Base-amino Acid Interactions Research Articles

Molecular Dynamics Simulations of Protein RNA Complexes by Using an Advanced Electrostatic Model.

Protein-RNA interactions are integral to the biological functions of RNA. It is well recognized that molecular dynamics (MD) simulations of protein-RNA complexes are more challenging than those of each component. The difficulty arises from the strong electrostatic interactions and the delicate balance between various types of physical forces at the interface. Previously, MD simulations of protein-RNA complexes have predominantly employed fixed-charge force fields. Although force field modifications have been developed to address problems identified in the simulations, some protein-RNA structures are still hard to reproduce by simulations. Here, we present MD simulations of two representative protein-RNA complexes using the AMOEBA polarizable force field. The van der Waals parameters were refined to reproduce accurate quantum-mechanical data of base-base and base-amino acid interactions. It was found that the refined parameters produced a more stable hydrogen-bond network in the interface. One of the complexes remained stable during the short simulations, whereas it could quickly break down in previous simulations using fixed-charge force fields. There was reversible breaking and formation of hydrogen bonds that are observed in the crystal structure, which may indicate the difference in solution and crystal structures. While further improvement and validation of the force fields are still needed, this work demonstrates that polarizable force fields are promising for the study of protein-RNA complexes.

A quantum chemical view of the interaction of RNA nucleobases and base pairs with the side chains of polar amino acids

Hydrogen bonding between amino acids and nucleobases is important for RNA–protein recognition. As a first step toward understanding the physicochemical features of these contacts, the present work employs density functional theory calculations to critically analyze the intrinsic structures and strength of all theoretically possible model hydrogen-bonded complexes involving RNA nucleobase edges and polar amino acid side chains. Our geometry optimizations uncover a number of unique complexes that involve variable hydrogen-bonding characteristics, including conventional donor–acceptor interactions, bifurcated interactions and single hydrogen-bonded contacts. Further, significant strength of these complexes in the gas phase (−27 kJ mol−1 to −226 kJ mol−1) and solvent phase (−19 kJ mol−1 to −78 kJ mol−1) points toward the ability of associated contacts to provide stability to RNA–protein complexes. More importantly, for the first time, our study uncovers the features of complexes involving protonated nucleobases, as well as those involving the weakly polar cysteine side chain, and thereby highlights their potential importance in biological processes that involve RNA–protein interactions. Additional analysis on select base pair-amino acid complexes uncovers the ability of amino acid side chain to simultaneously interact with both nucleobases of the base pair, and highlights the greater strength of such interactions compared to base-amino acid interactions. Overall, our analysis provides a basic physicochemical framework for understanding the molecular basis of nucleic acid–protein interactions. Further, our quantum chemical data can be used to design better algorithms for automated search of these contacts at the RNA–protein interface. Communicated by Ramaswamy H. Sarma

Characterization of the Photochemical Properties of 5-Benzyluracil via Time-Dependent Density Functional Theory.

We present a detailed study of the excited state properties of 5-benzyluracil (5BU) in the gas phase and in implicit solvent using different electronic structure approaches ranging from time-dependent density functional theory in the linear response regime (LR-TDDFT) to a set of different wave-function-based methods for excited states, namely perturbed coupled cluster (CC2), algebraic diagrammatic construction method to second order (ADC(2)), and perturbed configuration interaction (CIS(D)). 5BU has been used to investigate DNA base-amino acid interactions. In particular, it served as a model of protein-DNA photoinduced cross-linking. While LR-TDDFT is computationally the most efficient first-principles approach for static and dynamic simulations of this bichromophoric system, its accuracy is difficult to assess due to the presence of excited states with charge transfer character. In this work, the performance of different exchange correlation functionals is compared against accurate benchmarks obtained either from high level wave-function-based methods or directly from experimental absorption spectra. Our investigation shows that accurate results for the excitation energies can be obtained using the hybrid meta-GGA functional M06. In view of dynamical studies of the relaxation of 5BU after photoexcitation, we also show that the PBE functional, while failing in the Franck-Condon region, provides qualitatively good results for the characterisation of a possible photocyclization path.

ReadOut: structure-based calculation of direct and indirect readout energies and specificities for protein-DNA recognition.

Protein–DNA interactions play a central role in regulatory processes at the genetic level. DNA-binding proteins recognize their targets by direct base–amino acid interactions and indirect conformational energy contribution from DNA deformations and elasticity. Knowledge-based approach based on the statistical analysis of protein–DNA complex structures has been successfully used to calculate interaction energies and specificities of direct and indirect readouts in protein–DNA recognition. Here, we have implemented the method as a webserver, which calculates direct and indirect readout energies and Z-scores, as a measure of specificity, using atomic coordinates of protein–DNA complexes. This server is freely available at . The only input to this webserver is the Protein Data Bank (PDB) style coordinate data of atoms or the PDB code itself. The server returns total energy Z-scores, which estimate the degree of sequence specificity of the protein–DNA complex. This webserver is expected to be useful for estimating interaction energy and DNA conformation energy, and relative contributions to the specificity from direct and indirect readout. It may also be useful for checking the quality of protein–DNA complex structures, and for engineering proteins and target DNAs.

Role of inter and intramolecular interactions 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 between protein and DNA, and/or indirectly through the conformational properties of the DNA. In this work, we have analyzed the specificity of intermolecular interactions by statistical analysis of base–amino acid interactions within protein–DNA complexes as well as the computer simulations of base–amino acid interactions. The specificity of the intramolecular interactions was studied by statistical analysis of the sequence-dependent DNA conformational parameters and the elastic properties of DNA. Systematic comparison of these specificities in a large number of protein–DNA complexes revealed that both intermolecular and intramolecular interactions contribute to the specificity of protein–DNA recognition, and their relative contributions vary depending upon the protein–DNA complex. We demonstrated that combination of the intermolecular and intramolecular energies leads to enhanced specificity and 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.

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.

Specificity of protein-DNA recognition revealed by structure-based potentials: symmetric/asymmetric and cognate/non-cognate binding.

Asymmetric binding of protein homodimers to DNA, which has been observed in a number of protein-DNA complexes, leads to subtle structural differences between the two subunits. Such structural differences are frequently observed when the subunits form cognate and non-cognate protein-DNA complexes, respectively. Analysis of these structural effects on binding specificity should provide insight into the mechanism of protein-DNA recognition. We previously derived empirical potential functions for specific nucleotide base-amino acid interactions from statistical analyses of the structures of many protein-DNA complexes and used a combinatorial threading procedure to evaluate the fitness of the DNA sequences involved. We then introduced Z-scores to measure the specificity with which proteins bind to DNA within complexes, as compared to random DNA sequences. Here, we examined in detail the structural effects of asymmetric and cognate/non-cognate binding on specificity. Marked differences in the specificity of DNA binding were observed for the two subunits of lambda repressor, the glucocorticoid receptor, and for transcription factors containing a Zn(2)Cys(6) binuclear cluster domain, which are known to bind asymmetrically to DNA. Moreover, the differences in the specificity with which BamH1 and EcoRV endonucleases bind to their cognate and non-cognate DNA sequences were clearly detected using this approach; indeed, analysis of EcoRV binding enabled us to show the cooperative effect of sequence and structure on binding specificity. The present results demonstrate the utility of this approach when examining the structure-specificity relationship in protein-DNA recognition, as subtle structural differences in symmetric/asymmetric and cognate/non-cognate binding were clearly shown to cause marked differences in specificity. This method can also be used as a tool for checking new structures of protein-DNA complexes for their specificity.

Rational design of artificial zinc-finger proteins using a nondegenerate recognition code table.

We have developed a novel and simple method to rationally design artificial zinc-finger proteins (AZPs) targeting diverse DNA sequences using a nondegenerate recognition code table. The table was constructed based on known and potential DNA base-amino acid interactions. The table permits identification of an amino acid for each position (-1, 2, 3, and 6) of the alpha-helical region of the zinc-finger domain (position 1 is the starting amino acid in the alpha-helix) from overlapping 4-bp sequences in a given DNA target. Based on the table, we designed ten 3-finger AZPs, each of which targeted an arbitrarily chosen 10-bp DNA sequence, and characterized the binding properties. In vitro DNA-binding assays showed five of the AZPs tightly and specifically bound to their targets containing more than three guanine bases in the first 9-bp region. In addition, 6-finger AZPs, each of which was produced by combining two functional 3-finger AZPs, bound to their 19-bp targets with the dissociation constant of less than 3 pM. The in vivo functionality of the AZP was tested using Arabidopsis protoplasts. The AZP fused to a transcriptional activation domain efficiently activated expression of a reporter gene linked to a native promoter containing the AZP target site. Our simple AZP design method will provide a powerful approach to manipulation of endogenous gene expression by enabling rapid creation of numerous artificial DNA-binding proteins.

Evaluation of free energy landscape for base-amino acid interactions using ab initio force field and extensive sampling.

Structural data of protein-DNA complex show redundancy and flexibility in base-amino acid interactions. To understand the origin of the specificity in protein-DNA recognition, we calculated the interaction free energy, enthalpy, entropy, and minimum energy maps for AT-Asn, GC-Asn, AT-Ser, and GC-Ser by means of a set of ab initio force field with extensive conformational sampling. We found that the most preferable interactions in these pairs are stabilized by hydrogen bonding, and are mainly enthalpy driven. However, minima in the free energy maps are not necessarily the same as those in the minimum energy map or enthalpy maps, due to the entropic effect. The effect of entropy is particularly important in the case of GC-Asn. Experimentally observed structures of base-amino acid interactions are within preferable regions in the calculated free energy maps, where there are many different interaction configurations with similar energy. The full geometry optimization procedure using ab initio molecular orbital method was applied to get the optimal interaction geometries for AT-Asn, GC-Asn, AT-Ser, and GC-Ser. We found that there are various base-amino acid combinations with similar interaction energies. These results suggest that the redundancy and conformational flexibility in the base-amino acid interactions play an important role in the protein-DNA recognition.

Multicanonical Monte Carlo calculation of the free-energy map of the base-amino acid interaction

The specific interactions between base pairs and amino acids were studied by the multicanonical Monte Carlo method. We sampled numerous interaction configurations and side-chain conformations of the amino acid by the multicanonical algorithm, and calculated the free energies of the interactions between an amino acid at given Cα positions and a fixed base pair. The contour maps of free energy derived from this calculation represent the preferred Cα position of the amino acid around the base, and these maps of various combinations of bases and amino acids can be used to quantify the specificity of intrinsic base–amino acid interactions. Similarly, enthalpy and entropy maps will provide further details of the specific interactions. We have also calculated the free-energy map of the orientations of the CαCβ bond vector, which indicates the preferential orientation of the amino acid against the base. We compared the results obtained by the multicanonical method with those of the exhaustive sampling and canonical Monte Carlo methods. The free-energy map of the base–amino acid interaction obtained by the multicanonical simulation method was nearly identical to the accurate result derived from the exhaustive sampling method. This indicates that a single multicanonical Monte Carlo simulation can produce an accurate free-energy map. Multicanonical Monte Carlo sampling produced free-energy maps that were more accurate than those produced by canonical Monte Carlo sampling. Thus, the multicanonical Monte Carlo method can serve as a powerful tool for estimating the free-energy landscape of base–amino acid interactions and for elucidating the mechanism by which amino acids of proteins recognize particular DNA base pairs. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 954–962, 2000

1L1330 核酸塩基・アミノ酸相互作用の自由エネルギーランドスケープ : 蛋白質によるDNA認識における特異性

1L1330 核酸塩基・アミノ酸相互作用の自由エネルギーランドスケープ : 蛋白質によるDNA認識における特異性

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.

RNA base-amino acid interaction strengths derived from structures and sequences.

We investigate RNA base-amino acid interactions by counting their contacts in structures and their implicit contacts in various functional sequences where the structures can be assumed to be preserved. These frequencies are cast into equations to extract relative interaction energetics. Previously we used this approach in considering the major groove interactions of DNA, and here we apply it to the more diverse interactions observed in RNA. Structures considered are the three different tRNA synthetase complexes, the U1A spliceosomal protein with an RNA hairpin and the BIV TAR-Tat complex. We use binding data for the base frequencies for the seryl, aspartyl and glutaminyl tRNA-synthetase and U1 RNA-protein complexes. We compare with the previously reported DNA major groove peptide contacts the results for atoms of RNA bases, usually in the major groove. There are strong similarities between the rank orders of interacting bases in the DNA and the RNA cases. The apparent strongest RNA interaction observed is between arginine and guanine which was also one of the strongest DNA interactions. The similar data for base atomic interactions, whether base paired or not, support the importance of strong atomic interactions over local structure considerations, such as groove width and alpha-helicity.