with proteins whose functions have been defined experimentally. The new methodology increases the Z-score by 98% at the active site residues and finds 16% more active sites compared with the old ESST. We also find that discarding amino acids responsible for protein–protein interactions helps in the prediction of those residues although they are not as conserved as the residues of active sites. Our methodology can make the substitution tables better reflect and describe the substitution patterns of amino acids that are under structural restraints only.     

Hydration of protein–RNA recognition sites

We investigate the role of water molecules in 89 protein–RNA complexes taken from the Protein Data Bank. Those with tRNA and single-stranded RNA are less hydrated than with duplex or ribosomal proteins. Protein–RNA interfaces are hydrated less than protein–DNA interfaces, but more than protein–protein interfaces. Majority of the waters at protein–RNA interfaces makes multiple H-bonds; however, a fraction do not make any. Those making H-bonds have preferences for the polar groups of RNA than its partner protein. The spatial distribution of waters makes interfaces with ribosomal proteins and single-stranded RNA relatively ‘dry’ than interfaces with tRNA and duplex RNA. In contrast to protein–DNA interfaces, mainly due to the presence of the 2′OH, the ribose in protein–RNA interfaces is hydrated more than the phosphate or the bases. The minor groove in protein–RNA interfaces is hydrated more than the major groove, while in protein–DNA interfaces it is reverse. The strands make the highest number of water-mediated H-bonds per unit interface area followed by the helices and the non-regular structures. The preserved waters at protein–RNA interfaces make higher number of H-bonds than the other waters. Preserved waters contribute toward the affinity in protein–RNA recognition and should be carefully treated while engineering protein–RNA interfaces.     

Looking into DNA recognition: zinc finger binding specificity

We present a quantitative, theoretical analysis of the recognition mechanisms used by two zinc finger proteins: Zif268, which selectively binds to GC-rich sequences, and a Zif268 mutant, which binds to a TATA box site. This analysis is based on a recently developed method (ADAPT), which allows binding specificity to be analyzed via the calculation of complexation energies for all possible DNA target sequences. The results obtained with the zinc finger proteins show that, although both mainly select their targets using direct, pairwise protein–DNA interactions, they also use sequence-dependent DNA deformation to enhance their selectivity. A new extension of our methodology enables us to determine the quantitative contribution of these two components and also to measure the contributions of individual residues to overall specificity. The results show that indirect recognition is particularly important in the case of the TATA box binding mutant, accounting for 30% of the total selectivity. The residue-by-residue analysis of the protein–DNA interaction energy indicates that the existence of amino acid–base contacts does not necessarily imply sequence selectivity, and that side chains without contacts can nevertheless contribute to defining the protein's target sequence.     

DISPLAR: an accurate method for predicting DNA-binding sites on protein surfaces

Structural and physical properties of DNA provide important constraints on the binding sites formed on surfaces of DNA-targeting proteins. Characteristics of such binding sites may form the basis for predicting DNA-binding sites from the structures of proteins alone. Such an approach has been successfully developed for predicting protein–protein interface. Here this approach is adapted for predicting DNA-binding sites. We used a representative set of 264 protein–DNA complexes from the Protein Data Bank to analyze characteristics and to train and test a neural network predictor of DNA-binding sites. The input to the predictor consisted of PSI-blast sequence profiles and solvent accessibilities of each surface residue and 14 of its closest neighboring residues. Predicted DNA-contacting residues cover 60% of actual DNA-contacting residues and have an accuracy of 76%. This method significantly outperforms previous attempts of DNA-binding site predictions. Its application to the prion protein yielded a DNA-binding site that is consistent with recent NMR chemical shift perturbation data, suggesting that it can complement experimental techniques in characterizing protein–DNA interfaces.     

Altered target site specificity variants of the I-PpoI His-Cys box homing endonuclease

We used a yeast one-hybrid assay to isolate and characterize variants of the eukaryotic homing endonuclease I-PpoI that were able to bind a mutant, cleavage-resistant I-PpoI target or ‘homing’ site DNA in vivo. Native I-PpoI recognizes and cleaves a semi-palindromic 15-bp target site with high specificity in vivo and in vitro. This target site is present in the 28S or equivalent large subunit rDNA genes of all eukaryotes. I-PpoI variants able to bind mutant target site DNA had from 1 to 8 amino acid substitutions in the DNA–protein interface. Biochemical characterization of these proteins revealed a wide range of site–binding affinities and site discrimination. One-third of variants were able to cleave target site DNA, but there was no systematic relationship between site-binding affinity and site cleavage. Computational modeling of several variants provided mechanistic insight into how amino acid substitutions that contact, or are adjacent to, specific target site DNA base pairs determine I-PpoI site-binding affinity and site discrimination, and may affect cleavage efficiency.     

Probing binding hot spots at protein–RNA recognition sites

We use evolutionary conservation derived from structure alignment of polypeptide sequences along with structural and physicochemical attributes of protein–RNA interfaces to probe the binding hot spots at protein–RNA recognition sites. We find that the degree of conservation varies across the RNA binding proteins; some evolve rapidly compared to others. Additionally, irrespective of the structural class of the complexes, residues at the RNA binding sites are evolutionary better conserved than those at the solvent exposed surfaces. For recognitions involving duplex RNA, residues interacting with the major groove are better conserved than those interacting with the minor groove. We identify multi-interface residues participating simultaneously in protein–protein and protein–RNA interfaces in complexes where more than one polypeptide is involved in RNA recognition, and show that they are better conserved compared to any other RNA binding residues. We find that the residues at water preservation site are better conserved than those at hydrated or at dehydrated sites. Finally, we develop a Random Forests model using structural and physicochemical attributes for predicting binding hot spots. The model accurately predicts 80% of the instances of experimental ΔΔG values in a particular class, and provides a stepping-stone towards the engineering of protein–RNA recognition sites with desired affinity.     

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.     

Rapid antibody selection by mRNA display on a microfluidic chip

In vitro antibody-display technologies are powerful approaches for isolating monoclonal antibodies from recombinant antibody libraries. However, these display techniques require several rounds of affinity selection which is time-consuming. Here, we combined mRNA display with a microfluidic system for in vitro selection and evolution of antibodies and achieved ultrahigh enrichment efficiency of 10⁶- to 10⁸-fold per round. After only one or two rounds of selection, antibodies with high affinity and specificity were obtained from naïve and randomized single-chain Fv libraries of ~10¹² molecules. Furthermore, we confirmed that not only protein–protein (antigen–antibody) interactions, but also protein–DNA and protein–drug interactions were selected with ultrahigh efficiencies. This method will facilitate high-throughput preparation of antibodies and identification of protein interactions in proteomic and therapeutic fields.     

Dissecting protein-RNA recognition sites

We analyze the protein–RNA interfaces in 81 transient binary complexes taken from the Protein Data Bank. Those with tRNA or duplex RNA are larger than with single-stranded RNA, and comparable in size to protein–DNA interfaces. The protein side bears a strong positive electrostatic potential and resembles protein–DNA interfaces in its amino acid composition. On the RNA side, the phosphate contributes less, and the sugar much more, to the interaction than in protein–DNA complexes. On average, protein–RNA interfaces contain 20 hydrogen bonds, 7 that involve the phosphates, 5 the sugar 2′OH, and 6 the bases, and 32 water molecules. The average H-bond density per unit buried surface area is less with tRNA or single-stranded RNA than with duplex RNA. The atomic packing is also less compact in interfaces with tRNA. On the protein side, the main chain NH and Arg/Lys side chains account for nearly half of all H-bonds to RNA; the main chain CO and side chain acceptor groups, for a quarter. The 2′OH is a major player in protein–RNA recognition, and shape complementarity an important determinant, whereas electrostatics and direct base–protein interactions play a lesser part than in protein–DNA recognition.     

Simulation of non-specific protein-mRNA interactions

Protein–nucleic acid interactions exhibit varying degrees of specificity. Relatively high affinity, sequence-specific interactions, can be studied with structure determination, but lower affinity, non-specific interactions are also of biological importance. We report simulations that predict the population of nucleic acid paths around protein surfaces, and give binding constant differences for changes in the protein scaffold. The method is applied to the non-specific component of interactions between eIF4Es and messenger RNAs that are bound tightly at the cap site. Adding a fragment of eIF4G to the system changes both the population of mRNA paths and the protein–mRNA binding affinity, suggesting a potential role for non-specific interactions in modulating translational properties. Generally, the free energy simulation technique could work in harness with characterized tethering points to extend analysis of nucleic acid conformation, and its modulation by protein scaffolds.     

Structure of the DNA-binding domain of NgTRF1 reveals unique features of plant telomere-binding proteins

Telomeres are protein–DNA elements that are located at the ends of linear eukaryotic chromosomes. In concert with various telomere-binding proteins, they play an essential role in genome stability. We determined the structure of the DNA-binding domain of NgTRF1, a double-stranded telomere-binding protein of tobacco, using multidimensional NMR spectroscopy and X-ray crystallography. The DNA-binding domain of NgTRF1 contained the Myb-like domain and C-terminal Myb-extension that is characteristic of plant double-stranded telomere-binding proteins. It encompassed amino acids 561–681 (NgTRF1^561–681), and was composed of 4 α-helices. We also determined the structure of NgTRF1^561–681 bound to plant telomeric DNA. We identified several amino acid residues that interacted directly with DNA, and confirmed their role in the binding of NgTRF1 to telomere using site-directed mutagenesis. Based on a structural comparison of the DNA-binding domains of NgTRF1 and human TRF1 (hTRF1), NgTRF1 has both common and unique DNA-binding properties. Interaction of Myb-like domain with telomeric sequences is almost identical in NgTRF1^561–681 with the DNA-binding domain of hTRF1. The interaction of Arg-638 with the telomeric DNA, which is unique in NgTRF1^561–681, may provide the structural explanation for the specificity of NgTRF1 to the plant telomere sequences, (TTTAGGG)_n.     

Role of ATP hydrolysis in the DNA translocase activity of the bovine papillomavirus (BPV-1) E1 helicase

The E1 protein of bovine papillomavirus type-1 is the viral replication initiator protein and replicative helicase. Here we show that the C-terminal ~300 amino acids of E1, that share homology with members of helicase superfamily 3 (SF3), can act as an autonomous helicase. E1 is monomeric in the absence of ATP but assembles into hexamers in the presence of ATP, single-stranded DNA (ssDNA) or both. A 16 base sequence is the minimum for efficient hexamerization, although the complex protects ~30 bases from nuclease digestion, supporting the notion that the DNA is bound within the protein complex. In the absence of ATP, or in the presence of ADP or the non–hydrolysable ATP analogue AMP–PNP, the interaction with short ssDNA oligonucleotides is exceptionally tight (T_1/2 > 6 h). However, in the presence of ATP, the interaction with DNA is destabilized (T_1/2 ~60 s). These results suggest that during the ATP hydrolysis cycle an internal DNA-binding site oscillates from a high to a low-affinity state, while protein–protein interactions switch from low to high affinity. This reciprocal change in protein–protein and protein–DNA affinities could be part of a mechanism for tethering the protein to its substrate while unidirectional movement along DNA proceeds.     

A structural approach reveals how neighbouring C2H2 zinc fingers influence DNA binding specificity

Development of an accurate protein–DNA recognition code that can predict DNA specificity from protein sequence is a central problem in biology. C₂H₂ zinc fingers constitute by far the largest family of DNA binding domains and their binding specificity has been studied intensively. However, despite decades of research, accurate prediction of DNA specificity remains elusive. A major obstacle is thought to be the inability of current methods to account for the influence of neighbouring domains. Here we show that this problem can be addressed using a structural approach: we build structural models for all C₂H₂-ZF–DNA complexes with known binding motifs and find six distinct binding modes. Each mode changes the orientation of specificity residues with respect to the DNA, thereby modulating base preference. Most importantly, the structural analysis shows that residues at the domain interface strongly and predictably influence the binding mode, and hence specificity. Accounting for predicted binding mode significantly improves prediction accuracy of predicted motifs. This new insight into the fundamental behaviour of C₂H₂-ZFs has implications for both improving the prediction of natural zinc finger-binding sites, and for prioritizing further experiments to complete the code. It also provides a new design feature for zinc finger engineering.     

Directed co-evolution of interacting protein–peptide pairs by compartmentalized two-hybrid replication (C2HR)

Directed evolution methodologies benefit from read-outs quantitatively linking genotype to phenotype. We therefore devised a method that couples protein–peptide interactions to the dynamic read-out provided by an engineered DNA polymerase. Fusion of a processivity clamp protein to a thermostable nucleic acid polymerase enables polymerase activity and DNA amplification in otherwise prohibitive high-salt buffers. Here, we recapitulate this phenotype by indirectly coupling the Sso7d processivity clamp to Taq DNA polymerase via respective fusion to a high affinity and thermostable interacting protein–peptide pair. Escherichia coli cells co-expressing protein–peptide pairs can directly be used in polymerase chain reactions to determine relative interaction strengths by the measurement of amplicon yields. Conditional polymerase activity is further used to link genotype to phenotype of interacting protein–peptide pairs co-expressed in E. coli using the compartmentalized self-replication directed evolution platform. We validate this approach, termed compartmentalized two-hybrid replication, by selecting for high-affinity peptides that bind two model protein partners: SpyCatcher and the large fragment of NanoLuc luciferase. We further demonstrate directed co-evolution by randomizing both protein and peptide components of the SpyCatcher–SpyTag pair and co-selecting for functionally interacting variants.