Ensemble-based virtual screening of African natural products to target human thymidylate synthase.

Human thymidylate synthase (hTS) is a validated drug target for chemotherapy. A virtual screening experiment was used to prioritize a list of compounds from African Natural Products Databases docked against the orthosteric binding pocket of hTS. Consensus scores of binding affinities from ensemble-based virtual screening, hydrated docking and MM-PBSA calculations ranked compounds NEA4433 and NEA4434 as the best candidates owing to binding affinity scores in the picomolar order, their excellent ADMET profiles and the good stability of the protein-ligand complexes formed. The current study demonstrates the role of water in small molecule binding to hTS in mediating protein-ligand interactions. Similarly, the robust ensemble docking (relaxed scheme complex) ranked NEA4433 and NEA4434 as the best candidates. Furthermore, the best candidates prioritized were shown to strongly interact with the same residues that interacted with hTS substrate and cofactor.

Traditional herbal compounds as candidates to inhibit the SARS-CoV-2 main protease: an in silico study.

COVID-19, a disease caused by the SARS-CoV-2 virus, is responsible for a pandemic since March 2020 and it has no cure. Therefore, herein, different theoretical methods were used to obtain potential candidates from herbal compounds to inhibit the SARS-CoV-2 main protease (Mpro). Initially, the 16 best-scored compounds were selected from a library containing 4066 ligands using virtual screening by molecular docking. Among them, six molecules (physalin B 5,6-epoxide (PHY), methyl amentoflavone (MAM), withaphysalin C (WPC), daphnoline or trilobamine (TRI), cepharanoline (CEP) and tetrandrine (TET)) were selected based on Lipinski's rule and ADMET analysis as criteria. These compounds complexed with the Mpro were submitted to triplicate 100 ns molecular dynamics simulations. RMSD, RMSF, and radius of gyration results show that the overall protein structure is preserved along the simulation time. The average ΔGbinding values, calculated by the MM/PBSA method, were -41.7, -55.8, -45.2, -38.7, -49.3, and -57.9 kcal/mol for the PHY-Mpro, MAM-Mpro, WPC-Mpro, CEP-Mpro, TRI-Mpro, and TET-Mpro complexes, respectively. Pairwise decomposition analyses revealed that the binding pocket is formed by His41-Val42, Met165-Glu166-Leu167, Asp187, and Gln189. The PLS regression model generated by QSPR analysis indicated that non-polar and polar groups with the presence of hydrogen bond acceptors play an important role in the herbal compounds-Mpro interactions. Overall, we found six potential candidates to inhibit the SARS-CoV-2 Mpro and highlighted key residues from the binding pocket that can be used for future drug design. Communicated by Ramaswamy H. Sarma.

Targeting human thymidylate synthase: Ensemble-based virtual screening for drug repositioning and the role of water.

A drug repositioning computational approach was carried to search inhibitors for human thymidylate synthase. An ensemble-based virtual screening of FDA-approved drugs showed the drugs Imatinib, Lumacaftor and Naldemedine to be likely candidates for repurposing. The role of water in the drug-receptor interactions was revealed by the application of an extended AutoDock scoring function that included the water forcefield. The binding affinity scores when hydrated ligands were docked were improved in the drugs considered. Further binding free energy calculations based on the Molecular Mechanics Poisson-Boltzmann Surface Area method revealed that Imatinib, Lumacaftor and Naldemedine scored -130.7 ± 28.1, -210.6 ± 29.9 and -238.0 ± 25.4 kJ/mol, respectively, showing good binding affinity for the candidates considered. Overall, the analysis of the molecular dynamics trajectory of the receptor-drug complexes revealed stable structures for Imatinib, Lumacaftor and Naldemedine, for the entire simulation time.

Predicting octanol/water partition coefficients and pKa for the SAMPL7 challenge using the SM12, SM8 and SMD solvation models.

Blind predictions of octanol/water partition coefficients and pKa at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. Octanol/water partition coefficients were predicted from solvation free energies computed using electronic structure calculations with the SM12, SM8 and SMD solvation models. Within these calculations we compared the use of gas- and solution-phase optimized geometries of the solute. Based on these calculations we found that in general the use of solution phase-optimized geometries increases the affinity of the solutes for water as compared to octanol, with the use of gas-phase optimized geometries resulting in the better agreement with experiment. The pKa is computed using the direct approach, scaled solvent-accessible surface model, and the inclusion of an explicit water molecule, where the latter two methods have previously been shown to offer improved predictions as compared to the direct approach. We find that the use of an explicit water molecule provides superior predictions, and that the predicted macroscopic pKa is sensitive to the employed microstates.

Predicting octanol/water partition coefficients using molecular simulation for the SAMPL7 challenge: comparing the use of neat and water saturated 1-octanol.

Blind predictions of octanol/water partition coefficients at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. The octanol/water partition coefficients were predicted using solvation free energies computed using molecular dynamics simulations, wherein we considered the use of both pure and water-saturated 1-octanol to model the octanol-rich phase. Water and 1-octanol were modeled using TIP4P and TrAPPE-UA, respectively, which have been shown to well reproduce the experimental mutual solubility, and the solutes were modeled using GAFF. After the close of the SAMPL7 challenge, we additionally made predictions using TIP4P/2005 water. We found that the predictions were sensitive to the choice of water force field. However, the effect of water in the octanol-rich phase was found to be even more significant and non-negligible. The effect of inclusion of water was additionally sensitive to the chemical structure of the solute.

Repurposing approved drugs as inhibitors of SARS-CoV-2 S-protein from molecular modeling and virtual screening.

Herein, molecular modeling techniques were used with the main goal to obtain candidates from a drug database as potential targets to be used against SARS-CoV-2. This novel coronavirus, responsible by the COVID-19 outbreak since the end of 2019, became a challenge since there is not vaccine for this disease. The first step in this investigation was to solvate the isolated S-protein in water for molecular dynamics (MD) simulation, being observed a transition from "up" to "down" conformation of receptor-binding domain (RBD) of the S-protein with angle of 54.3 and 43.0 degrees, respectively. The RBD region was more exposed to the solvent and to the possible drugs due to its enhanced surface area. From the equilibrated MD structure, virtual screening by docking calculations were performed using a library contained 9091 FDA approved drugs. Among them, 24 best-scored ligands (14 traditional herbal isolate and 10 approved drugs) with the binding energy below -8.1 kcal/mol were selected as potential candidates to inhibit the SARS-CoV-2 S-protein, preventing the human cell infection and their replication. For instance, the ivermectin drug (present in our list of promise candidates) was recently used successful to control viral replication in vitro. MD simulations were performed for the three best ligands@S-protein complexes and the binding energies were calculated using the MM/PBSA approach. Overall, it is highlighted an important strategy, some key residues, and chemical groups which may be considered on clinical trials for COVID-19 outbreak. [Formula: see text]Communicated by Ramaswamy H. Sarma.

Expanding the Solubility Parameter Method MOSCED to Pyridinium-, Quinolinium-, Pyrrolidinium-, Piperidinium-, Bicyclic-, Morpholinium-, Ammonium-, Phosphonium-, and Sulfonium-Based Ionic Liquids.

MOSCED (modified separation of cohesive energy density) is a solubility parameter method that offers an improved treatment of association interactions. Solubility parameter methods are well known for their ability to both make quantitative predictions and offer a qualitative description of the underlying molecular-level driving forces, lending themselves to intuitive solvent selection and design. Currently, MOSCED parameters are available for 130 organic solvents, water, and 33 imidazolium-based room temperature ionic liquids (ILs). In this work, we expand MOSCED to cover 66 additional ILs containing the pyridinium, quinolinium, pyrrolidinium, piperidinium, bicyclic, morpholinium, ammonium, phosphonium, and sulfonium cations using 10,052 experimental limiting activity coefficients. The resulting parameters may readily be used to predict the phase behavior in mixtures involving ILs.

Predicting octanol/water partition coefficients for the SAMPL6 challenge using the SM12, SM8, and SMD solvation models.

Blind predictions of octanol/water partition coefficients at 298 K for 11 kinase inhibitor fragment like compounds were made for the SAMPL6 challenge. We used the conventional, "untrained", free energy based approach wherein the octanol/water partition coefficient was computed directly as the difference in solvation free energy in water and 1-octanol. We additionally proposed and used two different forms of a "trained" approach. Physically, the goal of the trained approach is to relate the partition coefficient computed using pure 1-octanol to that using water-saturated 1-octanol. In the first case, we assumed the partition coefficient using water-saturated 1-octanol and pure 1-octanol are linearly correlated. In the second approach, we assume the solvation free energy in water-saturated 1-octanol can be written as a linear combination of the solvation free energy in pure water and 1-octanol. In all cases here, the solvation free energies were computed using electronic structure calculations in the SM12, SM8, and SMD universal solvent models. In the context of the present study, our results in general do not support the additional effort of the trained approach.

Cassandra: An open source Monte Carlo package for molecular simulation.

Cassandra is an open source atomistic Monte Carlo software package that is effective in simulating the thermodynamic properties of fluids and solids. The different features and algorithms used in Cassandra are described, along with implementation details and theoretical underpinnings to various methods used. Benchmark and example calculations are shown, and information on how users can obtain the package and contribute to it are provided. © 2017 Wiley Periodicals, Inc.

Combining MOSCED with molecular simulation free energy calculations or electronic structure calculations to develop an efficient tool for solvent formulation and selection.

Solubility parameter based methods have long been a valuable tool for solvent formulation and selection. Of these methods, the MOdified Separation of Cohesive Energy Density (MOSCED) has recently been shown to correlate well the equilibrium solubility of multifunctional non-electrolyte solids. However, before it can be applied to a novel solute, a limited amount of reference solubility data is required to regress the necessary MOSCED parameters. Here we demonstrate for the solutes methylparaben, ethylparaben, propylparaben, butylparaben, lidocaine and ephedrine how conventional molecular simulation free energy calculations or electronic structure calculations in a continuum solvent, here the SMD or SM8 solvation model, can instead be used to generate the necessary reference data, resulting in a predictive flavor of MOSCED. Adopting the melting point temperature and enthalpy of fusion of these compounds from experiment, we are able to predict equilibrium solubilities. We find the method is able to well correlate the (mole fraction) equilibrium solubility in non-aqueous solvents over four orders of magnitude with good quantitative agreement.

Microscopic Structure and Solubility Predictions of Multifunctional Solids in Supercritical Carbon Dioxide: A Molecular Simulation Study.

Molecular dynamics simulations were employed to both estimate the solubility of nonelectrolyte solids, such as acetanilide, acetaminophen, phenacetin, methylparaben, and lidocaine, in supercritical carbon dioxide and understand the underlying molecular-level driving forces. The solubility calculations involve the estimation of the solute's limiting activity coefficient, which may be computed using conventional staged free-energy calculations. For the case of lidocaine, wherein the infinite dilution approximation is not appropriate, we demonstrate how the activity coefficient at finite concentrations may be estimated without additional effort using the dilute solution approximation and how this may be used to further understand the solvation process. Combining with experimental pure-solid properties, namely, the normal melting point and enthalpy of fusion, solubilities were estimated. The results are in good quantitative agreement with available experimental data, suggesting that molecular simulations may be a powerful tool for understanding supercritical processes and the design of carbon dioxide-philic molecular systems. Structural analyses were performed to shed light on the microscopic details of the solvation of different functional groups by carbon dioxide and the observed solubility trends.

Predicting cyclohexane/water distribution coefficients for the SAMPL5 challenge using MOSCED and the SMD solvation model.

We present blind predictions using the solubility parameter based method MOSCED submitted for the SAMPL5 challenge on calculating cyclohexane/water distribution coefficients at 298 K. Reference data to parameterize MOSCED was generated with knowledge only of chemical structure by performing solvation free energy calculations using electronic structure calculations in the SMD continuum solvent. To maintain simplicity and use only a single method, we approximate the distribution coefficient with the partition coefficient of the neutral species. Over the final SAMPL5 set of 53 compounds, we achieved an average unsigned error of [Formula: see text] log units (ranking 15 out of 62 entries), the correlation coefficient (R) was [Formula: see text] (ranking 35), and [Formula: see text] of the predictions had the correct sign (ranking 30). While used here to predict cyclohexane/water distribution coefficients at 298 K, MOSCED is broadly applicable, allowing one to predict temperature dependent infinite dilution activity coefficients in any solvent for which parameters exist, and provides a means by which an excess Gibbs free energy model may be parameterized to predict composition dependent phase-equilibrium.

Understanding the Solubility of Acetaminophen in 1-n-Alkyl-3-methylimidazolium-Based Ionic Liquids Using Molecular Simulation.

During the manufacturing of pharmaceutical compounds, solvent mixtures are commonly used, where the addition of a cosolvent allows for the tuning of the intermolecular interactions present in the system. Here we demonstrate how a similar effect can be accomplished using a room temperature ionic liquid. The pharmaceutical compound acetaminophen is studied in 21 common ionic liquids composed of a 1-n-alkyl-3-methylimidazolium cation with 1 of 7 anions. Using the acetate anion, we predict a large enhancement in solubility of acetaminophen relative to water. We show how this is caused by a synergistic effect of favorable interactions between the ionic liquid and the phenyl, hydroxyl and amide groups of acetaminophen, demonstrating how the ionic liquid cation and anion may be chosen to preferentially solvate different functional groups of complex pharmaceutical compounds. Additionally, while the use of charge scaling in ionic liquid force fields has previously been found to have a minute effect on ionic liquid structural properties, we find it appreciably affects the computed solvation free energy of acetaminophen, which in turn affects the predicted solubility.

Understanding the large solubility of lidocaine in 1-n-butyl-3-methylimidazolium based ionic liquids using molecular simulation.

Room temperature ionic liquids have been proposed as replacement solvents in a wide range of industrial separation processes. Here, we focus on the use of ionic liquids as solvents for the pharmaceutical compound lidocaine. We show that the solubility of lidocaine in seven common 1-n-butyl-3-methylimidazolium based ionic liquids is greatly enhanced relative to water. The predicted solubility is greatest in [BMIM](+)[CH3CO2](-), which we find results from favorable hydrogen bonding between the lidocaine amine hydrogen and the [CH3CO2](-) oxygen, favorable electrostatic interactions between the lidocaine amide oxygen with the [BMIM](+) aromatic ring hydrogens, while lidocaine does not interfere with the association of [BMIM](+) with [CH3CO2](-). Additionally, by removing functional groups from the lidocaine scaffold while maintaining the important amide group, we found that as the van der Waals volume increases, solubility in [BMIM](+)[CH3CO2](-) relative to water increases.

Using MD Simulations To Calculate How Solvents Modulate Solubility.

Here, our interest is in predicting solubility in general, and we focus particularly on predicting how the solubility of particular solutes is modulated by the solvent environment. Solubility in general is extremely important, both for theoretical reasons - it provides an important probe of the balance between solute-solute and solute-solvent interactions - and for more practical reasons, such as how to control the solubility of a given solute via modulation of its environment, as in process chemistry and separations. Here, we study how the change of solvent affects the solubility of a given compound. That is, we calculate relative solubilities. We use MD simulations to calculate relative solubility and compare our calculated values with experiment as well as with results from several other methods, SMD and UNIFAC, the latter of which is commonly used in chemical engineering design. We find that straightforward solubility calculations based on molecular simulations using a general small-molecule force field outperform SMD and UNIFAC both in terms of accuracy and coverage of the relevant chemical space.

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation.

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

A comparison of the solvation thermodynamics of amino acid analogues in water, 1-octanol and 1-n-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ionic liquids by molecular simulation.

A computational approach is developed to quantitatively study the solvation thermodynamics of amino acid analogues in ionic liquids via molecular simulation. The solvation thermodynamics of amino acid analogues in ionic liquids is important for an understanding of protein-ionic liquid interactions, shedding insight into the structure and solubility of proteins, and the activity of enzymes in ionic liquids. This information is additionally key to developing novel extraction processes. As a result of the challenge of quantitatively describing the solvation behavior of ionic liquids, a key outcome of the present study is the development of a "hydrophobicity" scale to quantitatively describe the amino acid analogues. The scale allows one to separate the results of both the hydrophobic and hydrophillic analogues, simplifying an understanding of the observed trends. Equipped with the proposed hydrophobicity scale, one needs only perform conventional solvation free energy calculations of the amino acid analogues in the ionic liquids of interest. The necessary simulation tools are available in most open-source simulation software, facilitating the adoption of this approach by the simulation community at large. We have studied the case of varying the cation alkyl-chain length of a 1-n-alkyl-3-methylimidazolium cation paired with the bis(trifluoromethylsulfonyl)imide anion. The findings suggest that a judicious selection of both the cation and anion could potentially lead to a solvent for which the amino acid analogues have an affinity far greater than that for both water and a non-polar reference solvent.

Small Molecule Solvation Free Energy: Enhanced Conformational Sampling Using Expanded Ensemble Molecular Dynamics Simulation.

We present an efficient expanded ensemble molecular dynamics method to calculate the solvation free energy (or residual chemical potential) of small molecules with complex topologies. The methodology is validated by computing the solvation free energy of ibuprofen in water, methanol, and ethanol at 300 K and 1 bar and comparing to reference simulation results using Bennett's acceptance ratio method. Difficulties with ibuprofen using conventional molecular dynamics methods stem from an inadequate sampling of the carboxylic acid functional group, which, for the present study, is subject to free energy barriers of rotation of 14-20 kBT. While several advances have been made to overcome such weaknesses, we demonstrate how this shortcoming is easily overcome by using an expanded ensemble methodology to facilitate conformational sampling. Not only does the method enhance conformational sampling but it also boosts the rate of exploration of the configurational phase space and requires only a single simulation to calculate the solvation free energy. Agreement between the expanded ensemble and the reference calculations is good for all three solvents, with the reported uncertainties of the expanded ensemble being comparable to the uncertainties of the reference calculations, while requiring less simulation time; the reduced simulation time demonstrates the improved performance gained from the expanded ensemble method.

Efficient Solvation Free Energy Calculations of Amino Acid Analogs by Expanded Ensemble Molecular Simulation.

We present an efficient, automated expanded ensemble method to calculate the residual chemical potential or solvation free energy by molecular dynamics simulation. The methodology is validated by computing the residual chemical potential of 13 amino acid analogs in water at 300 K and 1 bar and comparing to reference simulation data. Overall agreement is good, with the methodology of the present study reaching limiting precisions of less than 0.1 kBT in half of the total simulation time of the reference simulation study which utilized Bennett's acceptance ratio method. The apparent difference in the efficiencies is a result of the inherent advantages of the expanded ensemble method, which creates an improved decorrelation of simulation data and improves the sampling of the important regions of the configurational phase space of each subensemble. The present adaptation utilizes histograms of proposed transition energies collected throughout the entire simulation, to make extremely precise calculations of the relative free energy between neighboring subensembles.

A method for computing the solubility limit of solids: application to sodium chloride in water and alcohols.

We present an adaptable method to compute the solubility limit of solids by molecular simulation, which avoids the difficulty of reference state calculations. In this way, the method is highly adaptable to molecules of complex topology. Results are shown for solubility calculations of sodium chloride in water and light alcohols at atmospheric conditions. The pseudosupercritical path integration method is used to calculate the free energy of the solid and gives results that are in good agreement with previous studies that reference the Einstein crystal. For the solution phase calculations, the self-adaptive Wang-Landau transition-matrix Monte Carlo method is used within the context of an expanded isothermal-isobaric ensemble. The method shows rapid convergence properties and the uncertainty in the calculated chemical potential was 1% or less for all cases. The present study underpredicts the solubility limit of sodium chloride in water, suggesting a shortcoming of the molecular models. Importantly, the proper trend for the chemical potential in various solvents was captured, suggesting that relative solubilities can be computed by the method.