Implicit solvent simulations of DNA and DNA-protein complexes: agreement with explicit solvent vs experiment

Mutation pattern of cancer suppressor p53 gene in factory workers exposed to polypropylene and impact on their reproductive hormones

BACKGROUND

Polypropylene is a thermoplastic polymer playing the role of an endocrine disruptor that interferes with the union, emission, transport or elimination of normal hormones. Epidemiological information indicated the relation of endocrine-disturbing chemicals with prostate cancer, testis tumor and diminished fertility. p53 is a key tumor silencer gene. The present study aimed to evaluate luteinizing hormone (LH) and follicle-stimulating hormone (FSH) levels and the risk of p53 mutations as a result of exposure to polypropylene in non-tumorous adult male factory workers.

METHODS

In total, 150 (controls = 35, workers = 115) subjects were recruited. Groups were maintained according to the tenure of exposure G1 (1-5 years), G2 (6-10 years), G3 (11-15 years) and G4 (16-20 years). Concentrations of LH and FSH were determined through an enzyme-linked immunosorbent assay. Genotyping analysis was performed by polymerase chain reaction based gel electrophoresis followed by DNA sequencing. The structural and functional impact of the mutation on the p53 structure was evaluated using 50-ns molecular dynamics (MD) simulations and protein-DNA docking.

RESULTS

Mean plasma LH levels were significantly decreased in G1 (p > 0.05) as well as the G2, G3 and G4 (p > 0.001) groups. Similarly, FSH levels were significant decrease in G1 (p > 0.05), G2 (p > 0.01), G3 (p > 0.001) and G4 (p > 0.001) compared to the control group. Sequencing results found three variants i.e. g.13450 T>G, g.13430C>T and g.13737G>A. One of them was predicted to be disease-causing others are polymorphisms. MD simulation of missense mutation R273H showed no structural impact on the protein structure in MD simulation, but it resulted in weaker binding of p53 with the DNA that might lower the gene expression of cell cycle regulatory proteins.

CONCLUSIONS

These findings predict decreased fertility and risk of malignancies in the future. The spectrum of p53 mutations as a result of polypropylene exposure in the Pakistani population has not been investigated before. Further studies and meta-analyses are required to elucidate the role of different plasticizers in reproduction and cancer-causing risk factors in a larger population.

A Closed-Form, Analytical Approximation for Apparent Surface Charge and Electric Field of Molecules

Closed-form, analytical approximations for electrostatic properties of molecules are of unique value as these can provide computational speed, versatility, and physical insight. Here, we have derived a simple, closed-form formula for the apparent surface charge (ASC) as well as for the electric field generated by a molecular charge distribution in aqueous solution. The approximation, with no fitted parameters, was tested against numerical solutions of the Poisson equation, where it has produced a significant speed-up. For neutral small molecules, the hydration free energies estimated from the closed-form ASC formula are within 0.8 kcal/mol RMSD from the numerical Poisson reference; the electric field at the surface is in quantitative agreement with the reference. Performance of the approximation was also tested on larger structures, including a protein, a DNA fragment, and a viral receptor-target complex. For all structures tested, a near-quantitative agreement with the numerical Poisson reference was achieved, except in regions of high negative curvature, where the new approximation is still qualitatively correct. A unique efficiency feature of the proposed "source-based″ closed-form approximation is that the ASC and electric field can be estimated individually at any point or surface patch, without the need to obtain the full global solution. An open-source software implementation of the method is available: https://people.cs.vt.edu/~onufriev/CODES/aasc.zip.

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.

In-Silico Selection of Aptamer Targeting SARS-CoV-2 Spike Protein

Aptamers are single-stranded, short DNA or RNA oligonucleotides that can specifically bind to various target molecules. To diagnose the infected cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in time, numerous conventional methods are applied for viral detection via the amplification and quantification of DNA or antibodies specific to antigens on the virus. Herein, we generated a large number of mutated aptamer sequences, derived from a known sequence of receptor-binding domain (RBD)-1C aptamer, specific to the RBD of SARS-CoV-2 spike protein (S protein). Structural similarity, molecular docking, and molecular dynamics (MD) were utilized to screen aptamers and characterize the detailed interactions between the selected aptamers and the S protein. We identified two mutated aptamers, namely, RBD-1CM1 and RBD-1CM2, which presented better docking results against the S protein compared with the RBD-1C aptamer. Through the MD simulation, we further confirmed that the RBD-1CM1 aptamer can form the most stable complex with the S protein based on the number of hydrogen bonds formed between the two biomolecules. Based on the experimental data of quartz crystal microbalance (QCM), the RBD-1CM1 aptamer could produce larger signals in mass change and exhibit an improved binding affinity to the S protein. Therefore, the RBD-1CM1 aptamer, which was selected from 1431 mutants, was the best potential candidate for the detection of SARS-CoV-2. The RBD-1CM1 aptamer can be an alternative biological element for the development of SARS-CoV-2 diagnostic testing.

Structural transitions in the RNA 7SK 5' hairpin and their effect on HEXIM binding

7SK RNA, as part of the 7SK ribonucleoprotein complex, is crucial to the regulation of transcription by RNA-polymerase II, via its interaction with the positive transcription elongation factor P-TEFb. The interaction is induced by binding of the protein HEXIM to the 5′ hairpin (HP1) of 7SK RNA. Four distinct structural models have been obtained experimentally for HP1. Here, we employ computational methods to investigate the relative stability of these structures, transitions between them, and the effects of mutations on the observed structural ensembles. We further analyse the results with respect to mutational binding assays, and hypothesize a mechanism for HEXIM binding. Our results indicate that the dominant structure in the wild type exhibits a triplet involving the unpaired nucleotide U40 and the base pair A43-U66 in the GAUC/GAUC repeat. This conformation leads to an open major groove with enough potential binding sites for peptide recognition. Sequence mutations of the RNA change the relative stability of the different structural ensembles. Binding affinity is consequently lost if these changes alter the dominant structure.

Improved Poisson-Boltzmann Methods for High-Performance Computing

Implicit solvent models based on the Poisson-Boltzmann equation (PBE) have been widely used to study electrostatic interactions in biophysical processes. These models often treat the solvent and solute regions as high and low dielectric continua, leading to a large jump in dielectrics across the molecular surface which is difficult to handle. Higher order interface schemes are often needed to seek higher accuracy for PBE applications. However, these methods are usually very liberal in the use of grid points nearby the molecular surface, making them difficult to use on high-performance computing platforms. Alternatively, the harmonic average (HA) method has been used to approximate dielectric interface conditions near the molecular surface with surprisingly good convergence and is well suited for high-performance computing. By adopting a 7-point stencil, the HA method is advantageous in generating simple 7-banded coefficient matrices, which greatly facilitate linear system solution with dense data parallelism, on high-performance computing platforms such as a graphics processing unit (GPU). However, the HA method is limited due to its lower accuracy. Therefore, it would be of great interest for high-performance applications to develop more accurate methods while retaining the simplicity and effectiveness of the 7-point stencil discretization scheme. In this study, we have developed two new algorithms based on the spirit of the HA method by introducing more physical interface relations and imposing the discretized Poisson's equation to the second order, respectively. Our testing shows that, for typical biomolecules, the new methods significantly improve the numerical accuracy to that comparable to the second-order solvers and with ∼65% overall efficiency gain on widely available high-performance GPU platforms.

Generalized Born Implicit Solvent Models for Biomolecules

It would often be useful in computer simulations to use an implicit description of solvation effects, instead of explicitly representing the individual solvent molecules. Continuum dielectric models often work well in describing the thermodynamic aspects of aqueous solvation and can be very efficient compared to the explicit treatment of the solvent. Here, we review a particular class of so-called fast implicit solvent models, generalized Born (GB) models, which are widely used for molecular dynamics (MD) simulations of proteins and nucleic acids. These approaches model hydration effects and provide solvent-dependent forces with efficiencies comparable to molecular-mechanics calculations on the solute alone; as such, they can be incorporated into MD or other conformational searching strategies in a straightforward manner. The foundations of the GB model are reviewed, followed by examples of newer, emerging models and examples of important applications. We discuss their strengths and weaknesses, both for fidelity to the underlying continuum model and for the ability to replace explicit consideration of solvent molecules in macromolecular simulations.

An efficient second-order poisson-boltzmann method

Immersed interface method (IIM) is a promising high-accuracy numerical scheme for the Poisson-Boltzmann model that has been widely used to study electrostatic interactions in biomolecules. However, the IIM suffers from instability and slow convergence for typical applications. In this study, we introduced both analytical interface and surface regulation into IIM to address these issues. The analytical interface setup leads to better accuracy and its convergence closely follows a quadratic manner as predicted by theory. The surface regulation further speeds up the convergence for nontrivial biomolecules. In addition, uncertainties of the numerical energies for tested systems are also reduced by about half. More interestingly, the analytical setup significantly improves the linear solver efficiency and stability by generating more precise and better-conditioned linear systems. Finally, we implemented the bottleneck linear system solver on GPUs to further improve the efficiency of the method, so it can be widely used for practical biomolecular applications. © 2019 Wiley Periodicals, Inc.

Preferential binding effects on protein structure and dynamics revealed by coarse-grained Monte Carlo simulation

The effect of preferential binding of solute molecules within an aqueous solution on the structure and dynamics of the histone H3.1 protein is examined by a coarse-grained Monte Carlo simulation. The knowledge-based residue-residue and hydropathy-index-based residue-solvent interactions are used as input to analyze a number of local and global physical quantities as a function of the residue-solvent interaction strength (f). Results from simulations that treat the aqueous solution as a homogeneous effective solvent medium are compared to when positional fluctuations of the solute molecules are explicitly considered. While the radius of gyration (Rg) of the protein exhibits a non-monotonic dependence on solvent interaction over a wide range of f within an effective medium, an abrupt collapse in Rg occurs in a narrow range of f when solute molecules rapidly bind to a preferential set of sites on the protein. The structure factor S(q) of the protein with wave vector (q) becomes oscillatory in the collapsed state, which reflects segmental correlations caused by spatial fluctuations in solute-protein binding. Spatial fluctuations in solute binding also modify the effective dimension (D) of the protein in fibrous (D ∼ 1.3), random-coil (D ∼ 1.75), and globular (D ∼ 3) conformational ensembles as the interaction strength increases, which differ from an effective medium with respect to the magnitude of D and the length scale.

The "sugar" coarse-grained DNA model

More than 20 coarse-grained (CG) DNA models have been developed for simulating the behavior of this molecule under various conditions, including those required for nanotechnology. However, none of these models reproduces the DNA polymorphism associated with conformational changes in the ribose rings of the DNA backbone. These changes make an essential contribution to the DNA local deformability and provide the possibility of the transition of the DNA double helix from the B-form to the A-form during interactions with biological molecules. We propose a CG representation of the ribose conformational flexibility. We substantiate the choice of the CG sites (six per nucleotide) needed for the "sugar" GC DNA model, and obtain the potentials of the CG interactions between the sites by the "bottom-up" approach using the all-atom AMBER force field. We show that the representation of the ribose flexibility requires one non-harmonic and one three-particle potential, the forms of both the potentials being different from the ones generally used. The model also includes (i) explicit representation of ions (in an implicit solvent) and (ii) sequence dependence. With these features, the sugar CG DNA model reproduces (with the same parameters) both the B- and A- stable forms under corresponding conditions and demonstrates both the A to B and the B to A phase transitions. Graphical Abstract The proposed coarse-grained DNA model allows to reproduce both the B- and A- DNA forms and the transitions between them under corresponding conditions.

Partially Assembled Nucleosome Structures at Atomic Detail

The evidence is now overwhelming that partially assembled nucleosome states (PANS) are as important as the canonical nucleosome structure for the understanding of how accessibility to genomic DNA is regulated in cells. We use a combination of molecular dynamics simulation and atomic force microscopy to deliver, in atomic detail, structural models of three key PANS: the hexasome (H2A·H2B)·(H3·H4)₂, the tetrasome (H3·H4)₂, and the disome (H3·H4). Despite fluctuations of the conformation of the free DNA in these structures, regions of protected DNA in close contact with the histone core remain stable, thus establishing the basis for the understanding of the role of PANS in DNA accessibility regulation. On average, the length of protected DNA in each structure is roughly 18 basepairs per histone protein. Atomistically detailed PANS are used to explain experimental observations; specifically, we discuss interpretation of atomic force microscopy, Förster resonance energy transfer, and small-angle x-ray scattering data obtained under conditions when PANS are expected to exist. Further, we suggest an alternative interpretation of a recent genome-wide study of DNA protection in active chromatin of fruit fly, leading to a conclusion that the three PANS are present in actively transcribing regions in a substantial amount. The presence of PANS may not only be a consequence, but also a prerequisite for fast transcription in vivo.

Sequence-Specific Recognition of DNA by Proteins: Binding Motifs Discovered Using a Novel Statistical/Computational Analysis

Decades of intensive experimental studies of the recognition of DNA sequences by proteins have provided us with a view of a diverse and complicated world in which few to no features are shared between individual DNA-binding protein families. The originally conceived direct readout of DNA residue sequences by amino acid side chains offers very limited capacity for sequence recognition, while the effects of the dynamic properties of the interacting partners remain difficult to quantify and almost impossible to generalise. In this work we investigated the energetic characteristics of all DNA residue—amino acid side chain combinations in the conformations found at the interaction interface in a very large set of protein—DNA complexes by the means of empirical potential-based calculations. General specificity-defining criteria were derived and utilised to look beyond the binding motifs considered in previous studies. Linking energetic favourability to the observed geometrical preferences, our approach reveals several additional amino acid motifs which can distinguish between individual DNA bases. Our results remained valid in environments with various dielectric properties.

Kinetics from Implicit Solvent Simulations of Biomolecules as a Function of Viscosity

Kinetic properties of alanine dipeptide, the B1 domain of streptococcal protein G, and ubiquitin are compared between explicit solvent and implicit solvent simulations with the generalized Born molecular volume (GBMV) method. The results indicate that kinetics from explicit solvent simulations and experiments can be matched closely when the implicit solvent simulations are combined with Langevin dynamics and a friction coefficient near 10 ps(-1). Smaller and larger friction coefficients accelerate and slow down conformational sampling. It is found that local conformational exploration without the crossing of significant barriers can be accelerated by a factor of 4-5; however, the acceleration of barrier crossings is limited to about a factor of 2. The use of a Nosé-Hoover thermostat instead of Langevin dynamics greatly enhances local conformational sampling but slows down the crossing of barriers by at least an order of magnitude because of the lack of solute-solvent stochastic collisions.

Protein-Ligand Electrostatic Binding Free Energies from Explicit and Implicit Solvation

Accurate yet efficient computational models of solvent environment are central for most calculations that rely on atomistic modeling, such as prediction of protein-ligand binding affinities. In this study, we evaluate the accuracy of a recently developed generalized Born implicit solvent model, GBNSR6 (Aguilar et al. J. Chem. Theory Comput. 2010, 6, 3613-3639), in estimating the electrostatic solvation free energies (ΔG(pol)) and binding free energies (ΔΔG(pol)) for small protein-ligand complexes. We also compare estimates based on three different explicit solvent models (TIP3P, TIP4PEw, and OPC). The two main findings are as follows. First, the deviation (RMSD = 7.04 kcal/mol) of GBNSR6 binding affinities from commonly used TIP3P reference values is comparable to the deviations between explicit models themselves, e.g. TIP4PEw vs TIP3P (RMSD = 5.30 kcal/mol). A simple uniform adjustment of the atomic radii by a single scaling factor reduces the RMS deviation of GBNSR6 from TIP3P to within the above "error margin" - differences between ΔΔG(pol) estimated by different common explicit solvent models. The simple radii scaling virtually eliminates the systematic deviation (ΔΔG(pol)) between GBNSR6 and two out of the three explicit water models and significantly reduces the deviation from the third explicit model. Second, the differences between electrostatic binding energy estimates from different explicit models is disturbingly large; for example, the deviation between TIP4PEw and TIP3P estimates of ΔΔG(pol) values can be up to ∼50% or ∼9 kcal/mol, which is significantly larger than the "chemical accuracy" goal of ∼1 kcal/mol. The absolute ΔG(pol) calculated with different explicit models could differ by tens of kcal/mol. These discrepancies point to unacceptably high sensitivity of binding affinity estimates to the choice of common explicit water models. The absence of a clear "gold standard" among these models strengthens the case for the use of accurate implicit solvation models for binding energetics, which may be orders of magnitude faster.

Free energy landscape and transition pathways from Watson-Crick to Hoogsteen base pairing in free duplex DNA

Houghton (HG) base pairing plays a central role in the DNA binding of proteins and small ligands. Probing detailed transition mechanism from Watson–Crick (WC) to HG base pair (bp) formation in duplex DNAs is of fundamental importance in terms of revealing intrinsic functions of double helical DNAs beyond their sequence determined functions. We investigated a free energy landscape of a free B-DNA with an adenosine–thymine (A–T) rich sequence to probe its conformational transition pathways from WC to HG base pairing. The free energy landscape was computed with a state-of-art two-dimensional umbrella molecular dynamics simulation at the all-atom level. The present simulation showed that in an isolated duplex DNA, the spontaneous transition from WC to HG bp takes place via multiple pathways. Notably, base flipping into the major and minor grooves was found to play an important role in forming these multiple transition pathways. This finding suggests that naked B-DNA under normal conditions has an inherent ability to form HG bps via spontaneous base opening events.

Molecular modeling of nucleic Acid structure: electrostatics and solvation

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand its structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as a way of sampling conformational space for a better understanding of the relevance of a given model. This discussion highlighted the major limitations with modeling in general. When sampling conformational space effectively, difficult issues are encountered, such as multiple minima or conformational sampling problems, and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These subjects are discussed in detail in this unit.

Single-Walled Carbon Nanotubes Modulate the B- to A-DNA Transition

We study the conformational equilibrium between B-to-A forms of ds-DNA adsorbed onto a single-walled carbon nanotube (SWNT) using free energy profile calculations based on all-atom molecular dynamics simulations. The potential of mean force (PMF) of the B-to-A transition of ds-DNA in the presence of an uncharged (10,0) carbon nanotube for two dodecamers with poly-AT or poly-GC sequences is calculated as a function of a root-mean-square-distance (ΔRMSD) difference metric for the B-to-A transition. The calculations reveal that in the presence of a SWNT DNA favors B-form DNA significantly in both poly-GC and poly-AT sequences. Furthermore, the poly-AT DNA:SWNT complex shows a higher energy penalty for adopting an A-like conformation than poly-GC DNA:SWNT by several kcal/mol. The presence of a SWNT on either poly-AT or poly-GC DNA affects the PMF of the transition such that the B form is favored by as much as 10 kcal/mol. In agreement with published data, we find a potential energy minimum between A and B-form DNA at ΔRMSD ≈ -1.5 Å and that the presence of the SWNT moves this minimum by as much as ΔRMSD = 3 Å.

Conformational preferences of DNA in reduced dielectric environments

The effect of reduced dielectric environments on the conformational sampling of DNA was examined through molecular dynamics simulations. Different dielectric environments were used to model one aspect of cellular environments. Implicit solvent based on the Generalized Born methodology was used to reflect different dielectric environments in the simulations. The simulation results show a tendency of DNA structures to favor noncanonical A-like conformations rather than canonical A- and B-forms as a result of the reduced dielectric environments. The results suggest that the reduced dielectric response in cellular environments may be sufficient to enhance the sampling of A-like DNA structures compared to dilute solvent conditions.

Cooperative gene regulation by microRNA pairs and their identification using a computational workflow

MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation. In this paper, we present a computational workflow for the prediction and analysis of cooperating miRNAs and their mutual target genes, which we refer to as RNA triplexes. The workflow integrates methods of miRNA target prediction; triplex structure analysis; molecular dynamics simulations and mathematical modeling for a reliable prediction of functional RNA triplexes and target repression efficiency. In a case study we analyzed the human genome and identified several thousand targets of cooperative gene regulation. Our results suggest that miRNA cooperativity is a frequent mechanism for an enhanced target repression by pairs of miRNAs facilitating distinctive and fine-tuned target gene expression patterns. Human RNA triplexes predicted and characterized in this study are organized in a web resource at www.sbi.uni-rostock.de/triplexrna/.

A novel implicit solvent model for simulating the molecular dynamics of RNA

Although molecular dynamics simulations can be accelerated by more than an order of magnitude by implicitly describing the influence of the solvent with a continuum model, most currently available implicit solvent simulations cannot robustly simulate the structure and dynamics of nucleic acids. The difficulties become exacerbated especially for RNAs, suggesting the presence of serious physical flaws in the prior continuum models for the influence of the solvent and counter ions on the nucleic acids. We present a novel, to our knowledge, implicit solvent model for simulating nucleic acids by combining the Langevin-Debye model and the Poisson-Boltzmann equation to provide a better estimate of the electrostatic screening of both the water and counter ions. Tests of the model involve comparisons of implicit and explicit solvent simulations for three RNA targets with 20, 29, and 75 nucleotides. The model provides reasonable agreement with explicit solvent simulations, and directions for future improvement are noted.

Introducing Charge Hydration Asymmetry into the Generalized Born Model

The effect of charge hydration asymmetry (CHA)-non-invariance of solvation free energy upon solute charge inversion-is missing from the standard linear response continuum electrostatics. The proposed charge hydration asymmetric-generalized Born (CHA-GB) approximation introduces this effect into the popular generalized Born (GB) model. The CHA is added to the GB equation via an analytical correction that quantifies the specific propensity of CHA of a given water model; the latter is determined by the charge distribution within the water model. Significant variations in CHA seen in explicit water (TIP3P, TIP4P-Ew, and TIP5P-E) free energy calculations on charge-inverted "molecular bracelets" are closely reproduced by CHA-GB, with the accuracy similar to models such as SEA and 3D-RISM that go beyond the linear response. Compared against reference explicit (TIP3P) electrostatic solvation free energies, CHA-GB shows about a 40% improvement in accuracy over the canonical GB, tested on a diverse set of 248 rigid small neutral molecules (root mean square error, rmse = 0.88 kcal/mol for CHA-GB vs 1.24 kcal/mol for GB) and 48 conformations of amino acid analogs (rmse = 0.81 kcal/mol vs 1.26 kcal/mol). CHA-GB employs a novel definition of the dielectric boundary that does not subsume the CHA effects into the intrinsic atomic radii. The strategy leads to finding a new set of intrinsic atomic radii optimized for CHA-GB; these radii show physically meaningful variation with the atom type, in contrast to the radii set optimized for GB. Compared to several popular radii sets used with the original GB model, the new radii set shows better transferability between different classes of molecules.

Hydrophobic organic linkers in the self-assembly of small molecule-DNA hybrid dimers: a computational-experimental study of the role of linkage direction in product distributions and stabilities

Detailed computational and experimental studies reveal the crucial role that hydrophobic interactions play in the self-assembly of small molecule-DNA hybrids (SMDHs) into cyclic nanostructures. In aqueous environments, the distribution of the cyclic structures (dimers or higher-order structures) greatly depends on how well the hydrophobic surfaces of the organic cores in these nanostructures are minimized. Specifically, when the cores are attached to the 3'-ends of the DNA component strands, they can insert into the minor groove of the duplex that forms upon self-assembly, favoring the formation of cyclic dimers. However, when the cores are attached to the 5'-ends of the DNA component strands, such insertion is hindered, leading to the formation of higher-order cyclic structures. These computational insights are supported by experimental results that show clear differences in product distributions and stabilities for a broad range of organic core-linked DNA hybrids with different linkage directions and flexibilities.

VERIFICATION OF THE GENERALIZED BORN MODEL AT SHORT DISTANCES

The generalized Born (GB) model, one of the implicit solvent models, is widely applied in molecular dynamics (MD) simulations as a simple description of the solvation effect. In the GB model, an empirical function called the Still's formula, with the algorithmic simplicity, is utilized to calculate the solvation energy due to the polarization, termed as ΔG pol . Applications of the GB model have exhibited reasonable accuracy and high computational efficiency. However, there is still room for improvements. Most of the attempts to improve the GB model focus on optimizing effective Born radii. Contrarily, limited researches have been performed to improve the feasibility of the Still's formula. In this paper, analytical methods was applied to investigate the validity of the Still's formula at short distance. Taking advantage of the toroidal coordinates and Mehler–Fock transform, the analytical solutions of the GB model at short distances was derived explicitly for the first time. Additionally, the solvation energy was numerically computed using proper algorithms based on the analytical solutions and compared with ΔG pol calculated in the GB model. With the analysis on the deficiencies of the Still's formula at short distances, potential methods to improve the validity of the GB model were discussed.

Structural ensemble and dynamics of toroidal-like DNA shapes in bacteriophage ϕ29 exit cavity

In the bacteriophage ϕ29, DNA is packed into a preassembled capsid from which it ejects under high pressure. A recent cryo-EM reconstruction of ϕ29 revealed a compact toroidal DNA structure (30-40 basepairs) lodged within the exit cavity formed by the connector-lower collar protein complex. Using multiscale models, we compute a detailed structural ensemble of intriguing DNA toroids of various lengths, all highly compatible with experimental observations. In particular, coarse-grained (elastic rod) and atomistic (molecular dynamics) models predict the formation of DNA toroids under significant compression, a largely unexplored state of DNA. Model predictions confirm that a biologically attainable compressive force of 25 pN sustains the toroid and yields DNA electron density maps highly consistent with the experimental reconstruction. The subsequent simulation of dynamic toroid ejection reveals large reactions on the connector that may signal genome release.

Dynamic Heterogeneous Dielectric Generalized Born (DHDGB): An implicit membrane model with a dynamically varying bilayer thickness

An extension to the heterogeneous dielectric generalized Born (HDGB) implicit membrane formalism is presented to allow dynamic membrane deformations in response to membrane-inserted biomolecules during molecular dynamic simulations. The flexible membrane is implemented through additional degrees of freedom that represent the membrane deformation at the contact points of a membrane-inserted solute with the membrane. The extra degrees of freedom determine the dielectric and non-polar solvation free energy profiles that are used to obtain the solvation free energy in the presence of the membrane and are used to calculate membrane deformation free energies according to an elastic membrane model. With the dynamic HDGB (DHDGB) model the membrane is able to deform in response to the insertion of charged molecules thereby avoiding the overestimation of insertion free energies with static membrane models. The DHDGB model also allows the membrane to respond to the insertion of membrane-spanning solutes with hydrophobic mismatch. The model is tested with the membrane insertion of amino acid side chain analogs, arginine-containing helices, the WALP23 peptide, and the gramicidin A channel.

Carbohydrate recognition by the antiviral lectin cyanovirin-N

Cyanovirin-N (CVN) is a cyanobacterial lectin with potent antiviral activity and has been the focus of extensive preclinical investigation as a potential prophylactic for the prevention of the sexual transmission of the human immunodeficiency virus (HIV). Here we present a detailed analysis of carbohydrate recognition by this important protein, using a combination of computational methods, including extensive molecular dynamics simulations and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) energetic analysis. The simulation results strongly suggest that the observed tendency of wild-type CVN to form domain-swapped dimers is the result of a previously unidentified cis-peptide bond present in the monomeric state. The energetic analysis additionally indicates that the highest-affinity ligand for CVN characterized to date (α-Man-(1,2)-α-Man-(1,2)-α-Man) is recognized asymmetrically by the two binding sites. Finally, we are able to provide a detailed map of the role of all binding site functional groups (both backbone and side chain) to various aspects of molecular recognition: general affinity for cognate ligands, specificity for distinct oligosaccharide targets, and the asymmetric recognition of α-Man-(1,2)-α-Man-(1,2)-α-Man. Taken as a whole, these results complement past experimental characterization (both structural and thermodynamic) to provide the most complete understanding of carbohydrate recognition by CVN to date. The results also provide strong support for the application of similar approaches to the understanding of other protein-carbohydrate complexes.

Studies of base pair sequence effects on DNA solvation based on all-atom molecular dynamics simulations

Detailed analyses of the sequence-dependent solvation and ion atmosphere of DNA are presented based on molecular dynamics (MD) simulations on all the 136 unique tetranucleotide steps obtained by the ABC consortium using the AMBER suite of programs. Significant sequence effects on solvation and ion localization were observed in these simulations. The results were compared to essentially all known experimental data on the subject. Proximity analysis was employed to highlight the sequence dependent differences in solvation and ion localization properties in the grooves of DNA. Comparison of the MD-calculated DNA structure with canonical A- and B-forms supports the idea that the G/C-rich sequences are closer to canonical A- than B-form structures, while the reverse is true for the poly A sequences, with the exception of the alternating ATAT sequence. Analysis of hydration density maps reveals that the flexibility of solute molecule has a significant effect on the nature of observed hydration. Energetic analysis of solute-solvent interactions based on proximity analysis of solvent reveals that the GC or CG base pairs interact more strongly with water molecules in the minor groove of DNA that the AT or TA base pairs, while the interactions of the AT or TA pairs in the major groove are stronger than those of the GC or CG pairs. Computation of solvent-accessible surface area of the nucleotide units in the simulated trajectories reveals that the similarity with results derived from analysis of a database of crystallographic structures is excellent. The MD trajectories tend to follow Manning's counterion condensation theory, presenting a region of condensed counterions within a radius of about 17 A from the DNA surface independent of sequence. The GC and CG pairs tend to associate with cations in the major groove of the DNA structure to a greater extent than the AT and TA pairs. Cation association is more frequent in the minor groove of AT than the GC pairs. In general, the observed water and ion atmosphere around the DNA sequences is the MD simulation is in good agreement with experimental observations.

Constant pH Molecular Dynamics Simulations of Nucleic Acids in Explicit Solvent

The nucleosides of adenine and cytosine have pKa values of 3.50 and 4.08, respectively, and are assumed to be unprotonated under physiological conditions. However, evidence from recent NMR and X-Ray crystallography studies has revealed the prevalence of protonated adenine and cytosine in RNA macromolecules. Such nucleotides with elevated pKa values may play a role in stabilizing RNA structure and participate in the mechanism of ribozyme catalysis. With the work presented here, we establish the framework and demonstrate the first constant pH MD simulations (CPHMD) for nucleic acids in explicit solvent in which the protonation state is coupled to the dynamical evolution of the RNA system via λ-dynamics. We adopt the new functional form λ(Nexp) for λ that was recently developed for Multi-Site λ-Dynamics (MSλD) and demonstrate good sampling characteristics in which rapid and frequent transitions between the protonated and unprotonated states at pH = pKa are achieved. Our calculated pKa values of simple nucleotides are in a good agreement with experimentally measured values, with a mean absolute error of 0.24 pKa units. This work demonstrates that CPHMD can be used as a powerful tool to investigate pH-dependent biological properties of RNA macromolecules.

Evaluation of DNA Force Fields in Implicit Solvation

DNA structural deformations and dynamics are crucial to its interactions in the cell. Theoretical simulations are essential tools to explore the structure, dynamics, and thermodynamics of biomolecules in a systematic way. Molecular mechanics force fields for DNA have benefited from constant improvements during the last decades. Several studies have evaluated and compared available force fields when the solvent is modeled by explicit molecules. On the other hand, few systematic studies have assessed the quality of duplex DNA models when implicit solvation is employed. The interest of an implicit modeling of the solvent consists in the important gain in the simulation performance and conformational sampling speed. In this study, respective influences of the force field and the implicit solvation model choice on DNA simulation quality are evaluated. To this end, extensive implicit solvent duplex DNA simulations are performed, attempting to reach both conformational and sequence diversity convergence. Structural parameters are extracted from simulations and statistically compared to available experimental and explicit solvation simulation data. Our results quantitatively expose the respective strengths and weaknesses of the different DNA force fields and implicit solvation models studied. This work can lead to the suggestion of improvements to current DNA theoretical models.

Heat conductivity of DNA double helix

Thermal conductivity of isolated single molecule DNA fragments is of importance for nanotechnology, but has not yet been measured experimentally. Theoretical estimates based on simplified (1D) models predict anomalously high thermal conductivity. To investigate thermal properties of single molecule DNA we have developed a 3D coarse-grained (CG) model that retains the realism of the full all-atom description, but is significantly more efficient. Within the proposed model each nucleotide is represented by 6 particles or grains; the grains interact via effective potentials inferred from classical molecular dynamics (MD) trajectories based on a well-established all-atom potential function. Comparisons of 10 ns long MD trajectories between the CG and the corresponding all-atom model show similar root-mean-square deviations from the canonical B-form DNA, and similar structural fluctuations. At the same time, the CG model is 10 to 100 times faster depending on the length of the DNA fragment in the simulation. Analysis of dispersion curves derived from the CG model yields longitudinal sound velocity and torsional stiffness in close agreement with existing experiments. The computational efficiency of the CG model makes it possible to calculate thermal conductivity of a single DNA molecule not yet available experimentally. For a uniform (polyG-polyC) DNA, the estimated conductivity coefficient is 0.3 W/mK which is half the value of thermal conductivity for water. This result is in stark contrast with estimates of thermal conductivity for simplified, effectively 1D chains ("beads on a spring") that predict anomalous (infinite) thermal conductivity. Thus, full 3D character of DNA double-helix retained in the proposed model appears to be essential for describing its thermal properties at a single molecule level.

Transient Hoogsteen base pairs in canonical duplex DNA

Sequence-directed variations in the canonical DNA double helix structure that retain Watson-Crick base-pairing have important roles in DNA recognition, topology and nucleosome positioning. By using nuclear magnetic resonance relaxation dispersion spectroscopy in concert with steered molecular dynamics simulations, we have observed transient sequence-specific excursions away from Watson-Crick base-pairing at CA and TA steps inside canonical duplex DNA towards low-populated and short-lived A•T and G•C Hoogsteen base pairs. The observation of Hoogsteen base pairs in DNA duplexes specifically bound to transcription factors and in damaged DNA sites implies that the DNA double helix intrinsically codes for excited state Hoogsteen base pairs as a means of expanding its structural complexity beyond that which can be achieved based on Watson-Crick base-pairing. The methods presented here provide a new route for characterizing transient low-populated nucleic acid structures, which we predict will be abundant in the genome and constitute a second transient layer of the genetic code.

Effect of flanking residues on the conformational sampling of the internal fusion peptide from Ebola virus

Fusion peptides mediate viral and host-cell membrane fusion during viral entry. The monomeric form of the internal fusion peptide from Ebola virus was studied in membrane bilayer and water environments with computer simulations using replica exchange sampling and an implicit solvent description of the environment. Wild-type Ebola fusion peptide (EFP), the W8A mutant form, and an extended construct with flanking residues were examined. It was found that the monomeric form of wild-type EFP adopts coil-helix-coil structure with a short helix from residues 8 to 11 mostly sampling orientations parallel to the membrane surface. W8A mutation disrupts the helicity in the N-terminal region of the peptide and leads to a preference for slightly oblique orientation relative to the membrane surface. The addition of flanking residues also alters the fusion peptide conformation with either a helix-break-helix structure or extended N and C-termini and reduced membrane insertion. In water, the fusion peptide is found to adopt structures with low helicity.

Improving the description of salt bridge strength and geometry in a Generalized Born model

The Generalized Born (GB) solvent model is widely used in molecular dynamics simulations because it can be less computationally expensive and it samples conformational changes more efficiently than explicit solvent simulations. Meanwhile, great efforts have been made in the past to improve its precision and accuracy. Previous studies have shown that reducing intrinsic GB radii of some hydrogen atoms would improve AMBER GB-HCT solvent model's accuracy on salt bridges. Here we present our finding that similar correction also shows dramatic improvement for the AMBER GB-OBC solvent model. Potential of mean force and cluster analysis for small peptide replica exchange molecular dynamics simulations suggested that new radii GB simulation with ff99SB/GB-OBC corrected salt bridge strength and achieved significantly higher geometry similarity with TIP3P simulation. Improved performance in 60 ns HIV-1 protease GB simulation further validated this approach for large systems.

Effect of oligonucleotide length on the assembly of DNA materials: molecular dynamics simulations of layer-by-layer DNA films

DNA strand length has been found to be an important factor in many DNA-based nanoscale systems. Here, we apply molecular dynamics simulations in a synergistic effort with layer-by-layer experimental data to understand the effect of DNA strand length on the assembly of DNA films. The results indicate that short (less than 10 bases) and long (more than 30 bases) single-stranded DNAs do not exhibit optimal film growth, and this can be associated with the limited accessibility of the bases on the surface due to formation of self-protected interactions that prevent efficient hybridization. Interestingly, the presence of a duplex attached to a single strand significantly alters the persistence length of the polyT strands. Our study suggests that restrained polyT, compared to labile suspensions of free polyT, are more capable of hybridization and hence DNA-based assembly.

Nucleotides that are essential but not conserved; a sufficient L-tryptophan site in RNA

Conservation is often used to define essential sequences within RNA sites. However, conservation finds only invariant sequence elements that are necessary for function, rather than finding a set of sequence elements sufficient for function. Biochemical studies in several systems-including the hammerhead ribozyme and the purine riboswitch-find additional elements, such as loop-loop interactions, required for function yet not phylogenetically conserved. Here we define a critical test of sufficiency: We embed a minimal, apparently sufficient motif for binding the amino acid tryptophan in a random-sequence background and ask whether we obtain functional molecules. After a negative result, we use a combination of three-dimensional structural modeling, selection, designed mutations, high-throughput sequencing, and bioinformatics to explore functional insufficiency. This reveals an essential unpaired G in a diverse structural context, varied sequence, and flexible distance from the invariant internal loop binding site identified previously. Addition of the new element yields a sufficient binding site by the insertion criterion, binding tryptophan in 22 out of 23 tries. Random insertion testing for site sufficiency seems likely to be broadly revealing.

Energetic decomposition with the generalized-born and Poisson-Boltzmann solvent models: lessons from association of G-protein components

Continuum electrostatic models have been shown to be powerful tools in providing insight into the energetics of biomolecular processes. While the Poisson-Boltzmann (PB) equation provides a theoretically rigorous approach to computing electrostatic free energies of solution in such a model, computational cost makes its use for large ensembles of states impractical. The generalized-Born (GB) approximation provides a much faster alternative, although with a weaker theoretical framework. While much attention has been given to how GB recapitulates PB energetics for the overall stability of a biomolecule or the affinity of a complex, little attention has been given to how the contributions of individual functional groups are captured by the two methods. Accurately capturing these individual electrostatic components is essential both for the development of a mechanistic understanding of biomolecular processes and for the design of variant sequences and structures with desired properties. Here, we present a detailed comparison of the group-wise decomposition of both PB and GB electrostatic free energies of binding, using association of various components of the heterotrimeric-G-protein complex as a model. We find that, while net binding free energies are strongly correlated in the two models, the correlations of individual group contributions are highly variable; in some cases, strong correlation is seen, while in others, there is essentially none. Structurally, the GB model seems to capture the magnitude of direct, short-range electrostatic interactions quite well but performs more poorly with moderate-range "action-at-a-distance" interactions--GB has a tendency to overestimate solvent screening over moderate distances, and to underestimate the costs of desolvating charged groups somewhat removed from the binding interface. Despite this, however, GB does seem to be quite effective as a predictor of those groups that will be computed to be most significant in a PB-based model.

Conformational sampling of influenza fusion peptide in membrane bilayers as a function of termini and protonation states

Influenza fusion peptide is critical for mediating the fusion of viral and host cell membranes during viral entry. The interaction of monomeric influenza fusion peptide with membranes is studied with replica exchange molecular dynamics simulations using a new implicit membrane model to effectively reach microsecond to millisecond time scales. The conformational sampling of the fusion peptide was studied as a function of different N- and C-termini, including an experimental construct with an additional C-terminal tag, as well as a function of protonation of acidic residues. It is found that the influenza fusion peptide mostly adopts helical structures with a pronounced kink at residues 11-13 with both N-terminal and C-terminal helices oriented mostly parallel to the membrane surface. A charged C-terminus and the presence of a charge C-terminal tag significantly alters the conformational sampling of the fusion peptide and results in more diverse conformational ensembles that include obliquely inserted N-terminal peptide structures. Protonation of acidic residues also affects the conformational sampling, however, based on pK(a) shift estimates the overall effect of pH = 5 on the conformational sampling of the influenza fusion peptide appears to be only minor.

Quantitative analysis of Poisson-Boltzmann implicit solvent in molecular dynamics

A critical issue in the development of implicit solvent models is their quality in realistic simulations of non-trivial systems. In a previous study, we quantitatively compared the reaction field energies of static structures calculated with the Poisson-Boltzmann implicit solvent and the TIP3P explicit solvent and found an overall agreement, though a discrepancy was also observed in the electrostatic potentials of mean force for salt-bridging and hydrogen-bonding dimers (see J. Phys. Chem. B, 2006, 110, 18680). In this study, we are interested in how the implicit solvent performs in molecular dynamics simulations. To guarantee sampling convergence in simulated observables in the explicit solvent, we explored to use a high-temperature constant-volume simulation setting at 450 K but with the water density at 300 K. The relevance of the artificial simulation setting to room-temperature simulations of biomolecules was first investigated by systematic comparisons of the polar and nonpolar solvation free energies of 23 amino acid analogues at 300 K and 450 K, respectively. Assisted by the artificial simulation setting, we found the simulated secondary structure populations agree very well between the implicit and explicit solvents for tested dipeptides and peptides. In addition, the agreement in the populations of hydrophobic contacts is reasonable. However, our analysis also shows that the populations of the salt bridges are too low in the implicit solvent. The low salt-bridge population perhaps results from a combination of the atomic-centered modified van der Waals surface and the small solvent probe radius optimized to best reproduce the polar potential of mean force profiles. In addition, the lower accuracy of the electrostatic forces and the lack of water-bridged minima in the implicit solvents may also contribute to the instability of the salt bridge populations.

Nuance in the double-helix and its role in protein-DNA recognition

It has been known for some time that the double-helix is not a uniform structure but rather exhibits sequence-specific variations that, combined with base-specific intermolecular interactions, offer the possibility of numerous modes of protein-DNA recognition. All-atom simulations have revealed mechanistic insights into the structural and energetic basis of various recognition mechanisms for a number of protein-DNA complexes while coarser grained simulations have begun to provide an understanding of the function of larger assemblies. Molecular simulations have also been applied to the prediction of transcription factor binding sites, while empirical approaches have been developed to predict nucleosome positioning. Studies that combine and integrate experimental, statistical and computational data offer the promise of rapid advances in our understanding of protein-DNA recognition mechanisms.

A mesoscale model of DNA and its renaturation

A mesoscale model of DNA is presented (3SPN.1), extending the scheme previously developed by our group. Each nucleotide is mapped onto three interaction sites. Solvent is accounted for implicitly through a medium-effective dielectric constant and electrostatic interactions are treated at the level of Debye-Hückel theory. The force field includes a weak, solvent-induced attraction, which helps mediate the renaturation of DNA. Model parameterization is accomplished through replica exchange molecular dynamics simulations of short oligonucleotide sequences over a range of composition and chain length. The model describes the melting temperature of DNA as a function of composition as well as ionic strength, and is consistent with heat capacity profiles from experiments. The dependence of persistence length on ionic strength is also captured by the force field. The proposed model is used to examine the renaturation of DNA. It is found that a typical renaturation event occurs through a nucleation step, whereby an interplay between repulsive electrostatic interactions and colloidal-like attractions allows the system to undergo a series of rearrangements before complete molecular reassociation occurs.

Recent advances in implicit solvent-based methods for biomolecular simulations

Implicit solvent-based methods play an increasingly important role in molecular modeling of biomolecular structure and dynamics. Recent methodological developments have mainly focused on the extension of the generalized Born (GB) formalism for variable dielectric environments and accurate treatment of nonpolar solvation. Extensive efforts in parameterization of GB models and implicit solvent force fields have enabled ab initio simulation of protein folding to native or near-native structures. Another exciting area that has benefited from the advances in implicit solvent models is the development of constant pH molecular dynamics methods, which have recently been applied to the calculations of protein pK(a) values and the studies of pH-dependent peptide and protein folding.