Computational Chemistry Tools for Non-Covalent Interactions: Methods and Applications

Non-covalent interactions, such as hydrogen bonding, C-H∙∙∙p, p∙∙∙p, van der Waals forces, ion–ion interactions, dipole–dipole interactions, play a central role in supramolecular chemistry. Albeit weaker than covalent interactions, these non-covalent interactions are key in solid-state systems, biological processes, drug–receptor interactions, and even technological applications.[1] Modern computational technology has facilitated the development of sophisticated tools for the theoretical analysis of these interactions. The two most common computational approaches are quantum mechanics (QM) and molecular mechanics (MM). QM is based on an approximate solution of the Schrödinger equation, while MM relies on a classical description of atoms based on Newton’s laws. Recently, two new methods have been developed, i.e., the self-consistent-charge density functional tight-binding method (SCC-DFTB) [2] and the extended semiempirical tight-binding model (xtb).[3] These DFT approximations reduce the computational demand, making calculations 2–3 orders of magnitude faster than standard DFT, without significant loss of accuracy, thereby enabling computational characterization of large molecules (over 200 atoms). Identifying and quantifying non-covalent interactions through computational analysis is another crucial step. Historically, the Quantum Theory of Atoms in Molecules (QTAIM) analysis has been widely used for this purpose. However, a new method, the Independent Gradient Model, based on a new electronic density descriptor, has been developed [4]. All of these methods have been used to provide a picture of noncovalent interactions in three different systems: - Silver(I) halide n-picolylamine hybrid coordination polymers; - A supramolecular host-guest system, pyrene in an arene-ruthenium metalla-prism; - A Ru-based catalyst grafted on trihydroxy(octyl)silane-functionalized TiO2 rutile surface.