Decoding dominant interaction patterns in halogenated dimers: A journey from halogen bonding to Van der Waals interactions

Liu, Fang; Du, Likai

doi:10.1016/j.comptc.2024.114513

Cited by 3 publications

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Unveiling the energetic complexity of noncovalent interactions in halogenated dimers

Liu,

2024

Int J of Quantum Chemistry

View full text Add to dashboard Cite

The understanding of noncovalent interactions is crucial in explaining critical phenomena such as self‐assembly, chemical reactivity, and crystallization. This work examines the energetic diversity of conformations and local minima for several halogenated dimers, represented as R‐X (R = H, F, CH3, CF3; X = Cl, Br, I). Thousands of configurations are randomly generated and refined through geometric optimizations to yield a diverse set of molecular conformers. Frequency calculations were performed for all optimized conformers to confirm that they are local minima. The noncovalent interactions in optimized dimers of halogen‐containing molecules were analyzed with atom in molecules (AIM) method and symmetry‐adapted perturbation theory (SAPT). Additionally, a protocol for generating machine learning models to recover accurate predictions of the physically meaningful SAPT energy components with minor computational cost is presented. These results deepen our understanding of the intricate energy balance and dedicated equilibrium of different noncovalent interactions in halogenated dimers.

show abstract

Unveiling the energetic complexity of noncovalent interactions in halogenated dimers

Liu,

2024

Int J of Quantum Chemistry

View full text Add to dashboard Cite

show abstract

A data-driven exploration of the complexity of the phosphorus-centered pnictogen bonds

Liu,

Wang,

2024

Molecular Physics

View full text Add to dashboard Cite

Elucidating Electronic Structure Variations in Nucleic Acid-Protein Complexes Involved in Transcription Regulation Using a Tight-Binding Approach

Du,

Liu

2024

Preprint

Self Cite

View full text Add to dashboard Cite

Transcription factor (TF) are proteins that regulates the transcription of genetic information from DNA to messenger RNA by binding to a specific DNA sequence. Nucleic acid-protein interactions are crucial in regulating transcription in biological systems. This work presents a quick and convenient method for constructing tight-binding models and offers physical insights into the electronic structure properties of transcription factor complexes and DNA motifs. The tight binding Hamiltonian parameters are generated using the random forest regression algorithm, which reproduces the given ab-initio level calculations with reasonable accuracy. We present a library of residue-level parameters derived from extensive electronic structure calculations over various possible combinations of nucleobases and amino acid side chains from high-quality DNA-protein complex structures. As an example, our approach can reasonably generate the subtle electronic structure details for the orthologous transcription factors human AP-1 and Epstein-Barr virus Zta within a few seconds on a laptop. This method potentially enhances our understanding of the electronic structure variations of gene-protein interaction complexes, even those involving dozens of proteins and genes. We hope this study offers a powerful tool for analyzing transcription regulation mechanisms at an electronic structural level.

show abstract

Decoding dominant interaction patterns in halogenated dimers: A journey from halogen bonding to Van der Waals interactions

Cited by 3 publications

References 63 publications

Unveiling the energetic complexity of noncovalent interactions in halogenated dimers

Unveiling the energetic complexity of noncovalent interactions in halogenated dimers

A data-driven exploration of the complexity of the phosphorus-centered pnictogen bonds

Elucidating Electronic Structure Variations in Nucleic Acid-Protein Complexes Involved in Transcription Regulation Using a Tight-Binding Approach

Contact Info

Product

Resources

About