Molecular dynamics simulations of DNA-DNA and DNA-protein interactions

Transient interactions modulate the affinity of NF-κB transcription factors for DNA

The dimeric nuclear factor kappa B (NF-κB) transcription factors (TFs) regulate gene expression by binding to a variety of κB DNA elements with conserved G:C-rich flanking sequences enclosing a degenerate central region. Toward defining mechanistic principles of affinity regulated by degeneracy, we observed an unusual dependence of the affinity of RelA on the identity of the central base pair, which appears to be noncontacted in the complex crystal structures. The affinity of κB sites with A or T at the central position is ~10-fold higher than with G or C. The crystal structures of neither the complexes nor the free κB DNAs could explain the differences in affinity. Interestingly, differential dynamics of several residues were revealed in molecular dynamics simulation studies, where simulation replicates totaling 148 μs were performed on NF-κB:DNA complexes and free κB DNAs. Notably, Arg187 and Arg124 exhibited selectivity in transient interactions that orchestrated a complex interplay among several DNA-interacting residues in the central region. Binding and simulation studies with mutants supported these observations of transient interactions dictating specificity. In combination with published reports, this work provides insights into the nuanced mechanisms governing the discriminatory binding of NF-κB family TFs to κB DNA elements and sheds light on cancer pathogenesis of cRel, a close homolog of RelA.

MDverse: Shedding Light on the Dark Matter of Molecular Dynamics Simulations

The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the dark matter of MD - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2,000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identified systems with specific molecular composition and were able to characterize essential parameters of MD simulation such as temperature and simulation length, and could identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore the MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and to report and standardize metadata to reuse this valuable matter.

The structure and physical properties of a packaged bacteriophage particle

A string of nucleotides confined within a protein capsid contains all the instructions necessary to make a functional virus particle, a virion. Although the structure of the protein capsid is known for many virus species1,2, the three-dimensional organization of viral genomes has mostly eluded experimental probes3,4. Here we report all-atom structural models of an HK97 virion5, including its entire 39,732 base pair genome, obtained through multiresolution simulations. Mimicking the action of a packaging motor6, the genome was gradually loaded into the capsid. The structure of the packaged capsid was then refined through simulations of increasing resolution, which produced a 26 million atom model of the complete virion, including water and ions confined within the capsid. DNA packaging occurs through a loop extrusion mechanism7 that produces globally different configurations of the packaged genome and gives each viral particle individual traits. Multiple microsecond-long all-atom simulations characterized the effect of the packaged genome on capsid structure, internal pressure, electrostatics and diffusion of water, ions and DNA, and revealed the structural imprints of the capsid onto the genome. Our approach can be generalized to obtain complete all-atom structural models of other virus species, thereby potentially revealing new drug targets at the genome-capsid interface.

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.

A Novel Fractional Brownian Dynamics Method for Simulating the Dynamics of Confined Bottle-Brush Polymers in Viscoelastic Solution

In crowded fluids, polymer segments can exhibit anomalous subdiffusion due to the viscoelasticity of the surrounding environment. Previous single-particle tracking experiments revealed that such anomalous diffusion in complex fluids (e.g., in bacterial cytoplasm) can be described by fractional Brownian motion (fBm). To investigate how the viscoelastic media affects the diffusive behaviors of polymer segments without resolving single crowders, we developed a novel fractional Brownian dynamics method to simulate the dynamics of polymers under confinement. In this work, instead of using Gaussian random numbers ("white Gaussian noise") to model the Brownian force as in the standard Brownian dynamics simulations, we introduce fractional Gaussian noise (fGn) in our homemade fractional Brownian dynamics simulation code to investigate the anomalous diffusion of polymer segments by using a simple "bottle-brush"-type polymer model. The experimental results of the velocity autocorrelation function and the exponent that characterizes the subdiffusion of the confined polymer segments can be reproduced by this simple polymer model in combination with fractional Gaussian noise (fGn), which mimics the viscoelastic media.

Brewing COFFEE: A Sequence-Specific Coarse-Grained Energy Function for Simulations of DNA-Protein Complexes

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription and gene expression to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse-grained Force Field for Energy Estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the self-organized polymer model with side-chains for proteins and the three interaction site model for DNA in a modular fashion, without recalibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a data set of high-resolution crystal structures. The only parameter in COFFEE is the strength (λDNAPRO) of the DNA-protein contact potential. For an optimal choice of λDNAPRO, the crystallographic B-factors for DNA-protein complexes with varying sizes and topologies are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts scattering profiles that are in quantitative agreement with small-angle X-ray scattering experiments, as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which do not alter the balance of electrostatic interactions but affect chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

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.

Modeling genotype-protein interaction and correlation for Alzheimer's disease: a multi-omics imaging genetics study

Integrating and analyzing multiple omics data sets, including genomics, proteomics and radiomics, can significantly advance researchers' comprehensive understanding of Alzheimer's disease (AD). However, current methodologies primarily focus on the main effects of genetic variation and protein, overlooking non-additive effects such as genotype-protein interaction (GPI) and correlation patterns in brain imaging genetics studies. Importantly, these non-additive effects could contribute to intermediate imaging phenotypes, finally leading to disease occurrence. In general, the interaction between genetic variations and proteins, and their correlations are two distinct biological effects, and thus disentangling the two effects for heritable imaging phenotypes is of great interest and need. Unfortunately, this issue has been largely unexploited. In this paper, to fill this gap, we propose $\textbf{M}$ulti-$\textbf{T}$ask $\textbf{G}$enotype-$\textbf{P}$rotein $\textbf{I}$nteraction and $\textbf{C}$orrelation disentangling method ($\textbf{MT-GPIC}$) to identify GPI and extract correlation patterns between them. To ensure stability and interpretability, we use novel and off-the-shelf penalties to identify meaningful genetic risk factors, as well as exploit the interconnectedness of different brain regions. Additionally, since computing GPI poses a high computational burden, we develop a fast optimization strategy for solving MT-GPIC, which is guaranteed to converge. Experimental results on the Alzheimer's Disease Neuroimaging Initiative data set show that MT-GPIC achieves higher correlation coefficients and classification accuracy than state-of-the-art methods. Moreover, our approach could effectively identify interpretable phenotype-related GPI and correlation patterns in high-dimensional omics data sets. These findings not only enhance the diagnostic accuracy but also contribute valuable insights into the underlying pathogenic mechanisms of AD.

Exploration of the Character Representation of DNA Chiral Conformations and Deformations via a Curved Surface Discrete Frenet Frame

While undergoing structural deformation, DNA experiences changes in the interactions between its internal base pairs, presenting challenges to conventional elastic methods. To address this, we propose the Discrete Critical State (DCS) model in this paper. This model combines surface discrete frame theory with gauge theory and Landau phase transition theory to investigate DNA's structural deformation, phase transitions, and chirality. Notably, the DCS model considers both the internal interactions within DNA and formulates an overall equation using unified physical and geometric parameters. By employing the discrete frame, we derive the evolution of physical quantities along the helical axis of DNA, including geodesic curvature, geodesic torsion, and others. Our findings indicate that B-DNA has a significantly lower free energy density compared to Z-DNA, which is in agreement with experimental observations. This research reveals that the direction of base pairs is primarily governed by the geodesic curve within the helical plane, aligning closely with the orientation of the base pairs. Moreover, the geodesic curve has a profound influence on the arrangement of base pairs at the microscopic level and effectively regulates the configuration and geometry of DNA through macroscopic-level free energy considerations.

Kinetics of radiation-induced DNA double-strand breaks through coarse-grained simulations

Double-strand breaks (DSBs), i.e., the covalent cut of the DNA backbone over both strands, are a detrimental outcome of cell irradiation, bearing chromosomal aberrations and leading to cell apoptosis. In the early stages of the evolution of a DSB, the disruption of the residual interactions between the DNA moieties drives the fracture of the helical layout; in spite of its biological significance, the details of this process are still largely uncertain. Here, we address the mechanical rupture of DNA by DSBs via coarse-grained molecular dynamics simulations: the setup involves a 3855-bp DNA filament and diverse DSB motifs, i.e., within a range of distances between strand breaks (or DSB distance). By employing a coarse-grained model of DNA, we access the molecular details and characteristic timescales of the rupturing process. A sequence-nonspecific, linear correlation is observed between the DSB distance and the internal energy contribution to the disruption of the residual (Watson-Crick and stacking) contacts between DNA moieties, which is seemingly driven by an abrupt, cooperative process. Moreover, we infer an exponential dependence of the characteristic rupture times on the DSB distances, which we associate to an Arrhenius-like law of thermally-activated processes. This work lays the foundations of a detailed, mechanistic assessment of DSBs in silico as a benchmark to both numerical simulations and data from single-molecule experiments.

Brewing COFFEE: A sequence-specific coarse-grained energy function for simulations of DNA-protein complexes

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription, gene expression, to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse grained force field for energy estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the Self-Organized Polymer model with Side Chains for proteins and the Three Interaction Site model for DNA in a modular fashion, without re-calibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a dataset of high-resolution crystal structures. The only parameter in COFFEE is the strength (λ D N A P R O ) of the DNA-protein contact potential. For an optimal choice of λ D N A P R O , the crystallographic B-factors for DNA-protein complexes, with varying sizes and topologies, are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts the scattering profiles that are in quantitative agreement with SAXS experiments as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which does not alter the balance of electrostatic interactions, but affects chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

Oligonucleotide nanoassemblies with allyl bromide scaffold-based small molecules

The development of oligonucleotide nanoassemblies with small molecules has shown great potential in bio-medical applications. However, the interaction of negatively charged oligonucleotides with halogenated small molecules represents a scientific challenge. Here, we introduced a distinct allyl bromide halogenated scaffold, which exhibits specific interaction with adenine nucleic bases of the oligonucleotides, thus leading to the formation of self-assembled nanostructures.

The nucleotide excision repair proteins through the lens of molecular dynamics simulations

Mutations that affect the proteins responsible for the nucleotide excision repair (NER) pathway can lead to diseases such as xeroderma pigmentosum, trichothiodystrophy, Cockayne syndrome, and Cerebro-oculo-facio-skeletal syndrome. Hence, understanding their molecular behavior is needed to elucidate these diseases' phenotypes and how the NER pathway is organized and coordinated. Molecular dynamics techniques enable the study of different protein conformations, adaptable to any research question, shedding light on the dynamics of biomolecules. However, as important as they are, molecular dynamics studies focused on DNA repair pathways are still becoming more widespread. Currently, there are no review articles compiling the advancements made in molecular dynamics approaches applied to NER and discussing: (i) how this technique is currently employed in the field of DNA repair, focusing on NER proteins; (ii) which technical setups are being employed, their strengths and limitations; (iii) which insights or information are they providing to understand the NER pathway or NER-associated proteins; (iv) which open questions would be suited for this technique to answer; and (v) where can we go from here. These questions become even more crucial considering the numerous 3D structures published regarding the NER pathway's proteins in recent years. In this work, we tackle each one of these questions, revising and critically discussing the results published in the context of the NER pathway.

Atomistic Picture of Opening-Closing Dynamics of DNA Holliday Junction Obtained by Molecular Simulations

Holliday junction (HJ) is a noncanonical four-way DNA structure with a prominent role in DNA repair, recombination, and DNA nanotechnology. By rearranging its four arms, HJ can adopt either closed or open state. With enzymes typically recognizing only a single state, acquiring detailed knowledge of the rearrangement process is an important step toward fully understanding the biological function of HJs. Here, we carried out standard all-atom molecular dynamics (MD) simulations of the spontaneous opening-closing transitions, which revealed complex conformational transitions of HJs with an involvement of previously unconsidered "half-closed" intermediates. Detailed free-energy landscapes of the transitions were obtained by sophisticated enhanced sampling simulations. Because the force field overstabilizes the closed conformation of HJs, we developed a system-specific modification which for the first time allows the observation of spontaneous opening-closing HJ transitions in unbiased MD simulations and opens the possibilities for more accurate HJ computational studies of biological processes and nanomaterials.

Stability of End-to-End Base Stacking Interactions in Highly Concentrated DNA Solutions

Positionally ordered bilayer liquid crystalline nanostructures formed by gapped DNA (GDNA) constructs provide a practical window into DNA-DNA interactions at physiologically relevant DNA concentrations; concentrations several orders of magnitude greater than those in commonly used biophysical assays. The bilayer structure of these states of matter is stabilized by end-to-end base stacking interactions; moreover, such interactions also promote in-plane positional ordering of duplexes that are separated from each other by less than twice the duplex diameter. The end-to-end stacked as well as in-plane ordered duplexes exhibit distinct signatures when studied via small-angle X-ray scattering (SAXS). This enables analysis of the thermal stability of both the end-to-end and side-by-side interactions. We performed synchrotron SAXS experiments over a temperature range of 5-65 °C on GDNA constructs that differ only by the terminal base-pairs at the blunt duplex ends, resulting in identical side-by-side interactions, while end-to-end base stacking interactions are varied. Our key finding is that bilayers formed by constructs with GC termination transition into the monolayer state at temperatures as much as 30 °C higher than for those with AT termination, while mixed (AT/GC) terminations have intermediate stability. By modeling the bilayer melting in terms of a temperature-dependent reduction in the average fraction of end-to-end paired duplexes, we estimate the stacking free energies in DNA solutions of physiologically relevant concentrations. The free-energies thereby determined are generally smaller than those reported in single-molecule studies, which might reflect the elevated DNA concentrations in our studies.

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.

Intra-Domain Residue Coevolution in Transcription Factors Contributes to DNA Binding Specificity

Understanding the basis of the DNA-binding specificity of transcription factors (TFs) has been of long-standing interest. Despite extensive efforts to map millions of putative TF binding sequences, identifying the critical determinants for DNA binding specificity remains a major challenge. The coevolution of residues in proteins occurs due to a shared evolutionary history. However, it is unclear how coevolving residues in TFs contribute to DNA binding specificity. Here, we systematically collected publicly available data sets from multiple large-scale high-throughput TF-DNA interaction screening experiments for the major TF families with large numbers of TF members. These families included the Homeobox, HLH, bZIP_1, Ets, HMG_box, ZF-C4, and Zn_clus TFs. We detected TF subclass-determining sites (TSDSs) and showed that the TSDSs were more likely to coevolve with other TSDSs than with non-TSDSs, particularly for the Homeobox, HLH, Ets, bZIP_1, and HMG_box TF families. By in silico modeling, we showed that mutation of the highly coevolving residues could significantly reduce the stability of the TF-DNA complex. The distant residues from the DNA interface also contributed to TF-DNA binding activity. Overall, our study gave evidence that coevolved residues relate to transcriptional regulation and provided insights into the potential application of engineered DNA-binding domains and proteins. IMPORTANCE While unraveling DNA-binding specificity of TFs is the key to understanding the basis and molecular mechanism of gene expression regulation, identifying the critical determinants that contribute to DNA binding specificity remains a major challenge. In this study, we provided evidence showing that coevolving residues in TF domains contributed to DNA binding specificity. We demonstrated that the TSDSs were more likely to coevolve with other TSDSs than with non-TSDSs. Mutation of the coevolving residue pairs (CRPs) could significantly reduce the stability of THE TF-DNA complex, and even the distant residues from the DNA interface contribute to TF-DNA binding activity. Collectively, our study expands our knowledge of the interactions among coevolved residues in TFs, tertiary contacting, and functional importance in refined transcriptional regulation. Understanding the impact of coevolving residues in TFs will help understand the details of transcription of gene regulation and advance the application of engineered DNA-binding domains and protein.

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.

NARall: a novel tool for reconstruction of the all-atom structure of nucleic acids from heavily coarse-grained model

Nucleic acids are one of the most important cellular components. These molecules have been studied both experimentally and theoretically. As all-atom simulations are still limited to short time scales, coarse-grain modeling allows to study of those molecules on a longer time scale. Nucleic-Acid united RESidue (NARES-2P) is a low-resolution coarse-grained model with two centers of interaction per repeating unit. It has been successfully applied to study DNA self-assembly and telomeric properties. This force field enables the study of nucleic acids Behavior on a long time scale but lacks atomistic details. In this article, we present new software to reconstruct atomistic details from the NARES-2P model. It has been applied to RNA pseudoknot, nucleic acid four-way junction, G-quadruplex and DNA duplex converted to NARES-2P model and back. Moreover, it was applied to DNA structure folded and self-assembled with NARES-2P.

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.

Effects of External Perturbations on Protein Systems: A Microscopic View

Protein folding can be viewed as the origami engineering of biology resulting from the long process of evolution. Even decades after its recognition, research efforts worldwide focus on demystifying molecular factors that underlie protein structure-function relationships; this is particularly relevant in the era of proteopathic disease. A complex co-occurrence of different physicochemical factors such as temperature, pressure, solvent, cosolvent, macromolecular crowding, confinement, and mutations that represent realistic biological environments are known to modulate the folding process and protein stability in unique ways. In the current review, we have contextually summarized the substantial efforts in unveiling individual effects of these perturbative factors, with major attention toward bottom-up approaches. Moreover, we briefly present some of the biotechnological applications of the insights derived from these studies over various applications including pharmaceuticals, biofuels, cryopreservation, and novel materials. Finally, we conclude by summarizing the challenges in studying the combined effects of multifactorial perturbations in protein folding and refer to complementary advances in experiment and computational techniques that lend insights to the emergent challenges.

Spontaneous binding of single-stranded RNAs to RRM proteins visualized by unbiased atomistic simulations with a rescaled RNA force field

Recognition of single-stranded RNA (ssRNA) by RNA recognition motif (RRM) domains is an important class of protein-RNA interactions. Many such complexes were characterized using nuclear magnetic resonance (NMR) and/or X-ray crystallography techniques, revealing ensemble-averaged pictures of the bound states. However, it is becoming widely accepted that better understanding of protein-RNA interactions would be obtained from ensemble descriptions. Indeed, earlier molecular dynamics simulations of bound states indicated visible dynamics at the RNA-RRM interfaces. Here, we report the first atomistic simulation study of spontaneous binding of short RNA sequences to RRM domains of HuR and SRSF1 proteins. Using a millisecond-scale aggregate ensemble of unbiased simulations, we were able to observe a few dozen binding events. HuR RRM3 utilizes a pre-binding state to navigate the RNA sequence to its partially disordered bound state and then to dynamically scan its different binding registers. SRSF1 RRM2 binding is more straightforward but still multiple-pathway. The present study necessitated development of a goal-specific force field modification, scaling down the intramolecular van der Waals interactions of the RNA which also improves description of the RNA-RRM bound state. Our study opens up a new avenue for large-scale atomistic investigations of binding landscapes of protein-RNA complexes, and future perspectives of such research are discussed.

Dynamic Intramolecular Cap for Preserving Metallodrug Integrity─A Case of Catalytic Fluoroquinolones

A library of eight new fluoroquinolone-nuclease conjugates containing a guanidinoethyl or aminoethyl auxiliary pendant on the cyclen moiety was designed and synthesized to investigate their potential for overcoming the general issue of "metallodrug vulnerability" under physiological conditions. The Cu(II) and Co(III) complexes of the new designer compounds were synthesized, and their potential to operate a dynamic, intramolecular cap with DNase activity was explored. The lead Co(III)-cyclen-ciprofloxacin conjugate showed excellent in vitro hydrolytic DNase activity, which was retained in the presence of strong endogenous chelators and exhibited enhanced antibacterial activity relative to the metal-free ligand (in the absence of any adjuvants), thereby demonstrating a "proof of concept" in vitro and ex vivo, respectively, for the dynamic cap hypothesis. The lead conjugate nicked supercoiled plasmid DNA within the fluoroquinolone-gyrase-DNA ternary complex and thereby disabled the function of gyrase, a new mode of action not previously reported for any fluoroquinolone.

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.

Protein-Nucleic Acid Interactions for RNA Polymerase II Elongation Factors by Molecular Dynamics Simulations

RNA polymerase II (Pol II) forms a complex with elongation factors to proceed to the elongation stage of the transcription process. In this work, we studied the elongation factor SPT5 and explored the protein-nucleic acid interactions for the isolated systems of KOW1 and KOW4 domains of SPT5 with DNA and RNA, respectively. We performed molecular dynamics (MD) simulations using three commonly used force fields that are CHARMM c36m, AMBER ff14sb, and ff19sb. Simulations showed strong protein-nucleic acid interactions and low electrostatic binding free energies for all force fields used. RNA was found to be highly dynamic with all force fields, while DNA had relatively more stable conformations with the AMBER force fields compared to that with CHARMM. Furthermore, we performed MD simulations of the complete elongation complex using CHARMM c36m and AMBER ff19sb force fields to compare the dynamics and interactions with the isolated systems. Similarly, strong KOW1 and DNA interactions were observed in the complete elongation complex simulations and DNA was further stabilized by a network of interactions involving SPT5-KOW1, SPT4, and rpb2 of Pol II. Overall, our study showed that the differences between CHARMM and AMBER force fields strongly affect the dynamics of the nucleic acids. CHARMM provides highly flexible DNA, while AMBER largely stabilizes the DNA structure. Although the presence of the entire interaction network stabilized the DNA and decreased the differences in the results from the two force fields, the discrepancies of the force fields for smaller systems may reflect their problems in generating accurate dynamics of nucleic acids.

A Critical Review on the Sensing, Control, and Manipulation of Single Molecules on Optofluidic Devices

Single-molecule techniques have shifted the paradigm of biological measurements from ensemble measurements to probing individual molecules and propelled a rapid revolution in related fields. Compared to ensemble measurements of biomolecules, single-molecule techniques provide a breadth of information with a high spatial and temporal resolution at the molecular level. Usually, optical and electrical methods are two commonly employed methods for probing single molecules, and some platforms even offer the integration of these two methods such as optofluidics. The recent spark in technological advancement and the tremendous leap in fabrication techniques, microfluidics, and integrated optofluidics are paving the way toward low cost, chip-scale, portable, and point-of-care diagnostic and single-molecule analysis tools. This review provides the fundamentals and overview of commonly employed single-molecule methods including optical methods, electrical methods, force-based methods, combinatorial integrated methods, etc. In most single-molecule experiments, the ability to manipulate and exercise precise control over individual molecules plays a vital role, which sometimes defines the capabilities and limits of the operation. This review discusses different manipulation techniques including sorting and trapping individual particles. An insight into the control of single molecules is provided that mainly discusses the recent development of electrical control over single molecules. Overall, this review is designed to provide the fundamentals and recent advancements in different single-molecule techniques and their applications, with a special focus on the detection, manipulation, and control of single molecules on chip-scale devices.

Understanding the binding behavior of Malathion with calf thymus DNA by spectroscopic, cell viability and molecular dynamics simulation techniques: binary and ternary systems comparison

The interaction between calf thymus DNA (ctDNA) and Malathion in the absence and presence of Histone 1 has been enquired by the means of spectroscopic, viscometry, molecular modeling, and cell viability assay techniques. Malathion is capable of quenching the fluorescence of ct DNA in the absence and presence of H1. The binding constants of Malathion-ctDNA complex in the absence of H1 have been calculated to be 6.62 × 10⁴, 4.31 × 10⁴ and 1.93 × 10⁴ M^-1 at 298, 303, and 308 K, respectively that revealed static quenching in complex formation. The observed negative values of enthalpy and entropy changes indicate that the main binding interaction forces were van der Waals force and hydrogen bonding. The binding constant between Malathion and single-stranded ctDNA (ss ctDNA) seemed to be much weaker than that of Malathion and double-stranded ctDNA (ds ctDNA). Furthermore, Malathion can induce detectable alterations in the CD spectrum of ctDNA, along with changes in its viscosity. In the presence of H1, fluorescence quenching of ctDNA-Malathion complex displays dynamic behavior and binding constants were perceived to be 1.66 × 10⁴, 2.93 × 10⁴ and 5.77 × 10⁴ M^-1 at 298, 303, and 308 K, respectively. The different of interaction behavior between ctDNA and Malathion in the absence and presence of H1 clearly revealed H1 role in the complex formation and forces change between ctDNA and Malathion. The positive values of enthalpy and entropy changes have suggested that binding process is primarily driven by hydrophobic interactions. The tendency to interact with ss ctDNA, reduced viscosity have designated that the Malathion bound to ctDNA in the presence of H1 is groove binding. The results of molecular docking and molecular dynamics simulation also confirmed potent interactions between Malathion and the macromolecules in the binary and ternary systems.Communicated by Ramaswamy H. Sarma.

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.

Unusual Pseudopeptides: Syntheses and Structural Analyses of Ethylenediprolyl Peptides and Their Metal Complexes with Cu(II) Ion

The synthetic unnatural amino acids and their peptides as peptidomimetics have shown remarkable structural and functional properties. In the repertoire of synthetic peptides, pseudopeptides have emerged as attractive small peptidomimetics that are capable of forming the characteristic secondary structures in the solid/solution phase, as in natural peptides. This report describes the synthesis and structural analyses of novel pseudopeptides as ethylenediprolyl (etpro) tetra/hexapeptides, comprising a chiral diaminedicarboxylate scaffold. Their NMR and CD spectral analyses strongly support the formation of the β-turn-type structures in organic solvents (ACN/MeOH). Further, the single-crystal X-ray studies of tetrapseudopeptide confirm the formation of a unique self-assembly structure as β-strand type in the solid state through hydrogen bonding. Importantly, their diamine moiety influences the formation of Cu-complexes with Cu(II) ions. A tetrapseudopeptide monocarboxylate-Cu(II) complex forms the single crystal that is studied by the single-crystal X-ray diffractometer. The crystal structure of the tetrapseudopeptide-Cu(II) complex confirms the formation of the distorted square planar geometry structure, almost like the amyloid β(Aβ)-peptide-Cu(II) complex structural geometry. Hence, these etpro-pseudopeptides are emerging peptidomimatics that form β-turn types of structures and metal complexes mainly with Cu(II) ions. These molecules could be considered for the development of peptide-based catalysts and peptide-based therapeutic drug candidates.

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.

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

An accurate molecular mechanics force field forms the basis of Molecular Dynamics simulations to obtain a realistic view of the structure and dynamics of biomolecules such as DNA. Although frequently updated to improve agreement with available experimental data, DNA force fields still rely in part on parameters introduced more than 20 years ago. We have developed an entirely new DNA force field, Tumuc1, derived from quantum mechanical calculations to obtain a consistent set of bonded parameters and partial atomic charges. The performance of the force field was extensively tested on a variety of DNA molecules. It excels in accuracy of B-DNA simulations but also performs very well on other types of DNA structures and structure formation processes such as hairpin folding, duplex formation, and dynamics of DNA-protein complexes. It can complement existing force fields in order to provide an increasingly accurate description of the structure and dynamics of DNA during simulation studies.

Molecular mechanism of methyl-dependent and spatial-specific DNA recognition of c-Jun homodimer

DNA methylation is important in regulation of gene expression and normal development because it alters the interplay between protein and DNA. Experiments have shown that a single 5-methylcytosine at different CpG sites (mCpG) might have different effects on specific recognition, but the atomistic origin and dynamic details are largely unclear. In this work, we investigated the mechanism of monomethylation at different CpG sites in the cognate motif and the cooperativity of full methylation. By constructing four models of c-Jun/Jun protein binding to the 5[Formula: see text]-XGAGTCA-3[Formula: see text] (X represents C or methylated C) motif, we characterized the dynamics of the contact interface using the all-atom molecular dynamics method. Free energy analysis of MM/GBSA suggests that regardless of whether the C12pG13 site of the bottom strand is methylated, the effects from mC25 of the top strand are dominant and can moderately enhance the binding by [Formula: see text] 31 kcal/mol, whereas mC12 showed a relatively small contribution, in agreement with the experimental data. Remarkably, we found that this spatial-specific influence was induced by different regulatory rules. The influence of the mC25 site is mainly mediated by steric hindrance. The additional methyl group leads to the conformational changes in nearby residues and triggers an obvious structural bending in the protein, which results in the formation of a new T-Asn-C triad that enhances the specific recognition of TCA half-sites. The substitution of the methyl group at the mC12 site of the bottom strand breaks the original H-bonds directly. Such changes in electrostatic interactions also lead to the remote allosteric effects of protein by multifaceted interactions but have negligible contributions to binding. Although these two influence modes are different, they can both fine-tune the local environment, which might produce remote allosteric effects through protein-protein interactions. Further analysis reveals that the discrepancies in these two modes are primarily due to their location. Moreover, when both sites are methylated, the major determinant of binding specificity depends on the context and the location of the methylation site, which is the result of crosstalk and cooperativity.

The N-terminal Helix-Turn-Helix Motif of Transcription Factors MarA and Rob Drives DNA Recognition

DNA-binding proteins play an important role in gene regulation and cellular function. The transcription factors MarA and Rob are two homologous members of the AraC/XylS family that regulate multidrug resistance. They share a common DNA-binding domain, and Rob possesses an additional C-terminal domain that permits binding of low-molecular weight effectors. Both proteins possess two helix-turn-helix (HTH) motifs capable of binding DNA; however, while MarA interacts with its promoter through both HTH-motifs, prior studies indicate that Rob binding to DNA via a single HTH-motif is sufficient for tight binding. In the present work, we perform microsecond time scale all-atom simulations of the binding of both transcription factors to different DNA sequences to understand the determinants of DNA recognition and binding. Our simulations characterize sequence-dependent changes in dynamical behavior upon DNA binding, showcasing the role of Arg40 of the N-terminal HTH-motif in allowing for specific tight binding. Finally, our simulations demonstrate that an acidic C-terminal loop of Rob can control the DNA binding mode, facilitating interconversion between the distinct DNA binding modes observed in MarA and Rob. In doing so, we provide detailed molecular insight into DNA binding and recognition by these proteins, which in turn is an important step toward the efficient design of antivirulence agents that target these proteins.

Simulating Peptide Monolayer Formation: GnRH-I on Silica

Molecular dynamics (MD) simulations can provide a detailed view of molecule behaviour at an atomic level, which can be useful when attempting to interpret experiments or design new systems. The decapeptide gonadotrophin-releasing hormone I (GnRH-I) is known to control fertility in mammals for both sexes. It was previously shown that inoculation with silica nanoparticles (SiNPs) coated with GnRH-I makes an effective anti-fertility vaccine due to how the peptide adsorbs to the nanoparticle and is presented to the immune system. In this paper, we develop and employ a protocol to simulate the development of a GnRH-I peptide adlayer by allowing peptides to diffuse and adsorb in a staged series of trajectories. The peptides start the simulation in an immobile state in solution above the model silica surface, and are then released sequentially. This facile approach allows the adlayer to develop in a natural manner and appears to be quite versatile. We find that the GnRH-I adlayer tends to be sparse, with electrostatics dominating the interactions. The peptides are collapsed to the surface and are seemingly free to interact with additional solutes, supporting the interpretations of the GNRH-I/SiNP vaccine system.

A Bit Stickier, a Bit Slower, a Lot Stiffer: Specific vs. Nonspecific Binding of Gal4 to DNA

Transcription factors regulate gene activity by binding specific regions of genomic DNA thanks to a subtle interplay of specific and nonspecific interactions that is challenging to quantify. Here, we exploit Reflective Phantom Interface (RPI), a label-free biosensor based on optical reflectivity, to investigate the binding of the N-terminal domain of Gal4, a well-known gene regulator, to double-stranded DNA fragments containing or not its consensus sequence. The analysis of RPI-binding curves provides interaction strength and kinetics and their dependence on temperature and ionic strength. We found that the binding of Gal4 to its cognate site is stronger, as expected, but also markedly slower. We performed a combined analysis of specific and nonspecific binding—equilibrium and kinetics—by means of a simple model based on nested potential wells and found that the free energy gap between specific and nonspecific binding is of the order of one kcal/mol only. We investigated the origin of such a small value by performing all-atom molecular dynamics simulations of Gal4–DNA interactions. We found a strong enthalpy–entropy compensation, by which the binding of Gal4 to its cognate sequence entails a DNA bending and a striking conformational freezing, which could be instrumental in the biological function of Gal4.

DNA Nanodevices as Mechanical Probes of Protein Structure and Function

DNA nanotechnology has reported a wide range of structurally tunable scaffolds with precise control over their size, shape and mechanical properties. One promising application of these nanodevices is as probes for protein function or determination of protein structure. In this perspective we cover several recent examples in this field, including determining the effect of ligand spacing and multivalency on cell activation, applying forces at the nanoscale, and helping to solve protein structure by cryo-EM. We also highlight some future directions in the chemistry necessary for integrating proteins with DNA nanoscaffolds, as well as opportunities for computational modeling of hybrid protein-DNA nanomaterials.

Highlighting the potential utility of MBP crystallization chaperone for Arabidopsis BIL1/BZR1 transcription factor-DNA complex

The maltose-binding protein (MBP) fusion tag is one of the most commonly utilized crystallization chaperones for proteins of interest. Recently, this MBP-mediated crystallization technique was adapted to Arabidopsis thaliana (At) BRZ-INSENSITIVE-LONG (BIL1)/BRASSINAZOLE-RESISTANT (BZR1), a member of the plant-specific BZR TFs, and revealed the first structure of AtBIL1/BZR1 in complex with target DNA. However, it is unclear how the fused MBP affects the structural features of the AtBIL1/BZR1-DNA complex. In the present study, we highlight the potential utility of the MBP crystallization chaperone by comparing it with the crystallization of unfused AtBIL1/BZR1 in complex with DNA. Furthermore, we assessed the validity of the MBP-fused AtBIL1/BZR1-DNA structure by performing detailed dissection of crystal packings and molecular dynamics (MD) simulations with the removal of the MBP chaperone. Our MD simulations define the structural basis underlying the AtBIL1/BZR1-DNA assembly and DNA binding specificity by AtBIL1/BZR1. The methodology employed in this study, the combination of MBP-mediated crystallization and MD simulation, demonstrates promising capabilities in deciphering the protein-DNA recognition code.

Assessment of AMBER Force Fields for Simulations of ssDNA

Single-stranded DNA (ssDNA) plays an important role in biological processes and is used in DNA nanotechnology and other novel applications. Many important research questions can be addressed with molecular simulations of ssDNA molecules; however, no dedicated force field for ssDNA has been developed, and there is limited experimental information about ssDNA structures. This study assesses the accuracy and applicability of existing Amber force fields for all-atom simulations of ssDNA, such as ff99, bsc0, bsc1, and OL15, in implicit and explicit solvents via comparison to available experimental data, such as Forster resonance energy transfer and small angle X-ray scattering. We observed that some force fields agree better with experiments than others mainly due to the difference in parameterization of the propensity for hydrogen bonding and base stacking. Overall, the Amber ff99 force field in the IGB5 or IGB8 implicit solvent and the bsc1 force field in the explicit TIP3P solvent had the best agreement with experiment.