Series Of Molecular Descriptors Research Articles

Estimating the hydrophobicity extent of molecular fragments using reversed-phase liquid chromatography.

A fast HPLC method was developed to study the hydrophobicity extent of pharmaceutically relevant molecular fragments. By this strategy, the reduced amount of sample available for physico-chemical evaluations in early-phase drug discovery programs does not represent a limiting factor. The sixteen acid fragments investigated were previously synthesized also determining potentiometrically their experimental log D values. For four fragments it was not possible to determine such property since their values were outside of the instrumental working range (2<pKa <12). An RP-HPLC method was therefore optimized. For each scrutinized method, some derived chromatographic indices were calculated, and Pearson's correlation coefficient (r) allowed to select the so-called "φ0 index" as the best correlating with the log D. The was fixed at 3.5 and a modification of some variables [organic modifier (methanol vs. ACN), stationary phase (octyl vs. octadecyl), presence/absence of the additives n-octanol, n-butylamine, and n-octylamine], allowed to select the best correlation conditions, producing a r=0.94 (p<0.001). Importantly, the φ0 index enabled the estimation of log D values for four fragments which were unattainable by potentiometric titration. Moreover, a series of molecular descriptors were calculated to identify the chemical characteristics of the fragments explaining the obtained φ0 . The number of hydrogen bond donors and the index of cohesive interaction correlated with the experimental data.

Molecular Descriptors as a Facile Tool toward Designing Surface-Functionalized Nanoparticles for Drug Delivery.

Modulating the surface chemistry of nanoparticles, often by grafting hydrophilic polymer brushes (e.g., polyethylene glycol) to prepare nanoformulations that can resist opsonization in a hematic environment and negotiate with the mucus barrier, is a popular strategy toward developing biocompatible and effective nano-drug delivery systems. However, there is a need for tools that can screen multiple surface ligands and cluster them based on both structural similarity and physicochemical attributes. Molecular descriptors offer numerical readouts based on molecular properties and provide a fertile ground for developing quick screening platforms. Thus, a study was conducted with 14 monomers/repeating blocks of polymeric chains, namely, oxazoline, acrylamide, vinylpyrrolidone, glycerol, acryloyl morpholine, dimethyl acrylamide, hydroxypropyl methacrylamide, hydroxyethyl methacrylamide, sialic acid, carboxybetaine acrylamide, carboxybetaine methacrylate, sulfobetaine methacrylate, methacryloyloxyethyl phosphorylcholine, and vinyl-pyridinio propanesulfonate, capable of imparting hydrophilicity to a surface when assembled as polymeric brushes. Employing free, Web-based, and user-friendly platforms, such as SwissADME and ChemMine tools, a series of molecular descriptors and Tanimoto coefficient of molecular pairs were determined, followed by hierarchical clustering analyses. Molecular pairs of oxazoline/dimethyl acrylamide, hydroxypropyl methacrylamide/hydroxyethyl methacrylamide, acrylamide/glycerol, carboxybetaine acrylamide/vinyl-pyridinio propanesulfonate, and sulfobetaine methacrylate/methacryloyloxyethyl phosphorylcholine were clustered together. Similarly, the molecular pair of hydroxypropyl methacrylamide/hydroxyethyl methacrylamide demonstrated a high Tanimoto coefficient of >0.9, whereas the pairs oxazoline/vinylpyrrolidone, acrylamide/dimethyl acrylamide, acryloyl morpholine/dimethyl acrylamide, acryloyl morpholine/hydroxypropyl methacrylamide, acryloyl morpholine/hydroxyethyl methacrylamide, carboxybetaine methacrylate/sulfobetaine methacrylate, and glycerol/hydroxypropyl methacrylamide had a Tanimoto coefficient of >0.8. The analyzed data not only demonstrated the ability of such in silico tools as a facile technique in clustering molecules of interest based on their structure and physicochemical characteristics but also provided vital information on their behavior within biological systems, including the ability to engage an array of possible molecular targets when the monomers are self-assembled on nanoparticulate surfaces.

Prediction of Collision Cross Section Values: Application to Non-Intentionally Added Substance Identification in Food Contact Materials.

The synthetic chemicals in food contact materials can migrate into food and endanger human health. In this study, the traveling wave collision cross section in nitrogen values of more than 400 chemicals in food contact materials were experimentally derived by traveling wave ion mobility spectrometry. A support vector machine-based collision cross section (CCS) prediction model was developed based on CCS values of food contact chemicals and a series of molecular descriptors. More than 92% of protonated and 81% of sodiated adducts showed a relative deviation below 5%. Median relative errors for protonated and sodiated molecules were 1.50 and 1.82%, respectively. The model was then applied to the structural annotation of oligomers migrating from polyamide adhesives. The identification confidence of 11 oligomers was improved by the direct comparison of the experimental data with the predicted CCS values. Finally, the challenges and opportunities of current machine-learning models on CCS prediction were also discussed.

DFT calculations and electrochemical studies on azulene ligands for heavy metal ions detection using chemically modified electrodes

A computational study on three related derivatives of 5-[(azulen-1-yl)methylene]-2-thioxoimidazolidin-4-one was conducted using density functional theory by calculating a series of molecular descriptors and properties of their optimized geometries (electrostatic and local ionization potentials, molecular frontier orbitals, etc.). Thermodynamic properties (zero-point energy, enthalpy, constant volume heat capacity, entropy and Gibbs energy) for these derivatives have been calculated and related to ligands electrochemical behavior. Reduction and oxidation potentials have been correlated to their calculated energy levels for LUMO and HOMO orbitals. Chemically modified electrodes based on these derivatives have been tested in view of heavy metal ions recognition, and their detection limits have been correlated to the calculated values of electron affinity.

Quantitative structure–activity relationships study of photocytotoxicity of miscellaneous porphyrins with amino acid and uracil by gene expression programming

Photodynamic therapy (PDT) is a new medical treatment modality for cancer which employs the combination of light and a photosensitizing drug against cancerous tissue. Quantitative structure–activity relationship (QSAR) study of the photocytotoxicity of miscellaneous porphyrins with amino acid and uracil has been performed. A series of molecular descriptors have been calculated in QSAR for these photosensitizers, with selection of variables and construction of nonlinear QSAR models performed simultaneously by gene expression programming (GEP). These selected descriptors encode different aspects of the molecular structure, involving electronic, spatial, and thermodynamic effects. The main factors affecting the photocytotoxicity of the considered porphyrins have been identified.

Structure-Activity Relationship of the Antifungal 1-Aryl-2-(azol-1-yl)ethane Derivatives

The relationship between the chemical structure of 54 1-aryl-2-(azol-1-yl)ethane derivatives and their antifungal activities, tested on 30 fungal species, have been examined. Among the 1-keto derivatives the compounds with a longer alkyl chain at the carbon atom adjacent to the azole ring as well as the chloro substituent on the benzene ring showed the highest antifungal activity, meanwhile, a shorter chain at the same carbon atom led to highest activity among the 1-chloro derivatives. To find the physico-chemical properties influencing the antifungal activity two series of molecular descriptors have been calculated applying the Dragon and the Sybyl VolSurf computer programs. The 3D structures of the compounds to these calculations were generated with the HYPERCHEM and the SYBYL molecular modeling programs. From the equation, obtained with stepwise regression using the antifungal activity data as dependent and the descriptors as independent variables, it is obvious that the factors describing the chemical...

[(Arylpiperazinyl)alkyl]thio]thieno[2,3-d]pyrimidinone derivatives as high-affinity, selective 5-HT1A receptor ligands.

A series of 2-[[(4-aryl-1-piperazinyl)alkyl]thio]thieno[2,3-d]pyrimidin-4 (1H)-one and 3-substituted 2-[[(4-aryl-1-piperazinyl)alky]thio]thieno[2,3-d]pyrimidin-4 (3H)-one derivatives was prepared and evaluated for in vitro 5-HT1A receptor affinity by radioligand binding assays; the selectivity for 5-HT1A receptors rather than alpha 1-adrenoceptors was also examined (ratio of the IC50 alpha 1 to IC50 5-HT1A). The binding tests gave indications about the best features of the [(arylpiperazinyl)alkyl]thio moiety and of the substituents on the thiophene and pyrimidinone rings for efficacious and selective 5-HT1A ligands. The most effective derivative for displacing [3H]-8-OH-DPAT from rat hippocampal membranes was the 3-amino-2-[[3-[4-(2-methoxyphenyl)-1-piperazinyl] propyl]thio]-5,6-dimethylthieno[2,3-d]pyrimidin-4(3H)-one (70) (IC50 = 0.3 nM) with selectivity of 24 for the 5-HT1A over the alpha 1-adrenoceptor. Compound 73, where the 2-methoxyphenyl on the N4 piperazine ring was replaced with a pyrimidine group, showed the best selectivity, with a ratio of 74, while its affinity IC50 for 5-HT1A was 6.8 nM. These results, compared to those for compounds 46 (IC50 24 nM; selectivity 2) and 49 (IC50 226 nM; selectivity 5), N3 unsubstituted analogues of derivatives 70 and 73, show the importance of an amino group in position 3 of the thienopyrimidine system for the interaction with 5-HT1A receptor binding sites, although this fragment can affect the affinity and selectivity only if linked to the (arylpiperazinyl)alkyl moiety. The better selectivity of piperidine 74 (IC50 0.8; selectivity 45) compared to the analogous piperazine 70 is also noteworthy. Twenty of the 30 molecules used for determining the binding affinity to 5-HT1A and alpha 1-adrenergic receptors were selected for QSAR analysis using a series of molecular descriptors and calculated with the TSAR software.

Structure-activity considerations in risk assessment: a simulation study.

The use of quantitative structure-activity relationships (QSAR) is considered with respect to estimating the carcinogenic risk of untested chemicals. SAR derived from a retrospective classification of a series of aromatic amines were used to study the estimation of carcinogenic risk by analogy. Using pattern recognition methods, a series of molecular descriptors were developed for a data set of aromatic amines that supported a linear discriminant function capable of separating compounds testing positively for carcinogenicity from those testing negatively. Linear discriminant analysis correctly categorized the compounds as positive or negative in 94.9% of the cases. For each aromatic amine within the subset of positive compounds, the most appropriate analogue was identified using physicochemical, topological, geometric and electronic molecular descriptors as variables. An upper-limit unit risk estimate was calculated for each compound that was a positive carcinogen within the data set using the linearized multistage model. The actual risk and the risk estimated by analogy to a congener were compared for each compound within the positive subset. The results support estimating both qualitative and quantitative carcinogenic risk by analogy for this particular data set.