Effect of Atomic Charges on Octanol-Water Partition Coefficient Using Alchemical Free Energy Calculation

An in-silico receptor-pharmacophore based multistep molecular docking and simulation study to evaluate the inhibitory potentials against NS1 of DENV-2

DENV-2 strain is the most fatal and infectious of the five dengue virus serotypes. The non-structural protein NS1 encoded by its genome is the most significant protein required for viral pathogenesis and replication inside the host body. Thus, targeting the NS1 protein and designing an inhibitor to limit its stability and secretion is a propitious attempt in our fight against dengue. Four novel inhibitors are designed to target the conserved cysteine residues (C55, C313, C316, and C329) and glycosylation sites (N130 and N207) of the NS1 protein in an attempt to halt the spread of the dengue infection in the host body altogether. Numerous computer-aided drug designing techniques including molecular docking, molecular dynamics simulation, virtual screening, principal component analysis, and dynamic cross-correlation matrix were employed to determine the structural and functional activity of the NS1-inhibitor complexes. From our analysis, it was evident that the extent of structural and atomic level fluctuations of the ligand-bound protein exhibited a declining trend in contrast to unbound protein which was prominently noticeable through the RMSD, RMSF, Rg, and SASA graphs. The ADMET analysis of the four ligands revealed a promising pharmacokinetics and pharmacodynamic profile, along with good bioavailability and toxicity properties. The proposed drugs when bound to the targeted cavities resulted in stable conformations in comparison to their unbound state, implying they have good affinity promising effective drug action. Thus, they can be tested in vitro and used as potential anti-dengue drugs.Communicated by Ramaswamy H. Sarma.

How Molecular Orientation Affects the Static Permittivity Profile of the Polar and Nonpolar Liquid-Liquid Interface

The dielectric permittivity across the liquid-liquid interface presents an intrinsic response, with respect to the instantaneous interface reference. We hypothesize that dielectric responses across the nonpolar and polar liquid-liquid interfaces have different behaviors and underlying mechanisms. Molecular dynamics simulations were used to compare and contrast the dielectric response of a nonpolar (1,2-dichloroethane/water) and a polar (1-octanol/water) liquid-liquid interface system. We found that the enhanced dielectric permittivity at the nonpolar interface is attributed to the increased water dipole orientation and polarization density. In the case of the polar interface, strong association of the immiscible solvents inhibits the molecular dipole orientation, counteracting the effect from the enhanced surface water polarization density and resulting in a standard dielectric response. Detailed knowledge of the hydrogen bond networks and molecular dipole orientation with respect to the specific instantaneous interfacial and bulk regions reveals the effect of molecular proximity and the interaction with the opposing interfacial molecules on the mechanism of the dielectric permittivity response across the liquid-liquid interface phase boundary.

Design and Evaluation of Synthesized Pyrrole Derivatives as Dual COX-1 and COX-2 Inhibitors Using FB-QSAR Approach

This study delves into the intricate dynamics of the inflammatory response, unraveling the pivotal role played by cyclooxygenase (COX) enzymes, particularly COX-1 and COX-2 subtypes. Motivated by the pursuit of advancing scientific knowledge, our contribution to this field is marked by the design and synthesis of novel pyrrole derivatives. Crafted as potential inhibitors of COX-1 and COX-2 enzymes, our goal was to unearth molecules with heightened efficacy in modulating enzyme activity. A meticulous exploration of a synthesis library, housing around 3000 compounds, expedited the identification of potent candidates. Employing advanced docking studies and field-based Quantitative Structure-Activity Relationship (FB-QSAR) analyses enriched our understanding of the complex interactions between synthesized compounds and COX enzymes. Guided by FB-QSAR insights, our synthesis path led to the identification of compounds 4g, 4h, 4l, and 4k as potent COX-2 inhibitors, surpassing COX-1 efficacy. Conversely, compounds 5b and 5e exhibited heightened inhibitory activity against COX-1 relative to COX-2. The utilization of pyrrole derivatives as COX enzyme inhibitors holds promise for groundbreaking advancements in the domain of anti-inflammatory therapeutics, presenting avenues for innovative pharmaceutical exploration.

Development and test of highly accurate endpoint free energy methods. 2: Prediction of logarithm of n-octanol-water partition coefficient (logP) for druglike molecules using MM-PBSA method

The logarithm of n-octanol-water partition coefficient (logP) is frequently used as an indicator of lipophilicity in drug discovery, which has substantial impacts on the absorption, distribution, metabolism, excretion, and toxicity of a drug candidate. Considering that the experimental measurement of the property is costly and time-consuming, it is of great importance to develop reliable prediction models for logP. In this study, we developed a transfer free energy-based logP prediction model-FElogP. FElogP is based on the simple principle that logP is determined by the free energy change of transferring a molecule from water to n-octanol. The underlying physical method to calculate transfer free energy is the molecular mechanics-Poisson Boltzmann surface area (MM-PBSA), thus this method is named as free energy-based logP (FElogP). The superiority of FElogP model was validated by a large set of 707 structurally diverse molecules in the ZINC database for which the measurement was of high quality. Encouragingly, FElogP outperformed several commonly-used QSPR or machine learning-based logP models, as well as some continuum solvation model-based methods. The root-mean-square error (RMSE) and Pearson correlation coefficient (R) between the predicted and measured values are 0.91 log units and 0.71, respectively, while the runner-up, the logP model implemented in OpenBabel had an RMSE of 1.13 log units and R of 0.67. Given the fact that FElogP was not parameterized against experimental logP directly, its excellent performance is likely to be expanded to arbitrary organic molecules covered by the general AMBER force fields.

Efficient screening of protein-ligand complexes in lipid bilayers using LoCoMock score

Membrane proteins are attractive targets for drug discovery due to their crucial roles in various biological processes. Studying the binding poses of amphipathic molecules to membrane proteins is essential for understanding the functions of membrane proteins and docking simulations can facilitate the screening of protein-ligand complexes at low computational costs. However, identifying docking poses for a ligand in non-aqueous environments such as lipid bilayers can be challenging. To address this issue, we propose a new docking score called logP-corrected membrane docking (LoCoMock) score. To screen putative protein-ligand complexes embedded in a membrane, the LoCoMock score considers the affinity between a target ligand and the membrane. It combines the docking score of the protein-ligand complex with the logP of the target ligand. In demonstrations using several model ligands, the LoCoMock score screened more putative complexes than the conventional docking score. As extended docking, the LoCoMock score makes it possible to screen membrane proteins more effectively as drug targets than the conventional docking.

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.

Energy-entropy prediction of octanol-water logP of SAMPL7 N-acyl sulfonamide bioisosters

Partition coefficients quantify a molecule's distribution between two immiscible liquid phases. While there are many methods to compute them, there is not yet a method based on the free energy of each system in terms of energy and entropy, where entropy depends on the probability distribution of all quantum states of the system. Here we test a method in this class called Energy Entropy Multiscale Cell Correlation (EE-MCC) for the calculation of octanol-water logP values for 22 N-acyl sulfonamides in the SAMPL7 Physical Properties Challenge (Statistical Assessment of the Modelling of Proteins and Ligands). EE-MCC logP values have a mean error of 1.8 logP units versus experiment and a standard error of the mean of 1.0 logP units for three separate calculations. These errors are primarily due to getting sufficiently converged energies to give accurate differences of large numbers, particularly for the large-molecule solvent octanol. However, this is also an issue for entropy, and approximations in the force field and MCC theory also contribute to the error. Unique to MCC is that it explains the entropy contributions over all the degrees of freedom of all molecules in the system. A gain in orientational entropy of water is the main favourable entropic contribution, supported by small gains in solute vibrational and orientational entropy but offset by unfavourable changes in the orientational entropy of octanol, the vibrational entropy of both solvents, and the positional and conformational entropy of the solute.

Alkane/Water Partition Coefficient Calculation Based on the Modified AM1 Method and Internal Hydrogen Bonding Sampling Using COSMO-RS

We introduce a physics-based model for calculating partition coefficients of solutes between water and alkanes, using a combination of a semi-empirical method for COSMO charge density calculation and statistical sampling of internal hydrogen bonds (IHBs). We validate the model on the experimental partition data (∼3500 molecules) of small organics, drug-like molecules, and statistical assessment of modeling of proteins and ligand drugs. The model combines two novel algorithms: a bond-correction method for improving the calculation of COSMO charge density from AM1 calculations and a sampling method to deal with IHBs. From a comparison of simulated and experimental partition coefficients, we find a root-mean-square deviation of roughly one log 10 unit. From IHB analysis, we know that IHBs can be present in two states: open (in water) and closed (in apolar solvent). The difference can lead to a shift of as much as two log 10 units per IHB; not taking this effect into account can lead to substantial errors. The method takes a few minutes of calculation time on a single core, per molecule. Although this is still much slower than quantitative structure–activity relationship, it is much faster than molecular simulations and can be readily incorporated into any screening method.

E-pharmacophore based screening to identify potential HIV-1 gp120 and CD4 interaction blockers for wild and mutant types

HIV-1 gp120 provides a multistage viral entry process through the conserved CD4 binding site. Hunting of potential blockers can diminish the interaction of gp120 with the CD4 host receptor leading to the suppression of HIV-1 infection. Structure-based pharmacophore virtual screening followed by binding free energy calculation, molecular dynamics (MD) simulation and density functional theory (DFT) calculation is applied to discriminate the potential blockers from six small molecule databases. Five compounds from six databases exhibited vital interactions with key residues ASP368, GLU370, ASN425, MET426, TRP427 and GLY473 of gp120, involved in the binding with CD4, host receptor. Most importantly, compound NCI-254200 displayed strong communication with key residues of wild type and drug resistance single mutant gp120 (M426L and W427V) even in the dynamic condition, evidenced from MD simulation. This investigation provided a potential compound NCI-254200 which may show inhibitory activity against HIV-1 gp120 variant interactions with CD4 host cell receptors.

Identification of New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach

The cyclooxygenase-2 receptor is a therapeutic target for planning potential drugs with anti-inflammatory activity. The selective cyclooxygenase-2 (COX-2) inhibitor rofecoxib was selected as a pivot molecule to perform virtual ligand-based screening from six commercial databases. We performed the search for similarly shaped Rapid Overlay of Chemical Structures (ROCS) and electrostatic (EON) compounds. After, we used pharmacokinetic and toxicological parameters to determine the best potential compounds, obtained through the softwares QikProp and Derek, respectively. Then, the compounds proceeded to the molecular anchorage study, which showed promising results of binding affinity with the hCOX-2 receptor: LMQC72 (∆G = -11.0 kcal/mol), LMQC36 (∆G = -10.6 kcal/mol), and LMQC50 (∆G = -10.2 kcal/mol). LMQC72 and LMQC36 showed higher binding affinity compared to rofecoxib (∆G = -10.4 kcal/mol). Finally, molecular dynamics (MD) simulations were used to evaluate the interaction of the compounds with the target hCOX-2 during 150 ns. In all MD simulation trajectories, the ligands remained interacting with the protein until the end of the simulation. The compounds were also complexing with hCOX-2 favorably. The compounds obtained the following affinity energy values: rofecoxib: ΔGbind = -45.31 kcal/mol; LMQC72: ΔGbind = -38.58 kcal/mol; LMQC36: ΔGbind = -36.10 kcal/mol; and LMQC50: ΔGbind = -39.40 kcal/mol. The selected LMQC72, LMQC50, and LMQC36 structures showed satisfactory pharmacokinetic results related to absorption and distribution. The toxicological predictions of these compounds did not display alerts for possible toxic groups and lower risk of cardiotoxicity compared to rofecoxib. Therefore, future in vitro and in vivo studies are needed to confirm the anti-inflammatory potential of the compounds selected here with bioinformatics approaches based on rofecoxib ligand.

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.

Predicting Octanol-Water Partition Coefficients: Are Quantum Mechanical Implicit Solvent Models Better than Empirical Fragment-Based Methods?

In this work, we examined the performance of contemporary quantum mechanical implicit solvent models (SMD, SM8, SM12, and ADF-COSMO-RS) and empirical fragment-based methods for predicting octanol-water partition coefficients (log P_ow). Two test sets were chosen: the first is composed of 34 organic molecules from a recent study by Mobley J. Chem. Theory Comput , 2016 , 12 , 4015 - 4024 , and the second set is based on a collection of 55 fluorinated alkanols and carbohydrates from Linclau Angew. Chem., Int. Ed. , 2016 , 55 , 674 - 678 . Our analysis indicates that the errors in the solvation free energies of implicit models are reasonably systematic in both solvents such that there is substantial cancellation of errors in the calculation of transfer free energies. Overall, implicit solvent models performed very well across the two test sets with mean absolute errors (MAEs) of about 0.6 log unit and are superior to explicit solvent simulations (GAFF and GAFF-DC). Interestingly, the best performers were empirical fragment-based methods, including ALOGP and miLOGP with significantly lower MAEs (0.2 to 0.4 log unit). The ALOGP method was further tested against the recent SAMPL6 log P_ow challenge consisting of 11 drug-like molecules where it obtained an MAE of 0.32 log unit compared to the best-performing COSMOtherm model (0.31 log unit).

Molecular simulation as a computational pharmaceutics tool to predict drug solubility, solubilization processes and partitioning

In this review we will discuss how computational methods, and in particular classical molecular dynamics simulations, can be used to calculate solubility of pharmaceutically relevant molecules and systems. To the extent possible, we focus on the non-technical details of these calculations, and try to show also the added value of a more thorough and detailed understanding of the solubilization process obtained by using computational simulations. Although the main focus is on classical molecular dynamics simulations, we also provide the reader with some insights into other computational techniques, such as the COSMO-method, and also discuss Flory-Huggins theory and solubility parameters. We hope that this review will serve as a valuable starting point for any pharmaceutical researcher, who has not yet fully explored the possibilities offered by computational approaches to solubility calculations.

Molecular Insights into Water Clusters Formed in Tributylphosphate-Di-(2-ethylhexyl)phosphoric Acid Extractant Systems from Experiments and Molecular Dynamics Simulations

Di-(2-ethylhexyl)phosphoric acid (D2EHPA) and tributylphosphate (TBP) are two of the most studied and researched organophosphorous extractants. D2EHPA is an acidic extractant, offering both hydrogen bond donor and acceptor sites while TBP, a neutral extractant, only offers a single acceptor site per molecule. In spite of this, it is observed that 1 M D2EHPA in dodecane is a poorer extractant for water than 1 M TBP in dodecane. The objective of present work is to look into the molecular interactions that cause such behavior. Experiments were carried out with varying molar ratios of TBP and D2EHPA in the organic dodecane phase. Total extractant concentration was kept constant at 1 M with dodecane as diluent. Water extraction was quantified by measuring the moisture content of the organic phase after equilibration. ¹H and ³¹P NMR spectra of the organic phase samples were recorded to study the change in the chemical environment upon extraction. Small angle X-ray scattering data of water saturated extractant phases were analyzed for the possibility of a reverse micellar aggregate formation. Molecular dynamics simulations could calculate free energies in quantitative agreement with experiments. Experimental and simulation studies showed that aggregation in the organic phase was promoted by the presence of water. This combined approach, of experiments and simulation, has shown that water is indispensable for the formation of ordered aggregates of extractants in nonpolar organic solvents. It is seen that, in the organic phase, around 80% of water's hydrogen bonds are with extractant molecules rather than with itself. The analysis clearly indicates that, rather than forming an aqueous core surrounded by extractant, water acts as a bridge between extractant molecules.