The specific interactions between sulphonic acid protonated polyaniline (PANI) and solvents are here studied both by the semiempirical AM1 method and experimentally. Phenolic solvents are shown to have a relatively large interaction with the sulphonate anions of the counterions and with the amines in PANI. In addition, a properly functionalized counterion may form cyclic associations provided that there is a steric match between the molecules concerned. This concept is called molecular recognition and it is a novel concept in the context of PANI. For example, the carbonyl group in (±)-10-camphor sulphonic acid (CSA) can form a hydrogen bond to the hydroxyl group of m-cresol, whereby the phenyl ring becomes coplanar with one of the PANI rings thus enabling enhanced van der Waals interaction. This additional specific interaction agrees with our observed increased solubility with CSA doped PANI in m-cresol, compared to its solubility in dimethyl sulphoxide or chloroform, or to tosylene sulphonic acid doped PANI in m-cresol. The above cyclic associations are suggested for dilute solutions and for the amorphous domains of solid films. In the latter case, they provide a potential mechanism to yield planar conformation in the crystalline domains: during the evaporation of m-cresol, stacking to crystal structure may twist the rings due to the planar m-cresol molecules on top of PANI rings. This is in agreement with the observed high conductivity. The present results indicate that computational methods combined with the concept of molecular recognition may open new possibilities to tailor the rigidities and solubilities of macromolecules.

Due to its semirigid nature, electrically conductive polyaniline (PANI) has long been regarded as an intractable material, i.e. infusible and poorly soluble in organic compounds. Among the rare exceptions is camphorsulfonic acid (CSA) doped PANI, which exhibits good solubility in m-cresol, whereas for other sulfonic acid dopants (e.g. dodecylbenzenesulfonic acid (DBSA)) the solubility in common solvents is poor. We report exceptionally high solubility of fully DBSA and CSA protonated PANI in a crystalline compound, 1,3-dihydroxybenzene, i.e. resorcinol. Up to 20−30 wt % of PANI(DBSA)0.5 and PANI(CSA)0.5 can be dissolved in resorcinol at 200−220 °C to form particle-free films as observed by optical microscopy. High PANI complex concentrations require high temperatures for dissolution, suggesting UCST behavior with a high critical temperature. Optical microscopy, calorimetry, and X-ray analysis suggest that the solution initially is amorphous. With time, crystallinity develops within the sample, due to partial phase separation of resorcinol while part of it remains miscible. Calculations show that a resorcinol molecule is able to simultaneously form two hydrogen bonds and one phenyl/phenyl interaction with the PANI/sulfonic acid complex, because of their steric match. The conditions required to achieve such matching interactions, i.e. molecular recognition, are discussed. The concept can be extended to find a large category of novel solvents for electrically conductive PANI to yield soluble and fusible complexes.

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The cocrystal formation potential of itraconazole, a potent antifungal drug, with C2–C10 aliphatic dicarboxylic acids has been investigated. Using two experimental screening techniques (solvent-assisted grinding and evaporation-based crystallization), the cocrystals of itraconazole with C2–C7 dicarboxylic acids have been successfully synthesized and characterized by powder X-ray diffraction, solid state nuclear magnetic resonance, Raman spectroscopy, and thermal analysis. The characterized multicomponent compounds include anhydrous cocrystals (malonic, succinic, glutaric, and pimelic acids), a cocrystal hydrate (adipic acid), and cocrystal solvates with acetone and tetrahydrofuran (oxalic acid). This study is the first to demonstrate the diversity in itraconazole cocrystals with a range of aliphatic dicarboxylic acids of variable carbon chain lengths.

Achieving selectivity for small organic molecules toward biological targets is a main focus of drug discovery but has been proven difficult, for example, for kinases because of the high similarity of their ATP binding pockets. To support the design of more selective inhibitors with fewer side effects or with altered target profiles for improved efficacy, we developed a method combining ligand- and receptor-based information. Conventional QSAR models enable one to study the interactions of multiple ligands toward a single protein target, but in order to understand the interactions between multiple ligands and multiple proteins, we have used proteochemometrics, a multivariate statistics method that aims to combine and correlate both ligand and protein descriptions with affinity to receptors. The superimposed binding sites of 50 unique kinases were described by molecular interaction fields derived from knowledge-based potentials and Schrödinger's WaterMap software. Eighty ligands were described by Mold(2), Open Babel, and Volsurf descriptors. Partial least-squares regression including cross-terms, which describe the selectivity, was used for model building. This combination of methods allows interpretation and easy visualization of the models within the context of ligand binding pockets, which can be translated readily into the design of novel inhibitors.