Molecular compounds with permanent tubular architectures displaying radial π‐conjugation are exceedingly rare. Their radial and axial delocalization presents them with unique optical and electronic properties, such as remarkable tuning of their Stokes shifts, and redox switching between global and local aromaticity. Although these tubular compounds display large internal void spaces, these attributes have not been extensively explored, thus presenting future opportunities in the development of materials. By using cutting‐edge synthetic methodologies to bend aromatic surfaces, large opportunities in synthesis, property discovery, and applications are expected in new members of this family of conjugated molecular nanotubes.

Calculation of the solvation free energy of ionic molecules is the principal source of errors in the quantum chemical evaluation of pKa values using implicit polarizable continuum solvent models. One of the important parameters affecting the performance of these models is the choice of atomic radii. Here, we assess the performance of the solvation model based on density (SMD) implicit solvation model employing SMD default radii (SMD) and Bondi radii (SMD-B), a set of empirical atomic radii developed based on the crystallographic data. For a set of 112 ions (60 anions and 52 cations), the SMD-B model showed lower mean unsigned error (MUE) for predicted aqueous solvation free energies (4.0 kcal/mol for anions and 2.4 kcal/mol for cations) compared to the standard SMD model (MUE of 5.0 kcal/mol for anions and 2.9 kcal/mol for cations). In particular, usage of Bondi radii improves the aqueous solvation energies of sulfur-containing ions by >5 kcal/mol compared to the SMD default radii. Indeed, for a set of 45 thiols, the SMD-B model was found to dramatically improve the predicted pKa values, with ∼1 pKa unit mean deviation from the experimental values, compared to ∼7 pKa units mean deviation for the SMD model with the default radii. These findings highlight the importance of the choice of atomic radii on the performance of the implicit solvation models.

We report the synthesis and characterization of conjugated, conformationally rigid, and electroactive carbon-based nanotubes that we term tubularenes. These structures are constructed from a resorcin[nb]arene base. Cyclization of the conjugated...

Mechanism-based inactivation (MBI) refers to the metabolic bioactivation of a xenobiotic by cytochrome P450s to a highly reactive intermediate which subsequently binds to the enzyme and leads to the quasi-irreversible or irreversible inhibition. Xenobiotics, mainly drugs with specific functional units, are the major sources of MBI. Two possible consequences of MBI by medicinal compounds are drug–drug interaction and severe toxicity that are observed and highlighted by clinical experiments. Today almost all of these latent functional groups (e.g., thiophene, furan, alkylamines, etc.) are known, and their features and mechanisms of action, owing to the vast experimental and theoretical studies, are determined. In the past decade, molecular modeling techniques, mostly density functional theory, have revealed the most feasible mechanism that a drug undergoes by P450 enzymes to generate a highly reactive intermediate. In this review, we provide a comprehensive and detailed picture of computational advances toward the elucidation of the activation mechanisms of various known groups with MBI activity. To this aim, we briefly describe the computational concepts to carry out and analyze the mechanistic investigations, and then, we summarize the studies on compounds with known inhibition activity including thiophene, furan, alkylamines, terminal acetylene, etc. This study can be reference literature for both theoretical and experimental (bio)­chemists in several different fields including rational drug design, the process of toxicity prevention, and the discovery of novel inhibitors and catalysts.