Journal of Computational Chemistry

Giri, Sandip; Anoop, Anakuthil

doi: 10.1002/jcc.70287pmid: 41370132

Global minima of molecular clusters are one of the acute and long‐standing problems in the computational chemistry domain. It is important to understand the lowest energy geometry isomer of a given compound for further investigation of physical and chemical properties. The exponential growth of local minima with increasing cluster size makes the problem more relevant. The existing ab initio methods are accurate but very expensive in terms of computational resources. It opens the gap to find more efficient and reliable solutions for rapid exploration. On the other side, neural network potentials are the rising alternatives, with numerically accurate and reliable results for the molecular cluster problem. We integrate AIMNET2, a pretrained model, into our TABU‐based PyAR interface. Originally, this model was trained mostly on organic molecules, and we are using it for the PES explorations of molecular clusters, which is a neighboring domain but does not explicitly use any training input. We demonstrate the effectiveness of our methodology by exploring standard molecular clusters of water, ammonia, hydrogen peroxide, methanol, and acetic acid, with aggregation numbers ranging from 1–10. This work represents a significant step toward fully automated computational molecular cluster generation, paving the way for accelerated exploration and discovery in this field.

doi: 10.1002/jcc.27426pmid: N/A

doi: 10.1002/jcc.70284pmid: 41384638

E., Soorya; Pingale, Subhash S.

doi: 10.1002/jcc.70290pmid: 41391164

Molecular stacking, especially π‐stacking and H‐bond interactions, is important in various biochemical and material science fields. Stacking interactions are used to design supramolecular assemblies such as host‐guest complexes. Stacking interactions also play a crucial role in the structure and function of biomolecules like DNA, RNA, and proteins. G‐quadruplex, a non‐canonical DNA structure that is essential for a number of biological functions, such as gene control, telomere preservation, and DNA replication, is stabilized by stacking and H‐bond interactions. They are particularly important in cancer development as potential drug targets. Additionally, they are used in drug delivery systems and stimuli‐responsive materials. This study aims to cast light on the structure, energetics, and various intermolecular interactions involved in five differently stacked G‐quadruplex structures. The various computational methods employed for the calculations and analysis are Energy Decomposition Analysis using DFT calculations and Quantum Theory of Atoms in Molecules (QTAIM) at M062X/6‐311G(d,p) level in gas phase. The calculations performed show that the parallel conformations of G‐quadruplex are more stable than the other structures containing anti‐parallel conformations. Energy decomposition analysis suggests that with respect to stability, the parallel structure benefits more from stacking interactions over the anti‐parallel one. However, the H‐bond cooperativity contribution in the cyclic G‐quadruplex is found to be almost the same in both conformations. The structural stability is further analyzed by the QTAIM method, which shows that the greater number of stacking interactions in the parallel structure makes it more stable than the anti‐parallel structure. A detailed examination of the stacking interaction revealed its electrostatic nature.