Molecular flexibility in ab initio drug docking to DNA: binding-site and binding-mode transitions in all-atom Monte Carlo simulations

The dynamics of biological processes depend on the structure and flexibility of the interacting molecules. In particular, the conformational diversity of DNA allows for large deformations upon binding. Drug–DNA interactions are of high pharmaceutical interest since the mode of action of anticancer, antiviral, antibacterial and other drugs is directly associated with their binding to DNA. A reliable prediction of drug–DNA binding at the atomic level by molecular docking methods provides the basis for the design of new drug compounds. Here, we propose a novel Monte Carlo (MC) algorithm for drug–DNA docking that accounts for the molecular flexibility of both constituents and samples the docking geometry without any prior binding-site selection. The binding of the antimalarial drug methylene blue at the DNA minor groove with a preference of binding to AT-rich over GC-rich base sequences is obtained in MC simulations in accordance with experimental data. In addition, the transition between two drug–DNA-binding modes, intercalation and minor-groove binding, has been achieved in dependence on the DNA base sequence. The reliable ab initio prediction of drug–DNA binding achieved by our new MC docking algorithm is an important step towards a realistic description of the structure and dynamics of molecular recognition in biological systems

Control of DNA minor groove width and Fis protein binding by the purine 2-amino group.

The width of the DNA minor groove varies with sequence and can be a major determinant of DNA shape recognition by proteins. For example, the minor groove within the center of the Fis-DNA complex narrows to about half the mean minor groove width of canonical B-form DNA to fit onto the protein surface. G/C base pairs within this segment, which is not contacted by the Fis protein, reduce binding affinities up to 2000-fold over A/T-rich sequences. We show here through multiple X-ray structures and binding properties of Fis-DNA complexes containing base analogs that the 2-amino group on guanine is the primary molecular determinant controlling minor groove widths. Molecular dynamics simulations of free-DNA targets with canonical and modified bases further demonstrate that sequence-dependent narrowing of minor groove widths is modulated almost entirely by the presence of purine 2-amino groups. We also provide evidence that protein-mediated phosphate neutralization facilitates minor groove compression and is particularly important for binding to non-optimally shaped DNA duplexes

Experimental maps of DNA structure at nucleotide resolution distinguish intrinsic from protein-induced DNA deformations

Recognition of DNA by proteins depends on DNA sequence and structure. Often unanswered is whether the structure of naked DNA persists in a protein–DNA complex, or whether protein binding changes DNA shape. While X-ray structures of protein–DNA complexes are numerous, the structure of naked cognate DNA is seldom available experimentally. We present here an experimental and computational analysis pipeline that uses hydroxyl radical cleavage to map, at single-nucleotide resolution, DNA minor groove width, a recognition feature widely exploited by proteins. For 11 protein–DNA complexes, we compared experimental maps of naked DNA minor groove width with minor groove width measured from X-ray co-crystal structures. Seven sites had similar minor groove widths as naked DNA and when bound to protein. For four sites, part of the DNA in the complex had the same structure as naked DNA, and part changed structure upon protein binding. We compared the experimental map with minor groove patterns of DNA predicted by two computational approaches, DNAshape and ORChID2, and found good but not perfect concordance with both. This experimental approach will be useful in mapping structures of DNA sequences for which high-resolution structural data are unavailable. This approach allows probing of protein family-dependent readout mechanisms.National Institutes of Health [R01GM106056 to R.R., T.D.T.; U54CA121852 in part to T.D.T.]; Boston University Undergraduate Research Opportunities Program [Faculty Matching Grants to D.O. and Y.J.]; USC Graduate School [Research Enhancement Fellowship and Manning Endowed Fellowship to T.P.C.]. R.R. is an Alfred P. Sloan Research Fellow. Funding for open access charge: Boston University. (R01GM106056 - National Institutes of Health; U54CA121852 - National Institutes of Health; Boston University Undergraduate Research Opportunities Program; USC Graduate School; Boston University)https://academic.oup.com/nar/article/46/5/2636/4829691?searchresult=1https://academic.oup.com/nar/article/46/5/2636/4829691?searchresult=1Published versio

Transcription factor family‐specific DNA shape readout revealed by quantitative specificity models

Transcription factors (TFs) achieve DNA-binding specificity through contacts with functional groups of bases (base readout) and readout of structural properties of the double helix (shape readout). Currently, it remains unclear whether DNA shape readout is utilized by only a few selected TF families, or whether this mechanism is used extensively by most TF families. We resequenced data from previously published HT-SELEX experiments, the most extensive mammalian TF–DNA binding data available to date. Using these data, we demonstrated the contributions of DNA shape readout across diverse TF families and its importance in core motif-flanking regions. Statistical machine-learning models combined with feature-selection techniques helped to reveal the nucleotide position-dependent DNA shape readout in TF-binding sites and the TF family-specific position dependence. Based on these results, we proposed novel DNA shape logos to visualize the DNA shape preferences of TFs. Overall, this work suggests a way of obtaining mechanistic insights into TF–DNA binding without relying on experimentally solved all-atom structures

Systematic prediction of DNA shape changes due to CpG methylation explains epigenetic effects on protein–DNA binding

Background DNA shape analysis has demonstrated the potential to reveal structure-based mechanisms of protein–DNA binding. However, information about the influence of chemical modification of DNA is limited. Cytosine methylation, the most frequent modification, represents the addition of a methyl group at the major groove edge of the cytosine base. In mammalian genomes, cytosine methylation most frequently occurs at CpG dinucleotides. In addition to changing the chemical signature of C/G base pairs, cytosine methylation can affect DNA structure. Since the original discovery of DNA methylation, major efforts have been made to understand its effect from a sequence perspective. Compared to unmethylated DNA, however, little structural information is available for methylated DNA, due to the limited number of experimentally determined structures. To achieve a better mechanistic understanding of the effect of CpG methylation on local DNA structure, we developed a high-throughput method, methyl-DNAshape, for predicting the effect of cytosine methylation on DNA shape. Results Using our new method, we found that CpG methylation significantly altered local DNA shape. Four DNA shape features—helix twist, minor groove width, propeller twist, and roll—were considered in this analysis. Distinct distributions of effect size were observed for different features. Roll and propeller twist were the DNA shape features most strongly affected by CpG methylation with an effect size depending on the local sequence context. Methylation-induced changes in DNA shape were predictive of the measured rate of cleavage by DNase I and suggest a possible mechanism for some of the methylation sensitivities that were recently observed for human Pbx-Hox complexes. Conclusions CpG methylation is an important epigenetic mark in the mammalian genome. Understanding its role in protein–DNA recognition can further our knowledge of gene regulation. Our high-throughput methyl-DNAshape method can be used to predict the effect of cytosine methylation on DNA shape and its subsequent influence on protein–DNA interactions. This approach overcomes the limited availability of experimental DNA structures that contain 5-methylcytosine

Analysis of Genetic Variation Indicates DNA Shape Involvement in Purifying Selection.

Noncoding DNA sequences, which play various roles in gene expression and regulation, are under evolutionary pressure. Gene regulation requires specific protein-DNA binding events, and our previous studies showed that both DNA sequence and shape readout are employed by transcription factors (TFs) to achieve DNA binding specificity. By investigating the shape-disrupting properties of single nucleotide polymorphisms (SNPs) in human regulatory regions, we established a link between disruptive local DNA shape changes and loss of specific TF binding. Furthermore, we described cases where disease-associated SNPs may alter TF binding through DNA shape changes. This link led us to hypothesize that local DNA shape within and around TF binding sites is under selection pressure. To verify this hypothesis, we analyzed SNP data derived from 216 natural strains of Drosophila melanogaster. Comparing SNPs located in functional and nonfunctional regions within experimentally validated cis-regulatory modules (CRMs) from D. melanogaster that are active in the blastoderm stage of development, we found that SNPs within functional regions tended to cause smaller DNA shape variations. Furthermore, SNPs with higher minor allele frequency were more likely to result in smaller DNA shape variations. The same analysis based on a large number of SNPs in putative CRMs of the D. melanogaster genome derived from DNase I accessibility data confirmed these observations. Taken together, our results indicate that common SNPs in functional regions tend to maintain DNA shape, whereas shape-disrupting SNPs are more likely to be eliminated through purifying selection

Genome-wide features of neuroendocrine regulation in Drosophila by the basic helix-loop-helix transcription factor DIMMED.

Neuroendocrine (NE) cells use large dense core vesi-cles (LDCVs) to traffic, process, store and secrete neuropeptide hormones through the regulated secre-tory pathway. The dimmed (DIMM) basic helix-loop-helix transcription factor of Drosophila controls the level of regulated secretory activity in NE cells. To pursue its mechanisms, we have performed two in-dependent genome-wide analyses of DIMM’s activi-ties: (i) in vivo chromatin immunoprecipitation (ChIP) to define genomic sites of DIMM occupancy and (ii) deep sequencing of purified DIMM neurons to char-acterize their transcriptional profile. By this com-bined approach, we showed that DIMM binds to con-served E-boxes in enhancers of 212 genes whose expression is enriched in DIMM-expressing NE cells. DIMM binds preferentially to certain E-boxes within first introns of specific gene isoforms. Statistical ma-chine learning revealed that flanking regions of puta-tive DIMM binding sites contribute to its DNA binding specificity. DIMM’s transcriptional repertoire features at least 20 LDCV constituents. In addition, DIMM no-tably targets the pro-secretory transcription factor, creb-A, but significantly, DIMM does not target any neuropeptide genes. DIMM therefore prescribes the scale of secretory activity in NE neurons, by a sys-tematic control of both proximal and distal points in the regulated secretory pathway

Genome information processing by the INO80 chromatin remodeler positions nucleosomes [preprint]

The fundamental molecular determinants by which ATP-dependent chromatin remodelers organize nucleosomes across eukaryotic genomes remain largely elusive. Here, chromatin reconstitutions on physiological, whole-genome templates reveal how remodelers read and translate genomic information into nucleosome positions. Using the yeast genome and the multi-subunit INO80 remodeler as a paradigm, we identify DNA shape/mechanics encoded signature motifs as sufficient for nucleosome positioning and distinct from known DNA sequence preferences of histones. INO80 processes such information through an allosteric interplay between its core- and Arp8-modules that probes mechanical properties of nucleosomal and linker DNA. At promoters, INO80 integrates this readout of DNA shape/mechanics with a readout of co-evolved sequence motifs via interaction with general regulatory factors bound to these motifs. Our findings establish a molecular mechanism for robust and yet adjustable +1 nucleosome positioning and, more generally, remodelers as information processing hubs that enable active organization and allosteric regulation of the first level of chromatin

Simulation of structure formation and ligand binding of nucleic acids in the space of collective and internal variables

# Inhaltsverzeichnis Titel und Inhalt 1. Einleitung 1 2. Struktur und Funktion der Nukleinsäuren 4 2.1 Chemischer Aufbau und Modelle der Raumstruktur 4 2.2 Strukturelle Analyse von Nukleinsäuren 7 2.3 Ergebnisse experimenteller Methoden 12 2.4 Ergebnisse aus Theorie und Simulationen 15 2.5 Komplexbildung mit Liganden und Proteinen 19 2.6 Bedeutung und Anwendung der Erkenntnisse 22 3. Theoretische Methoden zur Simulation molekularer Strukturen 23 3.1 Molekulare Modelle 23 3.2 Simulationstechniken 33 4. Monte-Carlo-Algorithmus zur Simulation von Nukleinsäuren 46 4.1 Definition des molekularen Modells 46 4.2 Programmtechnische Implementierung 64 5. Monte-Carlo-Simulationen von DNA-Dekameren mit alternierenden AT und GC Basensequenzen 72 5.1 Equilibrierung der MC-Simulationen 73 5.2 Unabhängigkeit von der Startkonfiguration 82 5.3 Sequenzspezifische Konformation und Flexibilität von DNA-Dekameren mit alternierenden AT und GC Basensequenzen 84 5.4 Kondensation der expliziten Gegenionen 89 5.5 Diskussion der Resultate, Teil I 91 6. Sequenz- und Salzeffekte der Methylenblau-DNA-Bindung 98 6.1 Sequenzspezifische Bindung von Methylenblau und DNA-Dekameren mit alternierenden AT und GC Basensequenzen 98 6.2 Salzabhängigkeit der Methylenblau-DNA-Bindung 107 6.3 Diskussion der Resultate, Teil II 110 7. Monte-Carlo-Simulationen von Methylenblau-DNA-Komplexen 113 7.1 Komplexbildung durch Interkalation des Metylenblau 114 7.2 Komplexbildung durch Bindung des Metylenblau in den Furchen 128 7.3 Diskussion der Resultate, Teil III 137 8. Zusammenfassung 140 9. Summary 144 Literaturverzeichnis iEin im Raum kollektiver und innerer Variablen definierter Monte- Carlo(MC)-Algorithmus für Nukleinsäuren wird vorgestellt und erstmals angewendet. Mit diesem MC-Algorithmus gewonnene Resultate über die Sequenzspezifität der Konformation und Flexibilität von Nukleinsäure-Dekameren und Methylenblau(MB)- DNA-Komplexen werden diskutiert. Die Leistungsfähigkeit des Algorithmus wird durch Untersuchungen der Equilibrierung und der Abhängigkeit von der Startkonfiguration der MC-Simulationen bewertet. Ergänzt werden die MC-Simulationen durch Energieminimierungen von MB-DNA-Komplexen und Energiebewertungen der Konformationen dieser Komplexe durch eine Kontinuumsbehandlung elektrostatischer Lösungsmitteleffekte. Die Equilibrierung der MC-Simulationen in einer respektablen Zeit wird auf der Grundlage mittlerer Energien und mittlerer struktureller Parameter bewertet. Die Resultate der MC-Simulationen können als unabhängig von der Startkonfiguration betrachtet werden. Die Mittelwerte und Fluktuationen struktureller Parameter zeigen eine unterschiedlich stark ausgeprägte Sequenzspezifität. Neben den Konformationen der Nukleinsäuren werden die Bewegungen der expliziten Gegenionen statistisch analysiert. Die höhere Aufenthaltswahrscheinlichkeit der Ionen in der Umgebung der Dekamere entspricht qualitativ der erwarteten Kondensation expliziter Gegenionen an der DNA-Oberfläche. Für die medizinisch bedeutsame Methylenblau-DNA-Bindung werden durch Energieminimierung MB-DNA-Komplexe generiert, die die jeweils energetisch bevorzugte Bindung in den drei möglichen Bindungsmodi repräsentieren. Bei der Auswahl der MB-DNA-Komplexe nach dem Kriterium niedrigster Energie wurden elektrostatische Lösungsmitteleffekte durch eine Kontinuumsbehandlung mit der FDPB-Methode berücksichtigt. Salzeffekte der MB- DNA-Bindung werden durch Abschätzung von Bindungsenergien der Komplexe untersucht. MC-Simulationen der MB-DNA-Komplexe ermöglichen erstmals detaillierte Erkenntnisse über die Dynamik und Flexibilität einer DNA- Liganden-Bindung. In dem MC-Algorithmus werden die Bewegungen des Liganden relativ zur Target-DNA durch kollektive und innere MC-Variablen des MB beschrieben. Die symmetrischen und gauche Interkalationen des MB erweisen sich in den MC-Simulationen als stabil. Die Zuckerfaltungen der der Interkalationstasche benachbarten Nukleotide zeigen eine Sequenzspezifität für Interkalationen in YpR- und RpY-Basenschritte. Bei einer Bindung des MB in der kleinen Furche des AT alternierenden Dekamers ereignen sich wiederholte Übergänge zwischen alternativen Bindungsstellen. Die diskreten Bindungsstellen werden durch eine Orientierung des MB mit aus der Furche weisenden Methylgruppen und jeweils in der Ebene eines Basenpaares liegendem Schwefel- und zentralem Stickstoffatom charakterisiert. Die MC-Simulationen der MB-DNA- Komplexe identifizieren stabile Bindungszustände, beschreiben Übergänge zwischen alternativen Bindungsstellen des MB und eine Sequenzspezifität der durch die Bindung des MB verursachten Deformationen der Target-Nukleinsäuren. Die Resultate über die Flexibilität der MB-DNA-Komplexe tragen zum Verständnis der Ursachen und der Entstehung der Bindung bei. Die Daten ermöglichen zudem eine detailliertere Interpretation experimenteller Untersuchungen.A Monte Carlo (MC) algorithm for nucleic acids, defined in the space of collective and internal variables, is presented. First results on sequence- specific conformation and flexibility of nucleic acid decamers and methylene blue (MB)-DNA complexes are discussed. The performance and efficiency of the MC algorithm was investigated by analyzing the equilibration of the systems and the effects of the starting configurations on the simulation results. The MC studies are complemented by energy minimizations of MB-DNA complexes and by evaluating the energy of these complexes using a continuum treatment of solvent electrostatic effects. Equilibrations of the MC simulations are assessed on the basis of averaged energy and structural parameters. It is shown that the results of MC simulations do not depend on starting configuration. The average values and fluctuations of structural parameters show a different sequence-specificity. The movements of the explicit counterions have been also analyzed statistically. The higher occupancy of ions in the surrounding of the decamers fits qualitatively with the expected counterion condensation at the DNA surface. Results on the medically important methylene blue (MB)-DNA binding, obtained by energy minimizations, are discussed. Lowest-energy MB-DNA complex structures, representing the three different binding modes, were derived. The MB-DNA complexes were selected following the criterion of lowest total energy, taking into account electrostatic solvent effects by a continuum treatment using the FDPB method. Salt effects on the MB-DNA binding have been studied by estimating the binding energy as a function of monovalent salt concentration. MC simulations of MB- DNA complexes result in data that allow for the first time a thorough understanding of the dynamical properties of DNA-ligand binding. In addition to the degrees of freedom of flexible DNA, the MC algorithm uses collective and internal variables for describing the ligand movement relative to the target-DNA. The results of MC simulations show that both the symmetric and the gauche intercalations are stable. The position and orientation of MB in the intercalation pocket are less variable in the case of a symmetric intercalation compared to a gauche intercalation. Sugar puckering modes of the nucleotides flanking the intercalation site are shown to be sequence-specific as they differ for intercalations at 5'-YpR-3' and 5'-RpY-3' sites. Minor groove binding of MB to the AT alternating decamer shows frequent transitions between alternative binding sites. The discrete binding sites of MB are characterized by the methyl groups facing outside the minor groove and by the sulfur and the central nitrogen atom of MB lying approximately within a base- pair plane. The MC simulations of MB-DNA complexes identify stable binding states. They describe transitions between alternative binding sites of MB and sequence-specific deformations of the target nucleic acids upon MB binding. The results on the flexibility of MB-DNA complexes contribute to a deeper understanding of ligand binding and could assist in detailed interpretation of experimental data