Tumuc1: A New Accurate DNA Force Field Consistent with High-Level Quantum Chemistry

A Hybrid Bottom-Up and Data-Driven Machine Learning Approach for Accurate Coarse-Graining of Large Molecular Complexes

Bottom-up coarse-graining refers to the development of low-resolution simulation models that are thermodynamically consistent with certain distributions from fully atomistic simulations. Force-matching and relative entropy minimization represent two major, frequently applied methods that allow to develop such bottom-up models. Nevertheless, atomistic simulations can often provide only limited sampling of the phase space. For bottom-up coarse-graining, these limitations may result in overfitting of the atomistic reference data, especially for large molecular complexes, where the learning may be agnostic of the actual affinities between binding partners. As a solution to this problem, we devise a data-driven machine learning hybrid coarse-graining concept that represents a regularized version of the relative entropy minimization approach. We demonstrate that this new approach allows one to develop coarse-grained models for molecular complexes that reproduce the targeted binding affinity but also describe the underlying complex structure accurately. The trained models therefore show diverse behavior as they can undergo frequent unbinding and binding events and are also transferable for simulating entire protein lattices, e.g., for a virus capsid.

Kinetics and dynamics of oligonucleotide hybridization

The hybridization of short nucleic acid strands is a remarkable spontaneous process that is foundational to biotechnology and nanotechnology and plays a crucial role in gene expression, editing and DNA repair. Decades of research into the mechanism of hybridization have resulted in a deep understanding of its thermodynamics, but many questions remain regarding its kinetics and dynamics. Recent advances in experiments and molecular dynamics simulations of nucleic acids are enabling more direct insight into the structural dynamics of hybridization, which can test long-standing assumptions regarding its mechanism. In this Review, we summarize the current state of knowledge of hybridization kinetics, discuss the barriers to a molecular description of hybridization dynamics, and highlight the new approaches that have begun uncovering the dynamics of hybridization and the duplex ensemble. The kinetics and dynamics of hybridization are highly sensitive to the composition of nucleic acids, and we emphasize recent discoveries and open questions on the role of nucleobase sequence and chemical modifications.

Computational Methods for Modeling Lipid-Mediated Active Pharmaceutical Ingredient Delivery

Lipid-mediated delivery of active pharmaceutical ingredients (API) opened new possibilities in advanced therapies. By encapsulating an API into a lipid nanocarrier (LNC), one can safely deliver APIs not soluble in water, those with otherwise strong adverse effects, or very fragile ones such as nucleic acids. However, for the rational design of LNCs, a detailed understanding of the composition-structure-function relationships is missing. This review presents currently available computational methods for LNC investigation, screening, and design. The state-of-the-art physics-based approaches are described, with the focus on molecular dynamics simulations in all-atom and coarse-grained resolution. Their strengths and weaknesses are discussed, highlighting the aspects necessary for obtaining reliable results in the simulations. Furthermore, a machine learning, i.e., data-based learning, approach to the design of lipid-mediated API delivery is introduced. The data produced by the experimental and theoretical approaches provide valuable insights. Processing these data can help optimize the design of LNCs for better performance. In the final section of this Review, state-of-the-art of computer simulations of LNCs are reviewed, specifically addressing the compatibility of experimental and computational insights.

Comprehensive Assessment of Force-Field Performance in Molecular Dynamics Simulations of DNA/RNA Hybrid Duplexes

Mixed double helices formed by RNA and DNA strands, commonly referred to as hybrid duplexes or hybrids, are essential in biological processes like transcription and reverse transcription. They are also important for their applications in CRISPR gene editing and nanotechnology. Yet, despite their significance, the hybrid duplexes have been seldom modeled by atomistic molecular dynamics methodology, and there is no benchmark study systematically assessing the force-field performance. Here, we present an extensive benchmark study of polypurine tract (PPT) and Dickerson-Drew dodecamer hybrid duplexes using contemporary and commonly utilized pairwise additive and polarizable nucleic acid force fields. Our findings indicate that none of the available force-field choices accurately reproduces all the characteristic structural details of the hybrid duplexes. The AMBER force fields are unable to populate the C3'-endo (north) pucker of the DNA strand and underestimate inclination. The CHARMM force field accurately describes the C3'-endo pucker and inclination but shows base pair instability. The polarizable force fields struggle with accurately reproducing the helical parameters. Some force-field combinations even demonstrate a discernible conflict between the RNA and DNA parameters. In this work, we offer a candid assessment of the force-field performance for mixed DNA/RNA duplexes. We provide guidance on selecting utilizable force-field combinations and also highlight potential pitfalls and best practices for obtaining optimal performance.

Embracing exascale computing in nucleic acid simulations

This mini-review reports the recent advances in biomolecular simulations, particularly for nucleic acids, and provides the potential effects of the emerging exascale computing on nucleic acid simulations, emphasizing the need for advanced computational strategies to fully exploit this technological frontier. Specifically, we introduce recent breakthroughs in computer architectures for large-scale biomolecular simulations and review the simulation protocols for nucleic acids regarding force fields, enhanced sampling methods, coarse-grained models, and interactions with ligands. We also explore the integration of machine learning methods into simulations, which promises to significantly enhance the predictive modeling of biomolecules and the analysis of complex data generated by the exascale simulations. Finally, we discuss the challenges and perspectives for biomolecular simulations as we enter the dawning exascale computing era.

Three-State Diffusion Model of DNA Glycosylase Translocation along Stretched DNA as Revealed by Free Energy Landscapes at the All-Atom Level

DNA glycosylases play key roles in the maintenance of genomic integrity. These enzymes effectively find rare damaged sites in DNA and participate in subsequent base excision repair. Single-molecule and ensemble experiments have revealed key aspects of this damage-site searching mechanism and the involvement of facilitated diffusion. In this study, we describe free energy landscapes of enzyme translocation along nonspecific DNA obtained using a fully atomistic molecular dynamics (MD) simulation of a well-known DNA glycosylase, human 8-oxoguanine DNA glycosylase 1 (hOGG1). Based on an analysis of simulated free energy profiles, we propose a three-state model for the damage-site searching mechanism. In the three states, named the L1, L2, and L3 states, the L1 state is a helical sliding mode in close contact with DNA, whereas the L2 state is a major- or minor-groove tracking mode in loose contact with DNA and the L3 state is a two-dimensional freely diffusing mode during which hOGG1 is somewhat removed from the DNA surface (∼24 Å away from the surface). This three-state model well describes key experimental findings obtained from single-molecule and ensemble experiments and provides a unified molecular picture of the DNA lesion-searching mechanism of hOGG1.

Multistate B- to A- transition in protein-DNA Binding - How well is it described by current AMBER force fields?

When DNA interacts with a protein, its structure often undergoes a significant conformational adaptation, usually involving a transition from B-DNA towards the A-DNA form. This is not a two-state, but rather a multistate transition. The A- and B- forms differ mainly in sugar pucker (north/south) and glycosidic torsion χ (anti/high-anti). The combination of A-like pucker and B-like χ (and vice versa) represents the nature of the intermediate states between the pure A- and B- forms. Here we study how the A/B equilibrium and the A/B intermediate states at protein-DNA interfaces are modeled by current AMBER force fields. Eight diverse protein-DNA complexes and their naked (unbound) DNAs were simulated with OL15 and bsc1 force fields and an experimental combination OL15χOL3. We found that while the geometries of the A-like intermediate states agree well with the native X-ray geometries, their populations (stabilities) are significantly underestimated. Different force fields predict different propensities for A-like states growing in the order OL15 < bsc1 < OL15χOL3, yet all underestimate A-like form populations. Interestingly, the force fields seem to predict the correct sequence-dependent A-form propensity, as they predict larger populations of the A-like form in unbound DNA in those steps that acquire A-like conformations in protein-DNA complexes. The instability of A-like geometries in current force fields significantly alters the geometry of simulated protein-DNA complexes and destabilizes the binding motif, suggesting that refinement is required to improve description of protein-DNA interactions in AMBER force fields.

Isotopic Depletion Increases the Spatial Resolution of FPOP Top-Down Mass Spectrometry Analysis

Protein radical labeling, like fast photochemical oxidation of proteins (FPOP), coupled to a top-down mass spectrometry (MS) analysis offers an alternative analytical method for probing protein structure or protein interaction with other biomolecules, for instance, proteins and DNA. However, with the increasing mass of studied analytes, the MS/MS spectra become complex and exhibit a low signal-to-noise ratio. Nevertheless, these difficulties may be overcome by protein isotope depletion. Thus, we aimed to use protein isotope depletion to analyze FPOP-oxidized samples by top-down MS analysis. For this purpose, we prepared isotopically natural (IN) and depleted (ID) forms of the FOXO4 DNA binding domain (FOXO4-DBD) and studied the protein-DNA interaction interface with double-stranded DNA, the insulin response element (IRE), after exposing the complex to hydroxyl radicals. As shown by comparing tandem mass spectra of natural and depleted proteins, the ID form increased the signal-to-noise ratio of useful fragment ions, thereby enhancing the sequence coverage by more than 19%. This improvement in the detection of fragment ions enabled us to detect 22 more oxidized residues in the ID samples than in the IN sample. Moreover, less common modifications were detected in the ID sample, including the formation of ketones and lysine carbonylation. Given the higher quality of ID top-down MSMS data set, these results provide more detailed information on the complex formation between transcription factors and DNA-response elements. Therefore, our study highlights the benefits of isotopic depletion for quantitative top-down proteomics. Data are available via ProteomeXchange with the identifier PXD044447.

van der Waals Parameter Scanning with Amber Nucleic Acid Force Fields: Revisiting Means to Better Capture the RNA/DNA Structure through MD

Molecular dynamics simulations can be used in combination with experimental techniques to uncover the intricacies of biomolecular structure, dynamics, and the resulting interactions. However, many noncanonical nucleic acid structures have proven to be challenging to replicate in accurate agreement with experimental data, often attributed to known force field deficiencies. A common force field criticism is the handling of van der Waals (vdW) parameters, which have not been updated since the regular use of Ewald's methods became routine. This work dives into the effects of minute vdW radii shifts on RNA tetranucleotide, B-DNA, and Z-DNA model systems described by commonly used Amber force fields. Using multidimensional replica exchange molecular dynamics (M-REMD), the GACC RNA tetranucleotide demonstrated changes in the structural distribution between the NMR minor and anomalous structure populations based on the O2' vdW radii scanning. However, no significant change in the NMR Major conformation population was observed. There were minimal changes in the B-DNA structure but there were more substantial improvements in Z-DNA structural descriptions, specifically with the Tumuc1 force field. This occurred with both LJbb vdW radii adjustments and incorporation of the CUFIX nonbonded parameter modifications. Though the limited vdW modifications tested did not provide a universal fix to the challenge of simulating the various known nucleic acid structures, they do provide direction and a greater understanding for future force field development efforts.

Coupling of conformation and CPD damage in nucleosomal DNA

UV-light can cause photodimerization and hence damages in DNA. Most frequent are cyclobutane pyrimidine dimer (CPD) damages, which predominantly form at TpT (thymine-thymine) steps. It is well known that CPD damage probability is different for single-stranded or double stranded DNA and depends on the sequence context. However, DNA deformation due to packing in nucleosomes can also influence CPD formation. Quantum mechanical calculations and Molecular Dynamics simulations indicate little CPD damage probability for DNA's equilibrium structure. We find that DNA needs to be deformed in a specific way to allow the HOMO → LUMO transition required for CPD damage formation. The simulation studies further show that the periodic CPD damage patterns measured in chromosomes and nucleosomes can be directly explained by the periodic deformation pattern of the DNA in the nucleosome complex. It supports previous findings on characteristic deformation patterns found in experimental nucleosome structures that relate to CPD damage formation. The result may have important implications for our understanding of UV-induced DNA mutations in human cancers.

The development of nucleic acids force fields: From an unchallenged past to a competitive future

Molecular dynamics simulations have strongly matured as a method to study biomolecular processes. Their validity, however, is determined by the accuracy of the underlying force fields that describe the forces between all atoms. In this article, we review the development of nucleic acids force fields. We describe the early attempts in the 1990s and emphasize their strong influence on recent force fields. State-of-the-art force fields still use the same Lennard-Jones parameters derived 25 years ago in spite of the fact that these parameters were in general not fitted for nucleic acids. In addition, electrostatic parameters also are deprecated, which may explain some of the current force field deficiencies. We compare different force fields for various systems and discuss new tests of the recently developed Tumuc1 force field. The OL-force fields and Tumuc1 are arguably the best force fields to describe the DNA double helix. However, no force field is flawless. In particular, the description of sugar-puckering remains a problem for nucleic acids force fields. Future refinements are required, so we review methods for force field refinement and give an outlook to the future of force fields.

C-B-A Test of DNA Force Fields

The DNA duplex may be locally strongly bent in complexes with proteins, for example, with polymerases or in a nucleosome. At such bends, the DNA helix is locally in the noncanonical forms A (with a narrow major groove and a large amount of north sugars) or C (with a narrow minor groove and a large share of BII phosphates). To model the formation of such complexes by molecular dynamics methods, the force field is required to reproduce these conformational transitions for a naked DNA. We analyzed the available experimental data on the B-C and B-A transitions under the conditions easily implemented in modeling: in an aqueous NaCl solution. We selected six DNA duplexes which conformations at different salt concentrations are known reliably enough. At low salt concentrations, poly(GC) and poly(A) are in the B-form, classical and slightly shifted to the A-form, respectively. The duplexes ATAT and GGTATACC have a strong and salt concentration dependent bias toward the A-form. The polymers poly(AC) and poly(G) take the C- and A-forms, respectively, at high salt concentrations. The reproduction of the behavior of these oligomers can serve as a test for the balance of interactions between the base stacking and the conformational flexibility of the sugar-phosphate backbone in a DNA force field. We tested the AMBER bsc1 and CHARMM36 force fields and their hybrids, and we failed to reproduce the experiment. In all the force fields, the salt concentration dependence is very weak. The known B-philicity of the AMBER force field proved to result from the B-philicity of its excessively strong base stacking. In the CHARMM force field, the B-form is a result of a fragile balance between the A-philic base stacking (especially for G:C pairs) and the C-philic backbone. Finally, we analyzed some recent simulations of the LacI-, SOX-4-, and Sac7d-DNA complex formation in the framework of the AMBER force field.

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.

Force-Field-Dependent DNA Breathing Dynamics: A Case Study of Hoogsteen Base Pairing in A6-DNA

The Hoogsteen (HG) base pairing conformation, commonly observed in damaged and mutated DNA helices, facilitates DNA repair and DNA recognition. The free energy difference between HG and Watson-Crick (WC) base pairs has been computed in previous studies. However, the mechanism of the conformational transition is not well understood. A detailed understanding of the process of WC to HG base pair transition can provide a deeper understanding of DNA repair and recognition. In an earlier study, we explored the free energy landscape for this process using extensive computer simulation with the CHARMM36 force field. In this work, we study the impact of force field models in describing the WC to HG base pairing transition using meta-eABF enhanced sampling, quasi-harmonic entropy calculation, and nonbonded energy analysis. The secondary structures of both base pairing forms and the topology of the free energy landscapes were consistent over different force field models, although the relative free energy, entropy, and the interaction energies tend to vary. The relative stability of the WC and HG conformations is dictated by a delicate balance between the enthalpic stabilization and the reduced entropy of the structurally rigid HG structure. These findings highlight the impact that subtleties in force field models can have on accurately modeling DNA base pair dynamics and should stimulate further computational investigations into other dynamically important motions in DNA.

Computer Aided Development of Nucleic Acid Applications in Nanotechnologies

Utilization of nucleic acids (NAs) in nanotechnologies and nanotechnology-related applications is a growing field with broad application potential, ranging from biosensing up to targeted cell delivery. Computer simulations are useful techniques that can aid design and speed up development in this field. This review focuses on computer simulations of hybrid nanomaterials composed of NAs and other components. Current state-of-the-art molecular dynamics simulations, empirical force fields (FFs), and coarse-grained approaches for the description of deoxyribonucleic acid and ribonucleic acid are critically discussed. Challenges in combining biomacromolecular and nanomaterial FFs are emphasized. Recent applications of simulations for modeling NAs and their interactions with nano- and biomaterials are overviewed in the fields of sensing applications, targeted delivery, and NA templated materials. Future perspectives of development are also highlighted.

Duplex DNA Retains the Conformational Features of Single Strands: Perspectives from MD Simulations and Quantum Chemical Computations

Molecular dynamics simulations and geometry optimizations carried out at the quantum level as well as by quantum mechanical/molecular mechanics methods predict that short, single-stranded DNA oligonucleotides adopt conformations very similar to those observed in crystallographic double-stranded B-DNA, with rise coordinates close to ≈3.3 Å. In agreement with the experimental evidence, the computational results show that DNA single strands rich in adjacent purine nucleobases assume more regular arrangements than poly-thymine. The preliminary results suggest that single-stranded poly-cytosine DNA should also retain a substantial helical order in solution. A comparison of the structures of single and double helices confirms that the B-DNA motif is a favorable arrangement also for single strands. Indeed, the optimal geometry of the complementary single helices is changed to a very small extent in the formation of the duplex.

The Importance of Charge Transfer and Solvent Screening in the Interactions of Backbones and Functional Groups in Amino Acid Residues and Nucleotides

Quantum mechanical (QM) calculations at the level of density-functional tight-binding are applied to a protein–DNA complex (PDB: 2o8b) consisting of 3763 atoms, averaging 100 snapshots from molecular dynamics simulations. A detailed comparison of QM and force field (Amber) results is presented. It is shown that, when solvent screening is taken into account, the contributions of the backbones are small, and the binding of nucleotides in the double helix is governed by the base–base interactions. On the other hand, the backbones can make a substantial contribution to the binding of amino acid residues to nucleotides and other residues. The effect of charge transfer on the interactions is also analyzed, revealing that the actual charge of nucleotides and amino acid residues can differ by as much as 6 and 8% from the formal integer charge, respectively. The effect of interactions on topological models (protein -residue networks) is elucidated.

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

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

Development of Force Field Parameters for the Simulation of Single- and Double-Stranded DNA Molecules and DNA-Protein Complexes

Although molecular dynamics (MD) simulations have been used extensively to study the structural dynamics of proteins, the role of MD simulation in studies of nucleic acid based systems has been more limited. One contributing factor to this disparity is the historically lower level of accuracy of the physical models used in such simulations to describe interactions involving nucleic acids. By modifying nonbonded and torsion parameters of a force field from the Amber family of models, we recently developed force field parameters for RNA that achieve a level of accuracy comparable to that of state-of-the-art protein force fields. Here we report force field parameters for DNA, which we developed by transferring nonbonded parameters from our recently reported RNA force field and making subsequent adjustments to torsion parameters. We have also modified the backbone charges in both the RNA and DNA parameter sets to make the treatment of electrostatics compatible with our recently developed variant of the Amber protein and ion force field. We name the force field resulting from the union of these three parameter sets (the new DNA parameters, the revised RNA parameters, and the existing protein and ion parameters) DES-Amber. Extensive testing of DES-Amber indicates that it can describe the thermal stability and conformational flexibility of single- and double-stranded DNA systems with a level of accuracy comparable to or, especially for disordered systems, exceeding that of state-of-the-art nucleic acid force fields. Finally, we show that, in certain favorable cases, DES-Amber can be used for long-timescale simulations of protein–nucleic acid complexes.

The influence of Holliday junction sequence and dynamics on DNA crystal self-assembly

The programmable synthesis of rationally engineered crystal architectures for the precise arrangement of molecular species is a foundational goal in nanotechnology, and DNA has become one of the most prominent molecules for the construction of these materials. In particular, branched DNA junctions have been used as the central building block for the assembly of 3D lattices. Here, crystallography is used to probe the effect of all 36 immobile Holliday junction sequences on self-assembling DNA crystals. Contrary to the established paradigm in the field, most junctions yield crystals, with some enhancing the resolution or resulting in unique crystal symmetries. Unexpectedly, even the sequence adjacent to the junction has a significant effect on the crystal assemblies. Six of the immobile junction sequences are completely resistant to crystallization and thus deemed “fatal,” and molecular dynamics simulations reveal that these junctions invariably lack two discrete ion binding sites that are pivotal for crystal formation. The structures and dynamics detailed here could be used to inform future designs of both crystals and DNA nanostructures more broadly, and have potential implications for the molecular engineering of applied nanoelectronics, nanophotonics, and catalysis within the crystalline context.

Engineered crystal architectures from DNA have become a foundational goal for nanotechnological precise arrangement. Here, the authors systematically investigate the structures of 36 immobile Holliday junction sequences and identify the features allowing the crystallisation of most of them, while 6 are considered fatal.

Nearest-Neighbor dsDNA Stability Analysis Using Alchemical Free-Energy Simulations

The thermodynamic stability of double-stranded (ds)DNA depends on its sequence. It is influenced by the base pairing and stacking with neighboring bases along DNA molecules. Semiempirical schemes are available that allow us to predict the thermodynamic stability of DNA sequences based on empirically derived nearest-neighbor contributions of base pairs formed in the context of all possible nearest-neighbor base pairs. Current molecular dynamics (MD) simulations allow one to simulate the dynamics of DNA molecules in good agreement with experimentally obtained structures and available data on conformational flexibility. However, the suitability of current force field methods to reproduce dsDNA stability and its sequence dependence has been much less well tested. We have employed alchemical free-energy simulations of whole base pair transversions in dsDNA and in unbound single-stranded partner molecules. Such transversions change the sequence context but not the nucleotide content or base pairing in dsDNA and allow a direct comparison with the empirical nearest-neighbor dsDNA stability model. For the alchemical free-energy changes in the unbound single-stranded (ss)DNA partner molecules, we tested different setups assuming either complete unstacking or unrestrained simulations with partial stacking in the unbound ssDNA. The free-energy simulations predicted nearest-neighbor effects of similar magnitude, as observed experimentally but showed overall limited correlation with experimental data. An inaccurate description of stacking interactions and other possible reasons such as the neglect of electronic polarization effects are discussed. The results indicate the need to improve the realistic description of stacking interactions in current molecular mechanic force fields.

Multiscale computational investigations of the translesion synthesis bypass of tobacco-derived DNA adducts: critical insights that complement experimental biochemical studies

Among the numerous agents that damage DNA, tobacco products remain one of the most lethal and result in the most diverse set of DNA lesions. This perspective aims to provide an overview of computational work conducted to complement experimental biochemical studies on the mutagenicity of adducts derived from the most potent tobacco carcinogen, namely 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (nicotine-derived nitrosaminoketone or NNK). Lesions ranging from the smallest methylated thymine derivatives to the larger, flexible pyridyloxobutyl (POB) guanine adducts are considered. Insights are obtained from density functional theory (DFT) calculations and molecular dynamics (MD) simulations into the damaged nucleobase and nucleoside structures, the accommodation of the lesions in the active site of key human polymerases, the intrinsic base pairing potentials of the adducts, and dNTP incorporation opposite the lesions. Overall, the computational data provide atomic level information that can rationalize the differential mutagenic properties of tobacco-derived lesions and uncover important insights into the impact of adduct size, nucleobase, position, and chemical composition of the bulky moiety.