Sweet-Tasting Ionic Conjugates of Local Anesthetics and Vasoconstrictors.

Local anesthetics are widely utilized in dentistry, cosmetology, and medicine. Local anesthesia is essential to providing a pain-free experience during dental and local surgeries as well as cosmetic procedures. However, the injection itself may produce discomfort and be a source of aversion. A novel approach toward the taste modulation of local anesthetics is proposed, in which the anesthetics of the "-caine" family serve as cations and are coupled with anionic sweeteners such as saccharinate and acesulfamate. Ionic conjugates of vasoconstrictor epinephrine such as epinephrine saccharinate and epinephrine acesulfamate have also been synthesized. Novel ionic conjugates were developed using anion exchange techniques. Reported compounds are sweet-tasting and are safe to use both topically and as injections.

Macrocyclic peptidomimetics with antimicrobial activity: synthesis, bioassay, and molecular modeling studies.

Novel, cyclic peptidomimetics were synthesized by facile acylation reactions using benzotriazole chemistry. Microbiological testing of the synthesized compounds revealed an exceptionally high activity against Candida albicans with a minimum inhibitory concentration (MIC) two orders of magnitude lower than the MIC of the antifungal reference drug amphotericin B. A strikingly high activity was also observed against three Gram-negative bacterial strains (Pseudomonas aeruginosa, Klebsiella pneumoniae and Proteus vulgaris), two of which are known human pathogens. Thus the discovered chemotype is a potential polypharmacological agent. The toxicity against mammalian tumor cells was found to be low, as demonstrated in five different human cell lines (HeLa, cervical; PC-3, prostate; MCF-7, breast; HepG2, liver; and HCT-116, colon). The internal consistency of the experimental data was studied using 3D-pharmacophore and 2D-QSAR.

Ionic conjugates of lidocaine and sweeteners as better tasting local anesthetics for dentistry.

Lidocaine is the most widely utilized intraoral injected dental anesthetic, used for more than 500 million dental injections per year. Local anesthesia is essential for pain-free dentistry, yet intraoral injections are often considered painful and a source of anxiety for many patients. Any new anesthetics that will reduce the stress and anxiety of dental injection are expected to be beneficial. A novel chemical approach to taste modulation is proposed, in which the lidocaine cation is coupled with anionic sweeteners such as saccarinate and acesulfamate. The ionic conjugates synthesized using anion exchange techniques, were much less bitter, demonstrated a high local anesthetic potential in animal studies, and were as safe as the original hydrochloride. Based on the currently robust market for lidocaine it is expected that the resulting anesthetics will be in high demand in clinical practices worldwide.

Dual inhibition of the α-glucosidase and butyrylcholinesterase studied by molecular field topology analysis.

A striking dual inhibition of enzymes α-glucosidase and butyrylcholinesterase by small drug-like molecules, including 1,4-disubstituted-1,2,3-triazoles, chalcones, and benzothiazepines, was rationalized with the help of Molecular Field Topology Analysis, a 3D QSAR technique similar to CoMFA. A common pharmacophore supported the concept of a link existing between type-2 diabetes mellitus and Alzheimer's disease. These findings will be instrumental for rational design of drug candidates for both of these conditions.

Synthesis, bioassay, and molecular field topology analysis of diverse vasodilatory heterocycles.

A diverse training set composed of 76 in-house synthesized and 61 collected from the literature was subjected to molecular field topology analysis. This resulted in a high-quality quantitative structure-activity relationships model (R² = 0.932, Q² = 0.809) which was used for the topological functional core identification and prediction of vasodilatory activity of 19 novel pyridinecarbonitriles, which turned out to be active in experimental bioassay.

Promising Aedes aegypti repellent chemotypes identified through integrated QSAR, virtual screening, synthesis, and bioassay.

Molecular field topology analysis, scaffold hopping, and molecular docking were used as complementary computational tools for the design of repellents for Aedes aegypti, the insect vector for yellow fever, chikungunya, and dengue fever. A large number of analogues were evaluated by virtual screening with Glide molecular docking software. This produced several dozen hits that were either synthesized or procured from commercial sources. Analysis of these compounds by a repellent bioassay resulted in a few highly active chemicals (in terms of minimum effective dosage) as viable candidates for further hit-to-lead and lead optimization effort.

Computer-assisted rational design, synthesis, and bioassay of non-steroidal anti-inflammatory agents.

A focused dataset of previously synthesized and tested [1,2,4]-triazolo[1,5-a]pyridines and pyridine-3-carboxylates was studied by Molecular Field Topology Analysis (MFTA) to identify steric and electronic determinants of anti-inflammatory activity useful for the design and synthesis of new anti-inflammatory agents. Rational design based on the MFTA model identified eleven novel pyridine-3-carboxylates (2a-e and 3a-f) as promising. After synthesis and screening, three of (2a, 2c, 3a) revealed potent anti-inflammatory activity exceeding that of indomethacin, the reference inhibitor for artificially induced edema in rats.

Prediction of gas solubilities in ionic liquids.

Ionic liquids (of which it is estimated that there are at least one million simple fluids) generate a rich chemical space, which is now just at the beginning of its systematic exploration. Many properties of ionic liquids are truly unique and, which is more important, can be finely tuned. Differential solubility of industrial chemicals in ionic liquids is particularly interesting, because it can be a basis for novel, efficient, environmentally friendly technologies. Given the vast number of potential ionic liquids, and the impossibility of a comprehensive empirical exploration, it is essential to extract the maximum information from extant data. We report here some computational models of gas solubility. These multiple regression- and neural network-based models cover a chemical space spanned by 48 ionic liquids and 23 industrially important gases. Molecular polarisabilities and special Lewis acidity and basicity descriptors calculated for the ionic liquid cations and anions, as well as for the gaseous solutes, are used as input parameters. The quality of fit "observed versus predicted Henry's law constants" is particularly good for the neural network model. Validation was established with an external dataset, again with a high quality fit. In contrast to many other neural network models published, our model is no "black box", since contributions of the parameters and their nonlinearity characteristics are calculated and analysed.

New developments in hydrogen bonding acidity and basicity of small organic molecules for the prediction of physical and ADMET properties. Part 2. The universal solvation equation.

Theoretical quantifications of hydrogen bonding (HB) basicities and acidities, originally developed for aliphatic systems (J. Chem. Inf. Comput. Sci. 2004, 44, 1042-1055), are now extended to cover aromatic, heterocyclic, anionic, cationic and zwitter-ionic molecular fragments, thus encompassing a majority of druggable chemical space. The addition of terms accounting for cavity formation, polarity, hydrophobicity, and resonance allowed us to derive a new equation able to predict accurately free energies of solvation of diverse solutes, interphase transfers, and aqueous solubilities (log S(w)). We thus provide a "universal solvation equation" (USE) available for the accurate estimation of desolvation energies in protein-ligand docking, for the prediction of many physical and ADMET properties, and for studying fluid phase equilibria.

Theoretical scales of hydrogen bond acidity and basicity for application in QSAR/QSPR studies and drug design. Partitioning of aliphatic compounds.

Phenomenological analysis of existing hydrogen bond (HB) donor and acceptor scales and apparent physical considerations have enabled the establishment of new quantitative scales of hydrogen bond basicity and acidity. Chemical structures represented by molecular graphs and the orbital electronegativities of Hinze and Jaffe are utilized as an input data. The scales obtained correlate well with several experimental solvent polarity scales such as and, pK(HB), and E(T)(30). To demonstrate the applicability of the new quantities, we have applied them to seven equilibrium partitioning data sets: octanol-water, hexadecane-water, chloroform-water, gas-water, gas-octanol, gas-hexadecane, and gas-chloroform partition coefficients. The hydrogen bond descriptors when supplemented by a cavity-forming term and a dipolarity term show high performance in correlations of the partition coefficients of aliphatic compounds. These new HB descriptors can be used in studying hydrogen bonding and fluid phase equilibria as well as scoring functions in ligand docking and descriptors in ADME evaluations.

Aqueous biphasic systems. Partitioning of organic molecules: a QSPR treatment.

The partitioning of 29 small organic probes in a PEG-2000/(NH4)2SO4 biphasic system was investigated using a quantitative structure-property relationship (QSPR) approach. A three-descriptor equation with the squared correlation coefficient (R2) of 0.97 for the partition coefficient (log D) was obtained. All descriptors were derived solely from the chemical structure of the compounds. Using the same descriptors, a three-parameter model was also obtained for log P (octanol/water, R2=0.89); predicted log P values were used as an external descriptor for modeling log D.

A general treatment of solubility. 1. The QSPR correlation of solvation free energies of single solutes in series of solvents.

We present an extended QSPR modeling of solubilities of about 500 substances in series of up to 69 diverse solvents. The models are obtained with our new software package, CODESSA PRO, which is furnished with an advanced variable selection procedure and a large pool of theoretically derived molecular descriptors. The squared correlation coefficients and squared standard deviations (variances) range from 0.837 and 0.1 for 2-pyrrolidone to 0.998 and 0.02 for dipropyl ether, respectively. The predictive power of the models was verified by using the "leave-one-out" cross-validation procedure. The QSPR models presented are suitable for the rapid evaluation of solvation free energies of organic compounds.

A general treatment of solubility. 2. QSPR prediction of free energies of solvation of specified solutes in ranges of solvents.

As part of our general QSPR treatment of solubility (started in the preceding paper), we now present quantitative relationships between solvent structures and the solvation free energies of individual solutes. Solvation free energies of 80 diverse organic solutes are each modeled in a range from 15 to 82 solvents using our CODESSA PRO software. Significant correlations (in terms of squared correlation coefficient) are found for all the 80 solutes: the best fit is obtained for n-propylamine (R(2) = 0.996); the lowest R(2) corresponds to toluene (0.604).