Extended magnesium and calcium force field parameters for accurate ion-nucleic acid interactions in biomolecular simulations

Binding of Phosphate Species to Ca2+ and Mg2+ in Aqueous Solution

Phosphate derivatives and their interaction with metal cations are involved in many important biological phenomena, so an accurate characterization of the phosphate-metal interaction is necessary to properly understand the role of phosphate-metal contacts in mediating biological function. Herein, we improved the standard 12-6 Lennard-Jones (LJ) potential via the usage of the 12-6-4 LJ model, which incorporates ion-induced dipole interactions. Via parameter scanning, we fine-tuned the 12-6-4 LJ polarizability values to obtain accurate absolute binding free energies for the phosphate anions H2PO4-, HPO42-, PO43- coordinating with Ca2+ and Mg2+. First, we modified the phosphate 12-6-4 LJ parameters to reproduce the solvation free energies of the series of phosphate anions using the thermodynamic integration (TI) method. Then, using the potential mean force (PMF) method, the polarizability of the metal-phosphate interaction was obtained. We show that the free energy profiles of phosphate ions coordinated to Ca2+ and Mg2+ generally show similar trends at longer metal-phosphate distances, while the absolute binding energy values increased with deprotonation. The resulting parameters demonstrate the flexibility of the 12-6-4 LJ-type nonbonded model and its usefulness in accurately describing cation-anion interactions.

Micronutrient Status and Breast Cancer: A Narrative Review

Breast cancer is one of the most common cancers worldwide, at the same time being one of the most prevalent causes of women's death. Many factors such as alcohol, weight fluctuations, or hormonal replacement therapy can potentially contribute to breast cancer development and progression. Another important factor in breast cancer onset includes micronutrient status. In this narrative review, we analyzed 23 micronutrients and their possible influence on breast cancer onset and progression. Further, the aim of this study was to investigate the impact of micronutrient status on the prevention of breast cancer and its possible influence on various therapeutic pathways. We researched meta-analyses, systemic and narrative reviews, retrospective studies, as well as original studies on human and animal models. The results of these studies indicate a possible correlation between the different levels of micronutrients and a decreased risk of breast cancer as well as a better survival rate. However, further studies are necessary to establish adequate doses of supplementation of the chosen micronutrients and the exact mechanisms of micronutrient impact on breast cancer therapy.

Competition between Stacking and Divalent Cation-Mediated Electrostatic Interactions Determines the Conformations of Short DNA Sequences

Interplay between divalent cations (Mg2+ and Ca2+) and single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA), as well as stacking interactions, is important in nucleosome stability and phase separation in nucleic acids. Quantitative techniques accounting for ion-DNA interactions are needed to obtain insights into these and related problems. Toward this end, we created a sequence-dependent computational TIS-ION model that explicitly accounts for monovalent and divalent ions. Simulations of the rigid 24 base-pair (bp) dsDNA and flexible ssDNA sequences, dT30 and dA30, with varying amounts of the divalent cations show that the calculated excess number of ions around the dsDNA and ssDNA agree quantitatively with ion-counting experiments. Using an ensemble of all-atom structures generated from coarse-grained simulations, we calculated the small-angle X-ray scattering profiles, which are in excellent agreement with experiments. Although ion-counting experiments mask the differences between Mg2+ and Ca2+, we find that Mg2+ binds to the minor grooves and phosphate groups, whereas Ca2+ binds specifically to the minor groove. Both Mg2+ and Ca2+ exhibit a tendency to bind to the minor groove of DNA as opposed to the major groove. The dA30 conformations are dominated by stacking interactions, resulting in structures with considerable helical order. The near cancellation of the favorable stacking and unfavorable electrostatic interactions leads to dT30 populating an ensemble of heterogeneous conformations. The successful applications of the TIS-ION model are poised to confront many problems in DNA biophysics.

Hierarchical Assembly of Single-Stranded RNA

Single-stranded RNA (ssRNA) plays a major role in the flow of genetic information-most notably, in the form of messenger RNA (mRNA)-and in the regulation of biological processes. The highly dynamic nature of chains of unpaired nucleobases challenges structural characterizations of ssRNA by experiments or molecular dynamics (MD) simulations alike. Here, we use hierarchical chain growth (HCG) to construct ensembles of ssRNA chains. HCG assembles the structures of protein and nucleic acid chains from fragment libraries created by MD simulations. Applied to homo- and heteropolymeric ssRNAs of different lengths, we find that HCG produces structural ensembles that overall are in good agreement with diverse experiments, including nuclear magnetic resonance (NMR), small-angle X-ray scattering (SAXS), and single-molecule Förster resonance energy transfer (FRET). The agreement can be further improved by ensemble refinement using Bayesian inference of ensembles (BioEn). HCG can also be used to assemble RNA structures that combine base-paired and base-unpaired regions, as illustrated for the 5' untranslated region (UTR) of SARS-CoV-2 RNA.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Adsorbing DNA to Mica by Cations: Influence of Valency and Ion Type

Ion-mediated attraction between DNA and mica plays a crucial role in biotechnological applications and molecular imaging. Here, we combine molecular dynamics simulations and single-molecule atomic force microscopy experiments to characterize the detachment forces of single-stranded DNA at mica surfaces mediated by the metal cations Li+, Na+, K+, Cs+, Mg2+, and Ca2+. Ion-specific adsorption at the mica/water interface compensates (Li+ and Na+) or overcompensates (K+, Cs+, Mg2+, and Ca2+) the bare negative surface charge of mica. In addition, direct and water-mediated contacts are formed between the ions, the phosphate oxygens of DNA, and mica. The different contact types give rise to low- and high-force pathways and a broad distribution of detachment forces. Weakly hydrated ions, such as Cs+ and water-mediated contacts, lead to low detachment forces and high mobility of the DNA on the surface. Direct ion-DNA or ion-surface contacts lead to significantly higher forces. The comprehensive view gained from our combined approach allows us to highlight the most promising cations for imaging in physiological conditions: K+, which overcompensates the negative mica charge and induces long-ranged attractions. Mg2+ and Ca2+, which form a few specific and long-lived contacts to bind DNA with high affinity.

Characterization of an HNA aptamer suggests a non-canonical G-quadruplex motif

Nucleic acids not only form the basis of heredity, but are increasingly a source of novel nano-structures, -devices and drugs. This has spurred the development of chemically modified alternatives (xeno nucleic acids (XNAs)) comprising chemical configurations not found in nature to extend their chemical and functional scope. XNAs can be evolved into ligands (XNA aptamers) that bind their targets with high affinity and specificity. However, detailed investigations into structural and functional aspects of XNA aptamers have been limited. Here we describe a detailed structure-function analysis of LYS-S8-19, a 1',5'-anhydrohexitol nucleic acid (HNA) aptamer to hen egg-white lysozyme (HEL). Mapping of the aptamer interaction interface with its cognate HEL target antigen revealed interaction epitopes, affinities, kinetics and hot-spots of binding energy similar to protein ligands such as anti-HEL-nanobodies. Truncation analysis and molecular dynamics (MD) simulations suggest that the HNA aptamer core motif folds into a novel and not previously observed HNA tertiary structure, comprising non-canonical hT-hA-hT/hT-hT-hT triplet and hG4-quadruplex structures, consistent with its recognition by two different G4-specific antibodies.

Computational Modeling of DNA 3D Structures: From Dynamics and Mechanics to Folding

DNA carries the genetic information required for the synthesis of RNA and proteins and plays an important role in many processes of biological development. Understanding the three-dimensional (3D) structures and dynamics of DNA is crucial for understanding their biological functions and guiding the development of novel materials. In this review, we discuss the recent advancements in computer methods for studying DNA 3D structures. This includes molecular dynamics simulations to analyze DNA dynamics, flexibility, and ion binding. We also explore various coarse-grained models used for DNA structure prediction or folding, along with fragment assembly methods for constructing DNA 3D structures. Furthermore, we also discuss the advantages and disadvantages of these methods and highlight their differences.

Lipid Structure Determines the Differential Impact of Single Metal Additions and Binary Mixtures of Manganese, Calcium and Magnesium on Membrane Fluidity and Liposome Size

Unilamellar vesicles of the biologically relevant lipids phosphatidic acid (PA) and phosphatidylserine (PS) with fully saturated (DM-) or partly unsaturated (PO-) acyl side chains were exposed to Ca, Mn and Mg in single metal additions; in equimolar mixtures or by sequential additions of one metal at a time. Laurdan generalized polarization measured the membrane fluidity, while dynamic light scattering reported liposome size changes complemented by zeta potential. All metals induced membrane rigidity and increased liposome sizes across all systems. Mn had the strongest effect overall, but Mg was comparable for DMPS. Lipid side chain architecture was important as GP values for binary mixtures were higher than expected from the sum of values for single additions added to POPS but smaller for DMPS. Sequential additions were predominantly different for Ca:Mg mixtures. Mn induced the strongest increase of liposome size in saturated lipids whereas Ca effects dominated unsaturated matrices. Binary additions induced larger sizes than the sum of single additions for POPS, but much lower changes in DMPA. The order of addition was relevant for PS systems. Thus, lipid structure determines metal effects, but their impact is modulated by other ions. Thus, metal effects may differ with the local lipid architecture and metal concentrations within cells.

RNA Captures More Cations than DNA: Insights from Molecular Dynamics Simulations

The distribution of cations around nucleic acids is essential for a broad variety of processes ranging from DNA condensation and RNA folding to the detection of biomolecules in biosensors. Predicting the exact distribution of ions remains challenging since the distribution and, hence, a broad variety of nucleic acid properties depend on the salt concentration, the valency of the ions, and the ion type. Despite the importance, a general theory to quantify ion-specific effects for highly charged biomolecules is still lacking. Moreover, recent experiments reveal that despite their similar building blocks, DNA and RNA duplexes can react differently to the same ionic conditions. The aim of our current work is to provide a comprehensive set of molecular dynamics simulations using more than 180 μs of simulation time. For the mono- and divalent cations Li⁺, Na⁺, K⁺, Cs⁺, Ca²⁺, Sr²⁺, and Ba²⁺, the simulations allow us to reveal the ion-specific distributions and binding patterns for DNA and RNA duplexes. The microscopic insights from the simulations display the origin of ion-specificity and shed light on the question of why DNA and RNA show opposing behavior in the same ionic conditions. Finally, the detailed binding patterns from the simulations reveal why RNA can capture more cations than DNA.

Potential effects of metal ion induced two-state allostery on the regulatory mechanism of add adenine riboswitch

Riboswitches normally regulate gene expression through structural changes in response to the specific binding of cellular metabolites or metal ions. Taking add adenine riboswitch as an example, we explore the influences of metal ions (especially for K⁺ and Mg²⁺ ions) on the structure and dynamics of riboswitch aptamer (with and without ligand) by using molecular dynamic (MD) simulations. Our results show that a two-state transition marked by the structural deformation at the connection of J12 and P1 (C_J12-P1) is not only related to the binding of cognate ligands, but also strongly coupled with the change of metal ion environments. Moreover, the deformation of the structure at C_J12-P1 can be transmitted to P1 directly connected to the expression platform in multiple ways, which will affect the structure and stability of P1 to varying degrees, and finally change the regulation state of this riboswitch.

Molecular dynamic simulations are employed to assess the influence of metal ions on riboswitch structure and dynamics, suggesting a conformational control of riboswitch aptamers by metal ions before ligand binding.

Twisting DNA by salt

The structure and properties of DNA depend on the environment, in particular the ion atmosphere. Here, we investigate how DNA twist -one of the central properties of DNA- changes with concentration and identity of the surrounding ions. To resolve how cations influence the twist, we combine single-molecule magnetic tweezer experiments and extensive all-atom molecular dynamics simulations. Two interconnected trends are observed for monovalent alkali and divalent alkaline earth cations. First, DNA twist increases monotonously with increasing concentration for all ions investigated. Second, for a given salt concentration, DNA twist strongly depends on cation identity. At 100 mM concentration, DNA twist increases as Na⁺ < K⁺ < Rb⁺ < Ba²⁺ < Li⁺ ≈ Cs⁺ < Sr²⁺ < Mg²⁺ < Ca²⁺. Our molecular dynamics simulations reveal that preferential binding of the cations to the DNA backbone or the nucleobases has opposing effects on DNA twist and provides the microscopic explanation of the observed ion specificity. However, the simulations also reveal shortcomings of existing force field parameters for Cs⁺ and Sr²⁺. The comprehensive view gained from our combined approach provides a foundation for understanding and predicting cation-induced structural changes both in nature and in DNA nanotechnology.

Consistent Picture of Phosphate-Divalent Cation Binding from Models with Implicit and Explicit Electronic Polarization

The binding of divalent cations to the ubiquitous phosphate group is essential for a number of key biological processes, such as DNA compaction, RNA folding, or interactions of some proteins with membranes. Yet, probing their binding sites, modes, and associated binding free energy is a challenge for both experiments and simulations. In simulations, standard force fields strongly overestimate the interaction between phosphate groups and divalent cations. Here, we examine how different strategies to include electronic polarization effects in force fields─implicitly, through the use of scaled charges or pair-specific Lennard-Jones parameters, or explicitly, with the polarizable force fields Drude and AMOEBA─capture the interactions of a model phosphate compound, dimethyl phosphate, with calcium and magnesium divalent cations. We show that both implicit and explicit approaches, when carefully parameterized, are successful in capturing the overall binding free energy and that common trends emerge from the comparison of different simulation approaches. Overall, the binding is very moderate, slightly weaker for Ca²⁺ than Mg²⁺, and the solvent-shared ion pair is slightly more stable than the contact monodentate ion pair. The bidentate ion pair is higher in energy (or even fully unstable for Mg²⁺). Our results thus suggest practical ways to capture the divalent cations with biomolecular phosphate groups in complex biochemical systems. In particular, the computational efficiency of implicit models makes them ideally suited for large-scale simulations of biological assemblies, with improved accuracy compared to state-of-the-art fixed-charge force fields.

Magnesium Force Fields for OPC Water with Accurate Solvation, Ion-Binding, and Water-Exchange Properties: Successful Transfer from SPC/E

Magnesium plays a vital role in a large variety of biological processes. To model such processes by molecular dynamics simulations, researchers rely on accurate force field parameters for Mg2+ and water. OPC is one of the most promising water models yielding an improved description of biomolecules in water. The aim of this work is to provide force field parameters for Mg2+ that lead to accurate simulation results in combination with OPC water. Using twelve different Mg2+ parameter sets, that were previously optimized with different water models, we systematically assess the transferability to OPC based on a large variety of experimental properties. The results show that the Mg2+ parameters for SPC/E are transferable to OPC and closely reproduce the experimental solvation free energy, radius of the first hydration shell, coordination number, activity derivative, and binding affinity toward the phosphate oxygens on RNA. Two optimal parameter sets are presented: MicroMg yields water exchange in OPC on the microsecond timescale in agreement with experiments. NanoMg yields accelerated exchange on the nanosecond timescale and facilitates the direct observation of ion binding events for enhanced sampling purposes.

Artificial Intelligence Resolves Kinetic Pathways of Magnesium Binding to RNA

Magnesium is an indispensable cofactor in countless vital processes. In order to understand its functional role, the characterization of the binding pathways to biomolecules such as RNA is crucial. Despite the importance, a molecular description is still lacking since the transition from the water-mediated outer-sphere to the direct inner-sphere coordination is on the millisecond time scale and therefore out of reach for conventional simulation techniques. To fill this gap, we use transition path sampling to resolve the binding pathways and to elucidate the role of the solvent in the binding process. The results reveal that the molecular void provoked by the leaving phosphate oxygen of the RNA is immediately filled by an entering water molecule. In addition, water molecules from the first and second hydration shell couple to the concerted exchange. To capture the intimate solute-solvent coupling, we perform a committor analysis as the basis for a machine learning algorithm that derives the optimal deep learning model from thousands of scanned architectures using hyperparameter tuning. The results reveal that the properly optimized deep network architecture recognizes the important solvent structures, extracts the relevant information, and predicts the commitment probability with high accuracy. Our results provide detailed insights into the solute-solvent coupling which is ubiquitous for kosmotropic ions and governs a large variety of biochemical reactions in aqueous solutions.

Optimized Magnesium Force Field Parameters for Biomolecular Simulations with Accurate Solvation, Ion-Binding, and Water-Exchange Properties in SPC/E, TIP3P-fb, TIP4P/2005, TIP4P-Ew, and TIP4P-D

Magnesium is essential in many vital processes. To correctly describe Mg2+ in physiological processes by molecular dynamics simulations, accurate force fields are fundamental. Despite the importance, force fields based on the commonly used 12-6 Lennard-Jones potential showed significant shortcomings. Recently progress was made by an optimization procedure that implicitly accounts for polarizability. The resulting microMg and nanoMg force fields (J. Chem. Theory Comput. 2021, 17, 2530-2540) accurately reproduce a broad range of experimental solution properties and the binding affinity to nucleic acids in TIP3P water. Since countless simulation studies rely on available water models and ion force fields, we here extend the optimization and provide Mg2+ parameters in combination with the SPC/E, TIP3P-fb, TIP4P/2005, TIP4P-Ew, and TIP4P-D water models. For each water model, the Mg2+ force fields reproduce the solvation free energy, the distance to oxygens in the first hydration shell, the hydration number, the activity coefficient derivative in MgCl2 solutions, and the binding affinity and distance to the phosphate oxygens on nucleic acids. We present two parameter sets: MicroMg yields water exchange on the microsecond time scale and matches the experimental exchange rate. Depending on the water model, nanoMg yields accelerated water exchange in the range of 106 to 108 exchanges per second. The nanoMg parameters can be used to enhance the sampling of binding events, to obtain converged distributions of Mg2+, or to predict ion binding sites in biomolecular simulations. The parameter files are freely available at https://github.com/bio-phys/optimizedMgFFs.