Molecular dynamics of mismatch detection-How MutS uses indirect readout to find errors in DNA.

The mismatch repair protein MutS safeguards genomic integrity by finding and initiating repair of basepairing errors in DNA. Single-molecule studies show MutS diffusing on DNA, presumably scanning for mispaired/unpaired bases, and crystal structures show a characteristic "mismatch-recognition" complex with DNA enclosed within MutS and kinked at the site of error. But how MutS goes from scanning thousands of Watson-Crick basepairs to recognizing rare mismatches remains unanswered, largely because atomic-resolution data on the search process are lacking. Here, 10 µs all-atom molecular dynamics simulations of Thermus aquaticus MutS bound to homoduplex DNA and T-bulge DNA illuminate the structural dynamics underlying the search mechanism. MutS-DNA interactions constitute a multistep mechanism to check DNA over two helical turns for its 1) shape, through contacts with the sugar-phosphate backbone, 2) conformational flexibility, through bending/unbending engineered by large-scale motions of the clamp domain, and 3) local deformability, through basepair destabilizing contacts. Thus, MutS can localize a potential target by indirect readout due to lower energetic costs of bending mismatched DNA and identify a site that distorts easily due to weaker base stacking and pairing as a mismatch. The MutS signature Phe-X-Glu motif can then lock in the mismatch-recognition complex to initiate repair.

Toward a Universal Structural and Energetic Model for Prokaryotic Promoters.

With almost no consensus promoter sequence in prokaryotes, recruitment of RNA polymerase (RNAP) to precise transcriptional start sites (TSSs) has remained an unsolved puzzle. Uncovering the underlying mechanism is critical for understanding the principle of gene regulation. We attempted to search the hidden code in ∼16,500 promoters of 12 prokaryotes representing two kingdoms in their structure and energetics. Twenty-eight fundamental parameters of DNA structure including backbone angles, basepair axis, and interbasepair and intrabasepair parameters were used, and information was extracted from x-ray crystallography data. Three parameters (solvation energy, hydrogen-bond energy, and stacking energy) were selected for creating energetics profiles using in-house programs. DNA of promoter regions was found to be inherently designed to undergo a change in every parameter undertaken for the study, in all prokaryotes. The change starts from some distance upstream of TSSs and continues past some distance from TSS, hence giving a signature state to promoter regions. These signature states might be the universal hidden codes recognized by RNAP. This observation was reiterated when randomly selected promoter sequences (with little sequence conservation) were subjected to structure generation; all developed into very similar three-dimensional structures quite distinct from those of conventional B-DNA and coding sequences. Fine structural details at important motifs (viz. -11, -35, and -75 positions relative to TSS) of promoters reveal novel to our knowledge and pointed insights for RNAP interaction at these locations; it could be correlated with how some particular structural changes at the -11 region may allow insertion of RNAP amino acids in interbasepair space as well as facilitate the flipping out of bases from the DNA duplex.

A statistical thermodynamic model for investigating the stability of DNA sequences from oligonucleotides to genomes.

We describe the development and testing of a simple statistical mechanics methodology for duplex DNA applicable to sequences of any composition and extensible to genomes. The microstates of a DNA sequence are modeled in terms of blocks of basepairs that are assumed to be fully closed (paired) or open. This approach generates an ensemble of bubblelike microstates that are used to calculate the corresponding partition function. The energies of the microstates are calculated as additive contributions from hydrogen bonding, basepair stacking, and solvation terms parameterized from a comprehensive series of molecular dynamics simulations including solvent and ions. Thermodynamic properties and nucleotide stability constants for DNA sequences follow directly from the partition function. The methodology was tested by comparing computed free energies per basepair with the experimental melting temperatures of 60 oligonucleotides, yielding a correlation coefficient of -0.96. The thermodynamic stability of genic/nongenic regions was tested in terms of nucleotide stability constants versus sequence for the Escherichia coli K-12 genome. It showed clear differentiation of the genes from promoters and captures genic regions with a sensitivity of 0.94. The statistical thermodynamic model presented here provides a seemingly new handle on the challenging problem of interpreting genomic sequences.

Allosteric Signaling in PDZ Energetic Networks: Embedding Error Analysis.

Allosteric signaling in proteins has been known for some half a century, yet how the signal traverses the protein remains an active area of research. Recently, the importance of electrostatics to achieve long-range signaling has become increasingly appreciated. Our laboratory has been working on developing network approaches to capture such interactions. In this study, we turn our attention to the well-studied allosteric model protein, PDZ. We study the allosteric dynamics on a per-residue basis in key constructs involving the PDZ domain, its allosteric effector, and its peptide ligand. We utilize molecular dynamics trajectories to create the networks for the constructs to explore the allosteric effect by plotting the heat kernel results onto axes defined by principal components. We introduce a new metric to quantitate the volume sampled by a residue in the latent space. We relate our findings to PDZ and the greater field of allostery.

High Energy Channeling and Malleable Transition States: Molecular Dynamics Simulations and Free Energy Landscapes for the Thermal Unfolding of Protein U1A and 13 Mutants.

The spliceosome protein U1A is a prototype case of the RNA recognition motif (RRM) ubiquitous in biological systems. The in vitro kinetics of the chemical denaturation of U1A indicate that the unfolding of U1A is a two-state process but takes place via high energy channeling and a malleable transition state, an interesting variation of typical two-state behavior. Molecular dynamics (MD) simulations have been applied extensively to the study of two-state unfolding and folding of proteins and provide an opportunity to obtain a theoretical account of the experimental results and a molecular model for the transition state ensemble. We describe herein all-atom MD studies including explicit solvent of up to 100 ns on the thermal unfolding (UF) of U1A and 13 mutants. Multiple MD UF trajectories are carried out to ensure accuracy and reproducibility. A vector representation of the MD unfolding process in RMSD space is obtained and used to calculate a free energy landscape for U1A unfolding. A corresponding MD simulation and free energy landscape for the protein CI2, well known to follow a simple two state folding/unfolding model, is provided as a control. The results indicate that the unfolding pathway on the MD calculated free energy landscape of U1A shows a markedly extended transition state compared with that of CI2. The MD results support the interpretation of the observed chevron plots for U1A in terms of a high energy, channel-like transition state. Analysis of the MDUF structures shows that the transition state ensemble involves microstates with most of the RRM secondary structure intact but expanded by ~14% with respect to the radius of gyration. Comparison with results on a prototype system indicates that the transition state involves an ensemble of molten globule structures and extends over the region of ~1-35 ns in the trajectories. Additional MDUF simulations were carried out for 13 U1A mutants, and the calculated φ-values show close accord with observed results and serve to validate our methodology.

Estradiol induces allosteric coupling and partitioning of sex-hormone-binding globulin monomers among conformational states.

Sex-hormone-binding globulin (SHBG) regulates the transport and bioavailability of estradiol. The dynamics of estradiol's binding to SHBG are incompletely understood, although it is believed that estradiol binds to each monomer of SHBG dimer with identical affinity (Kd ∼2 nM). Contrary to the prevalent view, we show that estradiol's binding to SHBG is nonlinear, and the "apparent" Kd changes with varying estradiol and SHBG concentrations. Estradiol's binding to each SHBG monomer influences residues in the ligand-binding pocket of both monomers and differentially alters the conformational and energy landscapes of both monomers. Monomers are not energetically or conformationally equivalent even in fully bound state. Estradiol's binding to SHBG involves bidirectional, inter-monomeric allostery that changes the distribution of both monomers among various energy and conformational states. Inter-monomeric allostery offers a mechanism to extend the binding range of SHBG and regulate hormone bioavailability as estradiol concentrations vary widely during life.

Spectral analysis of molecular dynamics simulations on PDZ: MD sectors.

The idea of protein "sectors" posits that sparse subsets of amino acid residues form cooperative networks that are key elements of protein stability, ligand binding, and allosterism. To date, protein sectors have been calculated by the statistical coupling analysis (SCA) method of Ranganathan and co-workers via the spectral analysis of conservation-weighted evolutionary covariance matrices obtained from a multiple sequence alignments of homologous families of proteins. SCA sectors, a knowledge-based protocol, have been indentified with functional properties and allosterism for a number of systems. In this study, we investigate the utility of the sector idea for the analysis of physics-based molecular dynamics (MD) trajectories of proteins. Our test case for this procedure is PSD95- PDZ3, one of the smallest proteins for which allosterism has been observed. It has served previously as a model system for a number of prediction algorithms, and is well characterized by X-ray crystallography, NMR spectroscopy and site specific mutagenisis. All-atom MD simulations were performed for a total of 500 nanoseconds using AMBER, and MD-calculated covariance matrices for the fluctuations of residue displacements and non-bonded interaction energies were subjected to spectral analysis in a manner analogous to that of SCA. The composition of MD sectors was compared with results from SCA, site specific mutagenesis, and allosterism. The concordance indicates that MD sectors are a viable protocol for analyzing MD trajectories and provide insight into the physical origin of the phenomenon.Communicated by Ramaswamy H. Sarma.

Dynamics of water and ions near DNA: comparison of simulation to time-resolved stokes-shift experiments.

Time-resolved Stokes-shift experiments measure the dynamics of biomolecules and of the perturbed solvent near them on subnanosecond time scales, but molecular dynamics simulations are needed to provide a clear interpretation of the results. Here we show that simulations using standard methods quantitatively reproduce the main features of TRSS experiments in DNA and provide a molecular assignment for the dynamics. The simulations reproduce the magnitude and unusual power-law dynamics of the Stokes shift seen in recent experiments [ Andreatta, D., et al. J. Am. Chem. Soc. 2005, 127, 7270 ]. A polarization model is introduced to eliminate cross-correlations between the different components contributing to the signal. Using this model, well-defined contributions of the DNA, water, and counterion to the experimental signal are extracted. Water is found to have the largest contribution and to be responsible for the power-law dynamics. The counterions have a smaller, but non-negligible, contribution with a time constant of 220 ps. The contribution to the signal of the DNA itself is minor and fits a 30 ps stretched exponential. Both time-averaged and dynamic distributions are calculated. They show a small subset of ions with a different coupling but no other evidence of substates or rate heterogeneity.

Prokaryotic gene finding based on physicochemical characteristics of codons calculated from molecular dynamics simulations.

An ab initio model for gene prediction in prokaryotic genomes is proposed based on physicochemical characteristics of codons calculated from molecular dynamics (MD) simulations. The model requires a specification of three calculated quantities for each codon: the double-helical trinucleotide base pairing energy, the base pair stacking energy, and an index of the propensity of a codon for protein-nucleic acid interactions. The base pairing and stacking energies for each codon are obtained from recently reported MD simulations on all unique tetranucleotide steps, and the third parameter is assigned based on the conjugate rule previously proposed to account for the wobble hypothesis with respect to degeneracies in the genetic code. The third interaction propensity parameter values correlate well with ab initio MD calculated solvation energies and flexibility of codon sequences as well as codon usage in genes and amino acid composition frequencies in approximately 175,000 protein sequences in the Swissprot database. Assignment of these three parameters for each codon enables the calculation of the magnitude and orientation of a cumulative three-dimensional vector for a DNA sequence of any length in each of the six genomic reading frames. Analysis of 372 genomes comprising approximately 350,000 genes shows that the orientations of the gene and nongene vectors are well differentiated and make a clear distinction feasible between genic and nongenic sequences at a level equivalent to or better than currently available knowledge-based models trained on the basis of empirical data, presenting a strong support for the possibility of a unique and useful physicochemical characterization of DNA sequences from codons to genomes.

Affinity and specificity of protein U1A-RNA complex formation based on an additive component free energy model.

An MM-GBSA computational protocol was used to investigate wild-type U1A-RNA and F56 U1A mutant experimental binding free energies. The trend in mutant binding free energies compared to wild-type is well-reproduced. Following application of a linear-response-like equation to scale the various energy components, the binding free energies agree quantitatively with observed experimental values. Conformational adaptation contributes to the binding free energy for both the protein and the RNA in these systems. Small differences in DeltaGs are the result of different and sometimes quite large relative contributions from various energetic components. Residual free energy decomposition indicates differences not only at the site of mutation, but throughout the entire protein. MM-GBSA and ab initio calculations performed on model systems suggest that stacking interactions may nearly, but not completely, account for observed differences in mutant binding affinities. This study indicates that there may be different underlying causes of ostensibly similar experimentally observed binding affinities of different mutants, and thus recommends caution in the interpretation of binding affinities and specificities purely by inspection.

CTL recognition of a protective immunodominant influenza A virus nucleoprotein epitope utilizes a highly restricted Vbeta but diverse Valpha repertoire: functional and structural implications.

To investigate protective immunity conferred by CTL against viral pathogens, we have analyzed CD8(+) T cell responses to the immunodominant nucleoprotein epitope (NP(366-374)) of influenza A virus in B6 mice during primary and secondary infections in vivo. Unlike the highly biased TCR Vbeta repertoire, the associated Valpha repertoire specific for the NP(366-374)/D(b) ligand is quite diverse. Nonetheless, certain public and conserved CDR3alpha clonotypes with distinct molecular signatures were identified. Pairing of public Valpha and Vbeta domains creates an alphabeta TCR heterodimer that binds efficiently to the NP(366-374)/D(b) ligand and stimulates T cell activation. In contrast, private TCRs, each comprising a distinct alpha chain paired with the same public beta chain, interact very differently. Molecular dynamics simulation reveals that the conformation and mobility of the shared Vbeta CDR loops are governed largely by the associated Valpha domains. These results provide insight into molecular principles regarding public versus private TCRs linked to immune surveillance after infection with influenza A virus.

Characterization of the dynamics of an essential helix in the U1A protein by time-resolved fluorescence measurements.

The RNA recognition motif (RRM), one of the most common RNA-binding domains, recognizes single-stranded RNA. A C-terminal helix that undergoes conformational changes upon binding is often an important contributor to RNA recognition. The N-terminal RRM of the U1A protein contains a C-terminal helix (helix C) that interacts with the RNA-binding surface of a beta-sheet in the free protein (closed conformation), but is directed away from this beta-sheet in the complex with RNA (open conformation). The dynamics of helix C in the free protein have been proposed to contribute to binding affinity and specificity. We report here a direct investigation of the dynamics of helix C in the free U1A protein on the nanosecond time scale using time-resolved fluorescence anisotropy. The results indicate that helix C is dynamic on a 2-3 ns time scale within a 20 degrees range of motion. Steady-state fluorescence experiments and molecular dynamics simulations suggest that the dynamical motion of helix C occurs within the closed conformation. Mutation of a residue on the beta-sheet that contacts helix C in the closed conformation dramatically destabilizes the complex (Phe56Ala) and alters the steady-state fluorescence, but not the time-resolved fluorescence anisotropy, of a Trp in helix C. Mutation of Asp90 in the hinge region between helix C and the remainder of the protein to Ala or Gly subtly alters the dynamics of the U1A protein and destabilizes the complex. Together these results show that helix C maintains a dynamic closed conformation that is stable to these targeted protein modifications and does not equilibrate with the open conformation on the nanosecond time scale.

Identification of an aminoacridine derivative that binds to RNA tetraloops.

RNA folds into diverse structures that form unique targets for small molecules and thus provide significant potential for controlling biological processes involving RNA with small-molecule ligands. We are investigating molecular recognition of tetraloop RNA by small molecules. RNA tetraloops are four-nucleotide stem loops with unusual stability that are involved in biological processes involving RNA by forming binding sites for proteins and other RNAs. We have sequentially used the docking programs DOCK and AutoDock to screen 1990 small molecules in the NCI diversity set to identify molecules selective for RNA tetraloops over double-stranded RNA. The compounds predicted to bind to tetraloop RNA were evaluated for binding RNA tetraloops using 1H NMR spectroscopy and fluorescence techniques. An aminoacridine derivative (AD2) was identified that binds to a GAAA tetraloop in a 2:1 ratio with dissociation constants of 1.0 and 4.0 microM. AD2 binds with approximately 20-fold and 9-fold higher affinity to tetraloop RNA than to double- and single-stranded RNAs, respectively.

Molecular Dynamics-Markov State Model of Protein Ligand Binding and Allostery in CRIB-PDZ: Conformational Selection and Induced Fit.

Conformational selection and induced fit are well-known contributors to ligand binding and allosteric effects in proteins. Molecular dynamics (MD) simulations now enable the theoretical study of protein-ligand binding in terms of ensembles of interconverting microstates and the population shifts characteristic of "dynamical allostery." Here we investigate protein-ligand binding and allostery based on a Markov state model (MSM) with states and rates obtained from all-atom MD simulations. As an exemplary case, we consider the single domain protein par-6 PDZ with and without ligand and allosteric effector. This is one of the smallest proteins in which allostery has been experimentally observed. In spite of the increased complexity intrinsic to a statistical ensemble perspective, we find that conformational selection and induced fit mechanisms can be readily identified in the analysis. In the nonallosteric pathway, MD-MSM shows that PDZ binds ligand via conformational selection. However, the allosteric pathway requires an activation step that involves a conformational change induced by the allosteric effector Cdc42. Once in the allosterically activated state, we find that ligand binding can proceed by conformational selection. Our MD-MSM model predicts that allostery in this and possibly other systems involves both induced fit and conformational selection, not just one or the other.

Evolutionary Covariance Combined with Molecular Dynamics Predicts a Framework for Allostery in the MutS DNA Mismatch Repair Protein.

Mismatch repair (MMR) is an essential, evolutionarily conserved pathway that maintains genome stability by correcting base-pairing errors in DNA. Here we examine the sequence and structure of MutS MMR protein to decipher the amino acid framework underlying its two key activities-recognizing mismatches in DNA and using ATP to initiate repair. Statistical coupling analysis (SCA) identified a network (sector) of coevolved amino acids in the MutS protein family. The potential functional significance of this SCA sector was assessed by performing molecular dynamics (MD) simulations for alanine mutants of the top 5% of 160 residues in the distribution, and control nonsector residues. The effects on three independent metrics were monitored: (i) MutS domain conformational dynamics, (ii) hydrogen bonding between MutS and DNA/ATP, and (iii) relative ATP binding free energy. Each measure revealed that sector residues contribute more substantively to MutS structure-function than nonsector residues. Notably, sector mutations disrupted MutS contacts with DNA and/or ATP from a distance via contiguous pathways and correlated motions, supporting the idea that SCA can identify amino acid networks underlying allosteric communication. The combined SCA/MD approach yielded novel, experimentally testable hypotheses for unknown roles of many residues distributed across MutS, including some implicated in Lynch cancer syndrome.

The ABCs of molecular dynamics simulations on B-DNA, circa 2012.

This article provides a retrospective on the ABC initiative in the area of all-atom molecular dynamics (MD) simulations including explicit solvent on all tetranucleotide steps of duplex B-form DNA duplex, ca. 2012. The ABC consortium has completed two phases of simulations, the most current being a set of 50-100 trajectories based on the AMBER ff99 force field together with the parmbsc0 modification. Some general perspectives on the field of MD on DNA and sequence effects on DNA structure are provided, followed by an overview our MD results, including a detailed comparison of the ff99/parmbsc0 results with crystal and NMR structures available for d(CGCGAATTCGCG). Some projects inspired by or related to the ABC initiative and database are also reviewed, including methods for the trajectory analyses, informatics of dealing with the large database of results, compressions of trajectories for efficacy of distribution, DNA solvation by water and ions, parameterization of coarse-grained models with applications and gene finding and genome annotation.

Studies of base pair sequence effects on DNA solvation based on all-atom molecular dynamics simulations.

Detailed analyses of the sequence-dependent solvation and ion atmosphere of DNA are presented based on molecular dynamics (MD) simulations on all the 136 unique tetranucleotide steps obtained by the ABC consortium using the AMBER suite of programs. Significant sequence effects on solvation and ion localization were observed in these simulations. The results were compared to essentially all known experimental data on the subject. Proximity analysis was employed to highlight the sequence dependent differences in solvation and ion localization properties in the grooves of DNA. Comparison of the MD-calculated DNA structure with canonical A- and B-forms supports the idea that the G/C-rich sequences are closer to canonical A- than B-form structures, while the reverse is true for the poly A sequences, with the exception of the alternating ATAT sequence. Analysis of hydration density maps reveals that the flexibility of solute molecule has a significant effect on the nature of observed hydration. Energetic analysis of solute-solvent interactions based on proximity analysis of solvent reveals that the GC or CG base pairs interact more strongly with water molecules in the minor groove of DNA that the AT or TA base pairs, while the interactions of the AT or TA pairs in the major groove are stronger than those of the GC or CG pairs. Computation of solvent-accessible surface area of the nucleotide units in the simulated trajectories reveals that the similarity with results derived from analysis of a database of crystallographic structures is excellent. The MD trajectories tend to follow Manning's counterion condensation theory, presenting a region of condensed counterions within a radius of about 17 A from the DNA surface independent of sequence. The GC and CG pairs tend to associate with cations in the major groove of the DNA structure to a greater extent than the AT and TA pairs. Cation association is more frequent in the minor groove of AT than the GC pairs. In general, the observed water and ion atmosphere around the DNA sequences is the MD simulation is in good agreement with experimental observations.

U1A protein-stem loop 2 RNA recognition: prediction of structural differences from protein mutations.

Molecular dynamics (MD) simulations were carried out to compare the free and bound structures of wild type U1A protein with several Phe56 mutant U1A proteins that bind the target stem loop 2 (SL2) RNA with a range of affinities. The simulations indicate the free U1A protein is more flexible than the U1A-RNA complex for both wild type and Phe56 mutant systems. A complete analysis of the hydrogen-bonding (HB) and non-bonded (VDW) interactions over the course of the MD simulations suggested that changes in the interactions in the free U1A protein caused by the Phe56Ala and Phe56Leu mutations may stabilize the helical character in loop 3, and contribute to the weak binding of these proteins to SL2 RNA. Compared with wild type, changes in HB and VDW interactions in Phe56 mutants of the free U1A protein are global, and include differences in ß-sheet, loop 1 and loop 3 interactions. In the U1A-RNA complex, the Phe56Ala mutation leads to a series of differences in interactions that resonate through the complex, while the Phe56Leu and Phe56Trp mutations cause local differences around the site of mutation. The long-range networks of interactions identified in the simulations suggest that direct interactions and dynamic processes in both the free and bound forms contribute to complex stability.

A study of collective atomic fluctuations and cooperativity in the U1A-RNA complex based on molecular dynamics simulations.

Cooperative interactions play an important role in recognition and binding in macromolecular systems. In this study, we find that cross-correlated atomic fluctuations can be used to identify cooperative networks in a protein-RNA system. The dynamics of the RRM-containing protein U1A-stem loop 2 RNA complex have been calculated theoretically from a 10 ns molecular dynamics (MD) simulation. The simulation was analyzed by calculating the covariance matrix of all atomic fluctuations. These matrix elements are then presented in the form of a two-dimensional grid, which displays fluctuations on a per residue basis. The results indicate the presence of strong, selective cross-correlated fluctuations throughout the RRM in U1A-RNA. The atomic fluctuations correspond well with previous biophysical studies in which a multiplicity of cooperative networks have been reported and indicate that the various networks identified in separate individual experiments are fluctuationally correlated into a hyper-network encompassing most of the RRM. The calculated results also correspond well with independent results from a statistical covariance analysis of 330 aligned RRM sequences. This method has significant implications as a predictive tool regarding cooperativity in the protein-nucleic acid recognition process.

Structural bioinformatics of DNA: a web-based tool for the analysis of molecular dynamics results and structure prediction.

UNLABELLED: We report here the release of a web-based tool (MDDNA) to study and model the fine structural details of DNA on the basis of data extracted from a set of molecular dynamics (MD) trajectories of DNA sequences involving all the unique tetranucleotides. The dynamic web interface can be employed to analyze the first neighbor sequence context effects on the 10 unique dinucleotide steps of DNA. Functionality is included to build all atom models of any user-defined sequence based on the MD results. The backend of this interface is a relational database storing the conformational details of DNA obtained in 39 different MD simulation trajectories comprising all the 136 unique tetranucleotide steps. Examples of the use of this data to predict DNA structures are included. AVAILABILITY: http://humphry.chem.wesleyan.edu:8080/MDDNA. SUPPLEMENTARY INFORMATION: Supplementary data including color figures are available at Bioinformatics online.