μABC: a systematic microsecond molecular dynamics study of tetranucleotide sequence effects in B-DNA

The impact of sequence periodicity on DNA mechanics: investigating the origin of A-tract's curvature

Periodic sequences in phase with DNA helical shape are prevalent in genomes due to their capacity to modulate DNA elasticity on a global scale. However, how this occurs is not well understood. We use all-atom molecular dynamics simulations on 40 bp DNA fragments to assess the effect of periodicity on bending, twisting, and stretch elasticity. We observe that DNA static curvature is the mechanical parameter most influenced by periodicity, with A-tract sequences having the greatest effect. A-tracts generate global curvature by bending in distinct directions (minor groove and backbones) that complement the bending of the rest of DNA, which predominantly is towards the major groove. Even if A-tracts are rigid at the local scale, these small bends integrate with the greater bends from the sequences between, producing an amplifying effect. As a result, our findings support a 'delocalized bend' model in which the A-tract operates as an 'adaptable mechanical part'. By understanding how global curvature emerges from local fluctuations, we reconcile previous contradictory theories and open an avenue for manipulating DNA mechanics through sequence design.

Flexible RNA aptamers as inhibitors of Bacillus anthracis ribosomal protein S8: Insights from molecular dynamics simulations

Bacillus anthracis, the causative agent of anthrax, poses a substantial threat to public health and national security, and is recognized as a potential bioweapon due to its capacity to form resilient spores with enduring viability. Inhalation or ingestion of even minute quantities of aerosolized spores can lead to widespread illness and fatalities, underscoring the formidable lethality of the bacterium. With an untreated mortality rate of 100%, Bacillus anthracis is a disconcerting candidate for bioterrorism. In response to this critical scenario, we employed state-of-the-art computational tools to conceive and characterize flexible RNA aptamer therapeutics tailored for anthrax. The foundational structure of the flexible RNA aptamers was designed by removing the C2'-C3' in each nucleotide unit. Leveraging the crystal structure of Bacillus anthracis ribosomal protein S8 complexed with an RNA aptamer, we explored the structural, dynamic, and energetic aspects of the modified RNA aptamer - S8 protein complexes through extensive all-atom explicit-solvent molecular dynamics simulations (400 ns, 3 replicas each), followed by drawing comparisons to the control system. Our findings demonstrate the enhanced binding competencies of the flexible RNA aptamers to the S8 protein via better shape complementarity and improved H-bond network compared to the control RNA aptamer. This research offers valuable insights into the development of RNA aptamer therapeutics targeting Bacillus anthracis, paving the way for innovative strategies to mitigate the impact of this formidable pathogen.

Navigating the complexity of p53-DNA binding: implications for cancer therapy

Abstract

The tumor suppressor protein p53, a transcription factor playing a key role in cancer prevention, interacts with DNA as its primary means of determining cell fate in the event of DNA damage. When it becomes mutated, it opens damaged cells to the possibility of reproducing unchecked, which can lead to formation of cancerous tumors. Despite its critical role, therapies at the molecular level to restore p53 native function remain elusive, due to its complex nature. Nevertheless, considerable information has been amassed, and new means of investigating the problem have become available.

Objectives

We consider structural, biophysical, and bioinformatic insights and their implications for the role of direct and indirect readout and how they contribute to binding site recognition, particularly those of low consensus. We then pivot to consider advances in computational approaches to drug discovery.

Materials and methods

We have conducted a review of recent literature pertinent to the p53 protein.

Results

Considerable literature corroborates the idea that p53 is a complex allosteric protein that discriminates its binding sites not only via consensus sequence through direct H-bond contacts, but also a complex combination of factors involving the flexibility of the binding site. New computational methods have emerged capable of capturing such information, which can then be utilized as input to machine learning algorithms towards the goal of more intelligent and efficient de novo allosteric drug design.

Conclusions

Recent improvements in machine learning coupled with graph theory and sector analysis hold promise for advances to more intelligently design allosteric effectors that may be able to restore native p53-DNA binding activity to mutant proteins.

Clinical relevance

The ideas brought to light by this review constitute a significant advance that can be applied to ongoing biophysical studies of drugs for p53, paving the way for the continued development of new methodologies for allosteric drugs. Our discoveries hold promise to provide molecular therapeutics which restore p53 native activity, thereby offering new insights for cancer therapies.

Graphical Abstract

Structural representation of the p53 DBD (PDBID 1TUP). DNA consensus sequence is shown in gray, and the protein is shown in blue. Red beads indicate hotspot residue mutations, green beads represent DNA interacting residues, and yellow beads represent both.

CGeNArate: a sequence-dependent coarse-grained model of DNA for accurate atomistic MD simulations of kb-long duplexes

We present CGeNArate, a new model for molecular dynamics simulations of very long segments of B-DNA in the context of biotechnological or chromatin studies. The developed method uses a coarse-grained Hamiltonian with trajectories that are back-mapped to the atomistic resolution level with extreme accuracy by means of Machine Learning Approaches. The method is sequence-dependent and reproduces very well not only local, but also global physical properties of DNA. The efficiency of the method allows us to recover with a reduced computational effort high-quality atomic-resolution ensembles of segments containing many kilobases of DNA, entering into the gene range or even the entire DNA of certain cellular organelles.

A commentary on the ABC consortium and its impact on the development of mesoscopic models of DNA

In this commentary, it is presented how the Ascona B-DNA (ABC) consortium analyses of the DNA structure and deformability had a great influence in the development of mesoscopic models of DNA. The generation of databases using molecular dynamics ensembles to describe the DNA flexibility, allowed mesoscopic models to improve and become more accurate with a quality similar to that of all-atom MD simulations. All this will be translated in the future in the development of mesoscopic methods that could study and reproduce large biological systems such as chromatin structure, nucleosome arrangements, and protein recognition.

MD-DATA: the legacy of the ABC Consortium

The ABC Consortium has been generating nucleic-acids MD trajectories for more than 20 years. This brief comment highlights the importance of this data for the field, which triggered a number of critical studies, including force-field parameterization and development of new coarse-grained and mesoscopic models. With the world entering into a new data-driven era led by artificial intelligence, where data is becoming more essential than ever, the ABC initiative is leading the way for nucleic acid flexibility.

Structural dynamics of therapeutic nucleic acids with phosphorothioate backbone modifications

Antisense oligonucleotides (ASOs) offer ground-breaking possibilities for selective pharmacological intervention for any gene product-related disease. Therapeutic ASOs contain extensive chemical modifications that improve stability to enzymatic cleavage and modulate binding affinity relative to natural RNA/DNA. Molecular dynamics (MD) simulation can provide valuable insights into how such modifications affect ASO conformational sampling and target binding. However, force field parameters for chemically modified nucleic acids (NAs) are still underdeveloped. To bridge this gap, we developed parameters to allow simulations of ASOs with the widely applied phosphorothioate (PS) backbone modification, and validated these in extensive all-atom MD simulations of relevant PS-modified NA systems representing B-DNA, RNA, and DNA/RNA hybrid duplex structures. Compared to the corresponding natural NAs, single PS substitutions had marginal effects on the ordered DNA/RNA duplex, whereas substantial effects of phosphorothioation were observed in single-stranded RNA and B-DNA, corroborated by the experimentally derived structure data. We find that PS-modified NAs shift between high and low twist states, which could affect target recognition and protein interactions for phosphorothioated oligonucleotides. Furthermore, conformational sampling was markedly altered in the PS-modified ssRNA system compared to that of the natural oligonucleotide, indicating sequence-dependent effects on conformational preference that may in turn influence duplex formation.

Multiscale simulations of DNA from electrons to nucleosomes: 22 years of the Ascona B-DNA Consortium

This commentary provides a retrospective on the Ascona B-DNA Consortium (ABC) initiative and on the conference held in April 2023 at Ascona, Switzerland, where we celebrated 22 years of the consortium, sharing the latest advances in simulations and experiments of the effects of sequence on the mechanical properties of DNA from electrons to nucleosomes.

Identification of potential anti-mucor agents by targeting endothelial cell receptor glucose-regulated protein-78 using in silico approach

Mucormycosis is a fungal infection of the sinuses, brain and lungs that is the cause of approximately 50% mortality rate despite the available first-line therapy. Glucose-Regulated Protein 78 (GRP78) is already reported to be a novel host receptor that mediates invasion and damage of human endothelial cells by Rhizopus oryzae and Rhizopus delemar, the most common etiologic species of Mucorales. The expression of GRP78 is also regulated by the levels of iron and glucose in the blood. There are several antifungal drugs in the market but they pose a serious side effect to the vital organs of the body. Therefore, there is an immediate need to discover effective drug molecules having increased efficacy with no side effects. With the help of various computational tools, the current study was attempted to determine potential antimucor agents against GRP78. The receptor molecule GRP78 was screened against 8820 known drugs deposited in DrugBank library using high-throughput virtual screening method. Total top 10 compounds were selected based on the binding energies greater than the reference co-crystal molecule. Furthermore, molecular dynamic (MD) simulations using AMBER were performed to calculate the stability of the top-ranked compounds in the active site of GRP78. After extensive computational studies, we propose that two compounds (CID439153 and CID5289104) have inhibitory potency against mucormycosis and can serve as potential drugs that can form the basis of treating mucormycosis disease.Communicated by Ramaswamy H. Sarma.

Molecular Origin of Distinct Hydration Dynamics in Double Helical DNA and RNA Sequences

Water molecules are essential to determine the structure of nucleic acids and mediate their interactions with other biomolecules. Here, we characterize the hydration dynamics of analogous DNA and RNA double helices with unprecedented resolution and elucidate the molecular origin of their differences: first, the localization of the slowest hydration water molecules─in the minor groove in DNA, next to phosphates in RNA─and second, the markedly distinct hydration dynamics of the two phosphate oxygen atoms OR and OS in RNA. Using our Extended Jump Model for water reorientation, we assess the relative importance of previously proposed factors, including the local topography, water bridges, and the presence of ions. We show that the slow hydration dynamics at RNA OR sites is not due to bridging water molecules but is caused by both the larger excluded volume and the stronger initial H-bond next to OR, due to the different phosphate orientations in A-form double helical RNA.

Insights into elastic properties of coarse-grained DNA models: q-stiffness of cgDNA vs cgDNA

Coarse-grained models have emerged as valuable tools to simulate long DNA molecules while maintaining computational efficiency. These models aim at preserving interactions among coarse-grained variables in a manner that mirrors the underlying atomistic description. We explore here a method for testing coarse-grained vs all-atom models using stiffness matrices in Fourier space (q-stiffnesses), which are particularly suited to probe DNA elasticity at different length scales. We focus on a class of coarse-grained rigid base DNA models known as cgDNA and its most recent version, cgDNA+. Our analysis shows that while cgDNA+ closely follows the q-stiffnesses of the all-atom model, the original cgDNA shows some deviations for twist and bending variables, which are rather strong in the q → 0 (long length scale) limit. The consequence is that while both cgDNA and cgDNA+ give a suitable description of local elastic behavior, the former misses some effects that manifest themselves at longer length scales. In particular, cgDNA performs poorly on twist stiffness, with a value much lower than expected for long DNA molecules. Conversely, the all-atom and cgDNA+ twist are strongly length scale dependent: DNA is torsionally soft at a few base pair distances but becomes more rigid at distances of a few dozen base pairs. Our analysis shows that the bending persistence length in all-atom and cgDNA+ is somewhat overestimated.

Structural and dynamical aspect of DNA motif sequence specific binding of AP-1 transcription factor

Activator protein-1 (AP-1) comprises one of the largest and most evolutionary conserved families of ubiquitous eukaryotic transcription factors that act as a pioneer factor. Diversity in DNA binding interaction of AP-1 through a conserved basic-zipper (bZIP) domain directs in-depth understanding of how AP-1 achieves its DNA binding selectivity and consequently gene regulation specificity. Here, we address the structural and dynamical aspects of the DNA target recognition process of AP-1 using microsecond-long atomistic simulations based on the structure of the human AP-1 FosB/JunD bZIP-DNA complex. Our results show the unique role of DNA shape features in selective base specific interactions, characteristic ion population, and solvation properties of DNA grooves to form the motif sequence specific AP-1-DNA complex. The TpG step at the two terminals of the AP-1 site plays an important role in the structural adjustment of DNA by modifying the helical twist in the AP-1 bound state. We addressed the role of intrinsic motion of the bZIP domain in terms of opening and closing gripper motions of DNA binding helices, in target site recognition and binding of AP-1 factors. Our observations suggest that binding to the cognate motif in DNA is mainly accompanied with the precise adjustment of closing gripper motion of DNA binding helices of the bZIP domain.

Systematic Comparison of Atomistic Force Fields for the Mechanical Properties of Double-Stranded DNA

The response of double-stranded DNA to external mechanical stress plays a central role in its interactions with the protein machinery in the cell. Modern atomistic force fields have been shown to provide highly accurate predictions for the fine structural features of the duplex. In contrast, and despite their pivotal function, less attention has been devoted to the accuracy of the prediction of the elastic parameters. Several reports have addressed the flexibility of double-stranded DNA via all-atom molecular dynamics, yet the collected information is insufficient to have a clear understanding of the relative performance of the various force fields. In this work, we fill this gap by performing a systematic study in which several systems, characterized by different sequence contexts, are simulated with the most popular force fields within the AMBER family, bcs1 and OL15, as well as with CHARMM36. Analysis of our results, together with their comparison with previous work focused on bsc0, allows us to unveil the differences in the predicted rigidity between the newest force fields and suggests a roadmap to test their performance against experiments. In the case of the stretch modulus, we reconcile these differences, showing that a single mapping between sequence-dependent conformation and elasticity via the crookedness parameter captures simultaneously the results of all force fields, supporting the key role of crookedness in the mechanical response of double-stranded DNA.

Prediction and Control in DNA Nanotechnology

DNA nanotechnology is a rapidly developing field that uses DNA as a building material for nanoscale structures. Key to the field's development has been the ability to accurately describe the behavior of DNA nanostructures using simulations and other modeling techniques. In this Review, we present various aspects of prediction and control in DNA nanotechnology, including the various scales of molecular simulation, statistical mechanics, kinetic modeling, continuum mechanics, and other prediction methods. We also address the current uses of artificial intelligence and machine learning in DNA nanotechnology. We discuss how experiments and modeling are synergistically combined to provide control over device behavior, allowing scientists to design molecular structures and dynamic devices with confidence that they will function as intended. Finally, we identify processes and scenarios where DNA nanotechnology lacks sufficient prediction ability and suggest possible solutions to these weak areas.

Predicting DNA structure using a deep learning method

Understanding the mechanisms of protein-DNA binding is critical in comprehending gene regulation. Three-dimensional DNA structure, also described as DNA shape, plays a key role in these mechanisms. In this study, we present a deep learning-based method, Deep DNAshape, that fundamentally changes the current k-mer based high-throughput prediction of DNA shape features by accurately accounting for the influence of extended flanking regions, without the need for extensive molecular simulations or structural biology experiments. By using the Deep DNAshape method, DNA structural features can be predicted for any length and number of DNA sequences in a high-throughput manner, providing an understanding of the effects of flanking regions on DNA structure in a target region of a sequence. The Deep DNAshape method provides access to the influence of distant flanking regions on a region of interest. Our findings reveal that DNA shape readout mechanisms of a core target are quantitatively affected by flanking regions, including extended flanking regions, providing valuable insights into the detailed structural readout mechanisms of protein-DNA binding. Furthermore, when incorporated in machine learning models, the features generated by Deep DNAshape improve the model prediction accuracy. Collectively, Deep DNAshape can serve as versatile and powerful tool for diverse DNA structure-related studies.

Composition, physicochemical property and base periodicity for discriminating lncRNA and mRNA

Annotation of genome data with biological features is a challenging problem. One such problem deals with distinguishing lncRNA from mRNA. In this study, three groups of classification features, namely base periodicity, physicochemical property and nucleotide compositions were considered. We are attempting to propose a simple neural network model to obtain better results using judicious combination of the above said sequence features. Our approach uses balanced dataset, simple prediction model and use of limited features in distinguishing lncRNA and mRNA. Accordingly (a) two properties of base periodicity: peak power spectrum of the signal and noise-to-signal ratio (SNR) of this peak signal (b) three physicochemical properties: solvation, stacking and hydrogen-bonding energy and (c) all dinucleotides and trinucleotides compositions were used. Classification was performed by considering features independently followed by combining these properties for improvement. Classification metric was used to compare the result for seven eukaryotic organisms for various combinations of features. Nucleotide compositions combined with physicochemical property or base periodicity group of features becomes a strong classifier with more than 99 percentage accuracy. Base periodicity analysis with SNR can be used as discriminating feature of lncRNA from mRNA.

Deep DNAshape: Predicting DNA shape considering extended flanking regions using a deep learning method

Understanding the mechanisms of protein-DNA binding is critical in comprehending gene regulation. Three-dimensional DNA shape plays a key role in these mechanisms. In this study, we present a deep learning-based method, Deep DNAshape, that fundamentally changes the current k -mer based high-throughput prediction of DNA shape features by accurately accounting for the influence of extended flanking regions, without the need for extensive molecular simulations or structural biology experiments. By using the Deep DNAshape method, refined DNA shape features can be predicted for any length and number of DNA sequences in a high-throughput manner, providing a deeper understanding of the effects of flanking regions on DNA shape in a target region of a sequence. Deep DNAshape method provides access to the influence of distant flanking regions on a region of interest. Our findings reveal that DNA shape readout mechanisms of a core target are quantitatively affected by flanking regions, including extended flanking regions, providing valuable insights into the detailed structural readout mechanisms of protein-DNA binding. Furthermore, when incorporated in machine learning models, the features generated by Deep DNAshape improve the model prediction accuracy. Collectively, Deep DNAshape can serve as a versatile and powerful tool for diverse DNA structure-related studies.

Probing the Nucleic Acid Flexibility to Disarm the Viral Counter-Defense Machinery: Design and Characterization of Potent p19 Inhibitors

Plant viruses are highly destructive and significant contributors to several global pandemics and epidemics in plants. A viral disease outbreak in plants can cause a scarcity of food supply and is a severe concern to humanity. The siRNA (small interfering RNA)-mediated RNA-induced silencing complex (RISC) formation is a primary defense mechanism in plants against viruses, where the RISC binds and degrades viral mRNAs. As a counter-defense, many viruses encode RNA-silencing suppressor proteins (e.g., the p19 protein from the Tombusviridae family) for viral proliferation in plants. The functional form of p19 (homodimer) binds to plant siRNA with high affinities, thereby interrupting the RISC formation and thus preventing the viral mRNA silencing in plants. By altering the RISC formation, the p19 protein helps the virus invasion in the plant and ultimately stunts host growth. In this study, we designed several modified siRNA-based molecules for p19 inhibition. The viral p19 protein is known to interact predominantly through H-bonds with 2'-OH and phosphates of the plant siRNA. We utilized this information and in silico-designed flexible substituents of siRNA, where we removed the C2'-C3' bond in each nucleotide unit. We performed all-atom explicit-solvent molecular dynamics simulations (400 ns, 3 replicates each) for control/modified siRNA─p19 complexes (8 in total) followed by energetic estimations. Strikingly, in a few modified complexes, the siRNA not only retained the double-helical structural integrity but also displayed remarkably enhanced p19 binding compared to the control siRNA; hence, we consider it important to perform biological and chemical in vitro and in vivo studies on proposed flexible nucleic acids as p19 inhibitors for crop protection.

Mechanical codes of chemical-scale specificity in DNA motifs

In gene transcription, certain sequences of double-stranded (ds)DNA play a vital role in nucleosome positioning and expression initiation. That dsDNA is deformed to various extents in these processes leads us to ask: Could the genomic DNA also have sequence specificity in its chemical-scale mechanical properties? We approach this question using statistical machine learning to determine the rigidity between DNA chemical moieties. What emerges for the polyA, polyG, TpA, and CpG sequences studied here is a unique trigram that contains the quantitative mechanical strengths between bases and along the backbone. In a way, such a sequence-dependent trigram could be viewed as a DNA mechanical code. Interestingly, we discover a compensatory competition between the axial base-stacking interaction and the transverse base-pairing interaction, and such a reciprocal relationship constitutes the most discriminating feature of the mechanical code. Our results also provide chemical-scale understanding for experimental observables. For example, the long polyA persistence length is shown to have strong base stacking while its complement (polyAc) exhibits high backbone rigidity. The mechanical code concept enables a direct reading of the physical interactions encoded in the sequence which, with further development, is expected to shed new light on DNA allostery and DNA-binding drugs.

Sequence-Dependent Properties of the RNA Duplex

Sequence-dependent properties of the DNA duplex have been accurately described using extensive molecular dynamics simulations. The RNA duplex meanwhile─which is typically represented as a sequence-averaged rigid rod─does not benefit from having equivalent molecular dynamics simulations. In this paper, we present a massive simulation effort using a set of ABC-optimized duplexes from which we derived tetramer-resolution properties of the RNA duplex and a simple mesoscopic model that can represent elastic properties of long RNA duplexes. Despite the extreme chemical similarity between DNA and RNA, the local and global elastic properties of the duplexes are very different. DNA duplexes show a complex and nonelastic pattern of flexibility, for instance, while RNA duplexes behave as an elastic system whose deformations can be represented by simple harmonic potentials. In RNA duplexes (RNA2), not only are intra- and interbase pair parameters (equilibrium and mechanical) different from those in the equivalent DNA duplex sequences (DNA2) but the correlations between movements also differ. Simple statements on the relative flexibility or stability of both polymers are meaningless and should be substituted by a more detailed description depending on the sequence and the type of deformation considered.

Structural analysis of the Candida albicans mitochondrial DNA maintenance factor Gcf1p reveals a dynamic DNA-bridging mechanism

The compaction of mitochondrial DNA (mtDNA) is regulated by architectural HMG-box proteins whose limited cross-species similarity suggests diverse underlying mechanisms. Viability of Candida albicans, a human antibiotic-resistant mucosal pathogen, is compromised by altering mtDNA regulators. Among them, there is the mtDNA maintenance factor Gcf1p, which differs in sequence and structure from its human and Saccharomyces cerevisiae counterparts, TFAM and Abf2p. Our crystallographic, biophysical, biochemical and computational analysis showed that Gcf1p forms dynamic protein/DNA multimers by a combined action of an N-terminal unstructured tail and a long helix. Furthermore, an HMG-box domain canonically binds the minor groove and dramatically bends the DNA while, unprecedentedly, a second HMG-box binds the major groove without imposing distortions. This architectural protein thus uses its multiple domains to bridge co-aligned DNA segments without altering the DNA topology, revealing a new mechanism of mtDNA condensation.

Toward Force Fields with Improved Base Stacking Descriptions

Recent DNA force fields indicate good performance in describing flexibility and structural stability of double-stranded B-DNA. However, it is not clear how accurately base stacking interactions are represented that are critical for simulating structure formation processes and conformational changes. Based on the equilibrium nucleoside association and base pair nicking, we find that the recent Tumuc1 force field improves the description of base stacking compared to previous state-of-the-art force fields. Nevertheless, base pair stacking is still overstabilized compared to experiment. We propose a rapid method to reweight calculated free energies of stacking upon force field modifications in order to generate improved parameters. A decrease of the Lennard-Jones attraction between nucleo-bases alone appears insufficient; however, adjustments in the partial charge distribution on base atoms could help to further improve the force field description of base stacking.

Molecular dynamics simulation-based trinucleotide and tetranucleotide level structural and energy characterization of the functional units of genomic DNA

Genomes of most organisms on earth are written in a universal language of life, made up of four units - adenine (A), thymine (T), guanine (G), and cytosine (C), and understanding the way they are put together has been a great challenge to date. Multiple efforts have been made to annotate this wonderfully engineered string of DNA using different methods but they lack a universal character. In this article, we have investigated the structural and energetic profiles of both prokaryotes and eukaryotes by considering two essential genomic sites, viz., the transcription start sites (TSS) and exon-intron boundaries. We have characterized these sites by mapping the structural and energy features of DNA obtained from molecular dynamics simulations, which considers all possible trinucleotide and tetranucleotide steps. For DNA, these physicochemical properties show distinct signatures at the TSS and intron-exon boundaries. Our results firmly convey the idea that DNA uses the same dialect for prokaryotes and eukaryotes and that it is worth going beyond sequence-level analyses to physicochemical space to determine the functional destiny of DNA sequences.

Rigid Base Biasing in Molecular Dynamics Enables Enhanced Sampling of DNA Conformations

All-atom simulations have become increasingly popular to study conformational and dynamical properties of nucleic acids as they are accurate and provide high spatial and time resolutions. This high resolution, however, comes at a heavy computational cost, and, within the time scales of simulations, nucleic acids weakly fluctuate around their ideal structure exploring a limited set of conformations. We introduce the RBB-NA algorithm (available as a package in the Open Source Library PLUMED), which is capable of controlling rigid base parameters in all-atom simulations of nucleic acids. With suitable biasing potentials, this algorithm can "force" a DNA or RNA molecule to assume specific values of the six rotational (tilt, roll, twist, buckle, propeller, opening) and/or the six translational parameters (shift, slide, rise, shear, stretch, stagger). The algorithm enables the use of advanced sampling techniques to probe the structure and dynamics of locally strongly deformed nucleic acids. We illustrate its performance showing some examples in which DNA is strongly twisted, bent, or locally buckled. In these examples, RBB-NA reproduces well the unconstrained simulations data and other known features of DNA mechanics, but it also allows one to explore the anharmonic behavior characterizing the mechanics of nucleic acids in the high deformation regime.

Structure prediction and discovery of inhibitors against phosphopantothenoyl cysteine synthetase of Acinetobacter baumannii

Acinetobacter baumannii is an extremely dangerous multidrug-resistant (MDR) gram-negative pathogen which poses a serious life-threatening risk in immunocompromised patients. Phosphopantothenoyl cysteine synthetase (PPCS) catalyzes the formation of an amide bond between L-cysteine and phosphopantothenic acid (PPA) to form 4'- Phosphopantothenoylcysteine during Coenzyme A (CoA) biosynthesis. CoA is a crucial cofactor for cellular survival and inhibiting its synthesis will result in cell death. Bacterial PPCS differs from eukaryotic PPCS in a number of ways like it exists as a C-terminal domain of a PPCDC/PPCS fusion protein whereas eukaryotic PPCS exists as an independent protein. This difference makes it an attractive drug target. For which a conventional iterative approach of SBDD (structure-based drug design) was used, which began with three-dimensional structure prediction of AbPPCS using PHYRE 2.0. A database of FDA-approved compounds (Drug Bank) was then screened against the target of interest by means of docking score and glide energy, leading to the identification of 6 prominent drug candidates. The shortlisted 6 molecules were further subjected to all-atom MD simulation studies in explicit-solvent conditions (using AMBER force field). The MD simulation studies revealed that the ligands DB65103, DB449108 and DB443210, maintained several H-bonds with intense van der Waals contacts at the active site of the protein with high binding free energies: -11.42 kcal/mol, -10.49 kcal/mol and -10.98 kcal/mol, respectively, calculated via MM-PBSA method. Overall, binding of these compounds at the active site was found to be the most stable and robust highlighting the potential of these compounds to serve as antibacterials.Communicated by Ramaswamy H. Sarma.

Harmonizing Interstrand Electrostatic Repulsion by Conformational Rigidity in Counterion-Deprived Z-DNA: A Molecular Dynamics Study

Deoxyribonucleic acid (DNA) is a vital biomacromolecule. Although the right-handed B-DNA type helical structure is the most abundant and extensively studied form of DNA, several noncanonical forms, such as triplex, quadruplex, Z-DNA, A-DNA, and ss-DNA, have been probed from time to time to gain insights into the DNA's function. Z-DNA was recently found to be involved in cancer and several autoimmune diseases. In the present Article, we evaluated the conformational stability of locked-sugar-based Z-DNA via all-atom explicit-solvent molecular dynamics simulations and found that the modified DNA maintained the left-handed conformation even in the absence of counterions, wherein the structural rigidity dominates over the electrostatic repulsion between the complementary strands. The control Z-DNA without counterions, as expected, instantaneously resulted in unfolded states. The remarkable stability of the conformationally locked model system was thoroughly investigated via structural and energetic perspectives and was probably the result of the backbone widening in tandem with enhanced electrostatics between complementary strands. We believe that the design of the proposed modified Z-DNA construct could help understand the otherwise delicate Z-DNA conformation even in salt-deprived conditions. The design could also motivate the medicinal use of short segments of such modified nucleotides and could be utilized in more advanced modeling techniques, such as DNA origami which has gained popularity in recent years.

Deciphering the mechanical code of the genome and epigenome

Diverse DNA-deforming processes are impacted by the local mechanical and structural properties of DNA, which in turn depend on local sequence and epigenetic modifications. Deciphering this mechanical code (that is, this dependence) has been challenging due to the lack of high-throughput experimental methods. Here we present a comprehensive characterization of the mechanical code. Utilizing high-throughput measurements of DNA bendability via loop-seq, we quantitatively established how the occurrence and spatial distribution of dinucleotides, tetranucleotides and methylated CpG impact DNA bendability. We used our measurements to develop a physical model for the sequence and methylation dependence of DNA bendability. We validated the model by performing loop-seq on mouse genomic sequences around transcription start sites and CTCF-binding sites. We applied our model to test the predictions of all-atom molecular dynamics simulations and to demonstrate that sequence and epigenetic modifications can mechanically encode regulatory information in diverse contexts.

Sequence-Specific Structural Features and Solvation Properties of Transcription Factor Binding DNA Motifs: Insights from Molecular Dynamics Simulation

Sequence-specific recognition of transcription factor (TF) binding motifs in the target site of DNA over the vast amount of non-target DNA is of primary importance for the transcriptional regulation of gene expression by the TFs. Binding of TFs to the target site of DNA relies not only on the direct contact formation but also on the structural and conformational features of DNA. Recognition of DNA structural features or shape readout by proteins is an important factor in the context of TF-DNA interaction. Based on the atomistic molecular simulation, here we report the sequence-dependent unique structural features, solvation, and ion-binding properties of biologically relevant AT- and GC-rich human TF binding motifs in DNA. Counterion and water distribution around the motif is found to be sensitive to the motif sequence, which is accompanied with the DNA shape features. The motif sequence affects the electrostatic potential along the grooves, and cytosine methylation alters the DNA shape features. Characteristic solvation properties of TF binding motif DNA fragments infer that an ionic environment and hydration influences are essential to describe TF-DNA interactions.

An updated definition of V(D)J recombination signal sequences revealed by high-throughput recombination assays

In the adaptive immune system, V(D)J recombination initiates the production of a diverse antigen receptor repertoire in developing B and T cells. Recombination activating proteins, RAG1 and RAG2 (RAG1/2), catalyze V(D)J recombination by cleaving adjacent to recombination signal sequences (RSSs) that flank antigen receptor gene segments. Previous studies defined the consensus RSS as containing conserved heptamer and nonamer sequences separated by a less conserved 12 or 23 base-pair spacer sequence. However, many RSSs deviate from the consensus sequence. Here, we developed a cell-based, massively parallel assay to evaluate V(D)J recombination activity on thousands of RSSs where the 12-RSS heptamer and adjoining spacer region contained randomized sequences. While the consensus heptamer sequence (CACAGTG) was marginally preferred, V(D)J recombination was highly active on a wide range of non-consensus sequences. Select purine/pyrimidine motifs that may accommodate heptamer unwinding in the RAG1/2 active site were generally preferred. In addition, while different coding flanks and nonamer sequences affected recombination efficiency, the relative dependency on the purine/pyrimidine motifs in the RSS heptamer remained unchanged. Our results suggest RAG1/2 specificity for RSS heptamers is primarily dictated by DNA structural features dependent on purine/pyrimidine pattern, and to a lesser extent, RAG:RSS base-specific interactions.

DNA double-strand break-derived RNA drives TIRR/53BP1 complex dissociation

Tudor-interacting repair regulator (TIRR) is an RNA-binding protein and a negative regulator of the DNA-repair factor p53-binding protein 1 (53BP1). In non-damage conditions, TIRR is bound to 53BP1. After DNA damage, TIRR and 53BP1 dissociate, and 53BP1 binds the chromatin at the double-strand break (DSB) to promote non-homologous end joining (NHEJ)-mediated repair. However, the exact mechanistic details of this dissociation after damage are unknown. Increasing evidence has implicated RNA as a crucial factor in the DNA damage response (DDR). Here, we show that RNA can separate TIRR/53BP1. Specifically, RNA with a hairpin secondary structure, transcribed at the DSB by RNA polymerase II (RNAPII), promotes TIRR/53BP1 complex separation. This hairpin RNA binds to the same residues on TIRR as 53BP1. Our results uncover a role of DNA-damage-derived RNA in modulating a protein-protein interaction and contribute to our understanding of DSB repair.

Flexibility of flanking DNA is a key determinant of transcription factor affinity for the core motif

Selective gene regulation is mediated by recognition of specific DNA sequences by transcription factors (TFs). The extremely challenging task of searching out specific cognate DNA binding sites among several million putative sites within the eukaryotic genome is achieved by complex molecular recognition mechanisms. Elements of this recognition code include the core binding sequence, the flanking sequence context, and the shape and conformational flexibility of the composite binding site. To unravel the extent to which DNA flexibility modulates TF binding, in this study, we employed experimentally guided molecular dynamics simulations of ternary complex of closely related Hox heterodimers Exd-Ubx and Exd-Scr with DNA. Results demonstrate that flexibility signatures embedded in the flanking sequences impact TF binding at the cognate binding site. A DNA sequence has intrinsic shape and flexibility features. While shape features are localized, our analyses reveal that flexibility features of the flanking sequences percolate several basepairs and allosterically modulate TF binding at the core. We also show that lack of flexibility in the motif context can render the cognate site resistant to protein-induced shape changes and subsequently lower TF binding affinity. Overall, this study suggests that flexibility-guided DNA shape, and not merely the static shape, is a key unexplored component of the complex DNA-TF recognition code.

Mechanical properties of nucleic acids and the non-local twistable wormlike chain model

Mechanical properties of nucleic acids play an important role in many biological processes that often involve physical deformations of these molecules. At sufficiently long length scales (say, above ∼20-30 base pairs), the mechanics of DNA and RNA double helices is described by a homogeneous Twistable Wormlike Chain (TWLC), a semiflexible polymer model characterized by twist and bending stiffnesses. At shorter scales, this model breaks down for two reasons: the elastic properties become sequence-dependent and the mechanical deformations at distal sites get coupled. We discuss in this paper the origin of the latter effect using the framework of a non-local Twistable Wormlike Chain (nlTWLC). We show, by comparing all-atom simulations data for DNA and RNA double helices, that the non-local couplings are of very similar nature in these two molecules: couplings between distal sites are strong for tilt and twist degrees of freedom and weak for roll. We introduce and analyze a simple double-stranded polymer model that clarifies the origin of this universal distal couplings behavior. In this model, referred to as the ladder model, a nlTWLC description emerges from the coarsening of local (atomic) degrees of freedom into angular variables that describe the twist and bending of the molecule. Different from its local counterpart, the nlTWLC is characterized by a length-scale-dependent elasticity. Our analysis predicts that nucleic acids are mechanically softer at the scale of a few base pairs and are asymptotically stiffer at longer length scales, a behavior that matches experimental data.

Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under:Data Science > Computer Algorithms and ProgrammingData Science > Databases and Expert SystemsMolecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods.

BioExcel Building Blocks Workflows (BioBB-Wfs), an integrated web-based platform for biomolecular simulations

We present BioExcel Building Blocks Workflows, a web-based graphical user interface (GUI) offering access to a collection of transversal pre-configured biomolecular simulation workflows assembled with the BioExcel Building Blocks library. Available workflows include Molecular Dynamics setup, protein-ligand docking, trajectory analyses and small molecule parameterization. Workflows can be launched in the platform or downloaded to be run in the users’ own premises. Remote launching of long executions to user's available High-Performance computers is possible, only requiring configuration of the appropriate access credentials. The web-based graphical user interface offers a high level of interactivity, with integration with the NGL viewer to visualize and check 3D structures, MDsrv to visualize trajectories, and Plotly to explore 2D plots. The server requires no login but is recommended to store the users’ projects and manage sensitive information such as remote credentials. Private projects can be made public and shared with colleagues with a simple URL. The tool will help biomolecular simulation users with the most common and repetitive processes by means of a very intuitive and interactive graphical user interface. The server is accessible at https://mmb.irbbarcelona.org/biobb-wfs.

Revisiting DNA Sequence-Dependent Deformability in High-Resolution Structures: Effects of Flanking Base Pairs on Dinucleotide Morphology and Global Chain Configuration

DNA carries more than the list of biochemical ingredients that drive the basic functions of living systems. The sequence of base pairs includes a multitude of structural and energetic signals, which determine the degree to which the long, threadlike molecule moves and how it responds to proteins and other molecules that control its processing and govern its packaging. The chemical composition of base pairs directs the spatial disposition and fluctuations of successive residues. The observed arrangements of these moieties in high-resolution protein–DNA crystal structures provide one of the best available estimates of the natural, sequence-dependent structure and deformability of the double-helical molecule. Here, we update the set of knowledge-based elastic potentials designed to describe the observed equilibrium structures and configurational fluctuations of the ten unique base-pair steps. The large number of currently available structures makes it possible to characterize the configurational preferences of the DNA base-pair steps within the context of their immediate neighbors, i.e., tetrameric context. Use of these knowledge-based potentials shows promise in accounting for known effects of sequence in long chain molecules, e.g., the degree of curvature reported in classic gel mobility studies and the recently reported sequence-dependent responses of supercoiled minicircles to nuclease cleavage.

Accurate Sequence-Dependent Coarse-Grained Model for Conformational and Elastic Properties of Double-Stranded DNA

We introduce MADna, a sequence-dependent coarse-grained model of double-stranded DNA (dsDNA), where each nucleotide is described by three beads localized at the sugar, at the base moiety, and at the phosphate group, respectively. The sequence dependence is included by considering a step-dependent parametrization of the bonded interactions, which are tuned in order to reproduce the values of key observables obtained from exhaustive atomistic simulations from the literature. The predictions of the model are benchmarked against an independent set of all-atom simulations, showing that it captures with high fidelity the sequence dependence of conformational and elastic features beyond the single step considered in its formulation. A remarkably good agreement with experiments is found for both sequence-averaged and sequence-dependent conformational and elastic features, including the stretching and torsion moduli, the twist–stretch and twist–bend couplings, the persistence length, and the helical pitch. Overall, for the inspected quantities, the model has a precision comparable to atomistic simulations, hence providing a reliable coarse-grained description for the rationalization of single-molecule experiments and the study of cellular processes involving dsDNA. Owing to the simplicity of its formulation, MADna can be straightforwardly included in common simulation engines. Particularly, an implementation of the model in LAMMPS is made available on an online repository to ease its usage within the DNA research community.

Kinetics and thermodynamics of BI-BII interconversion altered by T:G mismatches in DNA

T:G mismatches in DNA result in humans primarily from deamination of methylated CpG sites. They are repaired by redundant systems, such as thymine DNA glycosylase (TDG) and methyl-binding domain enzyme (MBD4), and maintenance of these sites has been implicated in epigenetic processes. The process by which these enzymes identify a canonical DNA base in the incorrect basepairing context remains a mystery. However, the conserved contacts of the repair enzymes with the DNA backbone suggests a role for protein-phosphate interaction in the recognition and repair processes. We have used 31P NMR to investigate the energetics of DNA backbone BI-BII interconversion, and for this work have focused on alterations to the activation barriers to interconversion and the effect of a mismatch compared with canonical DNA. We have found that alterations to the ΔG of interconversion for T:G basepairs are remarkably similar to U:G basepairs in the form of stepwise differences in ΔG of 1-2 kcal/mol greater than equivalent steps in unmodified DNA, suggesting a universality of this result for TDG substrates. Likewise, we see perturbations to the free energy (∼1 kcal/mol) and enthalpy (2-5 kcal/mol) of activation for the BI-BII interconversion localized to the phosphates flanking the mismatch. Overall our results strongly suggest that the perturbed backbone energetics in T:G basepairs play a significant role in the recognition process of DNA repair enzymes.

Bicyclo-DNA mimics with enhanced protein binding affinities: insights from molecular dynamics simulations

DNA-protein interactions occur at all levels of DNA expression and replication and are crucial determinants for the survival of a cell. Several modified nucleotides have been utilized to manipulate these interactions and have implications in drug discovery. In the present article, we evaluated the binding of bicyclo-nucleotides (generated by forming a methylene bridge between C1' and C5' in sugar, leading to a bicyclo system with C2' axis of symmetry at the nucleotide level) to proteins. We utilized four ssDNA-protein complexes with experimentally known binding free energies and investigated the binding of modified nucleotides to proteins via all-atom explicit solvent molecular dynamics (MD) simulations (200 ns), and compared the binding with control ssDNA-protein systems. The modified ssDNA displayed enhanced binding to proteins as compared to the control ssDNA, as seen by means of MD simulations followed by MM-PBSA calculations. Further, the Delphi-based electrostatic estimation revealed that the high binding of modified ssDNA to protein might be related to the enhanced electrostatic complementarity displayed by the modified ssDNA molecules in all the four systems considered for the study. The improved binding achieved with modified nucleotides can be utilized to design and develop anticancer/antisense molecules capable of targeting proteins or ssRNAs.Communicated by Ramaswamy H. Sarma.

Discovery of the Lead Molecules Targeting the First Step of the Histidine Biosynthesis Pathway of Acinetobacter baumannii

Acinetobacter baumannii is a multidrug-resistant, opportunistic, nosocomial pathogen for which a new line of treatments is desperately needed. We have targeted the enzyme of the first step of the histidine biosynthesis pathway, viz., ATP-phosphoribosyltransferase (ATP-PRT). The three-dimensional structure of ATP-PRT was predicted on the template of the known three-dimensional structure of ATP-PRT from Psychrobacter arcticus (PaATPPRT) using a homology modeling approach. High-throughput virtual screening (HTVS) of the antibacterial library of Life Chemicals Inc., Ontario, Canada was carried out followed by molecular dynamics simulations of the top hit compounds. In silico results were then biochemically validated using surface plasmon resonance spectroscopy. We found that two compounds, namely, F0843-0019 and F0608-0626, were binding with micromolar affinities to the ATP-phosphoribosyltransferase from Acinetobacter baumannii (AbATPPRT). Both of these compounds were binding in the same way as AMP in PaATPPRT, and the important residues of the active site, viz., Val4, Ser72, Thr76, Tyr77, Glu95, Lys134, Val136, and Tyr156, were also interacting via hydrogen bonds. The calculated binding energies of these compounds were -10.5 kcal/mol and -11.1 kcal/mol, respectively. These two compounds can be used as the potential lead molecules for designing antibacterial compounds in the future, and this information will help in drug discovery programs against Acinetobacter worldwide.

emDNA - A Tool for Modeling Protein-decorated DNA Loops and Minicircles at the Base-pair Step Level

Computational modeling of nucleic acids plays an important role in molecular biology, enhancing our general understanding of the relationship between structure and function. Biophysical studies have provided a wealth of information on how double-helical DNA responds to proteins and other molecules in its local environment but far less understanding of the larger scale structural responses found in protein-decorated loops and minicircles. Current computational models of DNA range from detailed all-atom molecular dynamics studies, which produce rich time and spatially dependent depictions of small DNA fragments, to coarse-grained simulations, which sacrifice detailed physical and chemical information to treat larger scale systems. The treatment of DNA used here, at the base-pair step level with rigid-body parameters, allows one to develop quality models hundreds of base pairs long from local, sequence-specific features found from experiment. The emDNA software takes advantage of this framework, producing elastically optimized models of DNA at thermal equilibrium with built-in or user-generated elastic models. This versatile program, in combination with case studies included in this article, allows users of any skill level to develop and investigate mesoscale models of their own design. The functionality of emDNA includes a tool to incorporate experiment-specific configurations, e.g. protein-bound and/or melted DNA from known high-resolution structures, within higher-order 3D models by fixing the orientation and position of user-specified base pairs. The software provides a new avenue into multiscale genetic modeling, giving a wide range of users a deeper understanding of DNA mesoscale organization and the opportunity to pose new questions in genetic research. The publicly available emDNA software, including build instructions and usage information, is available on GitHub (https://nicocvn.github.io/emDNA/).

Searching for Low Probability Opening Events in a DNA Sliding Clamp

The β subunit of E. coli DNA polymererase III is a DNA sliding clamp associated with increasing the processivity of DNA synthesis. In its free form, it is a circular homodimer structure that can accomodate double-stranded DNA in a nonspecific manner. An open state of the clamp must be accessible before loading the DNA. The opening mechanism is still a matter of debate, as is the effect of bound DNA on opening/closing kinetics. We use a combination of atomistic, coarse-grained, and enhanced sampling strategies in both explicit and implicit solvents to identify opening events in the sliding clamp. Such simulations of large nucleic acid and their complexes are becoming available and are being driven by improvements in force fields and the creation of faster computers. Different models support alternative opening mechanisms, either through an in-plane or out-of-plane opening event. We further note some of the current limitations, despite advances, in modeling these highly charged systems with implicit solvent.

Computational investigation of the impact of core sequence on immobile DNA four-way junction structure and dynamics

Immobile four-way junctions (4WJs) are core structural motifs employed in the design of programmed DNA assemblies. Understanding the impact of sequence on their equilibrium structure and flexibility is important to informing the design of complex DNA architectures. While core junction sequence is known to impact the preferences for the two possible isomeric states that junctions reside in, previous investigations have not quantified these preferences based on molecular-level interactions. Here, we use all-atom molecular dynamics simulations to investigate base-pair level structure and dynamics of four-way junctions, using the canonical Seeman J1 junction as a reference. Comparison of J1 with equivalent single-crossover topologies and isolated nicked duplexes reveal conformational impact of the double-crossover motif. We additionally contrast J1 with a second junction core sequence termed J24, with equal thermodynamic preference for each isomeric configuration. Analyses of the base-pair degrees of freedom for each system, free energy calculations, and reduced-coordinate sampling of the 4WJ isomers reveal the significant impact base sequence has on local structure, isomer bias, and global junction dynamics.

Molecular basis of Arginine and Lysine DNA sequence-dependent thermo-stability modulation

We have used a variety of theoretical and experimental techniques to study the role of four basic amino acids-Arginine, Lysine, Ornithine and L-2,4-Diaminobutyric acid-on the structure, flexibility and sequence-dependent stability of DNA. We found that the presence of organic ions stabilizes the duplexes and significantly reduces the difference in stability between AT- and GC-rich duplexes with respect to the control conditions. This suggests that these amino acids, ingredients of the primordial soup during abiogenesis, could have helped to equalize the stability of AT- and GC-rich DNA oligomers, facilitating a general non-catalysed self-replication of DNA. Experiments and simulations demonstrate that organic ions have an effect that goes beyond the general electrostatic screening, involving specific interactions along the grooves of the double helix. We conclude that organic ions, largely ignored in the DNA world, should be reconsidered as crucial structural elements far from mimics of small inorganic cations.

Homologous basic helix–loop–helix transcription factors induce distinct deformations of torsionally-stressed DNA: a potential transcription regulation mechanism

Changing torsional restraints on DNA is essential for the regulation of transcription. Torsional stress, introduced by RNA polymerase, can propagate along chromatin facilitating topological transitions and modulating the specific binding of transcription factors (TFs) to DNA. Despite the importance, the mechanistic details on how torsional stress impacts the TFs-DNA complexation remain scarce. Herein, we address the impact of torsional stress on DNA complexation with homologous human basic helix–loop–helix (BHLH) hetero- and homodimers: MycMax, MadMax and MaxMax. The three TF dimers exhibit specificity towards the same DNA consensus sequence, the E-box response element, while regulating different transcriptional pathways. Using microseconds-long atomistic molecular dynamics simulations together with the torsional restraint that controls DNA total helical twist, we gradually over- and underwind naked and complexed DNA to a maximum of ± 5°/bp step. We observe that the binding of the BHLH dimers results in a similar increase in DNA torsional rigidity. However, under torsional stress the BHLH dimers induce distinct DNA deformations, characterised by changes in DNA grooves geometry and a significant asymmetric DNA bending. Supported by bioinformatics analyses, our data suggest that torsional stress may contribute to the execution of differential transcriptional programs of the homologous TFs by modulating their collaborative interactions.

DNA sequence and methylation prescribe the inside-out conformational dynamics and bending energetics of DNA minicircles

Eukaryotic genome and methylome encode DNA fragments' propensity to form nucleosome particles. Although the mechanical properties of DNA possibly orchestrate such encoding, the definite link between 'omics' and DNA energetics has remained elusive. Here, we bridge the divide by examining the sequence-dependent energetics of highly bent DNA. Molecular dynamics simulations of 42 intact DNA minicircles reveal that each DNA minicircle undergoes inside-out conformational transitions with the most likely configuration uniquely prescribed by the nucleotide sequence and methylation of DNA. The minicircles' local geometry consists of straight segments connected by sharp bends compressing the DNA's inward-facing major groove. Such an uneven distribution of the bending stress favors minimum free energy configurations that avoid stiff base pair sequences at inward-facing major grooves. Analysis of the minicircles' inside-out free energy landscapes yields a discrete worm-like chain model of bent DNA energetics that accurately account for its nucleotide sequence and methylation. Experimentally measuring the dependence of the DNA looping time on the DNA sequence validates the model. When applied to a nucleosome-like DNA configuration, the model quantitatively reproduces yeast and human genomes' nucleosome occupancy. Further analyses of the genome-wide chromatin structure data suggest that DNA bending energetics is a fundamental determinant of genome architecture.

Impact of DNA sequences on DNA 'opening' by the Rad4/XPC nucleotide excision repair complex

Rad4/XPC recognizes diverse DNA lesions to initiate nucleotide excision repair (NER). However, NER propensities among lesions vary widely and repair-resistant lesions are persistent and thus highly mutagenic. Rad4 recognizes repair-proficient lesions by unwinding ('opening') the damaged DNA site. Such 'opening' is also observed on a normal DNA sequence containing consecutive C/G's (CCC/GGG) when tethered to Rad4 to prevent protein diffusion. However, it was unknown if such tethering-facilitated DNA 'opening' could occur on any DNA or if certain structures/sequences would resist being 'opened'. Here, we report that DNA containing alternating C/G's (CGC/GCG) failed to be opened even when tethered; instead, Rad4 bound in a 180°-reversed manner, capping the DNA end. Fluorescence lifetime studies of DNA conformations in solution showed that CCC/GGG exhibits local pre-melting that is absent in CGC/GCG. In MD simulations, CGC/GCG failed to engage Rad4 to promote 'opening' contrary to CCC/GGG. Altogether, our study illustrates how local sequences can impact DNA recognition by Rad4/XPC and how certain DNA sites resist being 'opened' even with Rad4 held at that site indefinitely. The contrast between CCC/GGG and CGC/GCG sequences in Rad4-DNA recognition may help decipher a lesion's mutagenicity in various genomic sequence contexts to explain lesion-determined mutational hot and cold spots.

Machine Learning Approach to Calculate Electronic Couplings between Quasi-diabatic Molecular Orbitals: The Case of DNA

Diabatization of one-electron states in flexible molecular aggregates is a great challenge due to the presence of surface crossings between molecular orbital (MO) levels and the complex interaction between MOs of neighboring molecules. In this work, we present an efficient machine learning approach to calculate electronic couplings between quasi-diabatic MOs without the need of nonadiabatic coupling calculations. Using MOs of rigid molecules as references, the MOs that can be directly regarded to be quasi-diabatic in molecular dynamics are selected out, state tracked, and phase corrected. On the basis of this information, artificial neural networks are trained to characterize the structure-dependent onsite energies of quasi-diabatic MOs and the intermolecular electronic couplings. A representative sequence of DNA is systematically studied as an illustration. Smooth time evolution of electronic couplings in all base pairs is obtained with quasi-diabatic MOs. In particular, our method can calculate electronic couplings between different quasi-diabatic MOs independently, and thus, this possesses unique advantages in many applications.