Characterization of the TIP4P-Ew water model: vapor pressure and boiling point

Engineering salt-tolerant Cas12f1 variants for gene-editing applications

CRISPR has revolutionized the field of genome editing in life sciences by serving as a versatile and state-of-the-art tool. Cas12f1 is a small nuclease of the bacterial immunity CRISPR system with an ideal size for cellular delivery, in contrast to CRISPR-associated (Cas) proteins like Cas9 or Cas12. However, Cas12f1 works best at low salt concentrations. In this study, we find that the plasticity of certain Cas12f1 regions (K196-Y202 and I452-L515) is negatively affected by increased salt concentrations. On this line, key protein domains (REC1, WED, Nuc, lid) that are involved in the DNA-target recognition and the activation of the catalytic RuvC domain are in turn also affected. We suggest that salt concentration should be taken in to consideration for activity assessments of Cas engineered variants, especially if the mutations are on the protospacer adjacent motif interacting domain. The results can be exploited for the engineering of Cas variants and the assessment of their activity at varying salt concentrations. We propose that the K198Q mutation can restore at great degree the compromised plasticity and could potentially lead to salt-tolerant Cas12f1 variants. The methodology can be also employed for the study of biomolecules in terms of their salinity tolerance.Communicated by Ramaswamy H. Sarma.

Exploration of functionalizing graphene and the subsequent impact on PFAS adsorption capabilities via molecular dynamics

Per- and polyfluoroalkyl substances (PFAS) are extremely stable compounds due to their strong C-F bonds. They are used in water and stain proof coatings, aqueous film forming foams for fire suppression, cosmetics, paints, adhesives, etc. PFAS have been found in soils and waterways around the world due to their widespread usage and recalcitrance to degradation. Development of selective adsorbent materials is necessary to effectively capture a vast family of PFAS structures in order to remediate PFAS contamination in the environment. The work herein is focused on extracting design principles from molecular dynamics simulations of PFAS with functionalized graphene materials. Simulations examined how PFBA, PFOA, and PFOS interact with graphene, graphene oxide, nitrogen group-functionalized graphene oxide, partially fluorinated graphene flakes, and fully fluorinated flakes. Five flakes were used in each simulation to examine how interactions between flakes may lead to competitive interactions with respect to PFAS or formation of pores. Our study revealed that both the clustering mechanisms of the flakes and functional groups on the flake play a role in PFAS adsorption. The most effective functionalizations for PFAS adsorption are as follows: pristine graphene ≈ fully fluorinated > graphene oxide ≈ partially fluorinated > amine and amide functionalized graphene oxide flake. Long chain PFAS and sulfonate PFAS had higher propensity to adsorb to the materials compared to short chain PFAS and carboxylic head groups.

Thermodynamics perturbation theory for solvation of nonpolar solutes in rose model

A simple model of water, called the rose model, is used in this work. The rose model is a very simple model that can provide insight into the anomalous properties of water. In the rose water model, the molecules are represented as two-dimensional Lennard-Jones disks with potentials for orientation-dependent pairwise interactions mimicking formations of hydrogen bonds. We have recently applied a Wertheim integral equation theory (IET) and a thermodynamic perturbation theory (TPT) to the rose model in bulk. These analytical theories offer the advantage of being computationally less intensive than computer simulations by orders of magnitudes. Here we have applied the TPT to study the transfer of a nonpolar solute into rose water, the so-called hydrophobic effect. Similarly as in our previous work for bulk water, we have found that the theory reproduces the computer simulation results quite well at higher temperatures, while the theories predict the qualitative trends at low temperatures.

Neural Network Water Model Based on the MB-Pol Many-Body Potential

The MB-pol many-body potential accurately predicts many properties of water, including cluster, liquid phase, and vapor-liquid equilibrium properties, but its high computational cost can make applying it in large-scale simulations quite challenging. In order to address this limitation, we developed a "deep potential" neural network (DPMD) model based on the MB-pol potential for water. We find that a DPMD model trained on mostly liquid configurations yields a good description of the bulk liquid phase but severely underpredicts vapor-liquid coexistence densities. By contrast, adding cluster configurations to the neural network training set leads to a good agreement for the vapor coexistence densities. Liquid phase densities under supercooled conditions are also represented well, even though they were not included in the training set. These results confirm that neural network models can combine accuracy and transferability if sufficient attention is given to the construction of a representative training set for the target system.

Angle-dependent integral equation theory improves results of thermodynamics and structure of rose water model

Orientation-dependent integral equation theory (ODIET) was applied to the rose water model. Structural and thermodynamic properties of water modeled with the rose model were calculated using ODIET and compared to results from orientation-averaged integral equation theory (IET) and Monte Carlo simulations. Rose water model is a simple two-dimensional water model where molecules of water are represented as Lennard-Jones disks with explicit hydrogen bonding potential in form of rose functions. Orientational dependency significantly improves IET, as the thermodynamic results obtained using ODIET are significantly more in agreement with results calculated using MC than in the case of the orientationally averaged version. At high temperatures, the agreement between the simulation and theory is quantitative; however, when temperatures lower, a slight deviation between results obtained with different methods appear. ODIET correctly predicts the radial distribution function; moreover, ODIet also enables the calculation of angular distributions. While the angular distributions obtained with ODIET are in qualitative agreement with distributions from MC simulations, the height of the peaks in angular distributions differs between methods. Using results from ODIET, the spatial distribution of water molecules was constructed, which aids in the interpretation of other structural properties. ODIET was also used to calculate fractions of molecules with different number of hydrogen bonds, which is in the agreement with the simulations. Overall, use of ODIET significantly improves the obtained results in comparison to standard IET.

A Deep Potential model for liquid-vapor equilibrium and cavitation rates of water

Computational studies of liquid water and its phase transition into vapor have traditionally been performed using classical water models. Here, we utilize the Deep Potential methodology-a machine learning approach-to study this ubiquitous phase transition, starting from the phase diagram in the liquid-vapor coexistence regime. The machine learning model is trained on ab initio energies and forces based on the SCAN density functional, which has been previously shown to reproduce solid phases and other properties of water. Here, we compute the surface tension, saturation pressure, and enthalpy of vaporization for a range of temperatures spanning from 300 to 600 K and evaluate the Deep Potential model performance against experimental results and the semiempirical TIP4P/2005 classical model. Moreover, by employing the seeding technique, we evaluate the free energy barrier and nucleation rate at negative pressures for the isotherm of 296.4 K. We find that the nucleation rates obtained from the Deep Potential model deviate from those computed for the TIP4P/2005 water model due to an underestimation in the surface tension from the Deep Potential model. From analysis of the seeding simulations, we also evaluate the Tolman length for the Deep Potential water model, which is (0.091 ± 0.008) nm at 296.4 K. Finally, we identify that water molecules display a preferential orientation in the liquid-vapor interface, in which H atoms tend to point toward the vapor phase to maximize the enthalpic gain of interfacial molecules. We find that this behavior is more pronounced for planar interfaces than for the curved interfaces in bubbles. This work represents the first application of Deep Potential models to the study of liquid-vapor coexistence and water cavitation.

Fuzzy Drug Targets: Disordered Proteins in the Drug-Discovery Realm

Intrinsically disordered proteins (IDPs) and regions (IDRs) form a large part of the eukaryotic proteome. Contrary to the structure-function paradigm, the disordered proteins perform a myriad of functions in vivo. Consequently, they are involved in various disease pathways and are plausible drug targets. Unlike folded proteins, that have a defined structure and well carved out drug-binding pockets that can guide lead molecule selection, the disordered proteins require alternative drug-development methodologies that are based on an acceptable picture of their conformational ensemble. In this review, we discuss various experimental and computational techniques that contribute toward understanding IDP "structure" and describe representative pursuances toward IDP-targeting drug development. We also discuss ideas on developing rational drug design protocols targeting IDPs.

An overview of the SAMPL8 host-guest binding challenge

The SAMPL series of challenges aim to focus the community on specific modeling challenges, while testing and hopefully driving progress of computational methods to help guide pharmaceutical drug discovery. In this study, we report on the results of the SAMPL8 host–guest blind challenge for predicting absolute binding affinities. SAMPL8 focused on two host–guest datasets, one involving the cucurbituril CB8 (with a series of common drugs of abuse) and another involving two different Gibb deep-cavity cavitands. The latter dataset involved a previously featured deep cavity cavitand (TEMOA) as well as a new variant (TEETOA), both binding to a series of relatively rigid fragment-like guests. Challenge participants employed a reasonably wide variety of methods, though many of these were based on molecular simulations, and predictive accuracy was mixed. As in some previous SAMPL iterations (SAMPL6 and SAMPL7), we found that one approach to achieve greater accuracy was to apply empirical corrections to the binding free energy predictions, taking advantage of prior data on binding to these hosts. Another approach which performed well was a hybrid MD-based approach with reweighting to a force matched QM potential. In the cavitand challenge, an alchemical method using the AMOEBA-polarizable force field achieved the best success with RMSE less than 1 kcal/mol, while another alchemical approach (ATM/GAFF2-AM1BCC/TIP3P/HREM) had RMSE less than 1.75 kcal/mol. The work discussed here also highlights several important lessons; for example, retrospective studies of reference calculations demonstrate the sensitivity of predicted binding free energies to ethyl group sampling and/or guest starting pose, providing guidance to help improve future studies on these systems.

Introducing a New Bond-Forming Activity in an Archaeal DNA Polymerase by Structure-Guided Enzyme Redesign

DNA polymerases have evolved to feature a highly conserved activity across the tree of life: formation of, without exception, internucleotidyl O-P linkages. Can this linkage selectivity be overcome by design to produce xenonucleic acids? Here, we report that the structure-guided redesign of an archaeal DNA polymerase, 9°N, exhibits a new activity undetectable in the wild-type enzyme: catalyzing the formation of internucleotidyl N-P linkages using 3'-NH₂-ddNTPs. Replacing a metal-binding aspartate in the 9°N active site with asparagine was key to the emergence of this unnatural enzyme activity. MD simulations provided insights into how a single substitution enhances the productive positioning of a 3'-amino nucleophile in the active site. Further remodeling of the protein-nucleic acid interface in the finger subdomain yielded a quadruple-mutant variant (9°N-NRQS) displaying DNA-dependent NP-DNA polymerase activity. In addition, the engineered promiscuity of 9°N-NRQS was leveraged for one-pot synthesis of DNA─NP-DNA copolymers. This work sheds light on the molecular basis of substrate fidelity and latent promiscuity in enzymes.

The effects of surface hydration on capillary adhesion under nanoscale confinement

Nanoscale phenomena such as surface hydration and the molecular layering of liquids under strong nanoscale confinement play a critical role in liquid-mediated surface adhesion that is not accounted for by available models, which assume a uniform liquid density with or without considering surface forces and associated disjoining pressure effects. This work introduces an alternative theoretical description that via the potential of mean force (PMF) considers the strong spatial variation of the liquid number density under nanoscale confinement. This alternative description based on the PMF predicts a dual effect of surface hydration by producing: (i) strong spatial oscillations of the local liquid density and pressure and, more importantly, (ii) a configuration-dependent liquid-solid surface energy under nanoscale confinement. Theoretical analysis and molecular dynamics simulations for the case of an axisymmetric water bridge with nanoscale heights show that the latter hydration effect is critical for the accurate prediction of the surface energy and adhesion forces when a small volume of liquid is nanoscopically confined by two surfaces approaching contact.

Patched 1 regulates Smoothened by controlling sterol binding to its extracellular cysteine-rich domain

Smoothened (SMO) transduces the Hedgehog (Hh) signal across the plasma membrane in response to accessible cholesterol. Cholesterol binds SMO at two sites: one in the extracellular cysteine-rich domain (CRD) and a second in the transmembrane domain (TMD). How these two sterol-binding sites mediate SMO activation in response to the ligand Sonic Hedgehog (SHH) remains unknown. We find that mutations in the CRD (but not the TMD) reduce the fold increase in SMO activity triggered by SHH. SHH also promotes the photocrosslinking of a sterol analog to the CRD in intact cells. In contrast, sterol binding to the TMD site boosts SMO activity regardless of SHH exposure. Mutational and computational analyses show that these sites are in allosteric communication despite being 45 angstroms apart. Hence, sterols function as both SHH-regulated orthosteric ligands at the CRD and allosteric ligands at the TMD to regulate SMO activity and Hh signaling.

Open Force Field Evaluator: An Automated, Efficient, and Scalable Framework for the Estimation of Physical Properties from Molecular Simulation

Developing accurate classical force field representations of molecules is key to realizing the full potential of molecular simulations, both as a powerful route to gaining fundamental insights into a broad spectrum of chemical and biological phenomena and for predicting physicochemical and mechanical properties of substances. The Open Force Field Consortium is an industry-funded open science effort to this end, developing open-source tools for rapidly generating new high-quality small-molecule force fields. An integral aspect of this is the parameterization and assessment of force fields against high-quality, condensed-phase physical property data, curated from open data sources such as the NIST ThermoML Archive, alongside quantum chemical data. The quantity of such experimental data in open data archives alone would require an onerous amount of human and computational resources to both curate and estimate manually, especially when estimations must be obtained for numerous sets of force field parameters. Here, we present an entirely automated, highly scalable framework for evaluating physical properties and their gradients in terms of force field parameters. It is written as a modular and extensible Python framework, which employs an intelligent multiscale estimation approach that allows for the automated estimation of properties from simulation and cached simulation data, and a pluggable API for estimation of new properties. In this study, we demonstrate the utility of the framework by benchmarking the OpenFF 1.0.0 small-molecule force field and GAFF 1.8 and GAFF 2.1 force fields against a test set of binary density and enthalpy of mixing measurements curated using the framework utilities. Further, we demonstrate the framework's utility as part of force field optimization by using it alongside ForceBalance, a framework for systematic force field optimization, to retrain a set of nonbonded van der Waals parameters against a training set of density and enthalpy of vaporization measurements.

Atomistic Insights into the Droplet Size Evolution during Self-Microemulsification

Microemulsions have been attracting great attention for their importance in various fields, including nanomaterial fabrication, food industry, drug delivery, and enhanced oil recovery. Atomistic insights into the self-microemulsifying process and the underlying mechanisms are crucial for the design and tuning of the size of microemulsion droplets toward applications. In this work, coarse-grained models were used to investigate the role that droplet sizes played in the preliminary self-microemulsifying process. Time evolution of liquid mixtures consisting of several hundreds of water/surfactant/oil droplets was resolved in large-scale simulations. By monitoring the size variation of the microemulsion droplets in the self-microemulsifying process, the dynamics of diameter distribution of water/surfactant/oil droplets were studied. The underlying mass transport mechanisms responsible for droplet size evolution and stability were elucidated. Specifically, temperature effects on the droplet size were clarified. This work provides the knowledge of the self-microemulsification of water-in-oil microemulsions at the nanoscale. The results are expected to serve as guidelines for practical strategies for preparing a microemulsion system with desirable droplet sizes and properties.

Predicting the Solubility of Nonelectrolyte Solids Using a Combination of Molecular Simulation with the Solubility Parameter Method MOSCED: Application to the Wastewater Contaminants Monuron, Diuron, Atrazine and Atenolol

Methods to predict the equilibrium solubility of nonelectrolyte solids are indispensable for early-stage process development, design, and feasibility studies. Conventional analytic methods typically require reference data to regress parameters, which may not be available or limited for novel systems. Molecular simulation is a promising alternative, but is computationally intensive. Here, we demonstrate the ability to use a small number of molecular simulation free energy calculations to generate reference data to regress model parameters for the analytical MOSCED (modified separation of cohesive energy density) model. The result is an efficient analytical method to predict the equilibrium solubility of nonelectrolyte solids. The method is demonstrated for the wastewater contaminants monuron, diuron, atrazine and atenolol. Predictions for monuron, diuron and atrazine are in reasonable agreement with MOSCED parameters regressed using experimental solubility data. Predictions for atenolol are inferior, suggesting a potential limitation in the adopted molecular models, or the solvents selected to generate the necessary reference data.

Progress toward SHAPE Constrained Computational Prediction of Tertiary Interactions in RNA Structure

As more sequencing data accumulate and novel puzzling genetic regulations are discovered, the need for accurate automated modeling of RNA structure increases. RNA structure modeling from chemical probing experiments has made tremendous progress, however accurately predicting large RNA structures is still challenging for several reasons: RNA are inherently flexible and often adopt many energetically similar structures, which are not reliably distinguished by the available, incomplete thermodynamic model. Moreover, computationally, the problem is aggravated by the relevance of pseudoknots and non-canonical base pairs, which are hardly predicted efficiently. To identify nucleotides involved in pseudoknots and non-canonical interactions, we scrutinized the SHAPE reactivity of each nucleotide of the 188 nt long lariat-capping ribozyme under multiple conditions. Reactivities analyzed in the light of the X-ray structure were shown to report accurately the nucleotide status. Those that seemed paradoxical were rationalized by the nucleotide behavior along molecular dynamic simulations. We show that valuable information on intricate interactions can be deduced from probing with different reagents, and in the presence or absence of Mg2+. Furthermore, probing at increasing temperature was remarkably efficient at pointing to non-canonical interactions and pseudoknot pairings. The possibilities of following such strategies to inform structure modeling software are discussed.

Wide-angle X-ray scattering and molecular dynamics simulations of supercooled protein hydration water

Understanding the mechanism responsible for the protein low-temperature crossover observed at T≈ 220 K can help us improve current cryopreservation technologies. This crossover is associated with changes in the dynamics of the system, such as in the mean-squared displacement, whereas experimental evidence of structural changes is sparse. Here we investigate hydrated lysozyme proteins by using a combination of wide-angle X-ray scattering and molecular dynamics (MD) simulations. Experimentally we suppress crystallization by accurate control of the protein hydration level, which allows access to temperatures down to T = 175 K. The experimental data indicate that the scattering intensity peak at Q = 1.54 Å-1, attributed to interatomic distances, exhibits temperature-dependent changes upon cooling. In the MD simulations it is possible to decompose the water and protein contributions and we observe that, while the protein component is nearly temperature independent, the hydration water peak shifts in a fashion similar to that of bulk water. The observed trends are analysed by using the water-water and water-protein radial distribution functions, which indicate changes in the local probability density of hydration water.

Molecular dynamics simulations of allosteric motions and competitive inhibition of the Zika virus helicase

The 2015 Zika outbreak sparked major global concern and emphasized the reality and dangers still posed by mosquito borne pathogens. While efforts have been made to develop a vaccine and other therapeutics, there is still a great demand for antiviral drugs targeting Zika and other flaviviruses. The non-structural protein 3 (NS3) helicase is a vital component of the viral replication complex, tasked with unwinding the viral dsRNA molecule into single strands. Given this critical function, the Zika virus helicase is a potential therapeutic target and the focus of many ongoing research efforts. Using a combination of drug docking and molecular dynamics simulations, we have identified a list of competitive helicase inhibitors targeting the ATP hydrolysis site and have discovered a potential allosteric site capable of distorting both of the protein's active sites.

Peripheral Methionine Residues Impact Flavin Photoreduction and Protonation in an Engineered LOV Domain Light Sensor

Proton-coupled electron transfer reactions play critical roles in many aspects of sensory phototransduction. In the case of flavoprotein light sensors, reductive quenching of flavin excited states initiates chemical and conformational changes that ultimately transmit light signals to downstream targets. These reactions generally require neighboring aromatic residues and proton-donating side chains for rapid and coordinated electron and proton transfer to flavin. Although photoreduction of flavoproteins can produce either the anionic (ASQ) or neutral semiquinone (NSQ), the factors that favor one over the other are not well understood. Here we employ a biologically active variant of the light-oxygen-voltage (LOV) domain protein VVD devoid of the adduct-forming Cys residue (VVD-III) to probe the mechanism of flavin photoreduction and protonation. A series of isosteric and conservative residue replacements studied by rate measurements, fluorescence quantum yields, FTIR difference spectroscopy, and molecular dynamics simulations indicate that tyrosine residues facilitate charge recombination reactions that limit sustained flavin reduction, whereas methionine residues facilitate radical propagation and quenching and also gate solvent access for flavin protonation. Replacement of a single surface Met residue with Leu favors formation of the ASQ over the NSQ and desensitizes photoreduction to oxidants. In contrast, increasing site hydrophilicity by Gln substitution promotes rapid NSQ formation and weakens the influence of the redox environment. Overall, the photoreactivity of VVD-III can be understood in terms of redundant electron donors, internal hole quenching, and coupled proton transfer reactions that all depend upon protein conformation, dynamics, and solvent penetration.

Mapping Water Thermodynamics on Drug Candidates via Molecular Building Blocks: a Strategy to Improve Ligand Design and Rationalize SAR

The consideration of interactions involving water molecules in protein-ligand binding is widely appreciated in drug discovery nowadays. However, it is not ultimately clear how insights about these interactions translate into molecular design concepts. In this work, we introduce a computational strategy that, trained with high-precision experimental data, allows for the decomposition of water-related thermodynamic properties into chemically relevant building blocks (BBs) of a given ligand scaffold. For each of these BBs, a score based on solvation energy and entropy is computed, thus enabling the analysis of solvent-related affinity contributions for individual BBs. We find the nonvariable BB in a congeneric ligand pair to have a larger impact on the binding affinity than the variable part thus suggesting strong cooperative effects. Furthermore, we find enhanced solute-solvent interactions for a BB due to the presence of a C-F bond. Our investigation may be used to design drug molecules with tailored solvent thermodynamic properties.

AMBER-DYES in AMBER: Implementation of fluorophore and linker parameters into AmberTools

Molecular dynamics (MD) simulations of explicit representations of fluorescent dyes attached via a linker to a protein allow, e.g., probing commonly used approximations for dye localization and/or orientation or modeling Förster resonance energy transfer. However, setting up and performing such MD simulations with the AMBER suite of biomolecular simulation programs has remained challenging due to the unavailability of an easy-to-use set of parameters within AMBER. Here, we adapted the AMBER-DYES parameter set derived by Graen et al. [J. Chem. Theory Comput. 10, 5505 (2014)] into "AMBER-DYES in AMBER" to generate a force field applicable within AMBER for commonly used fluorescent dyes and linkers attached to a protein. In particular, the computationally efficient graphics processing unit (GPU) implementation of the AMBER MD engine can now be exploited to overcome sampling issues of dye movements. The implementation is compatible with state-of-the-art force fields such as GAFF, GAFF2, ff99SB, ff14SB, lipid17, and GLYCAM_06j, which allows simulating post-translationally modified proteins and/or protein-ligand complexes and/or proteins in membrane environments. It is applicable with frequently used water models such as TIP3P, TIP4P, TIP4P-Ew, and OPC. For ease of use, a LEaP-based workflow was created, which allows attaching (multiple) dye/linker combinations to a protein prior to further system preparation steps. Following the parameter development described by Graen et al. [J. Chem. Theory Comput. 10, 5505 (2014)] and the adaptation steps described here, AMBER-DYES in AMBER can be extended by additional linkers and fluorescent molecules.

Do Internal and External Surfaces of Metal-Organic Frameworks Have the Same Hydrophobicity? Insights from Molecular Simulations

Reliable information on the hydrophobicity of porous materials is important in the design of many catalytic and separation processes. In general, hydrophobicity is assessed by measuring the contact angle of water (external surface) or the adsorption isotherm of water (internal surface). However, it is not clear how these different assessments are related. In this paper, molecular dynamics simulations of microscopic water droplets on the external surfaces of metal-organic frameworks are used to investigate the influence of the surface nature and hydrophobicity on the contact angle. The metal-organic frameworks MOF-5 and CAU-10 were modeled with external surfaces of different hydrophobicities, while the internal surface was maintained. It was observed that microscopic droplets orientate their spreading to the nature of the external surfaces. Comparing the simulated contact angles and adsorption isotherms confirms the necessity to distinguish between internal and external hydrophobicity.

Probing the temperature profile across a liquid-vapor interface upon phase change

Understanding the temperature profile across a liquid-vapor interface in the presence of phase change is essential for the accurate prediction of evaporation, boiling, and condensation. It has been shown experimentally, from non-equilibrium thermodynamics and using molecular dynamics simulations, the existence of an inverted temperature profile across an evaporating liquid-vapor interface, where the vapor-side interface temperature observes the lowest value and the vapor temperature increases away from the interface, opposite to the direction of heat flow. It is worth noting, however, that an inverted temperature profile is not always the case from other experiments and simulations. In this study, we apply non-equilibrium molecular dynamics simulations to systematically study the temperature profile across a liquid-vapor interface during phase change under various heat fluxes in a two-interface setting consisting of both an evaporating and a condensing interface. The calculated vapor temperature shows different characteristics inside the Knudsen layer and in the bulk vapor. In addition, both the direction and magnitude of the vapor temperature gradient, as well as the temperature jump at the liquid-vapor interface, are functions of the applied heat flux. The interfacial entropy generation rate calculated from the vibrational density of state of the interfacial liquid and vapor molecules shows a positive production during evaporation, and the results qualitatively agree with the predictions from non-equilibrium thermodynamics.

Nucleotide Loading Modes of Human RNA Polymerase II as Deciphered by Molecular Simulations

Mapping the route of nucleoside triphosphate (NTP) entry into the sequestered active site of RNA polymerase (RNAP) has major implications for elucidating the complete nucleotide addition cycle. Constituting a dichotomy that remains to be resolved, two alternatives, direct NTP delivery via the secondary channel (CH2) or selection to downstream sites in the main channel (CH1) prior to catalysis, have been proposed. In this study, accelerated molecular dynamics simulations of freely diffusing NTPs about RNAPII were applied to refine the CH2 model and uncover atomic details on the CH1 model that previously lacked a persuasive structural framework to illustrate its mechanism of action. Diffusion and binding of NTPs to downstream DNA, and the transfer of a preselected NTP to the active site, are simulated for the first time. All-atom simulations further support that CH1 loading is transcription factor IIF (TFIIF) dependent and impacts catalytic isomerization. Altogether, the alternative nucleotide loading systems may allow distinct transcriptional landscapes to be expressed.

Assessment of the SM12, SM8, and SMD Solvation Models for Predicting Limiting Activity Coefficients at 298.15 K

The SMx (x = 12, 8, or D) universal solvent models are implicit solvent models which using electronic structure calculations can compute solvation free energies at 298.15 K. While solvation free energy is an important thermophysical property, within the thermodynamic modeling of phase equilibrium, limiting (or infinite dilution) activity coefficients are preferred since they may be used to parameterize excess Gibbs free energy models to model phase equilibrium. Conveniently, the two quantities are related. Therefore the present study was performed to assess the ability to use the SMx universal solvent models to predict limiting activity coefficients. Two methods of calculating the limiting activity coefficient where compared: (1) the solvation free energy and self-solvation free energy were both predicted and (2) the self-solvation free energy was computed using readily available vapor pressure data. Overall the first method is preferred as it results in a cancellation of errors, specifically for the case in which water is a solute. The SM12 model was compared to both the Universal Quasichemical Functional-group Activity Coefficients (UNIFAC) and modified separation of cohesive energy density (MOSCED) models. MOSCED was the highest performer, yet had the smallest available compound inventory. UNIFAC and SM12 exhibited comparable performance. Therefore further exploration and research should be conducted into the viability of using the SMx models for phase equilibrium calculations.

Integrated Structural Modeling of Full-Length LRH-1 Reveals Inter-domain Interactions Contribute to Receptor Structure and Function

Liver receptor homolog-1 (LRH-1; NR5A2) is a nuclear receptor that regulates a diverse array of biological processes. In contrast to dimeric nuclear receptors, LRH-1 is an obligate monomer and contains a subtype-specific helix at the C terminus of the DNA-binding domain (DBD), termed FTZ-F1. Although detailed structural information is available for individual domains of LRH-1, it is unknown how these domains exist in the intact nuclear receptor. Here, we developed an integrated structural model of human full-length LRH-1 using a combination of HDX-MS, XL-MS, Rosetta computational docking, and SAXS. The model predicts the DBD FTZ-F1 helix directly interacts with ligand binding domain helix 2. We confirmed several other predicted inter-domain interactions via structural and functional analyses. Comparison between the LRH-1/Dax-1 co-crystal structure and the integrated model predicted and confirmed Dax-1 co-repressor to modulate LRH-1 inter-domain dynamics. Together, these data support individual LRH-1 domains interacting to influence receptor structure and function.

Dynamics of water trapped in transition metal oxide-graphene nano-confinement

Motivated by practical implementation of transition-metal oxide-graphene heterostructures, we use all atom molecular dynamics simulations to study dynamics of water in a nano slit bounded by a transition metal oxide surface, namely, TiO2termination of SrTiO3, and graphene. The resultant asymmetric, strong confinement produces square ice-like crystallites of water pinned at TiO2surface and drives enhanced hydrophobicity of graphene via the proximity effect to the hydrophilic TiO2surface. This importantly brings in dynamic heterogeneity, both in translational and rotational degrees of freedom, due to coupling between the slow relaxing, strongly adsorbed water layer at the hydrophilic oxide surface, and faster relaxation of subsequent water layers. The heterogeneity is signalled in the ruggedness of the effective free energy landscapes. We discuss possible implications of our findings in drug delivery.

Comparing Alchemical Free Energy Estimates to Experimental Values Based on the Ben-Naim Formula: How Much Agreement Can We Expect?

The solvation free energy (SFE) plays a key role in thermodynamics. One well-established method for computing the SFE is through an alchemical transformation. However, experimental SFEs are generally determined according to the Ben-Naim equations relying on vapor pressure or density ratios. It is important to establish whether, or to what extent, typical alchemical-based free energy computations provide results comparable to experimental SFEs. In this work, we mimic experimental measurements by simulating the liquid-vapor coexistence of water without alchemical operations. The SFEs measured through vapor pressure and density ratios are used to validate the SFEs obtained through alchemical transformations. It is shown that proper consideration of the nonideal behavior of the vapor is important to ensure that the alchemical SFEs are consistent with the Ben-Naim SFEs. Alchemical transformations in the vapor phase should be performed in addition to solution phase transformations for strongly interacting solutes, such as those with low boiling temperatures and large second virial coefficients. A formula based on the virial expansion of pressure is proposed to provide a better estimate of the true SFE from the simulated vapor pressures. The proposed formula is also applicable to experimental determinations of SFE when the pressure-based route is used.

MDMS: Software Facilitating Performing Molecular Dynamics Simulations

Molecular Dynamics Made Simple (MDMS) is software that facilitates performing molecular dynamics (MD) simulations of solvated protein/protein-ligand complexes with Amber, one of the most popular MD codes. It guides users through the whole process of running MD starting with choosing a protein structure, preparing the model, parametrization of the system, establishing parameters for controlling MD, and finally running simulations. By accommodating every step required for running MD, this software ensures that the simulations performed by a user will provide as realistic insight as it is possible. Its sequential structure and a text-based interface ensure ease of use, while the flexibility required for complex cases is still preserved. MDMS also provides a very time-efficient and streamlined method to start MD simulations, which makes it a feasible tool for both novices and experienced computational chemists. © 2019 Wiley Periodicals, Inc.

Thermodynamics of Helix formation in small peptides of varying lengthin vacuo, implicit solvent and explicit solvent: Comparison between AMBER force fields

Helix formation is of great significance in protein folding. The helix-forming tendencies of amino acids are accumulated along the sequence to determine the helix-forming tendency of peptides. Computer simulation can be used to model this process in atomic details and give structural insights. In the current work, we employ equilibrate-state free energy simulation to systematically study the folding/unfolding thermodynamics of a series of mutated peptides. Two AMBER force fields including AMBER99SB and AMBER14SB are compared. The new 14SB force field uses refitted torsion parameters compared with 99SB and they share the same atomic charge scheme. We find that in vacuo the helix formation is mutation dependent, which reflects the different helix propensities of different amino acids. In general, there are helix formers, helix indifferent groups and helix breakers. The helical structure becomes more favored when the length of the sequence becomes longer, which arises from the formation of additional backbone hydrogen bonds in the lengthened sequence. Therefore, the helix indifferent groups and helix breakers will become helix formers in long sequences. Also, protonation-dependent helix formation is observed for ionizable groups. In 14SB, the helical structures are more stable than in 99SB and differences can be observed in their grouping schemes, especially in the helix indifferent group. In solvents, all mutations are helix indifferent due to protein–solvent interactions. The decrease in the number of backbone hydrogen bonds is the same with the increase in the number of protein–water hydrogen bonds. The 14SB in explicit solvent is able to capture the free energy minima in the helical state while 14SB in implicit solvent, 99SB in explicit solvent and 99SB in implicit solvent cannot. The helix propensities calculated under 14SB agree with the corresponding experimental values, while the 99SB results obviously deviate from the references. Hence, implicit solvent models are unable to correctly describe the thermodynamics even for the simple helix formation in isolated peptides. Well-developed force fields and explicit solvents are needed to correctly describe the protein dynamics. Aside from the free energy, differences in conformational ensemble under different force fields in different solvent models are observed. The numbers of hydrogen bonds formed under different force fields agree and they are mostly determined by the solvent model.

Molecular dynamics simulations on human fibulin-4 mutants D203A and E126K reveal conformational changes in EGF domains potentially responsible for enhanced protease lability and impaired extracellular matrix assembly

Fibulin-4 is a 50 kDa glycoprotein of elastic fibers and plays an important role in development and function of elastic tissues. Fibulin-4 consists of a tandem array of five calcium-binding epidermal growth factor-like modules flanked by N- and C-terminal domains. Mutations in the human fibulin-4 gene EFEMP2 have been identified in patients affected with various arteriopathies including aneurysm, arterial tortuosity, or stenosis, but the molecular basis of most genotype-phenotype correlations is unknown. Here we present biochemical and computer modelling approaches designed to gain further insight into changes in structure and function of two fibulin-4 mutations (E126K and D203A), which are potentially involved in Ca²⁺ binding in the EGF2 and EGF4 domain, respectively. Using recombinantly produced fibulin-4 mutant and wild type proteins we show that both mutations introduced additional protease cleavage sites, impaired extracellular assembly into fibers, and affected binding to to fibrillin-1, latent TGF-β-binding proteins, and the lysyl oxidase LOXL2. Molecular dynamics studies indicated that the E126K and D203A mutations do not necessarily result in a direct loss of the complexed Ca²⁺ ion after 500 ns simulation time, but in significantly enhanced fluctuations within the connecting loop between EGF3 and EGF4 domains and other conformational changes. In contrast, intentionally removing Ca²⁺ from EGF4 (D203A ΔCa) predicted dramatic changes in the protein structure. These results may explain the changes in protease cleavage sites, reduced secretion and impaired extracellular assembly of the E126K and D203A fibulin-4 mutants and provide further insight into understanding the molecular basis of the associated clinical phenotypes.

A multiscale model of mechanotransduction by the ankyrin chains of the NOMPC channel

Our senses of touch and hearing are dependent on the conversion of external mechanical forces into electrical impulses by the opening of mechanosensitive channels in sensory cells. This remarkable feat involves the conversion of a macroscopic mechanical displacement into a subnanoscopic conformational change within the ion channel. The mechanosensitive channel NOMPC, responsible for hearing and touch in flies, is a homotetramer composed of four pore-forming transmembrane domains and four helical chains of 29 ankyrin repeats that extend 150 Å into the cytoplasm. Previous work has shown that the ankyrin chains behave as biological springs under extension and that tethering them to microtubules could be involved in the transmission of external forces to the NOMPC gate. Here we combine normal mode analysis (NMA), full-atom molecular dynamics simulations, and continuum mechanics to characterize the material properties of the chains under extreme compression and extension. NMA reveals that the lowest-frequency modes of motion correspond to fourfold symmetric compression/extension along the channel, and the lowest-frequency symmetric mode for the isolated channel domain involves rotations of the TRP domain, a putative gating element. Finite element modeling reveals that the ankyrin chains behave as a soft spring with a linear, effective spring constantof 22 pN/nm for deflections ≤15 Å. Force-balance analysis shows that the entire channel undergoes rigid body rotation during compression, and more importantly, each chain exerts a positive twisting moment on its respective linker helices and TRP domain. This torque is a model-independent consequence of the bundle geometry and would cause a clockwise rotation of the TRP domain when viewed from the cytoplasm. Force transmission to the channel for compressions >15 Å depends on the nature of helix-helix contact. Our work reveals that compression of the ankyrin chains imparts a rotational torque on the TRP domain, which potentially results in channel opening.

Thermophysical properties of glyceline–water mixtures investigated by molecular modelling

Water activity and shear viscosity of water–glyceline mixtures are important process parameters that can be effectively calculated using molecular modelling.

Droplets on Slippery Lubricant-Infused Porous Surfaces: A Macroscale to Nanoscale Perspective

A recent design approach in creating super-repellent surfaces through slippery surface lubrication offers tremendous liquid-shedding capabilities. Previous investigations have provided significant insights into droplet-lubricant interfacial behaviors that govern antiwetting properties but have often studied using macroscale droplets. Despite drastically different governing characteristics of ultrasmall droplets on slippery lubricated surfaces, little is known about the effects at the micro- and nanoscale. In this investigation, we impregnate a three-dimensionally, well-ordered porous metal architecture with a lubricant to confirm durable slippery surfaces. We then reduce the droplet size to a nanoliter range and experimentally compare the droplet behaviors at different length scales. By experimentally varying the lubricant thickness levels, we also reveal that the effect of lubricant wetting around ultrasmall droplets is intensely magnified, which significantly affects the transient droplet dynamics. Molecular dynamics computations further examine the ultrasmall droplets with varying lubricant levels or pore cut levels at the nanoscale. The combined experimental and computational work provides insights into droplet interfacial phenomena on slippery surfaces from a macroscale to nanoscale perspective.

Complex Behavior of Ordered and Icelike Water in Carbon Nanotubes near Its Bulk Boiling Point

We report the results of extensive molecular dynamics (MD) simulation of water in a carbon nanotube (CNT) with a specific diameter over a wide range of temperatures from 343 to 423 K. In order to characterize the nature of water, we have computed the Kirkwood g-factor, the ten Wolde parameter, the radial distribution, the cage correlation, the intermediate scattering functions, the mean-square displacements of the water molecules, and the connectivity of the oxygen atoms. The computed properties provide evidence for complex behavior. Some of the properties indicate an icelike structure, while others point to ordered (but not necessarily frozen) water. The connectivity is close to 9. The ordered water exists both below and above its bulk boiling point. The order is identified based on the ten Wolde parameter and may explain, along with the dynamic slow down, the recent discovery of "ice" in CNTs near the bulk boiling point in a certain range of CNT diameters, not seen in tubes of other sizes.

The interplay between dynamic heterogeneities and structure of bulk liquid water: A molecular dynamics simulation study

In order to study the interplay between dynamical heterogeneities and structural properties of bulk liquid water in the temperature range 130-350 K, thus including the supercooled regime, we use the explicit trend of the distribution functions of some molecular properties, namely, the rotational relaxation constants, the atomic mean-square displacements, the relaxation of the cross correlation functions between the linear and squared displacements of H and O atoms of each molecule, the tetrahedral order parameter q and, finally, the number of nearest neighbors (NNs) and of hydrogen bonds (HBs) per molecule. Two different potentials are considered: TIP4P-Ew and a model developed in this laboratory for the study of nanoconfined water. The results are similar for the dynamical properties, but are markedly different for the structural characteristics. In particular, for temperatures higher than that of the dynamic crossover between "fragile" (at higher temperatures) and "strong" (at lower temperatures) liquid behaviors detected around 207 K, the rotational relaxation of supercooled water appears to be remarkably homogeneous. However, the structural parameters (number of NNs and of HBs, as well as q) do not show homogeneous distributions, and these distributions are different for the two water models. Another dynamic crossover between "fragile" (at lower temperatures) and "strong" (at higher temperatures) liquid behaviors, corresponding to the one found experimentally at T(∗) ∼ 315 ± 5 K, was spotted at T(∗) ∼ 283 K and T(∗) ∼ 276 K for the TIP4P-Ew and the model developed in this laboratory, respectively. It was detected from the trend of Arrhenius plots of dynamic quantities and from the onset of a further heterogeneity in the rotational relaxation. To our best knowledge, it is the first time that this dynamical crossover is detected in computer simulations of bulk water. On the basis of the simulation results, the possible mechanisms of the two crossovers at molecular level are discussed.

Molecular dynamics simulation of triclinic lysozyme in a crystal lattice

Molecular dynamics simulations of crystals can enlighten interpretation of experimental X-ray crystallography data and elucidate structural dynamics and heterogeneity in biomolecular crystals. Furthermore, because of the direct comparison against experimental data, they can inform assessment of molecular dynamics methods and force fields. We present microsecond scale results for triclinic hen egg-white lysozyme in a supercell consisting of 12 independent unit cells using four contemporary force fields (Amber ff99SB, ff14ipq, ff14SB, and CHARMM 36) in crystalline and solvated states (for ff14SB only). We find the crystal simulations consistent across multiple runs of the same force field and robust to various solvent equilibration schemes. However, convergence is slow compared with solvent simulations. All the tested force fields reproduce experimental structural and dynamic properties well, but Amber ff14SB maintains structure and reproduces fluctuations closest to the experimental model: its average backbone structure differs from the deposited structure by 0.37Å; by contrast, the average backbone structure in solution differs from the deposited by 0.65Å. All the simulations are affected by a small progressive deterioration of the crystal lattice, presumably due to imperfect modeling of hydrogen bonding and other crystal contact interactions; this artifact is smallest in ff14SB, with average lattice positions deviating by 0.20Å from ideal. Side-chain disorder is surprisingly low with fewer than 30% of the nonglycine or alanine residues exhibiting significantly populated alternate rotamers. Our results provide helpful insight into the methodology of biomolecular crystal simulations and indicate directions for future work to obtain more accurate energy models for molecular dynamics.

Biocatalytic route to chiral acyloins: P450-catalyzed regio- and enantioselective α-hydroxylation of ketones

P450-BM3 and mutants of this monooxygenase generated by directed evolution are excellent catalysts for the oxidative α-hydroxylation of ketones with formation of chiral acyloins with high regioselectivity (up to 99%) and enantioselectivity (up to 99% ee). This constitutes a new route to a class of chiral compounds that are useful intermediates in the synthesis of many kinds of biologically active compounds.