The role of solvent-accessible surface area in determining partition coefficients

Prediction of toluene/water partition coefficients in the SAMPL9 blind challenge: assessment of machine learning and IEF-PCM/MST continuum solvation models

In recent years the use of partition systems other than the widely used biphasic n-octanol/water has received increased attention to gain insight into the molecular features that dictate the lipophilicity of compounds. Thus, the difference between n-octanol/water and toluene/water partition coefficients has proven to be a valuable descriptor to study the propensity of molecules to form intramolecular hydrogen bonds and exhibit chameleon-like properties that modulate solubility and permeability. In this context, this study reports the experimental toluene/water partition coefficients (log P_tol/w) for a series of 16 drugs that were selected as an external test set in the framework of the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) blind challenge. This external set has been used by the computational community to calibrate their methods in the current edition (SAMPL9) of this contest. Furthermore, the study also investigates the performance of two computational strategies for the prediction of log P_tol/w. The first relies on the development of two machine learning (ML) models, which are built up by combining the selection of 11 molecular descriptors in conjunction with either the multiple linear regression (MLR) or the random forest regression (RFR) model to target a dataset of 252 experimental log P_tol/w values. The second consists of the parametrization of the IEF-PCM/MST continuum solvation model from B3LYP/6-31G(d) calculations to predict the solvation free energies of 163 compounds in toluene and benzene. The performance of the ML and IEF-PCM/MST models has been calibrated against external test sets, including the compounds that define the SAMPL9 log P_tol/w challenge. The results are used to discuss the merits and weaknesses of the two computational approaches.

Molecular dynamics simulations of quinine encapsulation into biodegradable nanoparticles: A possible new strategy against Sars-CoV-2

A new coronavirus disease, SARS-CoV-2, has spread into a global pandemic in December 2019. Since no specific therapeutic drugs for treating COVID-19 have been approved by FDA, recent studies suggest that the known antimalarial quinine and its derivatives (chloroquine and hydroxychloroquine) inhibit receptor binding of the viral particles and inhibits the strong "cytokine storm", which is the main cause of death among infected patients. In particular, the natural alkaloid quinine has shown to possess a better safety profile and greater tolerability compared to its derivatives. Dosage optimization of quinine is still necessary as the currently available dosage forms have controversial pharmacokinetics and safety profiles. Therefore, repurposing quinine dosage forms to improve its pharmacokinetics and safety profile may be necessary to support its use against SARS-CoV-2. In this context, biodegradable/biocompatible polymeric nanoparticles may provide a safe site-specific and controlled quinine delivery, reducing the frequency of drug administration and the dose. In this study, a full atomistic molecular dynamics simulation approach has been used to investigate the use of poly-(glycolic acid) and poly-(lactic acid) and their copolymer poly-(lactic-co-glycolic acid) as potential delivery systems for lipophilic quinine to get insights into the mechanism of quinine encapsulation and release at the atomic/molecular level.

In quest of small-molecules as potent non-competitive inhibitors against influenza

A series of scaffolds namely aurones, 3-indolinones, 4-quinolones and cinnamic acid-piperazine hybrids, was designed, synthesized and investigated in vitro against influenza A/H1N1pdm09 virus. Designed molecules adopted different binding mode i.e., in 430-cavity of neuraminidase, unlike sialic acid and oseltamivir in molecular docking studies. All molecules reduced the viral titer and exhibited non-cytotoxicity along with cryo-protective property towards MDCK cells. Molecules (Z)-2-(3'-Chloro-benzylidene)-1,2-dihydro-indol-3-one (2f), (Z)-2-(4'-Chloro-benzylidene)-1,2-dihydro-indol-3-one (2g) and 2-(2'-Methoxy-phenyl)-1H-quinolin-4-one (3a) were the most interesting molecules identified in this research, endowed with robust potencies showing low-nanomolar EC₅₀ values of 4.0 nM, 6.7 nM and 4.9 nM, respectively, compared to reference competitive and non-competitive inhibitors: oseltamivir (EC₅₀ = 12.7 nM) and quercetin (EC₅₀ = 0.56 µM), respectively. Besides, 2f, 2g and 3a exhibited good neuraminidase inhibitory activity in sub-micromolar range (IC₅₀ = 0.52 µM, 3.5 µM, 1.3 µM respectively). Moreover, these molecules were determined as non-competitive inhibitors similar to reference non-competitive inhibitor quercetin unlike reference competitive inhibitor oseltamivir in kinetics studies.

POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction

Whole genome/exome sequencing data for tumors are now abundant, and many tumor antigens, especially mutant antigens (neoantigens), have been identified for cancer immunotherapy. However, only a small fraction of the peptides from these antigens induce cytotoxic T cell responses. Therefore, efficient methods to identify these antigenic peptides are crucial. The current models of major histocompatibility complex (MHC) binding and antigenic prediction are still inaccurate. In this study, 360 9-mer peptides with verified immunological activity were selected to construct a prediction of tumor neoantigen (POTN) model, an immunogenic prediction model specifically for the human leukocyte antigen-A2 allele. Based on the physicochemical properties of amino acids, such as the residue propensity, hydrophobicity, and organic solvent/water, we found that the predictive capability of POTN is superior to that of the prediction programs SYPEITHI, IEDB, and NetMHCpan 4.0. We used POTN to screen peptides for the cancer-testis antigen located on the X chromosome, and we identified several peptides that may trigger immunogenicity. We synthesized and measured the binding affinity and immunogenicity of these peptides and found that the accuracy of POTN is higher than that of NetMHCpan 4.0. Identifying the properties related to the T cell response or immunogenicity paves the way to understanding the MHC/peptide/T cell receptor complex. In conclusion, POTN is an efficient prediction model for screening high-affinity immunogenic peptides from tumor antigens, and thus provides useful information for developing cancer immunotherapy.

In silico studies, synthesis and pharmacological evaluation to explore multi-targeted approach for imidazole analogues as potential cholinesterase inhibitors with neuroprotective role for Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder with multiple factors associated with its pathogenesis. Our strategy against AD involves design of multi-targeted 2-substituted-4,5-diphenyl-1H-imidazole analogues which can interact and inhibit AChE, thereby, increasing the synaptic availability of ACh, inhibit BuChE, relieve induced oxidative stress and confer a neuroprotective role. Molecular docking was employed to study interactions within the AChE active site. In silico ADME study was performed to estimate pharmacokinetic parameters. Based on computational studies, some analogues were synthesized and subjected to pharmacological evaluation involving antioxidant activity, toxicity and memory model studies in animals followed by detailed mechanistic in vitro cholinesterase inhibition study. Amongst the series, analogue 13 and 20 are the most promising multi-targeted candidates which can potentially increase memory, decrease free radical levels and protect neurons against cognitive deficit.

Entropy and Polarity Control the Partition and Transportation of Drug-like Molecules in Biological Membrane

Partition and transportation of drug in the plasma membrane of a mammalian cell are the prerequisite for its function on target protein. Therefore, comprehensive understanding of the physicochemical properties and mechanism behind these complex phenomena is crucial in pharmaceutical research. By using the state-of-art molecular simulations with polarization effect implicitly or explicitly included, we studied the permeation behavior of 2-aminoethoxydiphenyl borate (2-APB), a broad-spectrum modulator for a number of membrane proteins. We showed that the protonation state and therefore the polarity of the drug is critical for its partition, and that the drug is likely to switch between different protonation states along its permeation pathway. By changing the degrees of freedom, protonation further affects the thermodynamic of the permeation pathway of 2-APB, leading to different entropic contributions. A survey on 54 analog structures with similar backbone to 2-APB showed that delicate balance between entropy and polarity plays an important role in drugs’ potency.

Experimental and theoretical studies on the molecular properties of ciprofloxacin, norfloxacin, pefloxacin, sparfloxacin, and gatifloxacin in determining bioavailability

The aim of this investigation is to identify, by in silico and in vitro methods, the molecular determinants, e.g., solubility in an aqueous medium and lipophilic properties, which have an effect on the bioavailability of five selected fluoroquinolones. These properties were estimated by analysis of the electrostatic potential pattern and values of free energy of solvation as well as the partition coefficients of the studied compounds. The study is based on theoretical quantum-chemical methods and a simple experimental shake-flask technique with two immiscible phases, n-octanol and phosphate buffer. The solvation free energy values of compounds in both environments appeared to be negative. The wide range of electrostatic potential from negative to positive demonstrates the presence of dipole-dipole intermolecular interactions, while the high electron density at various sites indicates the possibility of hydrogen bond formation with solvent molecules. High partition coefficient values, obtained by summing the atomic contributions, did not take various correction factors into account and therefore were not accurate. Theoretical partition coefficient values based on more accurate algorithms, which included these correction factors (fragmental methods), yielded more accurate values. Theoretical methods are useful tools for predicting the bioavailability of fluoroquinolones.

Insilico studies of organosulfur-functional active compounds in garlic

Garlic has been used medicinally since antiquity because of its antimicrobial activity, anticancer activity, antioxidant activity, ability to reduce cardiovascular diseases, improving immune functions, and antidiabetic activities and also in reducing cardiovascular diseases and improving immune functions. Recent studies identify that the wide variety of medicinal functions are attributed to the sulfur compounds present in garlic. Epidemiological observations and laboratory studies in animal models have also showed anticarcinogenic potential of organosulfur compounds of garlic. In this study, in silico analysis of organosulfur compounds is reported using the methods of theoretical chemistry to elucidate the molecular properties of garlic as it is more time and cost efficient, reduces the number of wet experiments, and offers the possibility of replacing some animal tests with suitable in silico models. The analysis of molecular descriptors defined by Lipinski has been done. The solubility of drug in water has been determined as it is of useful importance in the process of drug discovery from molecular design to pharmaceutical formulation and biopharmacy. All toxicities associated with candidate drug have been calculated. P-Glycoprotein expressed in normal tissues as a cause of drug pharmacokinetics and pharmacodynamics has been examined. Drug-plasma protein binding and volume of distribution have also been calculated. To avoid rejection of drugs, it is becoming more important to determine pK(a), absorption, polar surface area, and other physiochemical properties associated with a drug, before synthetic work is undertaken. The present in silico study is aimed at examining these compounds of garlic to evaluate its possible efficacy and toxicity under conditions of actual use in humans.

The Classification of Solvents by Combining Classical QSPR Methodology with Principal Component Analysis

The results of a quantitative structure-property relationship (QSPR) analysis of 127 different solvent scales and 774 solvents using the CODESSA PRO program are presented. QSPR models for each scale were constructed using only theoretical descriptors. The high quality of the models is reflected by the squared multiple correlation coefficients that range from 0.726 to 0.999; only 18 models have R2< 0.800. This enables direct theoretical calculation of predicted values for any scale and/or for any organic solvent, including those previously unmeasured. The molecular descriptors involved in the models are classified and discussed according to (i) the origin of their calculation (i.e., constitutional, geometric, charge-related, etc.) and (ii) the commonly accepted classification of physical interactions between the solute and solvent molecules in liquid (condensed) media. A reduced matrix 774 (solvents) x 100 (solvent scales) was selected for the principal component analysis (PCA) by taking into account only the solvent scales with more than 20 experimental data points. The first 5 principal components account for 75% of the total variance. The robustness of the PCA model obtained was validated by the comparison models development for restricted submatrices of data and with the results obtained for the full data set. The total variance accounted for by the first three PCs, for the submatrices with the same number of solvent scales but different numbers of solvents, varies from 68.2% to 59.0%. This demonstrates that the total variance described by the first 3 components is essentially stable as the number of solvents involved varies from 100 to 774. Subsequently, a matrix with 703 diverse solvents and 100 solvent scales was selected for the general classification of the solvents and scales according to the scores and loadings obtained from the PCA treatment. Classification of the theoretical molecular descriptors, derived from the chemical structure alone, according to their relevance to specific types of intermolecular interaction (cavity formation, electrostatic polarization, dispersion, and hydrogen bonding) in liquid media enables a more easily comprehensible physical interpretation of the QSPR of molecular properties in liquids and solutions. The reported QSPR models for solvent scales with theoretical molecular descriptors and the results of the PCA analysis are potentially of great practical importance, as they extend the applicability of correlations with empirical solvent scales to many previously unmeasured systems.

Controlled drug release from gels using surfactant aggregates: I. Effect of lipophilic interactions for a series of uncharged substances

Gels are often used for the delivery of drugs because they have rheological properties that will give a long residence time. Most pharmaceutical gels consist of approximately 99% water and a polymer matrix that will not hinder the release of drugs with a small molecular weight. To fully take advantage of the residence time, it is necessary to have a sustained drug release. In this paper it is suggested that surfactant micelles can be used to control the release from gels. The in vitro release under physiological conditions of five parabens from four different poly(acrylic acid) gels (Carbopol 934, 940, 1342) and one gellan gum (Gelrite) gel was measured using a USP dissolution bath modified for gels, and the diffusion coefficients were calculated. The diffusion coefficient of uncharged parabens was generally lower in gels with lipophilic modifications, such as C1342, and the greatest effect was seen for butylparaben, with a diffusion that was 25% lower than that in C934 (lacking lipophilic modification). Addition of surfactant micelles to gels delayed the release of all the uncharged drugs in all types of gels studied. The slowest release was seen for butylparaben in a lipophilically modified gel with micelles present. The diffusion coefficient in such a system was almost 30 times smaller than that in C934 without micelles.

Caco-2 monolayers in experimental and theoretical predictions of drug transport

This review examines the use of Caco-2 monolayers in the prediction of intestinal drug absorption. First, the different routes of drug transport in Caco-2 monolayers are compared with those seen in vivo. Second, the prediction of drug absorption in vivo from transport experiments in cell monolayers is discussed for different classes of drugs. Finally, the use of Caco-2 monolayers as a reference model in physico-chemical and theoretical predictions of drug absorption is discussed. We conclude that Caco-2 monolayers can be used to identify drugs with potential absorption problems, and possibly also to select drugs with optimal passive absorption characteristics from series of pharmacologically active molecules generated in drug discovery programs.

Evaluation of hydrophobic/hydrophilic balance of bile acids by comparative molecular field analysis (CoMFA)

A comparative molecular field analysis (CoMFA) model, employing standard steric and electrostatic fields, is able to predict the hydrophobic/hydrophilic balance, expressed as reverse-phase HPLC capacity factor, for a series of both naturally occurring and semi-synthetic bile acids. The very high values of cross-validated R(2) (Q(2)) demonstrate that the CoMFA method can give useful information on the hydrophobic balance of newly synthesized bile acids.

The n-octanol and n-hexane/water partition coefficient of environmentally relevant chemicals predicted from the mobile order and disorder (MOD) thermodynamics

The quantitative thermodynamic development of the mobile order and disorder theory in H-bonded liquids is extended in order to predict the partition coefficient. With respect to the classical predictive methods, the great advantage of the present approach resides in the possibility of predicting partition coefficient not only in the reference n-octanol/water partitioning system, but also in any mutually saturated two-phase system made up of two largely immiscible solvents. Constructed from the various free energy contributions encoded in the distribution process, the model furthermore provides a useful tool to understand both the origin and the factors, like the solute molar volume, that determine the partitioning of non-electrolytes between two immiscible liquid phases. From the comparison of the relative magnitude of the terms which contribute to the overall log P value, much information can also be gained concerning the variation of the partition coefficients of the same substances in different distribution systems. For example, the model has successfully been applied to the log P prediction of a number of environmentally important chemicals of varying structure, size and chemical nature in the n-octanol/water and n-hexane/water systems. Whatever the complexing or non-complexing substances studied, the hydrophobic effect always represent the driving force that rules distribution processes in the aqueous environments. As the dominant contribution to the partition coefficient in any organic/aqueous binary system, it is evidenced why hydrophobicity is usually considered to be a good measure of lipophilicity.

Correlation and estimation of gas-chloroform and water-chloroform partition coefficients by a linear free energy relationship method

A linear free energy relationship, LFER, has been used to correlate 150 values of gas-chloroform partition coefficients, as log Lchl with a standard deviation, sd, of 0.23 log units, a correlation coefficient r2 of 0.985, and an F-statistic of 1919. The equation reveals that bulk chloroform is dipolar/polarizable, of little hydrogen-bond basicity, but as strong a hydrogen-bond acid as bulk methanol or bulk ethanol. However, the main influence on gaseous solubility in chloroform is due to solute-solvent London dispersion interactions. A slightly modified LFER has been used to correlate 302 values of water-chloroform partition coefficients, as log Pchl. The correlation equation predicts log Pchl for a further 34 compounds not used in the equation with sd = 0.17 log units. When the LFER is applied to all 335 log Pchl values, the resulting equation has sd = 0.25, r2 = 0.971, and F = 2218.

Structure-activity relationships of P-glycoprotein interacting drugs: kinetic characterization of their effects on ATPase activity

We have determined the kinetic parameters for stimulation and inhibition by 34 drugs of the P-glycoprotein ATPase in membranes derived from CR1R12 Chinese hamster ovary cells. The drugs chosen were sets of calmodulin antagonists, steroids, hydrophobic cations, hydrophobic peptides, chemotherapeutic substrates of P-glycoprotein, and some other drugs with lower affinity for P-glycoprotein. We studied how these kinetic parameters correlated with the partition coefficient and the Van der Waals surface area of the drugs. The maximum velocity of ATPase stimulation decreased with surface area and showed a suggestion of a maximum with increasing partition coefficient. The affinity of these drugs for P-glycoprotein showed no significant correlation with partition coefficient but was highly correlated with the surface area suggesting that binding between modulators and P-glycoprotein takes place across a wide interaction surface on the protein.

Correlation of drug absorption with molecular surface properties

The correlation between dynamic surface properties of drug molecules and drug absorption in two common in vitro models of the intestinal wall (Caco-2 monolayers and rat intestinal segments) has been investigated. A homologous series of beta-adrenoreceptor antagonists were used as model compounds. Dynamic molecular surface properties, considering all low-energy conformations, of the compounds were calculated. The flexibility of the molecules was studied by molecular mechanics calculations (MM2) and the van der Waals' (vdW), and water accessible surface areas were calculated and averaged according to a Boltzmann distribution. Excellent correlations were obtained between the dynamic polar vdW surface areas and cell permeabilities in Caco-2 cells and rat ileum (r2 = 0.99 and 0.92, respectively). These correlations were stronger than those between calculated octanol/buffer partition coefficients (log Doct,7.4) and permeability (r2 = 0.80 and 0.73, respectively). Moreover, the calculated log Doct,7.4 values failed to rank the permeability coefficients through Caco-2 monolayers and rat ileum in the correct order. The results indicate that dynamic polar surface area is a promising alternative model for the prediction of oral drug absorption.

Description of hydrophobicity parameters of a mixed set from their three-dimensional structures

The logarithm of capacity factors (log k') previously measured from the reversed-phase high-performance liquid chromatography (RP-HPLC) and the octanol-water partition coefficients (log P) of a mixed set of substituted benzene, furan, benzofuran, pyrrole, 1-Me-pyrrole, indole, and N-methyl indole derivatives are correlated with the descriptors obtained from their three-dimensional structures using the comparative molecular field analysis (CoMFA) approach. The results provide an example where log k' and log P values are calculated directly from the three-dimensional structures for a mixed set of compounds.

Calculation of hydrophobic parameters directly from three-dimensional structures using comparative molecular field analysis

Capacity ratio (log k') values, which are a measure of hydrophobicity, were calculated directly from the three-dimensional structures of 17 furans and 54 triazines using the comparative molecular field analysis approach. The H2O probe and the GRID force field, including hydrogen-bond potentials, yielded excellent correlations with the log k' values. Moreover, the predicted values of log k' from 14 additional triazine analogs showed excellent agreement with log k' values reported in the literature. Similar results were obtained for the octanol-water partition coefficients (log P) of 17 furans.