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.

Accurate Hellmann-Feynman forces from density functional calculations with augmented Gaussian basis sets.

The Hellmann-Feynman (HF) theorem provides a way to compute forces directly from the electron density, enabling efficient force calculations for large systems through machine learning (ML) models for the electron density. The main issue holding back the general acceptance of the HF approach for atom-centered basis sets is the well-known Pulay force which, if naively discarded, typically constitutes an error upward of 10 eV/Å in forces. In this work, we demonstrate that if a suitably augmented Gaussian basis set is used for density functional calculations, the Pulay force can be suppressed, and HF forces can be computed as accurately as analytical forces with state-of-the-art basis sets, allowing geometry optimization and molecular dynamics to be reliably performed with HF forces. Our results pave a clear path forward for the accurate and efficient simulation of large systems using ML densities and the HF theorem.

Rapid prototyping of arbitrary 2D and 3D wireframe DNA origami.

Wireframe DNA origami assemblies can now be programmed automatically from the top-down using simple wireframe target geometries, or meshes, in 2D and 3D, using either rigid, six-helix bundle (6HB) or more compliant, two-helix bundle (DX) edges. While these assemblies have numerous applications in nanoscale materials fabrication due to their nanoscale spatial addressability and high degree of customization, no easy-to-use graphical user interface software yet exists to deploy these algorithmic approaches within a single, standalone interface. Further, top-down sequence design of 3D DX-based objects previously enabled by DAEDALUS was limited to discrete edge lengths and uniform vertex angles, limiting the scope of objects that can be designed. Here, we introduce the open-source software package ATHENA with a graphical user interface that automatically renders single-stranded DNA scaffold routing and staple strand sequences for any target wireframe DNA origami using DX or 6HB edges, including irregular, asymmetric DX-based polyhedra with variable edge lengths and vertices demonstrated experimentally, which significantly expands the set of possible 3D DNA-based assemblies that can be designed. ATHENA also enables external editing of sequences using caDNAno, demonstrated using asymmetric nanoscale positioning of gold nanoparticles, as well as providing atomic-level models for molecular dynamics, coarse-grained dynamics with oxDNA, and other computational chemistry simulation approaches.

Predicting accurate ab initio DNA electron densities with equivariant neural networks.

One of the fundamental limitations of accurately modeling biomolecules like DNA is the inability to perform quantum chemistry calculations on large molecular structures. We present a machine learning model based on an equivariant Euclidean neural network framework to obtain accurate ab initio electron densities for arbitrary DNA structures that are much too large for conventional quantum methods. The model is trained on representative B-DNA basepair steps that capture both base pairing and base stacking interactions. The model produces accurate electron densities for arbitrary B-DNA structures with typical errors of less than 1%. Crucially, the error does not increase with system size, which suggests that the model can extrapolate to large DNA structures with negligible loss of accuracy. The model also generalizes reasonably to other DNA structural motifs such as the A- and Z-DNA forms, despite being trained on only B-DNA configurations. The model is used to calculate electron densities of several large-scale DNA structures, and we show that the computational scaling for this model is essentially linear. We also show that this machine learning electron density model can be used to calculate accurate electrostatic potentials for DNA. These electrostatic potentials produce more accurate results compared with classical force fields and do not show the usual deficiencies at short range.

Structure and conformational dynamics of scaffolded DNA origami nanoparticles.

Synthetic DNA is a highly programmable nanoscale material that can be designed to self-assemble into 3D structures that are fully determined by underlying Watson-Crick base pairing. The double crossover (DX) design motif has demonstrated versatility in synthesizing arbitrary DNA nanoparticles on the 5-100 nm scale for diverse applications in biotechnology. Prior computational investigations of these assemblies include all-atom and coarse-grained modeling, but modeling their conformational dynamics remains challenging due to their long relaxation times and associated computational cost. We apply all-atom molecular dynamics and coarse-grained finite element modeling to DX-based nanoparticles to elucidate their fine-scale and global conformational structure and dynamics. We use our coarse-grained model with a set of secondary structural motifs to predict the equilibrium solution structures of 45 DX-based DNA origami nanoparticles including a tetrahedron, octahedron, icosahedron, cuboctahedron and reinforced cube. Coarse-grained models are compared with 3D cryo-electron microscopy density maps for these five DNA nanoparticles and with all-atom molecular dynamics simulations for the tetrahedron and octahedron. Our results elucidate non-intuitive atomic-level structural details of DX-based DNA nanoparticles, and offer a general framework for efficient computational prediction of global and local structural and mechanical properties of DX-based assemblies that are inaccessible to all-atom based models alone.

Molecular model of J-aggregated pseudoisocyanine fibers.

Aggregated cyanines form ordered supramolecular structures with the potential to transport energy efficiently over long distances, a hallmark of photosynthetic light-harvesting complexes. In concentrated aqueous solution, pseudoisocyanine (PIC) spontaneously forms fibers with a chiral J-band red-shifted 1600 cm-1 from the monomeric 0-0 transition. A cryogenic transmission electron microscopy analysis of these fibers show an average fiber width of 2.89 nm, although the molecular-level structure of the aggregate is currently unknown. To determine a molecular model for these PIC fibers, the calculated spectra and dynamics using a Frenkel exciton model are compared to experiment. A chiral aggregate model in which the PIC monomers are neither parallel nor orthogonal to the long axis of the fiber is shown to replicate the experimental spectra most closely. This model can be physically realized by the sequential binding of PIC dimers and monomers to the ends of the fiber. These insights into the molecular aggregation model for aqueous PIC can also be applied to other similar cyanine-based supramolecular complexes with the potential for long-range energy transport, a key building block for the rational design of novel excitonic systems.

The proteolysis adaptor, NblA, binds to the N-terminus of ß-phycocyanin: Implications for the mechanism of phycobilisome degradation.

Phycobilisome (PBS) complexes are massive light-harvesting apparati in cyanobacteria that capture and funnel light energy to the photosystem. PBS complexes are dynamically degraded during nutrient deprivation, which causes severe chlorosis, and resynthesized during nutrient repletion. PBS degradation occurs rapidly after nutrient step down, and is specifically triggered by non-bleaching protein A (NblA), a small proteolysis adaptor that facilitates interactions between a Clp chaperone and phycobiliproteins. Little is known about the mode of action of NblA during PBS degradation. In this study, we used chemical cross-linking coupled with LC-MS/MS to investigate the interactions between NblA and phycobiliproteins. An isotopically coded BS3 cross-linker captured a protein interaction between NblA and ß-phycocyanin (PC). LC-MS/MS analysis identified the amino acid residues participating in the binding reaction, and demonstrated that K52 in NblA is cross-linked to T2 in ß-PC. These results were modeled onto the existing crystal structures of NblA and PC by protein docking simulations. Our data indicate that the C-terminus of NblA fits in an open groove of ß-PC, a region located inside the central hollow cavity of a PC rod. NblA may mediate PBS degradation by disrupting the structural integrity of the PC rod from within the rod. In addition, M1-K44 and M1-K52 cross-links between the N-terminus of NblA and the C-terminus of NblA are consistent with the NblA crystal structure, confirming that the purified NblA is structurally and biologically relevant. These findings provide direct evidence that NblA physically interacts with ß-PC.

Optical determination of the electronic coupling and intercalation geometry of thiazole orange homodimer in DNA.

Sequence-selective bis-intercalating dyes exhibit large increases in fluorescence in the presence of specific DNA sequences. This property makes this class of fluorophore of particular importance to biosensing and super-resolution imaging. Here we report ultrafast transient anisotropy measurements of resonance energy transfer (RET) between thiazole orange (TO) molecules in a complex formed between the homodimer TOTO and double-stranded (ds) DNA. Biexponential homo-RET dynamics suggest two subpopulations within the ensemble: 80% intercalated and 20% non-intercalated. Based on the application of the transition density cube method to describe the electronic coupling and Monte Carlo simulations of the TOTO/dsDNA geometry, the dihedral angle between intercalated TO molecules is estimated to be 81° ± 5°, corresponding to a coupling strength of 45 ± 22 cm-1. Dye intercalation with this geometry is found to occur independently of the underlying DNA sequence, despite the known preference of TOTO for the nucleobase sequence CTAG. The non-intercalated subpopulation is inferred to have a mean inter-dye separation distance of 19 Å, corresponding to coupling strengths between 0 and 25 cm-1. This information is important to enable the rational design of energy transfer systems that utilize TOTO as a relay dye. The approach used here is generally applicable to determining the electronic coupling strength and intercalation configuration of other dimeric bis-intercalators.

An 'all pigment' model of excitation quenching in LHCII.

The rapid, photoprotective down-regulation of plant light-harvesting in bright light proceeds via the non-photochemical quenching of chlorophyll excitation energy in the major photosystem II light-harvesting complex LHCII. However, there is currently no consensus regarding the precise mechanism by which excess energy is quenched. Current X-ray structures of this complex correspond to a dissipative conformation and therefore correct microscopic theoretical modelling should capture this property. Despite their accuracy in explaining the steady state spectroscopy of this complex, chlorophyll-only models (those that neglect the energetic role of carotenoids) do not explain the observed fluorescence quenching. To address this gap, we have used a combination of the semi-empirical MNDO-CAS-CI and the Transition Density Cube method to model all chlorophyll-carotenoid energy transfer pathways in the highly quenched LHCII X-ray structure. Our simulations reveal that the inclusion of carotenoids in this microscopic model results in profound excitation quenching, reducing the predicted excitation lifetime of the complex from 4 ns (chlorophyll-only) to 67 ps. The model indicates that energy dissipation proceeds via slow excitation transfer (>20 ps) from chlorophyll to the forbidden S1 excited state of the centrally bound lutein molecules followed by the rapid (∼10 ps) radiationless decay to the ground state, with the latter being assumed from experimental measurements of carotenoid excited state lifetimes. Violaxanthin and neoxanthin do not contribute to this quenching. This work presents the first all-pigment microscopic model of LHCII and the first attempt to capture the dissipative character of the known structure.

Building an ab initio solvated DNA model using Euclidean neural networks.

Accurately modeling large biomolecules such as DNA from first principles is fundamentally challenging due to the steep computational scaling of ab initio quantum chemistry methods. This limitation becomes even more prominent when modeling biomolecules in solution due to the need to include large numbers of solvent molecules. We present a machine-learned electron density model based on a Euclidean neural network framework that includes a built-in understanding of equivariance to model explicitly solvated double-stranded DNA. By training the machine learning model using molecular fragments that sample the key DNA and solvent interactions, we show that the model predicts electron densities of arbitrary systems of solvated DNA accurately, resolves polarization effects that are neglected by classical force fields, and captures the physics of the DNA-solvent interaction at the ab initio level.

Computational determination of the pigment binding motif in the chlorosome protein a of green sulfur bacteria.

We present a molecular-scale model of Bacteriochlorophyll a (BChl a) binding to the chlorosome protein A (CsmA) of Chlorobaculum tepidum, and the aggregated pigment­protein dimer, as determined from protein­ligand docking and quantum chemistry calculations. Our calculations provide strong evidence that the BChl a molecule is coordinated to the His25 residue of CsmA, with the magnesium center of the bacteriochlorin ring situated\3 A° from the imidazole nitrogen atom of the histidine sidechain, and the phytyl tail aligned along the nonpolar residues of the a-helix of CsmA. We also confirm that the Qy band in the absorption spectra of BChl a experiences a large (?16 to ?43 nm) redshift when aggregated with another BChl a molecule in the CsmA dimer, compared to the BChl a in solvent; this redshift has been previously established by experimental researchers. We propose that our model of the BChl a­CsmA binding motif, where the dimer contains parallel aligned N-terminal regions, serves as the smallest repeating unit in a larger model of the para-crystalline chlorosome baseplate protein.

Automated sequence design of 2D wireframe DNA origami with honeycomb edges.

Wireframe DNA origami has emerged as a powerful approach to fabricating nearly arbitrary 2D and 3D geometries at the nanometer-scale. Complex scaffold and staple routing needed to design wireframe DNA origami objects, however, render fully automated, geometry-based sequence design approaches essential for their synthesis. And wireframe DNA origami structural fidelity can be limited by wireframe edges that are composed only of one or two duplexes. Here we introduce a fully automated computational approach that programs 2D wireframe origami assemblies using honeycomb edges composed of six parallel duplexes. These wireframe assemblies show enhanced structural fidelity from electron microscopy-based measurement of programmed angles compared with identical geometries programmed using dual-duplex edges. Molecular dynamics provides additional theoretical support for the enhanced structural fidelity observed. Application of our top-down sequence design procedure to a variety of complex objects demonstrates its broad utility for programmable 2D nanoscale materials.

Automated Sequence Design of 3D Polyhedral Wireframe DNA Origami with Honeycomb Edges.

3D polyhedral wireframe DNA nanoparticles (DNA-NPs) fabricated using scaffolded DNA origami offer complete and independent control over NP size, structure, and asymmetric functionalization on the 10-100 nm scale. However, the complex DNA sequence design needed for the synthesis of these versatile DNA-NPs has limited their widespread use to date. While the automated sequence design algorithms DAEDALUS and vHelix-BSCOR apply to DNA-NPs synthesized using either uniformly dual or hybrid single-dual duplex edges, respectively, these DNA-NPs are relatively compliant mechanically and are therefore of limited utility for some applications. Further, these algorithms are incapable of handling DNA-NP edge designs composed of more than two duplexes, which are needed to enhance DNA-NP mechanical stiffness. As an alternative, here we introduce the scaffolded DNA origami sequence design algorithm TALOS, which is a generalized procedure for the fully automated design of wireframe 3D polyhedra composed of edges of any cross section with an even number of duplexes, and apply it to DNA-NPs composed uniformly of single honeycomb edges. We also introduce a multiway vertex design that enables the fabrication of DNA-NPs with arbitrary edge lengths and vertex angles and apply it to synthesize a highly asymmetric origami object. Sequence designs are demonstrated to fold robustly into target DNA-NP shapes with high folding efficiency and structural fidelity that is verified using single particle cryo-electron microscopy and 3D reconstruction. In order to test its generality, we apply TALOS to design an  in silico library of over 200 DNA-NPs of distinct symmetries and sizes, and for broad impact, we also provide the software as open source for the generation of custom NP designs.

Programming Structured DNA Assemblies to Probe Biophysical Processes.

Structural DNA nanotechnology is beginning to emerge as a widely accessible research tool to mechanistically study diverse biophysical processes. Enabled by scaffolded DNA origami in which a long single strand of DNA is weaved throughout an entire target nucleic acid assembly to ensure its proper folding, assemblies of nearly any geometric shape can now be programmed in a fully automatic manner to interface with biology on the 1-100-nm scale. Here, we review the major design and synthesis principles that have enabled the fabrication of a specific subclass of scaffolded DNA origami objects called wireframe assemblies. These objects offer unprecedented control over the nanoscale organization of biomolecules, including biomolecular copy numbers, presentation on convex or concave geometries, and internal versus external functionalization, in addition to stability in physiological buffer. To highlight the power and versatility of this synthetic structural biology approach to probing molecular and cellular biophysics, we feature its application to three leading areas of investigation: light harvesting and nanoscale energy transport, RNA structural biology, and immune receptor signaling, with an outlook toward unique mechanistic insight that may be gained in these areas in the coming decade.

Fine control of chlorophyll-carotenoid interactions defines the functionality of light-harvesting proteins in plants.

Photosynthetic antenna proteins can be thought of as "programmed solvents", which bind pigments at specific mutual orientations, thus tuning the overall energetic landscape and ensuring highly efficient light-harvesting. While positioning of chlorophyll cofactors is well understood and rationalized by the principle of an "energy funnel", the carotenoids still pose many open questions. Particularly, their short excited state lifetime (<25 ps) renders them potential energy sinks able to compete with the reaction centers and drastically undermine light-harvesting efficiency. Exploration of the orientational phase-space revealed that the placement of central carotenoids minimizes their interaction with the nearest chlorophylls in the plant antenna complexes LHCII, CP26, CP29 and LHCI. At the same time we show that this interaction is highly sensitive to structural perturbations, which has a profound effect on the overall lifetime of the complex. This links the protein dynamics to the light-harvesting regulation in plants by the carotenoids.

Internal Conversion and Vibrational Energy Redistribution in Chlorophyll A.

We have computationally investigated the role of intramolecular vibrational modes in determining nonradiative relaxation pathways of photoexcited electronic states in isolated chlorophyll A (ChlA) molecules. To simulate the excited state relaxation from the initially excited Soret state to the lowest excited state Qy, the approach of nonadiabatic excited state molecular dynamics has been adopted. The intramolecular vibrational energy relaxation and redistribution that accompany the electronic internal conversion process is followed by analyzing the excited state trajectories in terms of the ground state equilibrium normal modes. The time dependence of the normal mode velocities is determined by projecting instantaneous Cartesian velocities onto the normal mode vectors. Our analysis of the time evolution of the average mode energies uncovers that only a small subset of the medium-to-high frequency normal modes actively participate in the electronic relaxation processes. These active modes are characterized by the highest overlap with the nonadiabatic coupling vectors (NACRs) during the electronic transitions. Further statistical analysis of the nonadiabatic transitions reveals that the electronic and vibrational energy relaxation occurs via two distinct pathways with significantly different time scales on which the hopping from Soret to Qx occurs thereby dictating the overall dynamics. Furthermore, the NACRs corresponding to each of the transitions have been consistently found to be predominantly similar to a set of normal modes that vary depending upon the transition and the identified categories. Each pathway exhibits a differential time scale of energy transfer and also a differential set of predominant active modes. Our present analysis can be considered as a general approach allowing identification of a reduced subset of specific vibrational coordinates associated with nonradiative relaxation pathways. Therefore, it represents an adequate prior strategy that can particularly facilitates mixed quantum-classical approaches.

Efficient pathways of excitation energy transfer from delocalized S2 excitons in the peridinin-chlorophyll a-protein complex.

Excitation energy transfer (EET) in peridinin-chlorophyll-protein (PCP) complexes is dominated by the S1 → Qy pathway, but the high efficiencies cannot be solely explained by this one pathway. We postulate that EET from peridinin S2 excitons may also be important. We use complete active space configuration interaction calculations and the transition density cube method to calculate Coulombic couplings between peridinin and chlorophyll a in the PCP complex of the dinoflagellate Amphidinium carterae and compare monomeric and dimeric delocalized peridinin S2 excited states. Our calculations show that the S2 → Qy EET pathway from peridinin to chlorophyll a is the dominant energy transfer pathway from the S2 excited state in PCP, with several values in the sub-picosecond range. This result suggests that the S2 → Qy EET pathway may be responsible for the reported chlorophyll a bleaching signature seen in experiment at around 200 fs, and not the S2 → Qx pathway as previously suggested.

Distortions of the Xanthophylls Caused by Interactions with Neighboring Pigments and the LHCII Protein Are Crucial for Studying Energy Transfer Pathways within the Complex.

It has been proposed that photoprotective non-photochemical quenching (NPQ) in higher plants arises from a conformational change in the antenna which alters pigment-pigment interactions. This brings about the formation of energy quenching "traps" that capture and dissipate excitation energy as heat. We have used the semiempirical AM1-CAS-CI method combined with the transition density cube (TDC) approach to model chlorophyll (Chl) to xanthophyll (Xanth) resonant Coulomb couplings in the crystal structure of LHCII. Due to its proposed role as the NPQ quenching site we have focused on lutein interactions and have explored how distortions to lutein conformation, as well as interpigment distances and relative orientations, affect this coupling. Our calculations indicate that distortions as well as Chl-lutein angle have a significant effect on coupling, whereas interpigment distances have a relatively minor effect. We therefore conclude that particular attention to the distortions of the Xanths should be given for calculation of energy transfer pathways and study of the NPQ mechanism.

Non-radiative relaxation of photoexcited chlorophylls: theoretical and experimental study.

Nonradiative relaxation of high-energy excited states to the lowest excited state in chlorophylls marks the first step in the process of photosynthesis. We perform ultrafast transient absorption spectroscopy measurements, that reveal this internal conversion dynamics to be slightly slower in chlorophyll B than in chlorophyll A. Modeling this process with non-adiabatic excited state molecular dynamics simulations uncovers a critical role played by the different side groups in the two molecules in governing the intramolecular redistribution of excited state wavefunction, leading, in turn, to different time-scales. Even given smaller electron-vibrational couplings compared to common organic conjugated chromophores, these molecules are able to efficiently dissipate about 1 eV of electronic energy into heat on the timescale of around 200 fs. This is achieved via selective participation of specific atomic groups and complex global migration of the wavefunction from the outer to inner ring, which may have important implications for biological light-harvesting function.

Excitation energy transfer in the peridinin-chlorophyll a-protein complex modeled using configuration interaction.

We modeled excitation energy transfer (EET) in the peridinin-chlorophyll a-protein (PCP) complex of dinoflagellate Amphidinium carterae to determine which pathways contribute dominantly to the high efficiency of this process. We used complete active space configuration interaction (CAS-CI) to calculate electronic structure properties of the peridinin (PID) and chlorophyll a (CLA) pigments in PCP and the transition density cube (TDC) method to calculate Coulombic couplings between energy transfer donors and acceptors. Our calculations show that the S1 → Qy EET pathway from peridinin to chlorophyll a is the dominant energy transfer pathway in PCP, with two sets of interactions-between PID612 and CLA601 and between PID622 and CLA602-contributing most strongly. EET lifetimes for these two interactions were calculated to be 2.66 and 2.90, with quantum efficiencies of 85.75 and 84.65%, respectively. The calculated Coulombic couplings for EET between two peridinin molecules in the strongly allowed S2 excited states are extremely large and suggest excitonic coupling between pairs of peridinin S2 states. This methodology is also broadly applicable to the study of EET in other photosynthetic complexes and/or organic photovoltaics, where both single and double excitations are present and donor and acceptor molecules are tightly packed.