High‐resolution crystal structures leverage protein binding affinity predictions

Predicting protein binding affinities from structural data has remained elusive, a difficulty owing to the variety of protein binding modes. Using the structure‐affinity‐benchmark (SAB, 144 cases with bound/unbound crystal structures and experimental affinity measurements), prediction has been undertaken either by fitting a model using a handfull of predefined variables, or by training a complex model from a large pool of parameters (typically hundreds). The former route unnecessarily restricts the model space, while the latter is prone to overfitting. We design models in a third tier, using 12 variables describing enthalpic and entropic variations upon binding, and a model selection procedure identifying the best sparse model built from a subset of these variables. Using these models, we report three main results. First, we present models yielding a marked improvement of affinity predictions. For the whole dataset, we present a model predicting K_d within 1 and 2 orders of magnitude for 48% and 79% of cases, respectively. These statistics jump to 62% and 89% respectively, for the subset of the SAB consisting of high resolution structures. Second, we show that these performances owe to a new parameter encoding interface morphology and packing properties of interface atoms. Third, we argue that interface flexibility and prediction hardness do not correlate, and that for flexible cases, a performance matching that of the whole SAB can be achieved. Overall, our work suggests that the affinity prediction problem could be partly solved using databases of high resolution complexes whose affinity is known. Proteins 2016; 84:9–20. © 2015 Wiley Periodicals, Inc.     

Exploring additivity effects of double mutations on the binding affinity of protein‐protein complexes

Additivity in binding affinity of protein‐protein complexes refers to the change in free energy of binding (ΔΔG_bind) for double (or multiple) mutations which is approximately equal to the sum of their corresponding single mutation ΔΔG_bind values. In this study, we have explored the additivity effect of double mutants, which shows a linear relationship between the binding affinity of double and sum of single mutants with a correlation of 0.90. However, the comparison of ΔΔG_bind values showed a mean absolute deviation of 0.86 kcal/mol, and 25.6% of the double mutants show a deviation of more than 1 kcal/mol, which are identified as non‐additive. The additivity effects have been analyzed based on the influence of structural features such as accessible surface area, long range order, binding propensity change, surrounding hydrophobicity, flexibility, atomic contacts between the mutations and distance between the 2 mutations. We found that non‐additive mutations tend to be closer to each other and have more contacts. We have also used machine learning methods to discriminate additive and non‐additive mutations using structure‐based features, which showed the accuracies in the range of 0.77–0.92 for protein‐protein complexes belonging to different functions. Further, we have compared the additivity effects of protein stability along with binding affinity and explored the similarities and differences between them. The results obtained in this study provide insights into the effects of various structural features on binding affinity of double mutants, and will aid the development of accurate methods to predict the binding affinity of double mutants.     

The dataset for protein–RNA binding affinity

We have developed a non‐redundant protein–RNA binding benchmark dataset derived from the available protein–RNA structures in the Protein Database Bank. It consists of 73 complexes with measured binding affinity. The experimental conditions (pH and temperature) for binding affinity measurements are also listed in our dataset. This binding affinity dataset can be used to compare and develop protein–RNA scoring functions. The predicted binding free energy of the 73 complexes from three available scoring functions for protein–RNA docking has a low correlation with the binding Gibbs free energy calculated from K_d. © 2013 The Protein Society     

Synthesis and spectroscopic characterization study of new palladium complexes containing bioactive O,O-chelated ligands: evaluation of the DNA/protein BSA interaction,in vitro antitumoural activity and molecular docking

[Pd{(C,N)–C₆H₄CH₂NH(Et) (Qu)] (2) and [Pd{(C,N)–C₆H₄CH₂NH(Et) (Nar)] (3) (Qu = Quercetin, Nar = Naringin) mononuclear palladium (II) complexes have been synthesized and characterized using elemental analysis, IR and electronic spectroscopy. The interaction of the prepared complexes with calf thymus DNA and bovine serum albumin (BSA), monitored by UV–visible and fluorescence titrations, respectively, have been carried out to better understand the mode of their action under biological conditions. Intercalative binding mode between the complexes and DNA is suggested by the binding constant (K_b) values of 2.5 × 10⁶ and 3.2 × 10⁶ for complexes 2 and 3, respectively. In particular, the in vitro cytotoxicity of the complexes on two cancer cells lines (bladder carcinoma TCC and breast cancer MCF7) showed that the compounds had broad spectrum, anti-cancer activity with low IC₅₀ values and the order of in vitro anticancer activities is consistent with the DNA-binding affinities. In the meantime, the quenching of tryptophan emission with the addition of complexes using BSA as a model protein indicated the protein binding ability. The quenching mechanisms of BSA by the complexes were static processes, according to the results obtained. The competitive binding using Warfarin, Digoxin and Ibuprofen site markers, which contain definite biding sites, demonstrated that the complexes bind to site I on BSA. Ultimately, the binding sites of DNA and BSA with the complexes have been determined by molecular modelling studies.     

Feature selection and classification of protein–protein complexes based on their binding affinities using machine learning approaches

Protein–protein interactions are intrinsic to virtually every cellular process. Predicting the binding affinity of protein–protein complexes is one of the challenging problems in computational and molecular biology. In this work, we related sequence features of protein–protein complexes with their binding affinities using machine learning approaches. We set up a database of 185 protein–protein complexes for which the interacting pairs are heterodimers and their experimental binding affinities are available. On the other hand, we have developed a set of 610 features from the sequences of protein complexes and utilized Ranker search method, which is the combination of Attribute evaluator and Ranker method for selecting specific features. We have analyzed several machine learning algorithms to discriminate protein‐protein complexes into high and low affinity groups based on their K_d values. Our results showed a 10‐fold cross‐validation accuracy of 76.1% with the combination of nine features using support vector machines. Further, we observed accuracy of 83.3% on an independent test set of 30 complexes. We suggest that our method would serve as an effective tool for identifying the interacting partners in protein–protein interaction networks and human–pathogen interactions based on the strength of interactions. Proteins 2014; 82:2088–2096. © 2014 Wiley Periodicals, Inc.     

Highly efficient purification of protein complexes from mammalian cells using a novel streptavidin-binding peptide and hexahistidine tandem tag system: application to Bruton's tyrosine kinase

Tandem affinity purification (TAP) is a generic approach for the purification of protein complexes. The key advantage of TAP is the engineering of dual affinity tags that, when attached to the protein of interest, allow purification of the target protein along with its binding partners through two consecutive purification steps. The tandem tag used in the original method consists of two IgG‐binding units of protein A from Staphylococcus aureus (ProtA) and the calmodulin‐binding peptide (CBP), and it allows for recovery of 20–30% of the bait protein in yeast. When applied to higher eukaryotes, however, this classical TAP tag suffers from low yields. To improve protein recovery in systems other than yeast, we describe herein the development of a three‐tag system comprised of CBP, streptavidin‐binding peptide (SBP) and hexa‐histidine. We illustrate the application of this approach for the purification of human Bruton's tyrosine kinase (Btk), which results in highly efficient binding and elution of bait protein in both purification steps (>50% recovery). Combined with mass spectrometry for protein identification, this TAP strategy facilitated the first nonbiased analysis of Btk interacting proteins. The high efficiency of the SBP‐His₆ purification allows for efficient recovery of protein complexes formed with a target protein of interest from a small amount of starting material, enhancing the ability to detect low abundance and transient interactions in eukaryotic cell systems.     

Analysis of secondary structural and physicochemical changes in protein–protein complexes

Conformation switching in protein–protein complexes is considered important for the molecular recognition process. Overall analysis of 123 protein–protein complexes in a benchmark data-set showed that 6.8% of residues switched over their secondary structure conformation upon complex formation. Amino acid residue-wise preference for conformation change has been analyzed in binding and non-binding site residues separately. In this analysis, residues such as Ser, Leu, Glu, and Lys had higher frequency of secondary structural conformation change. The change of helix to coil and sheet to coil conformation and vice versa has been observed frequently, whereas the conformation change of helix to extended sheet occurred rarely in the studied complexes. Influence of conformation change toward the N and C terminal on either side of the binding site residues has been analyzed. Further, analysis on φ and ψ angle variation, conservation, stability, and solvent accessibility have been performed on binding site residues. Knowledge obtained from the present study could be effectively employed in the protein–protein modeling and docking studies.     

Protein�Cprotein binding affinities by pulse proteolysis: Application to TEM-1/BLIP protein complexes

Efficient methods for quantifying dissociation constants have become increasingly important for high‐throughput mutagenesis studies in the postgenomic era. However, experimentally determining binding affinity is often laborious, requires large amounts of purified protein, and utilizes specialized equipment. Recently, pulse proteolysis has been shown to be a robust and simple method to determine the dissociation constants for a protein–ligand pair based on the increase in thermodynamic stability upon ligand binding. Here, we extend this technique to determine binding affinities for a protein–protein complex involving the β‐lactamase TEM‐1 and various β‐lactamase inhibitor protein (BLIP) mutants. Interaction with BLIP results in an increase in the denaturation curve midpoint, C_m, of TEM‐1, which correlates with the rank order of binding affinities for several BLIP mutants. Hence, pulse proteolysis is a simple, effective method to assay for mutations that modulate binding affinity in protein–protein complexes. From a small set (n = 4) of TEM‐1/BLIP mutant complexes, a linear relationship between energy of stabilization (dissociation constant) and ΔC_m was observed. From this “calibration curve,” accurate dissociation constants for two additional BLIP mutants were calculated directly from proteolysis‐derived ΔC_m values. Therefore, in addition to qualitative information, armed with knowledge of the dissociation constants from the WT protein and a limited number of mutants, accurate quantitation of binding affinities can be determined for additional mutants from pulse proteolysis. Minimal sample requirements and the suitability of impure protein preparations are important advantages that make pulse proteolysis a powerful tool for high‐throughput mutagenesis binding studies.     

Mutation of conserved tryptophan residues at the dimer interface of Staphylococcus aureus nitric oxide synthase

Nitric oxide synthases (NOSs) share two invariant tryptophan residues within a conserved helical lariat that is part of the pterin-binding site and dimer interface. We mutated Staphylococcus aureus NOS Trp-314 (to alanine, phenylalanine, tyrosine and histidine) and Trp-316 (to alanine, phenylalanine and tyrosine) and characterized the effects of mutation on heme environment, quaternary structure, enzymatic activity, and substrate affinity. With arginine present, all saNOS variants bound heme with native thiolate ligation, formed high spin ferric complexes and were dimeric. All variants catalyze the peroxide-dependent oxidation of N-hydroxy-l-arginine, at rates from 10% to 55% of wild type activity. Arginine-free proteins are dimeric with the exception of W314A. Arginine affinity for all variants decreases with increasing temperature between 15 and 42 °C but is precipitous for position-314 variants. Previous structural and biophysical characterization of NOS oxygenase domains demonstrated that the protein can exist in either a tight or loose conformation, with the former corresponding to the active state of the protein. In the position-314 variants it is likely that the loose conformation is favoured, owing to the loss of a hydrogen bond between the indole side chain and the polypeptide backbone of the helical lariat.     

Locating the binding sites of retinol and retinoic acid with milk β-lactoglobulin

β-lactoglobulin (β-LG) is a member of lipocalin superfamily of transporters for small hydrophobic molecules such as retinoids. We located the binding sites of retinol and retinoic acid on β-LG in aqueous solution at physiological conditions, using FTIR, CD, fluorescence spectroscopic methods, and molecular modeling. The retinoid-binding sites and the binding constants as well as the effect of retinol and retinoic acid complexation on protein stability and secondary structure were determined. Structural analysis showed that retinoids bind strongly to β-LG via both hydrophilic and hydrophobic contacts with overall binding constants of K _{retinol- β -LG?}=?6.4 (±?.6)?×?10⁶?M^?1 and K _{retinoic acid- β -LG?}=?3.3 (±?.5)?×?10⁶?M^?1. The number of retinoid molecules bound per protein (n) is 1.1 (±?.2) for retinol and 1.5 (±?.3) for retinoic acid. Molecular modeling showed the participation of several amino acids in the retinoid–protein complexes with the free binding energy of ?8.11?kcal/mol for retinol and ?7.62?kcal/mol for retinoic acid. Protein conformation was altered with reduction of β-sheet from 59 (free protein) to 52–51% and a major increase in turn structure from 13 (free protein) to 24–22%, in the retinoid–β-LG complexes, indicating a partial protein destabilization.     

Anion interactions with Na,K-ATPase: simultaneous binding of nitrate and eosin

Nucleotide binding affinity to Na,K-ATPase is reduced by a number of anions such as nitrate and perchlorate in comparison with affinity in the presence of chloride (all with sodium as the cation). The reduction correlates with the position of these anions in the Hofmeister series. Transient kinetic experiments using the fluorescent dye eosin—which binds to the nucleotide site of the Na,K-ATPase—show that simultaneous anion binding, exemplified with nitrate, and eosin binding is possible. The effect of nitrate on eosin binding is reflected in a decreased binding-rate constant and an increased dissociation rate constant, leading to a decreased equilibrium binding constant for eosin. Since eosin binding is analogous with nucleotide binding to Na,K-ATPase, the results suggest the simultaneous presence of nucleotide and anion binding sites.Abbreviations E₁ the protein conformation in Na⁺ - E₂ the enzyme conformation in K⁺ - Eo eosin (tetrabromofluorescein) - F fluorescence - I ionic strength - k_i rate constant - K_i equilibrium dissociation constant - K_i,0 equilibrium dissociation constant at zero ionic strength - N nitrate - z_i net charge - charge product z_i·z_j     

Comparison of the biological activity of fusicoccin in higher plants with its binding to plasma membranes

The concentration dependences of the binding of fusicoccins (FCs) A, B, C, D, J and H to plasma membranes isolated from maize (Zea mays L.) roots have been studied in parallel with the effects of these compounds on elongation and ⁸⁶Rb transport in detached maize roots. The dissociation constants obtained showed a good correlation between the affinity of the FCs for the plasmalemma and their biological activity. However, the range of physiologically active FC concentrations proved to be about two orders of magnitude higher than that calculated from the dissociation constants. It was also shown that Vicia faba L. mesophyll protoplasts, unlike isolated plasma membranes, have two FC-binding sites, one with a K _D similar to that of the isolated plasmalemma while the other has a substantially higher K _D , apparently corresponding to the physiologically active state of the FC-binding proteins.Abbreviation FC fusicoccin     

Unravelling the binding mechanism and protein stability of human serum albumin while interacting with nefopam analogues: a biophysical and insilico approach

In this study, molecular binding affinity was investigated for Nefopam analogues (NFs), a functionalized benzoxazocine, with human serum albumin (HSA), a major transport protein in the blood. Its binding affinity and concomitant changes in its conformation, binding site and simulations were also studied. Fluorescence data revealed that the fluorescence quenching of HSA upon binding of NFs analogues is based on a static mechanism. The three analogues of NFs binding constants (K_A) are in the order of NF3 > NF2 > NF1 with values of 1.53 ± .057 × 10⁴, 2.16 ± .071 × 10⁴ and 3.6 ± .102 × 10⁵ M^?1, respectively. Concurrently, thermodynamic parameters indicate that the binding process was spontaneous, and the complexes were stabilized mostly by hydrophobic interactions, except for NF2 has one hydrogen bond stabilizes it along with hydrophobic interactions. Circular dichroism (CD) studies revealed that there is a decrease in α-helix with an increase in β-sheets and random coils signifying partial unfolding of the protein upon binding of NFs, which might be due to the formation of NFs-HSA complexes. Further, molecular docking studies showed that NF1, NF2 and NF3 bound to subdomains IIIA, IB and IIA through hydrophobic interactions. However, NF1 have additionally formed a single hydrogen bond with LYS 413. Furthermore, molecular simulations unveiled that NFs binding was in support with the structural perturbation observed in CD, which is evident from the root mean square deviation and R_g fluctuations. We hope our insights will provide ample scope for engineering new drugs based on the resemblances with NFs for enhanced efficacy with HSA.     

Protein–protein interactions: General trends in the relationship between binding affinity and interfacial buried surface area

Protein–protein interactions play key roles in many cellular processes and their affinities and specificities are finely tuned to the functions they perform. Here, we present a study on the relationship between binding affinity and the size and chemical nature of protein–protein interfaces. Our analysis focuses on heterodimers and includes curated structural and thermodynamic data for 113 complexes. We observe a direct correlation between binding affinity and the amount of surface area buried at the interface. For a given amount of surface area buried, the binding affinity spans four orders of magnitude in terms of the dissociation constant (K_d). Across the entire dataset, we observe no obvious relationship between binding affinity and the chemical composition of the interface. We also calculate the free energy per unit surface area buried, or “surface energy density,” of each heterodimer. For interfacial surface areas between 500 and 2000 Ų, the surface energy density decreases as the buried surface area increases. As the buried surface area increases beyond about 2000 Ų, the surface energy density levels off to a constant value. We believe that these analyses and data will be useful for researchers with an interest in understanding, designing or inhibiting protein–protein interfaces.     

Alu-family repeat binding protein from HeLa cells which interacts with regulatory region of SV40 virus genome

Using a gel retardation assay the protein which binds selectively to the Alu-family repeat (AFR) has been identified and partially purified from HeLa cell nuclear extract. The protein (AFR-binding protein, ABP) forms multiple discrete complexes with AFR even in the presence of 200 to 2000-fold excess of non-specific (E. coli) DNA. The most stable complex has a relative mobility in 4% polyacrylamide gel (as compared to the free Alu-fragment) of 0.54. Heterogeneity of protein-DNA bands seen in the polyacrylamide gel suggests that ABP is able to form multimeric complexes with AFR. Competition experiments show that ABP do not interact with the RNA polymerase III promoter and with the TGGCA-sequence, but a high affinity binding site for ABP was found within a 660 bp restriction fragment containing the SV40 virus promoter and replication origin.     

Structure-related changes of the electron spin resonance spectra of the monomeric nitrosyl haemoglobin IV from Chironomus thummi thummi

The monomeric haemoglobin IV from Chironomus thummi thummi (CTT IV) is an allosteric protein characterized by pH-dependent ligand affinities (Bohr-effect). The ligand-linked proton dissociation gives rise to a t r conformational transition. Furthermore, the Bohr-effect is ligand-dependent and decreases in magnitude following the order of ligands, O₂ > CO > NO. Although the Bohr-effect for NO is smallest, the electron spin resonance (ESR) spectra of frozen solutions of ¹⁵NO-ligated CTT IV measured as higher derivatives at 77 K reflect this pH-dependent conformation change. g Tensor and hyperfine constants coinciding with the principal directions of the g tensor have been evaluated for ⁵⁷Fe, ¹⁵NO, ¹⁴N_E-imidazole, and ¹⁴N-pyrroles.Hyperfine parameters and g values of both conformation states of this haemoglobin, i.e., of the t state at low pH with low ligand affinity and of the r state at high pH with high ligand affinity, are characteristic for a hexacoordinated nitrosyl haem complex. The change in pH leads to a variation of the Fe-N-O bond angle which is larger at high pH (r conformation) than at low pH (t conformation). Furthermore, the spin transfer from NO into iron orbitals is larger at high pH than at low pH. These results are consistent with the assumption that the interaction of proximal imidazole and iron is smaller in the r conformation than in the t conformation.Binding of anionic detergents to nitrosyl CTT IV causes a conversion of the native (t, r) into a denatured (super-r) structure. The latter, on the basis of hyperfine and g values, apparently contains a pentacoordinated nitrosyl haem complex. Because of the extreme displacement of the proximal imidazole in the super-r structure, the Fe-N-O gouping is nearly linear and a large spin transfer from NO into iron orbitals occurs. Removal of anionic detergents from the protein leads to a full reconversion of the super-r into the native conformations.These structure-related changes of hyperfine constants and g tensor further support the assumption that the trans-effect of the proximal imidazole is an important link of allosteric interactions in haemoglobins.     

An examination of the binding behavior of histidine-containing peptides with immobilized metal complexes derived from the macrocyclic ligand, 1,4,7-triazacyclononane

In this study, two different experimental approaches have been employed to examine the binding behavior of histidine-containing peptides with metal ion complexes derived from the macrocyclic ligand 1,4,7-triazacyclononane (tacn). Firstly, a molecular modeling approach has been employed to derive the strain energies for test peptide sequences that have a predicted propensity to readily adopt an α-helical conformation. To this end, binuclear metal complexes were examined with peptides containing two histidine residues in different locations in a pair of peptides of the same composition but different sequence. These modeling results indicate that there are no energetic constraints for two-point binding to occur with dicopper(II) binuclear complexes when two histidine residues are appropriately placed in an α-helical conformation. Secondly, binding experiments were carried out to establish the effect of one or more histidine residues within a peptide sequence on the affinity of a peptide for these Cu(II)–tacn derived binuclear complexes when immobilized onto a chromatographic support material. The results confirm that for all chelating systems, higher affinity is achieved as the histidine number in the peptide structure increases, although the relative location of the histidine residues in these small peptides did not introduce a significant constraint to the conformation on interacting with the immobilized Cu(II) binuclear complexes.     

On the mechanism of protein fold‐switching by a molecular sensor

Alternate frame folding (AFF) is a mechanism by which conformational change can be engineered into a protein. The protein structure switches from the wild‐type fold (N) to a circularly‐permuted fold (N′), or vice versa, in response to a signaling event such as ligand binding. Despite the fact that the two native states have similar structures, their interconversion involves folding and unfolding of large parts of the molecule. This rearrangement is reported by fluorescent groups whose relative proximities change as a result of the order–disorder transition. The nature of the conformational change is expected to be similar from protein to protein; thus, it may be possible to employ AFF as a general method to create optical biosensors. Toward that goal, we test basic aspects of the AFF mechanism using the AFF variant of calbindin D_9k. A simple three‐state model for fold switching holds that N and N′ interconvert through the unfolded state. This model predicts that the fundamental properties of the switch—calcium binding affinity, signal response (i.e., fluorescence change upon binding), and switching rate—can be controlled by altering the relative stabilities of N and N′. We find that selectively destabilizing N or N′ changes the equilibrium properties of the switch (binding affinity and signal response) in accordance with the model. However, kinetic data indicate that the switching pathway does not require whole‐molecule unfolding. The rate is instead limited by unfolding of a portion of the protein, possibly in concert with folding of a corresponding region. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

The role of calcium in the interaction between calmodulin and a minimal functional construct of eukaryotic elongation factor 2 kinase

Eukaryotic elongation factor 2 kinase (eEF‐2K) regulates protein synthesis by phosphorylating eukaryotic elongation factor 2 (eEF‐2), thereby reducing its affinity for the ribosome and suppressing global translational elongation rates. eEF‐2K is regulated by calmodulin (CaM) through a mechanism that is distinct from that of other CaM‐regulated kinases. We had previously identified a minimal construct of eEF‐2K (TR) that is activated similarly to the wild‐type enzyme by CaM in vitro and retains its ability to phosphorylate eEF‐2 efficiently in cells. Here, we employ solution nuclear magnetic resonance techniques relying on Ile δ1‐methyls of TR and Ile δ1‐ and Met ε‐methyls of CaM, as probes of their mutual interaction and the influence of Ca²⁺ thereon. We find that in the absence of Ca²⁺, CaM exclusively utilizes its C‐terminal lobe (CaM_C) to engage the N‐terminal CaM‐binding domain (CBD) of TR in a high‐affinity interaction. Avidity resulting from additional weak interactions of TR with the Ca²⁺‐loaded N‐terminal lobe of CaM (CaM_N) at increased Ca²⁺ levels serves to enhance the affinity further. These latter interactions under Ca²⁺ saturation result in minimal perturbations in the spectra of TR in the context of its complex with CaM, suggesting that the latter is capable of driving TR to its final, presumably active conformation, in the Ca²⁺‐free state. Our data are consistent with a scenario in which Ca²⁺ enhances the affinity of the TR/CaM interactions, resulting in the increased effective concentration of the CaM‐bound species without significantly modifying the conformation of TR within the final, active complex.     

The Role of Weak Specific and Nonspecific Interactions in Enzymatic Recognition and Conversion of Long DNAs

According to the currently accepted model, enzymes searching for specific recognition sequences or structural elements (modified nucleotides, breaks, single-stranded DNA fragments, etc.) slide at a high rate along DNA. Such sliding is possible only if the enzymes possess sufficiently high affinity for all DNA, sequence notwithstanding. Therefore, significant differences in their affinity for specific and nonspecific DNA sequences are unlikely, and the formation of a complex between an enzyme and its target DNA is not a basic factor of enzyme specificity. To elucidate such factors, we have analyzed many DNA replication, DNA repair, topoisomerization, integration, and recombination enzymes using a number of physicochemical methods, including the method of stepwise increase in ligand complexity developed in our laboratory. It has been shown that high affinity of all studied enzymes for long DNAs is provided by the formation of many weak contacts of the enzyme with all nucleotide units covered by the protein globule. The main role lies in the contact between positively charged amino acid residues and internucleoside phosphate groups; however, the contribution of each contact is very small, and the full contact interface usually resembles that characteristic of interactions between oppositely charged biopolymer surfaces. In some cases, a significant contribution to the affinity is made through hydrophobic and/or van der Waals interactions of the enzymes with nucleotide bases. On the whole, such nonspecific interactions provide for five to eight orders of enzyme affinity for DNA, depending on the enzyme. Specific interactions of enzymes with long DNAs, in contrast to their contacts with small ligands, are usually weak and comparable in efficiency with weak nonspecific contacts. The sum of specific interactions most often provides for approximately one or, rarely, two orders of affinity. According to structural data, DNA binding to any of the investigated enzymes is followed by a stage of DNA conformation adjustment, which includes partial or complete DNA melting, deformation of its backbone, stretching, compression, bending or kinking, eversion of nucleotides from the DNA helix, etc. The full set of such changes is specific for each individual enzyme. The fact that all enzyme-dependent changes in DNA are effected through weak specific (rather than strong) interactions is very important. Enzyme-specific changes in DNA conformation are required for effective adjustment of reacting orbitals to an accuracy of 10°–15°, which is possible only in the case of specific DNAs. A transition from nonspecific to specific DNA leads to an increase in the reaction rate (k _cat) by four to eight orders of magnitude. Thus, the stages of DNA conformation adjustment and catalysis proper provide for the high specificity of enzyme action.