Intermolecular and intramolecular readout mechanisms in protein-DNA recognition

Protein-DNA recognition plays an essential role in the regulation of gene expression. Regulatory proteins are known to recognize specific DNA sequences directly through atomic contacts (intermolecular readout) and/or indirectly through the conformational properties of the DNA (intramolecular readout). However, little is known about the respective contributions made by these so-called direct and indirect readout mechanisms. We addressed this question by making use of information extracted from a structural database containing many protein-DNA complexes. We quantified the specificity of intermolecular (direct) readout by statistical analysis of base-amino acid interactions within protein-DNA complexes. The specificity of the intramolecular (indirect) readout due to DNA was quantified by statistical analysis of the sequence-dependent DNA conformation. Systematic comparison of these specificities in a large number of protein-DNA complexes revealed that both intermolecular and intramolecular readouts contribute to the specificity of protein-DNA recognition, and that their relative contributions vary depending upon the protein-DNA complexes. We demonstrated that combination of the intermolecular and intramolecular energies derived from the statistical analyses lead to enhanced specificity, and that the combined energy could explain experimental data on binding affinity changes caused by base mutations. These results provided new insight into the relationship between specificity and structure in the process of protein-DNA recognition, which would lead to prediction of specific protein-DNA binding sites.     

Electron Correlated Ab Initio Study of Amino Group Flexibility for Improvement of Molecular Mechanics Simulations on Nucleic Acid Conformations and Interactions

High level ab initio studies demonstrate substantial conformational flexibility of amino groups of nucleic acid bases. This flexibility is important for biological functions of DNA. Existing force field models of molecular mechanics do not describe this phenomenon due to a lack of quantitative experimental data necessary for an adjustment of empirical parameters. We have performed extensive calculations of nucleic acid bases at the MP2/6-31G(d,p) level of ab initio theory for broad set of amino group configurations. Two-dimensional maps of energy and geometrical characteristics as functions of two amino hydrogen torsions have been constructed. We approximate the maps by polynomial expressions, which can be used in molecular mechanics calculations. Detailed considerations of these maps enable us to propose a method for determination of numerical coefficients in the developed formulae using restricted sets of points obtained via higher-level calculations.     

Structure-based prediction of DNA target sites by regulatory proteins

Regulatory proteins play a critical role in controlling complex spatial and temporal patterns of gene expression in higher organism, by recognizing multiple DNA sequences and regulating multiple target genes. Increasing amounts of structural data on the protein-DNA complex provides clues for the mechanism of target recognition by regulatory proteins. The analyses of the propensities of base-amino acid interactions observed in those structural data show that there is no one-to-one correspondence in the interaction, but clear preferences exist. On the other hand, the analysis of spatial distribution of amino acids around bases shows that even those amino acids with strong base preference such as Arg with G are distributed in a wide space around bases. Thus, amino acids with many different geometries can form a similar type of interaction with bases. The redundancy and structural flexibility in the interaction suggest that there are no simple rules in the sequence recognition, and its prediction is not straightforward. However, the spatial distributions of amino acids around bases indicate a possibility that the structural data can be used to derive empirical interaction potentials between amino acids and bases. Such information extracted from structural databases has been successfully used to predict amino acid sequences that fold into particular protein structures. We surmised that the structures of protein-DNA complexes could be used to predict DNA target sites for regulatory proteins, because determining DNA sequences that bind to a particular protein structure should be similar to finding amino acid sequences that fold into a particular structure. Here we demonstrate that the structural data can be used to predict DNA target sequences for regulatory proteins. Pairwise potentials that determine the interaction between bases and amino acids were empirically derived from the structural data. These potentials were then used to examine the compatibility between DNA sequences and the protein-DNA complex structure in a combinatorial "threading" procedure. We applied this strategy to the structures of protein-DNA complexes to predict DNA binding sites recognized by regulatory proteins. To test the applicability of this method in target-site prediction, we examined the effects of cognate and noncognate binding, cooperative binding, and DNA deformation on the binding specificity, and predicted binding sites in real promoters and compared with experimental data. These results show that target binding sites for several regulatory proteins are successfully predicted, and our data suggest that this method can serve as a powerful tool for predicting multiple target sites and target genes for regulatory proteins.     

Ab initio conformational maps for disaccharides in gas phase and aqueous solution

Ab initio conformational maps for beta-lactose in both the gas phase and in aqueous solution have been constructed at the HF/6-31G(d,p) level of calculation. The results of the gas-phase ab initio calculations allow us to conclude that a rigid conformational map is able to predict the regions of the minima in the potential energy surface of beta-lactose, in full agreement with those found in the relaxed conformational map. The solvation effects do not give rise to any new local minimum in the potential energy surface of beta-lactose, but just change the relative Boltzmann populations of the conformers found in the gas-phase calculations. The values obtained for heteronuclear spin coupling constant (3J(H,C)), using the seven most stable conformers in solution are in good agreement with the available experimental values. This is a good indication that ab initio rigid conformational maps can be reliably used to sort the most stable conformers of beta-lactose.     

Accounting for conformational entropy in predicting binding free energies of protein-protein interactions

Protein-protein interactions are governed by the change in free energy upon binding, ΔG = ΔH - TΔS. These interactions are often marginally stable, so one must examine the balance between the change in enthalpy, ΔH, and the change in entropy, ΔS, when investigating known complexes, characterizing the effects of mutations, or designing optimized variants. To perform a large-scale study into the contribution of conformational entropy to binding free energy, we developed a technique called GOBLIN (Graphical mOdel for BiomoLecular INteractions) that performs physics-based free energy calculations for protein-protein complexes under both side-chain and backbone flexibility. Goblin uses a probabilistic graphical model that exploits conditional independencies in the Boltzmann distribution and employs variational inference techniques that approximate the free energy of binding in only a few minutes. We examined the role of conformational entropy on a benchmark set of more than 700 mutants in eight large, well-studied complexes. Our findings suggest that conformational entropy is important in protein-protein interactions--the root mean square error (RMSE) between calculated and experimentally measured ΔΔGs decreases by 12% when explicit entropic contributions were incorporated. GOBLIN models all atoms of the protein complex and detects changes to the binding entropy along the interface as well as positions distal to the binding interface. Our results also suggest that a variational approach to entropy calculations may be quantitatively more accurate than the knowledge-based approaches used by the well-known programs FOLDX and Rosetta--GOBLIN's RMSEs are 10 and 36% lower than these programs, respectively.     

Effects of hydrated water on protein unfolding

The conformational stability of a protein in aqueous solution is described in terms of the thermodynamic properties such as unfolding Gibbs free energy, which is the difference in the free energy (Gibbs function) between the native and random conformations in solution. The properties are composed of two contributions, one from enthalpy due to intramolecular interactions among constituent atoms and chain entropy of the backbone and side chains, and the other from the hydrated water around a protein molecule. The hydration free energy and enthalpy at a given temperature for a protein of known three-dimensional structure can be calculated from the accessible surface areas of constituent atoms according to a method developed recently. Since the hydration free energy and enthalpy for random conformations are computed from those for an extended conformation, the thermodynamic properties of unfolding are evaluated quantitatively. The evaluated hydration properties for proteins of known transition temperature (Tm) and unfolding enthalpy (delta Hm) show an approximately linear dependence on the number of constituent heavy atoms. Since the unfolding free energy is zero at Tm, the enthalpy originating from interatomic interactions of a polypeptide chain and the chain entropy are evaluated from an experimental value of delta Hm and computed properties due to the hydrated water around the molecule at Tm. The chain enthalpy and entropy thus estimated are largely compensated by the hydration enthalpy and entropy, respectively, making the unfolding free energy and enthalpy relatively small. The computed temperature dependences of the unfolding free energy and enthalpy for RNase A, T4 lysozyme, and myoglobin showed a good agreement with the experimental ones.(ABSTRACT TRUNCATED AT 250 WORDS)     

Isothermal titration calorimetry of protein-protein interactions.

The interaction of biologicalmacromolecules, whether protein-DNA, antibody-antigen, hormone-receptor, etc., illustrates the complexity and diversity of molecular recognition. The importance of such interactions in the immune response, signal transduction cascades, and gene expression cannot be overstated. It is of great interest to determine the nature of the forces that stabilize the interaction. The thermodynamics of association are characterized by the stoichiometry of the interaction (n), the association constant (K(a)), the free energy (DeltaG(b)), enthalpy (DeltaH(b)), entropy (DeltaS(b)), and heat capacity of binding (DeltaC(p)). In combination with structural information, the energetics of binding can provide a complete dissection of the interaction and aid in identifying the most important regions of the interface and the energetic contributions. Various indirect methods (ELISA, RIA, surface plasmon resonance, etc.) are routinely used to characterize biologically important interactions. Here we describe the use of isothermal titration calorimetry (ITC) in the study of protein-protein interactions. ITC is the most quantitative means available for measuring the thermodynamic properties of a protein-protein interaction. ITC measures the binding equilibrium directly by determining the heat evolved on association of a ligand with its binding partner. In a single experiment, the values of the binding constant (K(a)), the stoichiometry (n), and the enthalpy of binding (DeltaH(b)) are determined. The free energy and entropy of binding are determined from the association constant. The temperature dependence of the DeltaH(b) parameter, measured by performing the titration at varying temperatures, describes the DeltaC(p) term. As a practical application of the method, we describe the use of ITC to study the interaction between cytochrome c and two monoclonal antibodies.     

Contribution of cation-pi interactions to the stability of protein-DNA complexes

Cation-pi interactions between an aromatic ring and a positive charge located above it have proven to be important in protein structures and biomolecule associations. Here, the role of these interactions at the interface of protein-DNA complexes is investigated, by means of ab initio quantum mechanics energy calculations and X-ray structure analyses. Ab initio energy calculations indicate that Na ions and DNA bases can form stable cation-pi complexes, whose binding strength strongly depends on the type of base, on the position of the Na ion, and whether the base is isolated or included in a double-stranded B-DNA. A survey of protein-DNA complex structures using appropriate geometrical criteria revealed cation-pi interactions in 71% of the complexes. More than half of the cation-pi pairs involve arginine residues, about one-third asparagine or glutamine residues that only carry a partial charge, and one-seventh lysine residues. The most frequently observed pair, which is also the most stable as monitored by ab initio energy calculations, is arginine- guanine. Arginine-adenine interactions are also favorable in general, although to a lesser extent, whereas those with thymine and cytosine are not. Our calculations show that the major contribution to cation-pi interactions with DNA bases is of electrostatic nature. These interactions often occur concomitantly with hydrogen bonds with adjacent bases; their strength is estimated to be from three to four times lower than that of hydrogen bonds. Finally, the role of cation-pi interactions in the stability and specificity of protein-DNA complexes is discussed.     

Elucidating protein thermodynamics from the three-dimensional structure of the native state using network rigidity

Given the three-dimensional structure of a protein, its thermodynamic properties are calculated using a recently introduced distance constraint model (DCM) within a mean-field treatment. The DCM is constructed from a free energy decomposition that partitions microscopic interactions into a variety of constraint types, i.e., covalent bonds, salt-bridges, hydrogen-bonds, and torsional-forces, each associated with an enthalpy and entropy contribution. A Gibbs ensemble of accessible microstates is defined by a set of topologically distinct mechanical frameworks generated by perturbing away from the native constraint topology. The total enthalpy of a given framework is calculated as a linear sum of enthalpy components over all constraints present. Total entropy is generally a nonadditive property of free energy decompositions. Here, we calculate total entropy as a linear sum of entropy components over a set of independent constraints determined by a graph algorithm that builds up a mechanical framework one constraint at a time, placing constraints with lower entropy before those with greater entropy. This procedure provides a natural mechanism for enthalpy-entropy compensation. A minimal DCM with five phenomenological parameters is found to capture the essential physics relating thermodynamic response to network rigidity. Moreover, two parameters are fixed by simultaneously fitting to heat capacity curves for histidine binding protein and ubiquitin at five different pH conditions. The three free parameter DCM provides a quantitative characterization of conformational flexibility consistent with thermodynamic stability. It is found that native hydrogen bond topology provides a key signature in governing molecular cooperativity and the folding-unfolding transition.     

Computational study of the conformational preferences of the (R)-8-amino-pentacyclo[5.4.0.0(2,6).0(3,10).0(5,9)]undecane-8-carboxylic acid monopeptide.

alpha-Amino acids are important building blocks for the synthesis of a large number of bioactive compounds and pharmaceutical drugs. However, a literature survey revealed that no theoretical conformational study of alpha-amino acids with cage carbon frameworks has been performed to date. This paper reports the results of a conformational study on the (R)-8-amino-pentacyclo[5.4.0.0(2,6).0(3,10).0(5,9)]undecane-8-carboxylic acid monopeptide (cage monopeptide), using molecular mechanics and ab initio methods. The in vacuo Ramachandran maps computed using the different parameterizations of the AMBER force field show the C7eq structure as the most favourable conformation, in contrast to the C7ax structure, that is the lowest energy conformation at the ab initio level. Analysis of these maps reveals the helical preference for the monopeptide and provides the potential for the cage residue to be incorporated into constrained peptide analogues.     

The role of flexibility and hydration on the sequence-specific DNA recognition by the Tn916 integrase protein: a molecular dynamics analysis

The N-terminal domain of the Tn916 integrase protein (INT-DBD) is responsible for DNA binding in the process of strand cleavage and joining reactions required for transposition of the Tn916 conjugative transposon. Site-specific association is facilitated by numerous protein-DNA contacts from the face of a three-stranded beta-sheet inserted into the major groove. The protein undergoes a subtle conformational transition and is slightly unfolded in the protein-DNA complex. The conformation of many charged residues is poorly defined by NMR data but mutational studies have indicated that removal of polar side chains decreases binding affinity, while non-polar contacts are malleable. Based on analysis of the binding enthalpy and binding heat capacity, we have reasoned that dehydration of the protein-DNA interface is incomplete. This study presents results from a molecular dynamics investigation of the INT-DBD-DNA complex aimed at a more detailed understanding of the role of conformational dynamics and hydration in site-specific binding. Comparison of simulations (total of 13 ns) of the free protein and of the bound protein conformation (in isolation or DNA-bound) reveals intrinsic flexibility in certain parts of the molecule. Conformational adaptation linked to partial unfolding appears to be induced by protein-DNA contacts. The protein-DNA hydrogen-bonding network is highly dynamic. The simulation identifies protein-DNA interactions that are poorly resolved or only surmised from the NMR ensemble. Single water molecules and water clusters dynamically optimize the complementarity of polar interactions at the 'wet' protein-DNA interface. The simulation results are useful to establish a qualitative link between experimental data on individual residue's contribution to binding affinity and thermodynamic properties of INT-DBD alone and in complex with DNA.     

A graph-theory algorithm for rapid protein side-chain prediction

Fast and accurate side-chain conformation prediction is important for homology modeling, ab initio protein structure prediction, and protein design applications. Many methods have been presented, although only a few computer programs are publicly available. The SCWRL program is one such method and is widely used because of its speed, accuracy, and ease of use. A new algorithm for SCWRL is presented that uses results from graph theory to solve the combinatorial problem encountered in the side-chain prediction problem. In this method, side chains are represented as vertices in an undirected graph. Any two residues that have rotamers with nonzero interaction energies are considered to have an edge in the graph. The resulting graph can be partitioned into connected subgraphs with no edges between them. These subgraphs can in turn be broken into biconnected components, which are graphs that cannot be disconnected by removal of a single vertex. The combinatorial problem is reduced to finding the minimum energy of these small biconnected components and combining the results to identify the global minimum energy conformation. This algorithm is able to complete predictions on a set of 180 proteins with 34342 side chains in <7 min of computer time. The total chi(1) and chi(1 + 2) dihedral angle accuracies are 82.6% and 73.7% using a simple energy function based on the backbone-dependent rotamer library and a linear repulsive steric energy. The new algorithm will allow for use of SCWRL in more demanding applications such as sequence design and ab initio structure prediction, as well addition of a more complex energy function and conformational flexibility, leading to increased accuracy.     

Analysis of the conformational profile of trishomocubane amino acid dipeptide

4-Amino-(D3)-trishomocubane-4-carboxylic acid is a constrained alpha-amino acid residue that exhibits promising conformational characteristics, i.e., helical and beta-turns. As part of the development of conformational guidelines for the design of peptides and protein surrogates, the conformational energy calculations on trishomocubane using molecular mechanics and ab initio methods are presented. The C(alpha) carbon of trishomocubane forms part of the cyclic structure, and consequently a peptidic environment was simulated with an acetyl group on its N-terminus and a methylamide group on its C-terminus. Ramachandran maps computed at the molecular mechanics level using the standard AMBER (parm94) force field libraries compared reasonably well with the corresponding maps computed at the Hartree Fock level, using the 6-31G* basis set. Trishomocubane peptide (Ac-Tris-NHMe) is characterized by four low energy conformers corresponding to the C7ax, C7eq, 3(10), and alpha(L) helical structures.     

Recognition of 5'-YpG-3' sequences by coupled stacking/hydrogen bonding interactions with amino acid residues

The combined biochemical and structural study of hundreds of protein-DNA complexes has indicated that sequence-specific interactions are mediated by two mechanisms termed direct and indirect readout. Direct readout involves direct interactions between the protein and base-specific atoms exposed in the major and minor grooves of DNA. For indirect readout, the protein recognizes DNA by sensing conformational variations in the structure dependent on nucleotide sequence, typically through interactions with the phosphodiester backbone. Based on our recent structure of Ndt80 bound to DNA in conjunction with a search of the existing PDB database, we propose a new method of sequence-specific recognition that utilizes both direct and indirect readout. In this mode, a single amino acid side-chain recognizes two consecutive base-pairs. The 3'-base is recognized by canonical direct readout, while the 5'-base is recognized through a variation of indirect readout, whereby the conformational flexibility of the particular dinucleotide step, namely a 5'-pyrimidine-purine-3' step, facilitates its recognition by the amino acid via cation-pi interactions. In most cases, this mode of DNA recognition helps explain the sequence specificity of the protein for its target DNA.     

The entropic nature of protein thermal stabilization

We performed thermodynamic analysis of temperature-induced unfolding of mesophilic and thermophilic proteins. It was shown that the variability in protein thermostability associated with pH-dependent unfolding or linked to the substitution of amino acid residues on the protein surface is evidence of the governing role of the entropy factor. Numerical values of conformational components in enthalpy, entropy and free energy which characterize protein unfolding in the “gas phase” were obtained. Based on the calculated absolute values of entropy and free energy, a model of protein unfolding is proposed in which the driving force is the conformational entropy of native protein, as an energy of the heat motion (T·S^NC) increasing with temperature and acting as an factor devaluating the energy of intramolecular weak bonds in the transition state.     

蛋白质结构从头预测方法研究进展

蛋白质结构从头预测是不依赖模板仅从氨基酸序列信息得到天然结构。它的关键是正确定义能量函数、精确选用计算机搜索算法来寻找能量最低值。基于此,本文系统介绍了能量函数和构象搜索策略,并列举了几种比较成功的从头预测方法,通过比较得出结论:基于统计学知识的能量函数是近年来从头预测发展的主要方向,现有从头预测的构象搜索都用到Monte Carlo法。这表明随着蛋白质结构预测研究的深入,能量函数的构建、构象搜索方法的选择、大分子蛋白质结构的从头预测等关键性问题都取得了突破性进展。     

Conformational dynamics and thermodynamics of protein-ligand binding studied by NMR relaxation

Protein conformational dynamics can be critical for ligand binding in two ways that relate to kinetics and thermodynamics respectively. First, conformational transitions between different substates can control access to the binding site (kinetics). Secondly, differences between free and ligand-bound states in their conformational fluctuations contribute to the entropy of ligand binding (thermodynamics). In the present paper, I focus on the second topic, summarizing our recent results on the role of conformational entropy in ligand binding to Gal3C (the carbohydrate-recognition domain of galectin-3). NMR relaxation experiments provide a unique probe of conformational entropy by characterizing bond-vector fluctuations at atomic resolution. By monitoring differences between the free and ligand-bound states in their backbone and side chain order parameters, we have estimated the contributions from conformational entropy to the free energy of binding. Overall, the conformational entropy of Gal3C increases upon ligand binding, thereby contributing favourably to the binding affinity. Comparisons with the results from isothermal titration calorimetry indicate that the conformational entropy is comparable in magnitude to the enthalpy of binding. Furthermore, there are significant differences in the dynamic response to binding of different ligands, despite the fact that the protein structure is virtually identical in the different protein-ligand complexes. Thus both affinity and specificity of ligand binding to Gal3C appear to depend in part on subtle differences in the conformational fluctuations that reflect the complex interplay between structure, dynamics and ligand interactions.     

154 Protein folding and binding funnels: a common driving force and a common mechanism

Under the free energy landscape theory, both the protein-folding and protein–ligand binding processes are driven by the decrease in total Gibbs free energy of the protein-solvent or protein–ligand-solvent system, which involves the non-complementary changes between the entropy and enthalpy, ultimately leading to a global free energy minimization of these thermodynamic systems (Ji & Liu, 2011; Liu et al., 2012; Yang, Ji & Liu, 2012). In the case of protein folding, the lowering of the system free energy coupled with the gradual reduction in conformational degree of freedom of the folding intermediates determines that the shape of the free energy landscape for protein folding must be funnel-like (Dill & Chan, 1997), rather than non-funneled shapes (Ben-Naim, 2012). In the funnel-like free energy landscape, protein folding can be viewed as going down the hill via multiple parallel routes from a vast majority of individual non-native states on surface outside the funnel to the native states located around the bottom of the funnel. The first stage of folding, i.e. the rapid hydrophobic collapse process, is driven by the solvent entropy maximization. Concretely, the water molecules squeeze and sequestrate the hydrophobic amino acid side chains within the interior of the folding intermediates while exposing the polar and electrostatically charged side chains on the intermediate surface so as to minimize the solvent-accessible surface area of the solute and thus, the minimal contacts between the folding intermediates and the water molecules. This will maximize the entropy of the solvent, thus contributing substantially to lowering of the system free energy due to an absolute advantage of the solvent in both quantity and mass (Yang, Ji & Liu, 2012). The resulting molten globule states (Ohgushi & Wada, 1983), within which a few transient secondary structural components and tertiary contacts have been formed but many native contacts or close residue–residue interactions has yet to form, need to be further sculptured into the native states. This is a relatively slow “bottleneck” process because the competitive interactions between protein residues within the folding intermediates and between residues and water molecules may repeat many rounds to accumulate a large enough number of stable noncovalent bonds capable of counteracting the conformational entropy loss of the intermediates, thus putting this bottleneck stage under the enthalpy control (i.e. negative enthalpy change), contributing further to the lowering of the system free energy. Although the protein–ligand association occurs around the rugged bottom of the free energy landscape, the exclusion of water from the binding interfaces and the formation of noncovalent bonds between the two partners can still lower the system free energy. In conjunction with the loss of the rotational and translational degrees of freedom of the two partners as well as the loss of the conformational entropy of the protein, these processes could merge, downwards expand, and further narrow the free energy wells within which the protein–ligand binding process takes place, thereby making them look like a funnel, which we term the binding funnel. In this funnel, the free energy downhill process follows a similar paradigm to the protein-folding process. For example, if the initial collisions/contacts occur between the properly complementary interfaces of the protein and ligand, a large amount of water molecules (which usually form a water network around the solute surface) will be displaced to suit the need for maximizing the solvent entropy. This process is similar to that of the hydrophobic collapse during protein folding, resulting in a loosely associated protein–ligand complex that needs also to be further adapted into a tight complex, i.e. the second step which is mainly driven by the negative enthalpy change through intermolecular competitive interactions to gradually accumulate the noncovalent bonds and ultimately, to stabilize the complex at a tightly bound state. Taken together, we conclude that whether in the protein-folding or in the protein–ligand binding process, both the entropy-driven first step and the enthalpy-driven second step contribute to the lowering of the system free energy, resulting in the funnel-like folding or binding free energy landscape.