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Heterocyclic thiones have recently been identified as reversible covalent warheads, consistent with their mild electrophilic nature. Little is known so far about their mechanism of action in labelling nucleophilic sidechains, especially cysteines. The vast number of tractable cysteines promotes a wide range of target proteins to examine; however, our focus was put on functional cysteines. We chose the main protease of SARS-CoV-2 harboring Cys145 at the active site that is a structurally characterized and clinically validated target of covalent inhibitors. We screened an in-house, cysteine-targeting covalent inhibitor library which resulted in several covalent fragment hits with benzoxazole, benzothiazole and benzimidazole cores. Thione derivatives and Michael acceptors were selected for further investigations with the objective of exploring the mechanism of inhibition of the thiones and using the thoroughly characterized Michael acceptors for benchmarking our studies. Classical and hybrid quantum mechanical/molecular mechanical (QM/MM) molecular dynamics simulations were carried out that revealed a new mechanism of covalent cysteine labelling by thione derivatives, which was supported by QM and free energy calculations and by a wide range of experimental results. Our study shows that the molecular recognition step plays a crucial role in the overall binding of both sets of molecules., (© 2023 The Authors. ChemPhysChem published by Wiley-VCH GmbH.)

Conducting statistical inference on systems described by ordinary differential equations (ODEs) is a challenging problem. Repeatedly numerically solving the system of equations incurs a high computational cost, making many methods based on explicitly solving the ODEs unsuitable in practice. Gradient matching methods were introduced in order to deal with the computational burden. These methods involve minimising the discrepancy between predicted gradients from the ODEs and those from a smooth interpolant. Work until now on gradient matching methods has focused on parameter inference. This paper considers the problem of model selection. We combine the method of thermodynamic integration to compute the log marginal likelihood with adaptive gradient matching using Gaussian processes, demonstrating that the method is robust and able to outperform BIC and WAIC. [ABSTRACT FROM AUTHOR]

Hydrogeological field studies rely often on a single conceptual representation of the subsurface. This is problematic since the impact of a poorly chosen conceptual model on predictions might be significantly larger than the one caused by parameter uncertainty. Furthermore, conceptual models often need to incorporate geological concepts and patterns in order to provide meaningful uncertainty quantification and predictions. Consequently, several geologically realistic conceptual models should ideally be considered and evaluated in terms of their relative merits. Here, we propose a full Bayesian methodology based on Markov chain Monte Carlo to enable model selection among 2‐D conceptual models that are sampled using training images and concepts from multiple‐point statistics. More precisely, power posteriors for the different conceptual subsurface models are sampled using sequential geostatistical resampling and Graph Cuts. To demonstrate the methodology, we compare and rank five alternative conceptual geological models that have been proposed in the literature to describe aquifer heterogeneity at the MAcroDispersion Experiment site in Mississippi, USA. We consider a small‐scale tracer test for which the spatial distribution of hydraulic conductivity impacts multilevel solute concentration data observed along a 2‐D transect. The thermodynamic integration and the stepping‐stone sampling methods were used to compute the evidence and associated Bayes factors using the computed power posteriors. We find that both methods are compatible with multiple‐point statistics‐based inversions and provide a consistent ranking of the competing conceptual models considered. Key Points: A full Bayesian method is proposed for model selection among geologically realistic conceptual modelsThermodynamic integration and stepping‐stone sampling provide consistent ranking of conceptual modelsThe method is applied to solute concentration data collected during a tracer test at the MADE site [ABSTRACT FROM AUTHOR]

Highlights • A cavity-based method to calculate relative solubilities of large solutes in pairs of solvents is presented. • The cavity-based method is benchmarked against direct molecular simulations employing coarse-grained fluid models. • Relative solubilities of pyrene in heptane and toluene are calculated at high pressures and temperatures. Abstract In this paper, we benchmark a cavity-based simulation method for calculating the relative solubility of large molecules in explicit solvents. The essence of the procedure is the accounting of the Gibbs energy change associated with an alchemical thermodynamic cycle where, in sequence, a cavity is created in a solvent, a solute is inserted in the cavity and the cavity is annihilated. The Gibbs energy change is equated to the excess chemical potential allowing the comparison of solubilities in different solvents. The results obtained using the cavity-based method are compared to direct large-scale molecular dynamics simulations performed using coarse-grained models for calculating the partition coefficient of pyrene between heptane and toluene. We demonstrate the applicability of this cavity-based technique under high pressure/temperature conditions. [ABSTRACT FROM AUTHOR]

Peptide‐based therapeutics are an alternative to small molecule drugs as they offer superior specificity, lower toxicity, and easy synthesis. Here we present an approach that leverages the dramatic performance increase afforded by the recent arrival of GPU accelerated thermodynamic integration (TI). GPU TI facilitates very fast, highly accurate binding affinity optimization of peptides against therapeutic targets. We benchmarked TI predictions using published peptide binding optimization studies. Prediction of mutations involving charged side‐chains was found to be less accurate than for non‐charged, and use of a more complex 3‐step TI protocol was found to boost accuracy in these cases. Using the 3‐step protocol for non‐charged side‐chains either had no effect or was detrimental. We use the benchmarked pipeline to optimize a peptide binding to our recently discovered cancer target: EME1. TI calculations predict beneficial mutations using both canonical and non‐canonical amino acids. We validate these predictions using fluorescence polarization and confirm that binding affinity is increased. We further demonstrate that this increase translates to a significant reduction in pancreatic cancer cell viability. [ABSTRACT FROM AUTHOR]

Abstract The pyroprocessing technology of spent fuel is promise because of its advantages compared with the wet-processing technology; however, the development of pyroprocessing technology depends on the availability of basic physical chemistry properties for the relevant molten salt mixtures. In this work, the first principles molecular dynamics (FPMD) simulation is applied to the evaluation of redox potential of tetravalent actinides (Pa4+, U4+, and Np4+) in molten LiCl–KCl (ClLiK) eutectic. The reduction energetics, referenced to Th4+, is analyzed in terms of vertical substitution and relaxation, and satisfactory agreement is reached between our FPMD evaluations and experimental results reported in literatures. Highlights • Redox potentials of tetravalent actinides in molten LiCl-KCl eutectic are calculated. • First principles molecular dynamics is applied to the calculation of redox potential. • Vertical substitution is employed for the calculation of relative energy. • Relaxation is proposed for the evaluation of relative energy. • Coordination structures of tetravalent actinides in molten LiCl-KCl eutectic are studied. [ABSTRACT FROM AUTHOR]

We present a molecular dynamics simulation study of alkali metal cation transport through the double‐helical and the head‐to‐head conformers of the gramicidin ion channel. Our approach is based on a thermodynamic integration network, which consists of a sequence of transport reactions, absolute free energies of solvation and cycles of alchemical transmutations of the ions. In this manner, we can reliably estimate free energies and their statistical errors via a least‐squares method without imposing external forces on the system. Within the double helical channel, we find a free energy surface typical for hopping transport between isoenergetic sites of ion localization, separated by comparatively large activation barriers. For fast transport through the head‐to‐head conformation, the thermodynamic network scheme starts to break down. © 2018 Wiley Periodicals, Inc. Ion migration in the gramicidin protein channel is simulated using a thermodynamic integration network, which consists of transport reactions, absolute free energies of solvation and alchemical transmutations of ions. For a double helical channel, we find a free energy surface typical for hopping transport between isoenergetic sites of ion localization, whereas the scheme starts to break down for fast transport through a head‐to‐head conformation. [ABSTRACT FROM AUTHOR]

A wide range of mutations in the kinesin motor Kif5A have been linked to a neuronal disorder called hereditary spastic paraplegia (HSP). The position of these mutations can vary, and a range of different motile behaviors have been observed, indicating that the HSP mutants can alter distinct aspects of kinesin mechanochemistry. While focusing on four key HSP-associated mutants, this study examined the structural and dynamic perturbations that arise from these mutations using a series of different computational methods, ranging from bioinformatics analyses to all-atom simulations, that account for solvent effects explicitly. We show that two catalytic domain mutations (R280S and K253N) reduce the microtubule (MT) binding affinity of the kinesin head domains appreciably, while N256S has a much smaller impact. Bioinformatics analysis suggests that the stalk mutation A361V perturbs motor dimerization. Subsequent integration of these effects into a coarse-grained structure-based model of dimeric kinesin revealed that the order-disorder transition of the neck linker is substantially affected, indicating a hampered directionality and processivity of kinesin. The present analyses therefore suggest that, in addition to kinesin-MT binding and coiled-coil dimerization, HSP mutations affecting motor stepping transitions and processivity can lead to disease. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The solid-liquid interfacial free energy, γ , was computed for the Cu-Zr system. • γ was found to increase with decreasing temperature. • Two methods for computing γ were found to be in agreement. Abstract The solid-liquid portion of the equilibrium phase diagram at the Cu rich side of a Finnis-Sinclair description of Cu-Zr was determined by a combination of molecular dynamics and semi-grand canonical Monte Carlo simulations and the model system was found to be in very good agreement with experiment. Molecular dynamics simulations and the capillary fluctuation method were used to compute the solid-liquid interfacial free energy, γ , and its anisotropy as a function of undercooling. Unlike the case of pure metals and in contrast to most previous atomistic studies in alloy systems, γ was found to increase with decreasing temperature and the increase is quite pronounced. To verify the unusual results, the excess energy and number of Zr atoms were computed for the [1 0 0] interface and from the excess thermodynamic quantities γ was obtained through a thermodynamic integration. The results of the two approaches for computing γ are in agreement to within the statistical uncertainties. The implications of the temperature behavior of γ is discussed in terms of crystal nucleation from the melt and glass formation. [ABSTRACT FROM AUTHOR]

Mutation in the ethionamide (ETH) activating enzyme, EthA, is the main factor determining resistance to this drug, used to treat TB patients infected with MDR and XDR Mycobacterium tuberculosis isolates. Many mutations in EthA of ETH resistant (ETH-R) isolates have been described but their roles in resistance remain uncharacterized, partly because structural studies on the enzyme are lacking. Thus, we took a two-tier approach to evaluate two mutations (Y50C and T453I) found in ETH-R clinical isolates. First, we used a combination of comparative modeling, molecular docking, and molecular dynamics to build an EthA model in complex with ETH that has hallmark features of structurally characterized homologs. Second, we used free energy computational calculations for the reliable prediction of relative free energies between the wild type and mutant enzymes. The ΔΔG values for Y50C and T453I mutant enzymes in complex with FADH2-NADP-ETH were 3.34 (+/−0.55) and 8.11 (+/−0.51) kcal/mol, respectively, compared to the wild type complex. The positive ΔΔG values indicate that the wild type complex is more stable than the mutants, with the T453I complex being the least stable. These are the first results shedding light on the molecular basis of ETH resistance, namely reduced complex stability of mutant EthA.

We present a novel implementation of the adaptively annealed thermodynamic integration technique using Hamiltonian Monte Carlo (HMC). Thermodynamic integration with importance sampling and adaptive annealing is an especially useful method for estimating model evidence for problems that use physics-based mathematical models. Because it is based on importance sampling, this method requires an efficient way to refresh the ensemble of samples. Existing successful implementations use binary slice sampling on the Hilbert curve to accomplish this task. This implementation works well if the model has few parameters or if it can be broken into separate parts with identical parameter priors that can be refreshed separately. However, for models that are not separable and have many parameters, a different method for refreshing the samples is needed. HMC, in the form of the MC-Stan package, is effective for jointly refreshing the ensemble under a high-dimensional model. MC-Stan uses automatic differentiation to compute the gradients of the likelihood that HMC requires in about the same amount of time as it computes the likelihood function itself, easing the programming burden compared to implementations of HMC that require explicitly specified gradient functions. We present a description of the overall TI-Stan procedure and results for representative example problems.

While model evidence is considered by Bayesian statisticians as a gold standard for model selection (the ratio in model evidence between two models giving the Bayes factor), its calculation is often viewed as too computationally demanding for many applications. By contrast, the widely used deviance information criterion (DIC), a different measure that balances model accuracy against complexity, is commonly considered a much faster alternative. However, recent advances in computational tools for efficient multi-temperature Markov chain Monte Carlo algorithms, such as steppingstone sampling (SS) and thermodynamic integration schemes, enable efficient calculation of the Bayesian model evidence. This paper compares both the capability (i.e. ability to select the true model) and speed (i.e. CPU time to achieve a given accuracy) of DIC with model evidence calculated using SS. Three important model classes are considered: linear regression models, mixed models and compartmental models widely used in epidemiology. While DIC was found to correctly identify the true model when applied to linear regression models, it led to incorrect model choice in the other two cases. On the other hand, model evidence led to correct model choice in all cases considered. Importantly, and perhaps surprisingly, DIC and model evidence were found to run at similar computational speeds, a result reinforced by analytically derived expressions.

Human serum retinol-binding protein (RBP) is a plasma transport protein for vitamin A. RBP is a prime subclass of lipocalins, which bind nonpolar ligands within a β-barrel. To understand the role of Trp 24, one of the highly conserved residues in RBP, free energy simulations have been carried out to understand the effects of the mutations from Trp at position 24 to Leu, Phe, and Tyr in the apo-RBP on its thermal stability. We examine various unfolded systems to study the dependence of the free energy differences on the denatured structure. Our calculated free energy difference values for the three mutations are in excellent agreement with the experimental values when the initial coordinates of the seven-residue peptide segments truncated from the crystal structure are used for the denatured systems. Our free energy change differences for the Trp→Leu, Trp→Phe, and Trp→Tyr mutations are 2.50   ±   0.69, 2.58   ±   0.50, and 2.49   ±   0.48   kcal/mol, respectively, when the native-like seven-residue peptides are used as models for the denatured systems. The main contributions to the free energy change differences for the Trp24→Leu and Trp24→Phe mutations are mainly from van der Waals and covalent interactions, respectively. Electrostatic, van der Waals and covalent terms equally contribute to the free energy change difference for the Trp24→Tyr mutation. The free energy simulation helps understand the detailed microscopic mechanism of the stability of the RBP mutants relative to the wild type and the role of the highly conserved residue, Trp24, of the human RBP.Communicated by Ramaswamy H. Sarma.

Since polyphenols are highly bioactive, their separation and purification are active research topics. In the optimization of such processes, the trend of solubility at different conditions is of major interest, although obtaining experimental solubility data for polyphenols is lengthy and costly. A simple and previously explored thermodynamic integration (TI) procedure was applied to estimate the Gibbs hydration free energies at different temperatures for benzoic acid, (+)-catechin and toluene. These hydration energies were compared with experimental solubilities. An extensive test with 10 replications comprising a total of 200 molecular dynamics (MD) TI simulations was conducted. Linear trends were observed for the estimated Gibbs hydration free energy at different temperatures. Electrostatic contributions showed a strong effect for the studied polyphenols due to hydrogen bonds. Lennard-Jones (LJ) contributions to hydration free energies were small, being more significant for toluene due to cavity formation. The estimated Gibbs free energy of hydration presented an exponential trend for benzoic acid and (+)-catechin when compared to experimental solubility data. These trends were fitted to an empirical expression. To understand the physical meaning of the empirical fitting parameters, the effect of temperature in the sublimation enthalpy and in the entropy of the solid solute should be estimated. [ABSTRACT FROM AUTHOR]

The phase equilibria knowledge of fatty acid and water mixtures play a crucial role in the design and operation of processes such as bio-diesel synthesis, sea water desalination and novel solvent design. Experimental data on the mutual solubility of fatty acid and water are scattered and limited. Atomistic molecular simulation approach can be a viable substitute for these predictions. In this work, a molecular simulation method is proposed that does not require molecular transfer between dense phases as in the Gibbs ensemble method and is based on determining phase equilibria by computing and equating the fugacity of water in the two phases. Assuming that the fugacity of water-rich phase is identical to that of pure water, an expression for the solubility of fatty acid in water is derived. In the current formalism, fugacity is determined by computing the residual chemical potential of water and fatty acids via thermodynamic integration. Mutual solubility between water and three different fatty acids are calculated over a range of temperatures and shown to yield good agreement with experimental data. Microscopic structural properties elucidating the role of the hydrogen bonding interactions between water and fatty acid and the aggregation of water molecules which gives rise to the observed macroscopic properties are also studied. [ABSTRACT FROM AUTHOR]

The free energetics of water density fluctuations in bulk water, at interfaces, and in hydrophobic confinement inform the hydration of hydrophobic solutes as well as their interactions and assembly. The characterisation of such free energetics is typically performed using enhanced sampling techniques such as umbrella sampling. In umbrella sampling, order parameter distributions obtained from adjacent biased simulations must overlap in order to estimate free energy differences between biased ensembles. Many biased simulations are typically required to ensure such overlap, which exacts a steep computational cost. We recently introduced a sparse sampling method, which circumvents the overlap requirement by using thermodynamic integration to estimate free energy differences between biased ensembles. Here we build upon and generalise sparse sampling for characterising the free energetics of water density fluctuations in systems near liquid-vapor coexistence. We also introduce sensible heuristics for choosing the biasing potential parameters and strategies for adaptively refining them, which facilitate the estimation of such free energetics accurately and efficiently. We illustrate the method by characterising the free energetics of cavitation in a large volume in bulk water. We also use sparse sampling to characterise the free energetics of capillary evaporation for water confined between two hydrophobic plates. In both cases, sparse sampling is nearly two orders of magnitude faster than umbrella sampling. Given its efficiency, the sparse sampling method is particularly well suited for characterising free energy landscapes for systems wherein umbrella sampling is prohibitively expensive. [ABSTRACT FROM AUTHOR]

Here, we describe a computational approach for studying enzymes that catalyze complex multi‐step reactions and apply it to Ribulose 1,5‐bisphosphate carboxylase–oxygenase (Rubisco), the enzyme that fixes atmospheric carbon dioxide within photosynthesis. In the 5‐step carboxylase reaction, the substrate Ribulose‐1,5‐bisphosphate (RuBP) first binds Rubisco and undergoes enolization before binding the second substrate, CO2. Hydration of the RuBP.CO2 complex is followed by CC bond scission and stereospecific protonation. However, details of the roles and protonation states of active‐site residues, and sources of protons and water, remain highly speculative. Large‐scale computations on active‐site models provide a means to better understand this complex chemical mechanism. The computational protocol comprises a combination of hybrid semi‐empirical quantum mechanics and molecular mechanics within constrained molecular dynamics simulations, together with constrained gradient minimization calculations using density functional theory. Alternative pathways for hydration of the RuBP.CO2 complex and associated active‐site protonation networks and proton and water sources were investigated. The main findings from analysis of the resulting energetics advocate major revision to existing mechanisms such that: hydration takes place anti to the CO2; both hydration and CC bond scission require early protonation of CO2 in the RuBP.CO2 complex; CC bond scission and stereospecific protonation reactions are concerted and, effectively, there is only one stable intermediate, the C3‐gemdiolate complex. Our main conclusions for interpreting enzyme kinetic results are that the gemdiolate may represent the elusive Michaelis–Menten‐like complex corresponding to the empirical Km (=Kc) with turnover to product via bond scission concerted with stereospecific protonation consistent with the observed catalytic rate. © 2018 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

We report the calculation of the potential of mean force (PMF) of different types of associations by various techniques: two no biased methods (thermodynamic integration and finite difference thermodynamic integration), a constraint biased technique (adaptive biasing force) and an umbrella biased method (umbrella sampling).We apply these methodologies to the association between two methane molecules in water, to the formation of an ion pair in water and to the formation of an insertion complex between a macrocycle and a cation. The different PMFs are compared to each other on the basis of the depth of the free energy minimum and on the location of different specific points. [ABSTRACT FROM AUTHOR]

Knowledge of free energies of crystalline solid phases is pivotal in determination of phase equilibria; however, their computations using molecular simulations are quite challenging. In this paper, we apply the Einstein molecule method to compute the excess free energies of crystalline molecular solids comprising of molecules described by flexible models. This work can be viewed as an extension of the method described in Aragones et al. [J Chem Phys. 2013;139:a034104]. In this article, we present our calculations of the free energies of ice-Ih described by q-TIP4P/F model and Orcinol Form I described by the OPLS-AA forcefield. The free energies computed for ice-Ih are in agreement with previous reported results, and those of Orcinol are shown to be thermodynamically consistent. We demonstrate that the efficiency of our calculations compares favourably with existing methods. The method described here can be easily implemented in popular publicly available molecular dynamics packages without any modification to their existing source codes. [ABSTRACT FROM AUTHOR]

The paper reviews several modern methods for calculation of Helmholtz free energy, associated with atomic vibrations: quasiharmonic approximation, self-consistent lattice dynamics method, calculation based on velocity autocorrelation function, temperature-dependent effective potential and thermodynamic integration. The results of free energy calculation by these methods are compared with each other in a wide temperature range, and their applicability is discussed. As a tool we use classical molecular dynamics modeling on the example of bcc molybdenum and fcc aluminum. The relation is observed between how the vibrational spectrum changes with temperature due to the anharmonicity of the potential and how free energy is reproduced. All methods are consistent with each other within 10 meV/at. at relatively low temperatures. At high temperatures, the discrepancy reaches tens of meV/at., although the relative error is less than 5%. [ABSTRACT FROM AUTHOR]

The free energy is central to statistical mechanics and thermodynamics, and its accurate calculation via. computational modelling is important for a large number of applications, especially when its experimental value is hard to obtain. Several established and general methods for calculating the Helmholtz free energy across different length scales, including continuum, atomistic and quantum mechanical, are compared and analyzed. A computational approach is then proposed to calculate the temperature dependences of internal energy and absolute Helmholtz free energy for solid and liquid phases with the coupling of thermodynamic integration (TI) and harmonic approximation calculations from both classical molecular dynamics (MD) and density functional theory (DFT). We use the Lennard-Jones system as an example ( i.e. argon) for the demonstration of the approach. It is observed that the free energy transits smoothly from being describable by the harmonic approximation to including anharmonic effects at a transition temperature around 0.56 T m ; below this temperature, the quantum behavior of atoms is important. At higher temperatures ( T  > 0.56 T m ), the TI and harmonic approximation results for the Helmholtz free energy functions become increasingly divergent with the increase of temperature. This work demonstrates that a multiscale approach employing TI, MD, and DFT can provide accurate calculations of the temperature dependence of absolute Helmholtz free energy for both solid and liquid phases. [ABSTRACT FROM AUTHOR]

Mutations of cysteine are often introduced to e.g. avoid formation of non-physiological inter-molecular disulfide bridges in in-vitro experiments, or to maintain specificity in labeling experiments. Alanine or serine is typically preferred, which usually do not alter the overall protein stability, when the original cysteine was surface exposed. However, selecting the optimal mutation for cysteines in the hydrophobic core of the protein is more challenging. In this work, the stability of selected Cys mutants of 14-3-3ζ was predicted by free-energy calculations and the obtained data were compared with experimentally determined stabilities. Both the computational predictions as well as the experimental validation point at a significant destabilization of mutants C94A and C94S. This destabilization could be attributed to the formation of hydrophobic cavities and a polar solvation of a hydrophilic side chain. A L12E, M78K double mutant was further studied in terms of its reduced dimerization propensity. In contrast to naïve expectations, this double mutant did not lead to the formation of strong salt bridges, which was rationalized in terms of a preferred solvation of the ionic species. Again, experiments agreed with the calculations by confirming the monomerization of the double mutants. Overall, the simulation data is in good agreement with experiments and offers additional insight into the stability and dimerization of this important family of regulatory proteins. [ABSTRACT FROM AUTHOR]

The octanol–water partition coefficient (logPow) is an important index for measuring solubility, membrane permeability, and bioavailability in the drug discovery field. In this paper, the logPow values of 58 compounds were predicted by alchemical free energy calculation using molecular dynamics simulation. In free energy calculations, the atomic charges of the compounds are always fixed. However, they must be recalculated for each solvent. Therefore, three different sets of atomic charges were tested using quantum chemical calculations, taking into account vacuum, octanol, and water environments. The calculated atomic charges in the different environments do not necessarily influence the correlation between calculated and experimentally measured ∆Gwater values. The largest correlation coefficient values of the solvation free energy in water and octanol were 0.93 and 0.90, respectively. On the other hand, the correlation coefficient of logPow values calculated from free energies, the largest of which was 0.92, was sensitive to the combination of the solvation free energies calculated from the calculated atomic charges. These results reveal that the solvent assumed in the atomic charge calculation is an important factor determining the accuracy of predicted logPow values. [ABSTRACT FROM AUTHOR]

Targeting drugs to the inflamed intestinal tissue(s) represents a major advancement in the treatment of inflammatory bowel disease (IBD). In this work we present a powerful in-silico modeling approach to guide the molecular design of novel prodrugs targeting the enzyme PLA, which is overexpressed in the inflamed tissues of IBD patients. The prodrug consists of the drug moiety bound to the sn-2 position of phospholipid (PL) through a carbonic linker, aiming to allow PLA to release the free drug. The linker length dictates the affinity of the PL-drug conjugate to PLA, and the optimal linker will enable maximal PLA-mediated activation. Thermodynamic integration and Weighted Histogram Analysis Method (WHAM)/Umbrella Sampling method were used to compute the changes in PLA transition state binding free energy of the prodrug molecule (∆∆G) associated with decreasing/increasing linker length. The simulations revealed that 6-carbons linker is the optimal one, whereas shorter or longer linkers resulted in decreased PLA-mediated activation. These in-silico results were shown to be in excellent correlation with experimental in-vitro data. Overall, this modern computational approach enables optimization of the molecular design of novel prodrugs, which may allow targeting the free drug specifically to the diseased intestinal tissue of IBD patients. [ABSTRACT FROM AUTHOR]

Recently, we have investigated the cucurbit[7]uril (CB7) recognition of the α- and β-anomers of neutral, protonated, and acetylated forms of glucosamine in water. In the present work, we employed molecular dynamics (MD) and thermodynamic integration methods (TI) to investigate the recognition of these molecules by cucurbit[6]uril (CB6) and cucurbit[8]uril (CB8). MD revealed the formation of stable 1:1 inclusion complexes by all studied molecules with cucurbit[ n ]urils (CB n), and 2:1 complex by the α-anomer of the acetylated form of glucosamine with the large homologue CB8. CB6 forms roughly twice as many hydrogen bonds with the guest molecules as CB8. MM-PBSA results indicated that the electrostatic contribution to the binding free energy of each guest:CB complex was larger for CB6 than for CB8, and that CB6 and CB8 have lower affinity toward the different forms of glucosamine compared to CB7. Furthermore, TI was used to estimate the relative affinities of CB6 and CB8 toward the α- and β-anomers for each form of the studied glucosamine and compare with CB7. [ABSTRACT FROM AUTHOR]

Configuration entropy is believed to stabilize disordered solid solution phases in multicomponent systems at elevated temperatures over intermetallic compounds by lowering the Gibbs free energy. Traditionally, the increment of configuration entropy with temperature was computed by time-consuming thermodynamic integration methods. In this work, a new formalism based on a hybrid combination of the Cluster Expansion (CE) Hamiltonian and Monte Carlo simulations is developed to predict the configuration entropy as a function of temperature from multi-body cluster probability in a multi-component system with arbitrary average composition. The multi-body probabilities are worked out by explicit inversion and direct product of a matrix formulation within orthonomal sets of point functions in the clusters obtained from symmetry independent correlation functions. The matrix quantities are determined from semi canonical Monte Carlo simulations with Effective Cluster Interactions (ECIs) derived from Density Functional Theory (DFT) calculations. The formalism is applied to analyze the 4-body cluster probabilities for the quaternary system Cr-Fe-Mn-Ni as a function of temperature and alloy concentration. It is shown that, for two specific compositions (Cr 25Fe 25Mn 25Ni 25 and Cr 18Fe 27Mn 27Ni 28), the high value of probabilities for Cr-Fe-Fe-Fe and Mn-Mn-Ni-Ni are strongly correlated with the presence of the ordered phases L1 2 -CrFe 3 and L1 0-MnNi, respectively. These results are in an excellent agreement with predictions of these ground state structures by ab initio calculations. The general formalism is used to investigate the configuration entropy as a function of temperature and for 285 different alloy compositions. It is found that our matrix formulation of cluster probabilities provides an efficient tool to compute configuration entropy in multi-component alloys in a comparison with the result obtained by the thermodynamic integration method. At high temperatures, it is shown that many-body cluster correlations still play an important role in understanding the configuration entropy before reaching the solid solution limit of high-entroy alloys (HEAs).