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.     

Cavities in protein–DNA and protein–RNA interfaces

An analysis of cavities present in protein–DNA and protein–RNA complexes is presented. In terms of the number of cavities and their total volume, the interfaces formed in these complexes are akin to those in transient protein–protein heterocomplexes. With homodimeric proteins protein–DNA interfaces may contain cavities involving both the protein subunits and DNA, and these are more than twice as large as cavities involving a single protein subunit and DNA. A parameter, cavity index, measuring the degree of surface complementarity, indicates that the packing of atoms in protein–protein/DNA/RNA is very similar, but it is about two times less efficient in the permanent interfaces formed between subunits in homodimers. As within the tertiary structure and protein–protein interfaces, protein–DNA interfaces have a higher inclination to be lined by β-sheet residues; from the DNA side, base atoms, in particular those in minor grooves, have a higher tendency to be located in cavities. The larger cavities tend to be less spherical and solvated. A small fraction of water molecules are found to mediate hydrogen-bond interactions with both the components, suggesting their primary role is to fill in the void left due to the local non-complementary nature of the surface patches.     

Beauty Is in the Eye of the Beholder: Proteins Can Recognize Binding Sites of Homologous Proteins in More than One Way

Understanding the mechanisms of protein–protein interaction is a fundamental problem with many practical applications. The fact that different proteins can bind similar partners suggests that convergently evolved binding interfaces are reused in different complexes. A set of protein complexes composed of non-homologous domains interacting with homologous partners at equivalent binding sites was collected in 2006, offering an opportunity to investigate this point. We considered 433 pairs of protein–protein complexes from the ABAC database (AB and AC binary protein complexes sharing a homologous partner A) and analyzed the extent of physico-chemical similarity at the atomic and residue level at the protein–protein interface. Homologous partners of the complexes were superimposed using Multiprot, and similar atoms at the interface were quantified using a five class grouping scheme and a distance cut-off. We found that the number of interfacial atoms with similar properties is systematically lower in the non-homologous proteins than in the homologous ones. We assessed the significance of the similarity by bootstrapping the atomic properties at the interfaces. We found that the similarity of binding sites is very significant between homologous proteins, as expected, but generally insignificant between the non-homologous proteins that bind to homologous partners. Furthermore, evolutionarily conserved residues are not colocalized within the binding sites of non-homologous proteins. We could only identify a limited number of cases of structural mimicry at the interface, suggesting that this property is less generic than previously thought. Our results support the hypothesis that different proteins can interact with similar partners using alternate strategies, but do not support convergent evolution.     

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.     

What Forces Can Determine the Formation of Highly Specific Protein–Protein Complexes?

A software package was designed and used in a detailed study of the contact regions (interfaces) of a large number of protein–protein complexes using the PDB data. It appeared that for about 75% of the complexes the amino acid composition of the subunit surface in the contact region is not essential. Thus one may suggest that, along with the amino acid residues at the interface, the residues in the interior of the globules substantially contribute to protein–protein recognition. Such interactions between quite remote residues are most probably of electrical nature, and are involved in recognition by contributing to the overall electric field created by the protein molecule; the configuration of this field is perhaps the definitive factor of recognition. The overall field of the protein molecule is additively built of the fields created by each constituent residue, and it can be calculated as a sum of the fields created by the protein multipole (aggregate of partial electric charges assigned to every atom of the protein molecule). Preliminary assessment of the remote electrostatic interaction has been performed for ribonuclease subunits in vacuum. The results are indicative of a real possibility that the electric field created by the protein multipole can strongly influence the mutual orientation of molecules before Brownian collision.     

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.     

Mass spectrometry-based footprinting of protein–protein interactions

We present a high-resolution mass spectrometric (MS) footprinting method enabling identification of contact amino acids in protein–protein complexes. The method is based on comparing surface topologies of a free protein versus its complex with the binding partner using differential accessibility of small chemical group selective modifying reagents. Subsequent MS analysis reveals the individual amino acids selectively shielded from modification in the protein–protein complex. The current report focuses on probing interactions between full-length HIV-1 integrase and its principal cellular partner lens epithelium-derived growth factor. This method has a generic application and is particularly attractive for studying large protein–protein interactions that are less amenable for crystallographic or NMR analysis.     

Protein–DNA binding: complexities and multi-protein codes

Binding of proteins to particular DNA sites across the genome is a primary determinant of specificity in genome maintenance and gene regulation. DNA-binding specificity is encoded at multiple levels, from the detailed biophysical interactions between proteins and DNA, to the assembly of multi-protein complexes. At each level, variation in the mechanisms used to achieve specificity has led to difficulties in constructing and applying simple models of DNA binding. We review the complexities in protein–DNA binding found at multiple levels and discuss how they confound the idea of simple recognition codes. We discuss the impact of new high-throughput technologies for the characterization of protein–DNA binding, and how these technologies are uncovering new complexities in protein–DNA recognition. Finally, we review the concept of multi-protein recognition codes in which new DNA-binding specificities are achieved by the assembly of multi-protein complexes.     

Structure-based method for analyzing protein–protein interfaces

Hydrogen bond, hydrophobic and vdW interactions are the three major non-covalent interactions at protein–protein interfaces. We have developed a method that uses only these properties to describe interactions between proteins, which can qualitatively estimate the individual contribution of each interfacial residue to the binding and gives the results in a graphic display way. This method has been applied to analyze alanine mutation data at protein–protein interfaces. A dataset containing 13 protein–protein complexes with 250 alanine mutations of interfacial residues has been tested. For the 75 hot-spot residues (G1.5 kcal mol^-1), 66 can be predicted correctly with a success rate of 88%. In order to test the tolerance of this method to conformational changes upon binding, we utilize a set of 26 complexes with one or both of their components available in the unbound form. The difference of key residues exported by the program is 11% between the results using complexed proteins and those from unbound ones. As this method gives the characteristics of the binding partner for a particular protein, in-depth studies on protein–protein recognition can be carried out. Furthermore, this method can be used to compare the difference between protein–protein interactions and look for correlated mutation. Figure Key interaction grids at the interface between barnase and barstar. Key interaction grid for barnase and barstar are presented in one figure according to their coordinates. In order to distinguish the two proteins, different icons were assigned. Crosses represent key grids for barstar and dots represent key grids for barnase. The four residues in ball and stick are Asp40 in barstar and Arg83, Arg87, His102 in barnase.     

Highly conserved amino acids in Pax and Ets proteins are required for DNA binding and ternary complex assembly

Combinatorial association of DNA-binding proteins on composite binding sites enhances their nucleotide sequence specificity and functional synergy. As a paradigm for these interactions, Pax-5 (BSAP) assembles ternary complexes with Ets proteins on the B cell-specific mb-1 promoter through interactions between their respective DNA-binding domains. Pax-5 recruits Ets-1 to bind the promoter, but not the closely related Ets protein SAP1a. Here we show that, while several different mutations increase binding of SAP1a to an optimized Ets binding site, only conversion of Val68 to an acidic amino acid facilitates ternary complex assembly with Pax-5 on the mb-1 promoter. This suggests that enhanced DNA binding by SAP1a is not sufficient for recruitment by Pax-5, but instead involves protein–protein interactions mediated by the acidic side chain. Recruitment of Ets proteins by Pax-5 requires Gln22 within the N-terminal β-hairpin motif of its paired domain. The β-hairpin also participates in recognition of a subset of Pax-5-binding sites. Thus, Pax-5 incorporates protein–protein interaction and DNA recognition functions in a single motif. The Caenorhabditis elegans Pax protein EGL-38 also binds specifically to the mb-1 promoter and recruits murine Ets-1 or the C.elegans Ets protein T08H4.3, but not the related LIN-1 protein. Together, our results define specific amino acid requirements for Pax–Ets ternary complex assembly and show that the mechanism is conserved between evolutionarily related proteins of diverse animal species. Moreover, the data suggest that interactions between Pax and Ets proteins are an important mechanism that regulates fundamental biological processes in worms and humans.     

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.     

Common fold in helix-hairpin-helix proteins

Helix–hairpin–helix (HhH) is a widespread motif involved in non-sequence-specific DNA binding. The majority of HhH motifs function as DNA-binding modules, however, some of them are used to mediate protein–protein interactions or have acquired enzymatic activity by incorporating catalytic residues (DNA glycosylases). From sequence and structural analysis of HhH-containing proteins we conclude that most HhH motifs are integrated as a part of a five-helical domain, termed (HhH)₂ domain here. It typically consists of two consecutive HhH motifs that are linked by a connector helix and displays pseudo-2-fold symmetry. (HhH)₂ domains show clear structural integrity and a conserved hydrophobic core composed of seven residues, one residue from each α-helix and each hairpin, and deserves recognition as a distinct protein fold. In addition to known HhH in the structures of RuvA, RadA, MutY and DNA-polymerases, we have detected new HhH motifs in sterile alpha motif and barrier-to-autointegration factor domains, the α-subunit of Escherichia coli RNA-polymerase, DNA-helicase PcrA and DNA glyco­s­y­lases. Statistically significant sequence similarity of HhH motifs and pronounced structural conservation argue for homology between (HhH)₂ domains in different protein families. Our analysis helps to clarify how non-symmetric protein motifs bind to the double helix of DNA through the formation of a pseudo-2-fold symmetric (HhH)₂ functional unit.     

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.     

Solution measurement of DNA curvature in papillomavirus E2 binding sites

‘Indirect readout’ refers to the proposal that proteins can recognize the intrinsic three-dimensional shape or flexibility of a DNA binding sequence apart from direct protein contact with DNA base pairs. The differing affinities of human papillomavirus (HPV) E2 proteins for different E2 binding sites have been proposed to reflect indirect readout. DNA bending has been observed in X-ray structures of E2 protein–DNA complexes. X-ray structures of three different E2 DNA binding sites revealed differences in intrinsic curvature. DNA sites with intrinsic curvature in the direction of protein-induced bending were bound more tightly by E2 proteins, supporting the indirect readout model. We now report solution measurements of intrinsic DNA curvature for three E2 binding sites using a sensitive electrophoretic phasing assay. Measured E2 site curvature agrees well the predictions of a dinucleotide model and supports an indirect readout hypothesis for DNA recognition by HPV E2.     

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.