Structural Investigation of Small Molecule Selectivity for Cardiolipin

Efficient development of new materials and drugs is becoming increasingly relevant. For targeted molecular design, information is needed about the physical and chemical properties governing function. An automated approach for identifying the chemical interactions crucial for binding selectivity of a drug-like compound to a biomolecular target was recently demonstrated^[1]. But the mere presence of these interactions is only part of the picture, in this work we investigate the structure-property relationship of a small molecule candidate with respect to target selectivity. Extracting mechanistic insights from MD simulations is a complex problem, with exact quantum-chemical solutions often computationally infeasible. Instead, we adapt the atomistic SLATM^[2] representation for use on already present coarse-grained trajectory data to systematically obtain 1-, 2-, and 3-body interactions between small molecules and their environment. By correlating these interaction modes with their corresponding physical and chemical properties, we gain insight into the structural aspects of binding selectivity of candidate compounds to the phospholipid Cardiolipin.

[1] Mohr, Bernadette, et al. "Data-driven discovery of cardiolipin-selective small molecules by computational active learning." Chemical Science 13.16 (2022): 4498-4511.

[2] Huang, Bing, Nadine O. Symonds, and O. Anatole von Lilienfeld. "The fundamentals of quantum machine learning." arXiv preprint arXiv:1807.04259 (2018).